In order to explore the application of the new integrated intelligent spore capture system developed in China in the prediction of cucumber downy mildew and cucumber powdery mildew, the main working parameters of the integrated intelligent spore capture system, such as the presence or absence of air cutting head, the height of air collection port and the time of air collection, were optimized by identifying the morphology of captured spores in the case of natural disease in the field. The relationship between the disease index of cucumber downy mildew and cucumber powdery mildew in greenhouse and the amount of spores captured was analyzed through the dynamic monitoring of disease and spores. The results show that when the air cutting head is not installed, the height of the air collection port is 70 cm, and the period of 10: 00–10: 30 was beneficial to the capture of spores. The disease index of cucumber downy mildew and cucumber powdery mildew had a strong positive correlation with the total amount of spores captured for 7 consecutive days. Continuous monitoring of cucumber downy mildew sporangia and rapid increase in the number is a predictor of the occurrence or rapid increase of cucumber downy mildew. The conidia of cucumber powdery mildew were not detected before the disease onset, and the number of conidia captured was still small at the peak of the disease. The research shows that the integrated intelligent spore capture system is suitable for the prediction of cucumber downy mildew, but there are still some problems in the prediction of cucumber powdery mildew.

The possibility of preoperative prediction of pathologic complete response in rectal cancer has been studied in order to identify patients who would respond to neoadjuvant therapy and to individualize therapeutic strategies. Endoscopic ultrasound of the rectum is an accurate method for the evaluation of local tumor and lymph node invasion. Objective: To evaluate the potential of endoscopic ultrasound as a predictor of complete pathological response to neoadjuvant treatment in patients with locally advanced rectal cancer. Material and methods: Retrospective study of patients with rectal cancer from January 2014 to December 2016. Results: We obtained a statistical association between T stage by endoscopic ultrasound and complete pathological response (p = 0.015). It is not so for N, sphincter involvement, circumferential involvement and maximum tumor thickness (p = 0.723, p = 0.510, p = 0.233 and p = 0.114, respectively). When multivariate logistic regression analysis was applied to assess the degree of influence of the predictor variables on pathologic response, none of these variables was associated with complete pathologic response. Conclusion: Prediction of pathologic complete response in rectal cancer has been considered as the crucial point upon which treatments for rectal cancer could be individualized. So far, no imaging method has been able to demonstrate efficacy in predicting complete pathologic response, and in turn there is no direct association between any endosonographic finding that can accurately predict it.

This article explored mineral resources and their relation to structural settings in the Central Eastern Desert (CED) of Egypt. Integration of remote sensing (RS) with aeromagnetic (AMG) data was conducted to generate a mineral predictive map. Several image transformation and enhancement techniques were performed to Landsat Operational Land Imager (OLI) and Shuttle Radar Topography Mission (SRTM) data. Using band ratios and oriented principal component analysis (PCA) on OLI data allowed delineating hydrothermal alteration zones (HAZs) and highlighted structural discontinuity. Moreover, processing of the AMG using Standard Euler deconvolution and residual magnetic anomalies successfully revealed the subsurface structural features. Zones of hydrothermal alteration and surface/subsurface geologic structural density maps were combined through GIS technique. The results showed a mineral predictive map that ranked from very low to very high probability. Field validation allowed verifying the prepared map and revealed several mineralized sites including talc, talc-schist, gold mines and quartz veins associated with hematite. Overall, integration of RS and AMG data is a powerful technique in revealing areas of potential mineralization involved with hydrothermal processes.

Ebola virus is a potent infectious disease virus that can cause Ebola haemorrhagic fever caused by human and primate. It has high mortality and easy infectivity to form a great obstacle to the steady development of human society. The profound understanding of the virus is particularly important harm. In this paper, a number of mathematical models are established to solve this problem. The software is used to analyze and predict the propagation of Ebola virus. The residual analysis is used to test the model. Finally, the effects of various control measures on controlling the epidemic are analyzed. In order to solve the problem, we will establish the infectious disease model to dynamically describe the spread of the virus in the 'virtual orangutan population'. Considering that the latent population is analyzed in this question, we will improve the model. Join the latent group (), and the migrants are divided into self-healing () and the dead (), to establish a suitable solution to this problem model. According to the relevant data given in the title, differential equations were established. For the second question, this question involves the one-way transmission of the virus across the species, so we can improve the model, on the basis of human contact with orangutans infected groups, the establishment of a one-way model to solve this problem. On the basis of the problem one, the differential equation is established, the model is predicted and tested. In the case of question 3, the number of human susceptible groups is much higher than that of the orangutan infection group by comparing the relevant data with the increase of the cure rate to 80% after the intervention of the outside experts. Therefore, the original data of human populations from experts can be ignored. Since then the virus spreads within a single species, the differential equation can be established according to the model in question 1 and the data values in the virtual human population are predicted. For question 4, the effect of the measures such as the strict enforcement of the various epidemic control measures and the improvement of the drug effect on the control of the epidemic are analyzed by comparing the above-mentioned models with the control measures.

There has been a growing interest in studying dysfunctional personality traits in the workplace. In line with this trend, this study examines how the Dark Triad personalities (Machiavellianism, narcissism, and psychopathy) can predict innovative work behavior. Additionally, the study builds on Trait Activation Theory and proposes a moderating effect of training satisfaction on this relationship. The purpose of this study is to understand if the Dark Triad traits predict innovative behavior while simultaneously examining the role of training satisfaction in channeling these traits toward innovative behavior. A questionnaire-based survey was conducted on the five largest telecommunication companies in Pakistan. The data gathered was analyzed using structural equation modeling. Results established a positive relationship between each trait of the Dark Triad and innovative work behavior. Moreover, training satisfaction was found to moderate the relationship between the psychopathy trait and innovative work behavior. In light of these findings, the study contributes to personality-behavior research in organizations by demonstrating that the Dark Triad predicts innovative work behavior in managers and that the innovative behaviors associated with the psychopathy trait can be enhanced in the presence of training satisfaction.

Heat removal has become an increasingly crucial issue for microelectronic chips due to increasingly high speed and high performance. One solution is to increase the thermal conductivity of the corresponding dielectrics. However, traditional approach to adding solid heat conductive nanoparticles to polymer dielectrics led to a significant weight increase. Here we propose a dielectric polymer filled with heat conductive hollow nanoparticles to mitigate the weight gain. Our mesoscale simulation of heat conduction through this dielectric polymer composite microstructure using the phase-field spectral iterative perturbation method demonstrates the simultaneous achievement of enhanced effective thermal conductivity and the low density. It is shown that additional heat conductivity enhancement can be achieved by wrapping the hollow nanoparticles with graphene layers. The underlying mesoscale mechanism of such a microstructure design and the quantitative effect of interfacial thermal resistance will be discussed. This work is expected to stimulate future efforts to develop light-weight thermal conductive polymer nanocomposites.