Functional networks have largely been identified in

Functional networks have largely been identified in task-based data by graph theory methods, where synchronized activity across different regions is thought to reflect intrinsic connectivity (Shafto and Tyler, 2014). Networks are formed from the wavelet coherence of multiple head electrode points and are thought to be functionally specialized by virtue of their interregional connectivity. Much of our understanding of ephrin receptor connectivity rests on the way that it is measured and modeled. We consider a functional connective model approach: it has its basis in graph theory that aims to describe the network topology of (undirected) connections of the sort measured by noninvasive functional connectivity between remote sites. After brain network is constructed based on wavelet coherence, different time stages are divided during the stimuli process, the module is got by minimum spanning tree in every stage, and these are applied in dynamic programing in different states to construct the dynamic evolution model. The aim of the present study was to evaluate a possible correlation between the brain connectivity architecture and dynamic evolution processing as extracted from EEG recordings by dynamic model. EEG recording in the brain functional connectivity via wavelet coherence can be technically challenging. We aimed to assess the feasibility and the efficacy of auditory stimuli EEG (Lachaux et al., 2002).

Brain network construct and analysis
Functional connectivity between brain regions is defined as the statistical dependence between neurophysiological signals in different brain areas and is typically determined by calculating the relationship between regional times series using wavelet coherence, The nodes of the network are EEG channels, and the edges of the network are weighed by the wavelet coherence values, a weighted graph is a mathematical representation of a set of elements (vertices) that may be linked through connections of variable weights (edges). In the present study, weighted and undirected networks were built. The vertices of the networks are the estimated cortical sources in the EEG, and the edges are weighted by the wavelet coherence within each pair of vertices. The undirected networks are constructed based on the threshold by the weighted Clustering coefficient and Weighted Characteristic Path length , and module is got by minimum spanning tree. The process is as shown in Fig. 1.

Conclusion
The model indicates that a complete cognitive control process is perceptual detection, identification detection, and conflict resolution during the auditory Stroop task. Understanding the role EEG oscillations is important for comprehending mechanisms of cognitive decline in the network dynamics of auditory stimuli and could serve as a model for understanding large-scale brain network dynamics and their relation to other cognitive phenomena or structural modulations. This study opens interesting avenues into future researches investigating eventual modifications of brain connectivity in the evolution of neurodegenerative processes beginning at the very early, pre-clinical stages. Node degree is used to construct the model in this paper, in the future, more topological parameters are considered to build the model. There are still a few details that need ironing out, for example, the length of the time window, dynamic programing algorithm optimization (Fares et al., 2015), etc. In brief, such methodologies will be suitable for capturing the dynamic evolution of the time varying connectivity patterns that reflect certain cognitive tasks or brain pathologies.

Acknowledgements
Our thanks to supports from the National Natural Science Foundation of China (61171186, 61271345, 61671187), Key Laboratory Opening Funding of MOE-Microsoft Key Laboratory of Natural Language Processing and Speech (HIT.KLOF.20150xx, HIT.KLOF.20160xx), Shenzhen science and technology project (JCYJ20150929143955341), and the Fundamental Research Funds for the Central Universities (HIT.NSRIF.2012047). Heilongjiang Provincial Department of Education Science and Technology Research Project (12533051), The Project of young talents of Heilongjiang University of Science and Technology of China in 2013 (NO. Q20130106).

Another individual difference variable relevant in the current

Another individual difference variable relevant in the current context is seafaring experience. It is plausible that previous experience with working in ICEs could familiarize individuals with what to expect in terms of stressors in the environment, and in extension equip them with adequate coping strategies [9]. One could therefore conceive of seafarers with greater experience developing strategies for dealing with stress over long voyages. Since experience and responsibility tend to coincide with age, a contrasting ephrin receptor could be that work-related stress increases with experience and responsibility, because work-related stress tends to increase with age. Griffiths et al [18], for instance, reviewed several large scale studies related to age and stress, and concluded that work-related stress increases with age, peaking at about 50–55 years.
To achieve these aims, we sampled seafarers from two different maritime organizations. One sample consisted of seafarers working on supply vessels serving the offshore oil and gas industry. The other sample consisted of seafarers working on board combined cargo and passenger roll-on/roll-off (ro-ro) ferries. In addition to providing two different maritime contexts in which to explore our aims, this design also allows for comparing the two maritime contexts in terms of fatigue.

Materials and methods

Results
Fig. 1 depicts the relationships between duration at sea and fatigue and sleep for the ro-ro ferry sample. As is evident from the figure, no discernible linear relations were evident between duration at sea with either subjective sleep quality or fatigue. This is further corroborated by the null correlations presented in Table 1.
Fig. 2 displays the corresponding relations for the supply vessel sample. Again, there did not seem to be much of a relation between duration at sea and sleep quality or fatigue. Table 2 nevertheless shows that there was indeed a small, but statistically significant, positive relation between duration at sea and fatigue (r = 0.10, p = 0.046).
We next performed a series of regression analyses regressing fatigue and sleep quality on our explanatory variables. In the ro-ro ferry sample, the explanatory variables were seafaring experience, duration at sea, environmental stressors and PsyCap. In addition, we included age and sex as control variables. Because of missing values on the explanatory and criterion variables, our sample size was reduced to n=290 (n=291 for the analysis involving sleep quality). The results from the series of regressions in the ro-ro ferry sample are presented in Tables 3 and 4.
As can be seen from Tables 3 and 4, environmental stress and PsyCap both significantly predicted fatigue and sleep quality. Seafarers reporting being disturbed by environmental factors also report poorer sleep quality (B = 0.26, 95% confidence interval: 0.15–0.37) and report being more fatigued (B = 0.53, 95% confidence interval: 0.24–0.82). PsyCap, by contrast, was negatively related to both criteria, with B = −0.46 (95% confidence interval: −0.92 to −0.01) for fatigue and B = −0.26 (95% confidence interval: −0.47 to −0.06) for poor sleep quality. Combined, our explanatory variables explained 22.3% of the variance in fatigue and 18.3% of the variance in sleep quality.
Entering the product terms in Step 2 of the regression analyses revealed a significant interaction between PsyCap and duration at sea for both fatigue and sleep quality, explaining an additional 2.3% and 1.1% of the variance in fatigue and poor sleep quality, respectively. To probe these significant interactions further, we computed the regions of significance using the JN technique. A plot visualizing the results for the conditional effects of duration at sea on fatigue is presented in Fig. 3. Duration at sea can be seen to have a positive ephrin receptor relation with poor sleep quality at lower levels of the moderator PsyCap, and a negative relation at the extremes of the moderator PsyCap. The region of significance can be defined as the values of the moderator for which the confidence interval for the conditional effect does not contain the value zero. Fig. 3 thus shows X-chromosome the conditional effect of duration at sea on fatigue is only statistically significant at very high levels of PsyCap, at values of 5.2 and above, to be precise.

AM fungal root colonization in host plants is nonspecific

AM fungal root colonization in host plants is nonspecific and more than one ephrin receptor of AM fungi have been found across multiple plant species (Boyetchko and Tewari, 1990; Simpson and Daft, 1990; Tewari et al., 1993). The potential of native AM fungi that improve the growth and nutrient uptake of crop plants such as sorghum is therefore of great interest. Effective AM fungi inocula might be an alternative source for sorghum biofertilizer and for sustainable agriculture. The objective of this experiment was to find suitable AM fungal species that can improve the production of sorghum.

Materials and methods

Results and discussion

Conflict of interest

Acknowledgments
This study was financially supported by the Kasetsart University Research and Development Institute (KURDI) (grant no. 04111387), Bang Kean, Bangkok, Thailand. The authors would like to express their sincere thanks to Assoc. Prof. Poonpilai Suwanarit from the Department of Microbiology, Prof. Dr. Ngampong Kongkathip from the Department of Chemistry, Faculty of Science, Kasetsart University, Thailand and Ms. Yadana Nath Desmond, CPRE, Teachers College Columbia University, USA, for fruitful discussion and valuable comments.

Introduction
The application of entomopathogenic microorganisms for the control of insect pests is one of the alternative tactics to reduce pesticide use as fungal spores of some biological control agents have been regarded as potential alternatives to agrochemicals because they can often be easily produced and may be adapted to survive unfavorable conditions (Qiu et al., 2013).
The utilization of the fungal genus Aschersonia for control of insect pests has a long history and has been studied extensively in other countries. Aschersonia aleyrodis was the first fungal species used for the control of insect pests in North America with the successful control of citrus whiteflies in Florida being achieved in the early 1900 s through the introduction of A. aleyrodis into a citrus orchard to seed epizootic disease in the whitefly population (Burger, 1921; Liu et al., 2006). Aschersonia spp. are not hazardous to humans and some species can be potential biological control agents against insect pests (Qiu et al., 2013).
Aschersonia placenta Berkeley and Broom belongs to the Ascomycota, Deuteromycotina, Sordariomycetes, Hypocreomycetidae, Hypocreales, Clavicipitaceae. This fungus has been recognized as an important biological control agent able to cause spectacular epizootic disease in whiteflies (Aleyrodidae) and scale insects (Coccidae) in the tropics and subtropics (Evans and Hywel-Jones, 1990; Fransen, 1990; Zhu et al., 2008). A. placenta has morphological characteristics similar to A. aleyrodis which means it could have great potential to be used to control whiteflies (Wang et al., 2013).
Black parlatoria (Parlatoria ziziphi (Lucas) [Hemiptera: Diaspididae]) is an important pest of citrus in many countries such as Brazil, China, Egypt, Iran, Italy, France, Libya, Nigeria, Puerto Rico, Taiwan, and Tunisia (Hanene, 2011). It was noted that in some countries the scale insect may not be considered as a pest, but a population occasionally causes problems in localized areas (Hanene, 2011). In Thailand, to date P. ziziphi populations have reached outbreak levels only in certain areas, but in the future, P. ziziphi may spread and cause problems in citrus orchards. Hence, prevention by gaining some basic information is necessary. The destruction of plants by P. ziziphi was described by Hanene (2011) as follows. The insect absorbed sap on the leaves of pomelo which caused the fruit color to become yellow—a state known as “chlorosis”. The immature fruits, which were infested by this insect species, had a hard pulp, stopped development and later dropped from the tree. The infestation on mature fruits had no effect on the pulp but reduced market prices.

Mesoporous materials are defined as having pore diameters of

Mesoporous materials are defined as having pore diameters of between 2 and 50nm. Catalysis that is based on these materials normally provides benefits in reactions where diffusion limitations play an important role. Substantial work has been carried out on the use of silica [19] and alumina [20] in the semi-hydrogenation of alkynes in an effort to overcome diffusion resistance [21]. The hydrogenation of alkynes on solid Pd surfaces is generally structure sensitive, which is an important characteristic in the understanding of such catalytic processes [15]. Unselective hydrogenation proceeds on hydrogen-saturated β-hydride, whereas selective hydrogenation has only been possible after decoupling bulk properties from the surface events [22]. Only gas phase surface hydrogen is able to generate alkenes [23].
Although the highly selective semi-hydrogenation of alkynes using heterogeneous catalysts under mild conditions has recently been investigated [24–26], the production of fine chemicals requires new, cheaper and more environmentally sustainable technologies, which not only utilize heterogeneous catalysis but also take into account reactor engineering aspects and non-conventional energy sources. Classic catalytic hydrogenation is carried out under a hydrogen ephrin receptor and often at elevated temperatures in pressure resistant reactors that usually display slow heating/cooling rates. This can negatively affect selectivity and generate unwanted side reactions. The beneficial effects of ultrasound (US) are well documented in the literature [2,27]. This non-conventional enabling technology furthers process intensification and combines safer protocols, cost reduction and energy savings [28]. Ultrasound has been applied to the activation of heterogeneous catalytic hydrogenation since the early 1980s [29–31].
Significant enhancements in selectivity, rates and yields as well as milder reaction conditions in both homogeneous and heterogeneous systems are all recognized hallmarks of sonication [32–34], which has also been shown to enhance catalyst robustness, selectivity and activity [35–37]. It also improves organic synthesis and accelerates the hydrogenation of unsaturated hydrocarbons [29].
The chemical and physical effects of US arise from the phenomenon of cavitation which produces extreme but localized conditions. When a cavitation bubble violently collapses near a solid surface, high-speed jets of liquid are driven into particle surfaces [32]. The high-speed liquid microjets and violent cavity implosion driven shock waves grant US its significant mechanical effects, such as increasing the surface area of particles, changing surface morphology, composition and particle size as well as accelerating dissolution and/or renewing the surface of a solid reactant or catalyst [38]. Besides triggering free radical reactions, it is also known to produce high localized temperatures and pressures [39]. Catalyst activity is therefore increased by catalyst surface deformation which exposes fresh, highly active surfaces and reduces diffusion length in catalyst pores [38]. The local turbulent flow associated with acoustic streaming also improves mass transfer between the liquid phase and the surface, thus increasing observed reaction rates [40].
However, little is known about the effects of US in the semi-hydrogenation of alkynes. The excellent selective reduction results provided by sonochemical protocols in previous studies have prompted us to explore the promise of the US-assisted semi-hydrogenation of alkynes [8,41]. The aim of the present work is to investigate the influence of US on the activity and selectivity of the Pd/Boehmite-catalyzed hydrogenation of phenylacetylene (PA), diphenylacetylene (DPA) and 2-butyne-1,4-diol (ByD). Pd content, specific surface areas and other catalyst textural properties have been evaluated using ICP, nitrogen adsorption isotherms and TEM studies. This article therefore describes the effects of hydrogenation factors, such as substrate and catalyst proportions, hydrogen pressure, temperature and quinoline content on activity and selectivity. In addition, US has been shown to cause significant metal leaching when used with the standard Lindlar catalyst (Pd-Pb on calcium carbonate) [42]. We therefore also wanted to investigate whether our lead-free catalysts show higher robustness under sonication and reduced metal leaching.

br Experimental The workflow from

Experimental
The workflow from surgical tissue resection to Monte Carlo leave-one-third-out cross-validated classification is schematically illustrated in Fig. 1. A strict standard operating procedure was followed to ensure maximum reproducibility of sample handling and spectrum collection. Colorectal cancer tissue was surgically removed according to actual clinical standard procedures. Absorbance infrared spectra were collected from tissue areas of the washed colon lumen. All samples that were characterised by spectroscopy underwent a routine histopathological assessment by expert pathologists, who also provided the grading information, as being the diagnostic gold standard.

Results and discussion
Collection of infrared spectra from the resected tissue surface with the fibre optical probes was performed in a straightforward manner. In previous studies, the spectral influence of water on the sampled surface was reduced by air-drying. Whereas this step was efficient in the reduction of external water absorption, the sample inner-water strongly contributed to the recorded spectra [38]. As a clinically acceptable alternative, we present sampling procedures compatible with colonoscopy, i.e., accepting wet tissue surfaces. The quality of the histological examination due to the non-invasive spectral analysis was unaffected and undisputed.
Equivalent spectra were recorded with both fibre-optic probes, as demonstrated with the exemplary absorbance spectra of distilled water (Fig. 3). As expected, system specific spectral contributions were not observed, as both were using two internal reflections within the diamond ATR-elements. With the improved spectral quality provided by the Matrix MF/A.R.T. Photonics system, a faster ephrin receptor measurement with a fewer number of co-added interferograms was possible.

Conclusion
The utilisation of two different systems and the successful combination of the spectral data indicated the applicability of the technique in multi-centric studies. So far, the suitability of the presented technology for discrimination between healthy and tumorous areas was verified. A two-step prediction system for direct grading assessment was developed within the presented study. In future, FTIR-spectroscopy might help to detect if an organ invasion has been caused by a malign tumour, or if changes are just due to inflammation. During a surgical operation, this information is very important for the decision of giving up ephrin receptor (e.g., a long part of gut) or taking risk of a complex restoration (e.g., of blood vessels). Using a further validated set of spectral biomarkers with an endoscopic spectrometer system, a colonoscopist or surgeon could gather immediate insights into the tumour malignancy. This could supplement the essential histopathology with an immediate spectroscopic assessment in-situ.

Acknowledgements

Introduction
Nowadays, Raman spectroscopy has been widely used in biological applications [1–4] including disease detection [5–9], investigations of metabolism [10], bacteria identification [11–15], intraoperative decision making [16] and forensic analysis [17]. These applications benefit from developments of not only instrumentation and computation, but also chemometrics [17,18]. The sensitivity of Raman spectroscopy is enhanced by chemometrics, which is capable of distinguishing subtle between-class spectral differences, even if this is not possible with the naked eye [19,20]. Moreover, chemometrical methods make biological diagnostics more objective since little or even no human intervention is required. Last but not least, chemometrics dramatically speeds up biological diagnostic procedures and it becomes possible to deal with large-size Raman spectral datasets within an acceptable time.
The basic idea of chemometrics is quite simple. First statistical models are built based on a certain number of known Raman spectra, namely a training set. The models can be qualitative or quantitative, depending on the tasks. Afterwards these models are saved to be used for predicting Raman spectra of unknown samples. These unknown samples may be measured with different instruments or under different conditions as the training samples. In this case, the unknown Raman spectra feature wavenumber shifts and intensity variations caused by changes of experimental conditions [21,22]. Such spectral changes may be tolerated by the current statistical models, if they are smaller compared to the between-group differences. However, there is always the risk of failure, especially if wavenumber positions are important for the statistical model, for example those involving wavenumber selection techniques. More caution is required for biological applications, because the between-group spectral differences are usually tiny. Thus the statistical models are strongly affected by the spectral changes caused by environmental changes. Consequently, the prediction accuracy significantly degrades for a new dataset measured under different conditions compared with the conditions of the training set [23,24,22]. Unfortunately, it requires a large number of samples to build a new model for this new dataset, which may be expensive or even impossible. Therefore a model transfer problem comes up, where the training set and the new dataset is respectively termed as primary and secondary set [25]. The corresponding methods intend to achieve precise predictions for both datasets by either making the two datasets more similar or reinforcing the current models to tolerate variations caused by the conditions changes. There are two mechanisms for model transfer problems [23,21]: spectral standardization and model updating.

br Multiple linear regression analysis using

Multiple linear regression analysis using all variables as factors (Model 1) demonstrated that weight, BMI, and tidal volume were independently associated with the bilateral excursion of the diaphragms (all P < 0.05) after adjusting for other clinical variables, including age, gender, smoking history, height, VC, %VC, FEV1, FEV1%, and %FEV1. There were no significant associations between the excursion of the diaphragms and variables including age, gender, smoking history, height, VC, %VC, FEV1, FEV1%, and %FEV1 (Table 4). Additionally, a multiple linear regression model using age, gender, BMI, tidal volume, VC, FEV1, and smoking history as factors (Model 2) was also fit as a sensitivity analysis, taking into account the correlation among variables (eg, BMI, height, and weight; VC and %VC; FEV1, FEV1%, and %FEV1). Model 2 (Supplementary Data S1) gave results consistent with Model 1 (Table 4): higher BMI and higher tidal volume were independently associated with the increased bilateral excursion of the diaphragms (all P < 0.05). The adjusted R2 in Model 1 was numerically higher than that in Model 2 (right, 0.19 vs. 0.16, respectively; left, 0.16 vs. 0.13, respectively).

Discussion

Our study determined the average excursion of the diaphragms during tidal breathing in a standing position in a health screening center cohort using dynamic chest radiography (“dynamic X-ray phrenicography”). These findings are important because they provide reference values of diaphragmatic motion during tidal breathing useful for the diagnosis of diseases related to respiratory kinetics. Our study also suggests that dynamic X-ray phrenicography is a useful method for the quantitative evaluation of diaphragmatic motion with a radiation dose comparable to conventional posteroanterior chest radiography (22).

Our study demonstrated that the average excursions of the bilateral ephrin receptor during tidal breathing (right: 11.0 mm, 95% CI 10.4 to 11.6 mm; left: 14.9 mm, 95% CI 14.2 to 15.5 mm) were numerically less than those during forced breathing in previous studies using other modalities 2; 7 ;  8. Using fluoroscopy, Alexander reported that the average right excursion was 27.5 mm and the average left excursion was 31.5 mm during forced breathing in the standing position in 127 patients (2). Using ultrasound, Harris et al. reported that the average right diaphragm excursion was 48 mm during forced breathing in the supine position in 53 healthy adults (7). Using MR fluoroscopy, Gierada et al. reported that the average right excursion was 44 mm and the average left excursion was 42 mm during forced breathing in the supine position in 10 healthy volunteers (8). The difference in diaphragmatic excursion during tidal breathing versus forced breathing is unsurprising.

Our study showed that the excursion and peak motion speed of the left diaphragm are significantly greater and faster than those of the right. With regard to the excursion, the results of our study are consistent with those of previous reports using fluoroscopy in a standing position 2 ;  3. However, in the previous studies evaluating diaphragmatic motion in the supine position, the asymmetric diaphragmatic motion was not mentioned 7 ;  8. The asymmetric excursion of the bilateral diaphragm may be more apparent in the standing position, but may not be detectable or may disappear in the supine position. Although we cannot explain the reason for the asymmetry in diaphragmatic motion, we speculate that the presence of the liver may limit the excursion of the right diaphragm. Regarding the motion speed, to the best of our knowledge this study is the first to evaluate it. The faster motion speed of the left diaphragm compared to that of the right diaphragm would be related to the greater excursion of the left diaphragm.