Search

The fierce competition in tourism has brought a string of problems, such as the homogeneous development of regional tourism resources and the escalation of regional competition. One key issue in urban tourism today is how to identify competitors, recognize own advantageous resources, and clarify the direction of development. This paper evaluates the competitiveness of regional tourism in three steps: setting up an evaluation system, calculating niche and niche overlap, and conducting synthesis and cluster analysis. Firstly, a comprehensive evaluation system of urban tourism niche was established, which includes such four dimensions as tourism resources, tourism market, social economy, and eco-environment, and the weight of each index was calculated by entropy method. Next, regional niche and niche overlap were computed by niche theory. Taking the mean of niche overlap and that of composite niche as the references, the authors drew an overall distribution map of regional tourism niche. After that, a cluster analysis was carried out with the four-dimensional niche and composite niche of regional tourism. Finally, an empirical analysis was performed on the tourism competitiveness in ten prefectures of Shaanxi Province, using the data in 2010–2018. The results show that the prefectures differed greatly in tourism development and competed fiercely against each other.

As a multi-objective decision-making system, water security evaluation is suitable for the evaluation with a matter-element model. However, in the traditional matter-element model, the eigenvalue of matter-element cannot be calculated when it is beyond the range of nodes, and the calculation process is complex and error-prone. In this paper, improved analytic hierarchy process with entropy weight were combined to calculate the water security comprehensive evaluation index weight, avoiding the over-subjective or over-objective weight value. The normalization of matter-element improves the rationality of the matter-element correlation function and expands the application scope of the model, while the standardization of comprehensive proximity improves the accuracy of model results. Guangdong Province was taken as an example to verify the practicability of the model in the evaluation of the water security comprehensive index. The results show that from 2004 to 2019, the overall water security of Guangdong Province showed a trend rising from deteriorated grade to safe grade and the model results were in line with the facts. As a result, the water security comprehensive evaluation model based on comprehensive weight and improved matter-element is simple, practical, and suitable for the multi-level and multi-factor regional water security comprehensive evaluation.

Background: Periplogenin (PPG), a natural compound isolated from traditional Chinese herb Cortex Periplocae, has been reported to possess anti-inflammatory and anti-cancer properties. Objective: The present study aims to investigate the antitumor effects of PPG and the underlying mechanism in human colorectal cancer cells. Methods: The inhibition of cell growth in vitro was assessed by MTT assay. The induction of apoptosis and the ROS production induced by PPG was investigated by flow cytometry analysis. Western blotting was applied to measure the protein expression. Small interference RNA (siRNA) and a specific pharmacological inhibitor were used to knock down or inhibit the expression of related genes. Results: PPG was able to cause the production of ROS, inhibit the cancer cell growth and induce apoptosis. Nacetylcysteine was able to inhibit ROS production and apoptosis. PPG up-regulated the protein levels of BIP, peIF2α and CHOP as well as IRE1α and p-JNK, and down-regulated the protein level of p-ASK1, all of which were reversed by N-acetylcysteine. Importantly, knockdown of CHOP or JNK protein level attenuated the PPGelicited apoptosis. Conclusion: PPG-induced apoptosis was regulated by ROS-mediated BIP/eIF2α/CHOP and BIP/ASK1/JNK signaling pathways in colon cancer cells, suggesting that PPG is a promising therapeutic agent for the treatment of human colon cancer.

In the field of bioinformatics, the prediction of phage virion proteins helps us understand the interaction between phage and its host cells and promotes the development of new antibacterial drugs. However, traditional experimental methods to identify phage virion proteins are expensive and inefficient, more researchers are working to develop new computational methods. In this review, we summarized the machine learning methods for predicting phage virion proteins during recent years, and briefly described their advantages and limitations. Finally, some research directions related to phage virion proteins are listed.

The plasma chaotic system is a dissipative dynamical system modeled by a parametric plasma instability arising from the interaction of the whistler and ion acoustic waves with the plasma oscillation near the lower hybrid resonance. The amplitudes of these three oscillations obey a three-dimensional system of ordinary differential equations that exhibits chaos for certain parameter values. Besides the maximal Lyapunov exponent technique, a generalized-competitive-mode (GCM) technique has been proposed to evaluate parameter values associated with chaos. A mechanical analysis has also been proposed to reveal the mechanisms underlying the different dynamical modes including chaos. In a series of comparisons between the GCM analysis and mechanical analysis, chaos for the plasma chaotic system is determined. The mechanism and causes by which the plasma chaotic system produces different dynamical behaviors are interpreted. Furthermore, using the whistler-parameter variation of the Casimir function and Casimir power for the plasma system, the generating mechanisms of the different orbital modes and the different levels of chaos are uncovered.

The idea of green poverty reduction is an important part of precision poverty alleviation. It is also an effective way to realize Xi Jinping's accurate poverty alleviation. On the basis of constructing the evaluation index system of green poverty reduction effect which includes economic green ability, resource utilization and protection ability, social development ability and poverty alleviation and development ability, the regional green poverty reduction effect index was calculated by comprehensive weighting TOPSIS method, and then the regional green poverty reduction effect index was divided by cluster analysis. The empirical results showed that the effect of green poverty reduction in southern Shaanxi could be divided into zone I (poverty alleviation and development advantage zone), zone II (economic green development advantage zone) and zone III (green development pressure zone). Zone I was Hanbin district, Zone II was Zhenba County, and Zone III were other counties. On the whole, the effect of green poverty reduction was not ideal.

Plasma is normally investigated via fluid dynamics, and to investigate the force and energy underlying a plasma chaotic system, it is first transformed into a Kolmogorov-type system. This system describes a general form of fluid and forced-dissipative rigid body system. The vector field of the plasma chaotic system is decomposed into four types of torque: inertial torque, internal torque, dissipation, and external torque. The Hamiltonian energy transfer between kinetic energy and potential is discovered. The various combinations of these four types of torque are constructed to uncover the effect of each on the generation of the dynamic mode of the chaotic system. The physical functions of the whistler and dampening of the pump are identified in producing the different plasma dynamics. Aside from the torque effects, the rate of change of the Casimir function is also a key factor in characterizing the orbit behavior of the plasma system. Last, a supremum bound of the plasma chaotic attractor is proposed.

Circular RNAs (circRNAs) are a new kind of endogenous non-coding RNAs, which have been discovered continuously. More and more studies have shown that circRNAs are related to the occurrence and development of human diseases. Identification of circRNAs associated with diseases can contribute to understand the pathogenesis, diagnosis and treatment of diseases. However, experimental methods of circRNA prediction remain expensive and time-consuming. Therefore, it is urgent to propose novel computational methods for the prediction of circRNA-disease associations. In this study, we develop a computational method called LLCDC that integrates the known circRNA-disease associations, circRNA semantic similarity network, disease semantic similarity network, reconstructed circRNA similarity network, and reconstructed disease similarity network to predict circRNAs related to human diseases. Specifically, the reconstructed similarity networks are obtained by using Locality-Constrained Linear Coding (LLC) on the known association matrix, cosine similarities of circRNAs and diseases. Then, the label propagation method is applied to the similarity networks, and four relevant score matrices are respectively obtained. Finally, we use 5-fold cross validation (5-fold CV) to evaluate the performance of LLCDC, and the AUC value of the method is 0.9177, indicating that our method performs better than the other three methods. In addition, case studies on gastric cancer, breast cancer and papillary thyroid carcinoma further verify the reliability of our method in predicting disease-associated circRNAs.

Accumulating biological experiments have shown that circRNAs are closely related to the occurrence and development of many complex human diseases. During recent years, the associations of circRNA with disease have caused more and more researchers to pay attention and to analyze their correlation mechanisms. However, experimental methods for determining the associations of circRNA with a particular disease are still expensive, difficult, and time consuming. Moreover, the available databases related to circRNA-disease correlations have only recently been updated, and only a few computational methods are constructed to predict potential circRNA-disease correlations. Taking into account the limitations of experimental studies, we develop a novel computational method, named IBNPKATZ, for predicting potential circRNA-disease associations, which integrates the bipartite network projection algorithm and KATZ measure. This model is based on the known circRNA-disease associations, combining circRNA similarity and disease similarity. Specifically, the circRNA similarity is derived from the average of the semantic similarity and the Gaussian interaction profile (GIP) kernel similarity of circRNA. Similarly, disease similarity is the mean of the semantic similarity and the GIP kernel similarity of disease. Furthermore, it is semi-supervised and does not require negative samples. Finally, IBNPKATZ achieves reliable AUC of 0.9352 in the leave-one-out cross validation, and case studies show that the circRNA-disease correlations predicted by our method can be successfully demonstrated by relevant experiments. The IBNPKATZ is expected to be a useful biomedical research tool for predicting potential circRNA-disease associations.

To elucidate the effect of stacking fault energies (SFEs) on defect formation by the collision cascade process for face-centred cubic metals, we used six sets of interatomic potentials with different SFEs while keeping the other properties almost identical. Molecular dynamic simulations of the collision cascade were carried out using these potentials with primary knock-on atom energies (EPKA) of 10 and 20 keV at 100 K. Neither the number of residual defects nor the size distributions for both self-interstitial atom (SIA) type and vacancy type clusters were affected by the difference in the SFE. In the case of EPKA = 20 keV, the ratio of glissile SIA clusters increased as the SFE decreased, which was not expected by a prediction based on the classical dislocation theory. The trend did not change after annealing at 1100 K for 100 ps. For vacancy clusters, few stacking fault tetrahedrons (SFTs) formed before the annealing. However, lower SFEs tended to increase the SFT fraction after the annealing, w...

A method for finding hidden chaotic attractors in the plasma system is presented. Using the Routh–Hurwitz criterion, the stability distribution associated with two parameters is identified to find the region around the equilibrium points of the stable nodes, stable focus-nodes, saddles and saddle-foci for the purpose of investigating hidden chaos. A physical interpretation is provided of the stability distribution for each type of equilibrium point. The basin of attraction and parameter region of hidden chaos are identified by excluding the self-excited chaotic attractors of all equilibrium points. Homotopy and numerical continuation are also employed to check whether the basin of chaotic attraction intersects with the neighborhood of a saddle equilibrium. Bifurcation analysis, phase portrait analysis, and basins of different dynamical attraction are used as tools to distinguish visually the self-excited chaotic attractor and hidden chaotic attractor. The Casimir power reflects the error power between the dissipative energy and the energy supplied by the whistler field. It explains physically, analytically, and numerically the conditions that generate the different dynamics, such as sinks, periodic orbits, and chaos.

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) interactions play important roles in diagnostic biomarkers and therapeutic targets for various human diseases. However, experimental methods for finding miRNAs associated with a particular lncRNA are costly, time consuming, and only a few theoretical approaches play a role in predicting potential lncRNA–miRNA associations. In this study, we have established a novel matrix factorization model to predict lncRNA–miRNA interactions, namely lncRNA–miRNA interactions prediction by logistic matrix factorization with neighborhood regularized (LMFNRLMI). Meanwhile, it only utilizes known positive samples to mine potential associations in data that lack negative samples. As a result, this new model obtains reliable performance in the leave-one-out cross validation (the AUC of 0.9319) and 5-fold cross validation (the AUC of 0.9220), which has significantly improved performance in predicting potential lncRNA–miRNA associations compared to other models. Furthermore, comparison with several other network algorithms, and test based on all kinds of similarity, our model successfully confirms the superiority of LMFNRLMI. Whereby, we hope that LMFNRLMI can be a useful tool for potential lncRNA–miRNA association identification in the future.

This study investigated water-insoluble corn flour (WICF) as a novel biosorbent for removing patulin from aqueous solutions, including contaminated fruit juices. Batch adsorption experiments were performed to assess the effect of granularity of WICF, adsorbent dosage, contact time, temperature, pH, and initial patulin concentration. The results showed that the maximum removal percentage of 92.21% was achieved at 37 °C, pH value of 4.0 in 100 µg/L patulin concentration for 25 hr. The adsorption data could be well fitted with the Freundlich isotherm model and the pseudo-first order model. Thermodynamic parameters indicated that mycotoxin adsorption is an endothermic and spontaneous process. Subsequently, scanning electron microscopy images showed obvious morphological changes in WICF after adsorbing patulin. Fourier transform infrared spectroscopy spectroscopic evidence demonstrated that the main functional groups involved in the adsorption were O-H, C = O and C-O groups. Practical applications Patulin was found as a contaminant in various fruit juices, which raised serious concerns about developing an effective and cheap adsorbent for detoxification of patulin toxin in fruit juice and their products. Water-insoluble corn flour was applied to strengthen the control of patulin for the first time. Results of this study indicated that water-insoluble corn flour has a strong ability to remove patulin from aqueous solutions and various fruit juices. Therefore, using water-insoluble corn flour as an adsorbent and combining the filtration process could be potentially applied in fruit juice industry for detoxification of patulin.

(1−x)(K0.42Na0.58)(Nb0.96Sb0.04)O3–x(Bi0.5Na0.5)0.90Mg0.10ZrO3 [(1−x)KNNS–xBNMZ] lead-free ceramics have been prepared by the normal sintering, and effects of BNMZ content on their phase structure, microstructure, and electrical properties have been systematically investigated. These ceramics with 0.045 ≤ x ≤ 0.05 possess a rhombohedral–tetragonal (R–T) phase boundary, as confirmed by the temperature dependence of dielectric properties and X-ray diffraction patterns. The grain size of the ceramics first increases and then decreases as the BNMZ content increases, and the ceramic with x = 0.06 possesses much smaller grains (

In this article, the problem of state observer design for a class of multi-input multi-output nonlinear systems is considered. Via state transformation and the constructive use of a Lyapunov function, the new observer design approach is addressed by introducing a parameter e in the observer. Some sufficient conditions are given which guarantee the estimation error to asymptotically converge to zero under adaptive conditions. An example is included to illustrate the method.

Pompe disease is due to a deficiency in acid-α-glucosidase (GAA) and results in debilitating skeletal muscle wasting, characterized by the accumulation of glycogen and autophagic vesicles. Given the role of lysosomes as a platform for mTORC1 activation, we examined mTORC1 activity in models of Pompe disease. GAA-knockdown C2C12 myoblasts and GAA-deficient human skin fibroblasts of infantile Pompe patients were found to have decreased mTORC1 activation. Treatment with the cell-permeable leucine analog l-leucyl-l-leucine methyl ester restored mTORC1 activation. In vivo, Pompe mice also displayed reduced basal and leucine-stimulated mTORC1 activation in skeletal muscle, whereas treatment with a combination of insulin and leucine normalized mTORC1 activation. Chronic leucine feeding restored basal and leucine-stimulated mTORC1 activation, while partially protecting Pompe mice from developing kyphosis and the decline in muscle mass. Leucine-treated Pompe mice showed increased spontaneous activity and running capacity, with reduced muscle protein breakdown and glycogen accumulation. Together, these data demonstrate that GAA deficiency results in reduced mTORC1 activation that is partly responsible for the skeletal muscle wasting phenotype. Moreover, mTORC1 stimulation by dietary leucine supplementation prevented some of the detrimental skeletal muscle dysfunction that occurs in the Pompe disease mouse model.

The problem of constructing full-order state estimators for a class of multi-input multi-output affine nonlinear systems is addressed. By using the Lipschitz condition jointly with the Lyapunov stability theory, a sufficient condition has been obtained that guarantee the asymptotic stability of the estimation error. Performance of the proposed approach are illustrated through a numerical example.

Previous studies have demonstrated that glucose disposal is increased in the Fyn knockout (FynKO) mice due to increased insulin sensitivity. FynKO mice also display fasting hypoglycaemia despite decreased insulin levels, which suggested that hepatic glucose production was unable to compensate for the increased basal glucose utilization. The present study investigates the basis for the reduction in plasma glucose levels and the reduced ability for the liver to produce glucose in response to gluconeogenic substrates. FynKO mice had a 5-fold reduction in phosphoenolpyruvate carboxykinase (PEPCK) gene and protein expression and a marked reduction in pyruvate, pyruvate/lactate-stimulated glucose output. Remarkably, de novo glucose production was also blunted using gluconeogenic substrates that bypass the PEPCK step. Impaired conversion of glycerol to glucose was observed in both glycerol tolerance test and determination of the conversion of (13)C-glycerol to glucose in the fasted state. α-glycerol phosphate levels were reduced but glycerol kinase protein expression levels were not changed. Fructose-driven glucose production was also diminished without alteration of fructokinase expression levels. The normal levels of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate observed in the FynKO liver extracts suggested normal triose kinase function. Fructose-bisphosphate aldolase (aldolase) mRNA or protein levels were normal in the Fyn-deficient livers, however, there was a large reduction in liver fructose-6-phosphate (30-fold) and fructose-1,6-bisphosphate (7-fold) levels as well as a reduction in glucose-6-phosphate (2-fold) levels. These data suggest a mechanistic defect in the allosteric regulation of aldolase activity.