Detection of Heavy Metal Ions by Ratiometric Photoelectric Sensor

In recent years, heavy metal pollution has become increasingly serious. Heavy metals exist in an environment mainly in the form of ions (heavy metal ions, HMs). They can contaminate food, water, soil, and the atmosphere, leading to serious harm to plants and animals. With high bioavailability and nonbiodegradability, HMs can accumulate through biomagnification. Consequently, heavy metal pollution has become the cause of many fatal diseases threatening human health and ecological environment. Therefore, the accurate detection of HMs is vital and necessary. In this paper, the harm and limit standards of heavy metals were systematically summarized and the common analysis methods were overviewed and compared. Specifically, the latest research progress of ratiometric photoelectric sensor, including optical and electrical sensor, were mainly described. The research status and advantages and disadvantages of a photoelectric sensor were summarized. Furthermore, the future directions were proposed, which provided the reference for the further research and application of the ratiometric photoelectric sensor

Data for: A process to acquire essential oil by distillation concatenated liquid-liquid extraction and flavonoids by solid-liquid extraction simultaneously from Helichrysum arenarium inflorescences under ionic liquid-microwave mediated

Supplementary materia

Mean latencies and their standard deviations (ms) of each S1-evoked potential for AWS and AFS and the results of <i>t</i>-tests.

Mean latencies and their standard deviations (ms) of each S1-evoked potential for AWS and AFS and the results of t-tests.</p

Mean latencies and standard deviations (ms) of S-N2 and P3 for AWS and AFS.

Mean latencies and standard deviations (ms) of S-N2 and P3 for AWS and AFS.</p

The S1-evoked ERPs for AWS (red line) and AFS (black line).

The mean amplitudes of ERPs at different electrodes are presented. Examples of S1-N1 and S1-N2 are shown at Fz, and examples of S1-P2 and S1-P3 are shown at Pz.</p

Mean RTs, ACCs, FAs and their standard deviations for AWS and AFS.

Mean RTs, ACCs, FAs and their standard deviations for AWS and AFS.</p

The mean slope values and standard deviations at the nine electrodes for AFS and AWS.

<p>The mean slope values and standard deviations at the nine electrodes for AFS and AWS.</p

Speech Timing Deficit of Stuttering: Evidence from Contingent Negative Variations

<div><p>The aim of the present study was to investigate the speech preparation processes of adults who stutter (AWS). Fifteen AWS and fifteen adults with fluent speech (AFS) participated in the experiment. The event-related potentials (ERPs) were recorded in a foreperiod paradigm. The warning signal (S1) was a color square, and the following imperative stimulus (S2) was either a white square (the Go signal that required participants to name the color of S1) or a white dot (the NoGo signal that prevents participants from speaking). Three differences were found between AWS and AFS. First, the mean amplitude of the ERP component parietal positivity elicited by S1 (S1-P3) was smaller in AWS than in AFS, which implies that AWS may have deficits in investing working memory on phonological programming. Second, the topographic shift from the early phase to the late phase of contingent negative variation occurred earlier for AWS than for AFS, thus suggesting that the motor preparation process is promoted in AWS. Third, the NoGo effect in the ERP component parietal positivity elicited by S2 (S2-P3) was larger for AFS than for AWS, indicating that AWS have difficulties in inhibiting a planned speech response. These results provide a full picture of the speech preparation and response inhibition processes of AWS. The relationship among these three findings is discussed. However, as stuttering was not manipulated in this study, it is still unclear whether the effects are the causes or the results of stuttering. Further studies are suggested to explore the relationship between stuttering and the effects found in the present study.</p></div

Peak amplitudes for AWS and AFS.

<p>The mean peak amplitudes and the standard deviations of S2-N2 and S2-P3 elicited by the Go and the NoGo signals are shown for AWS and AFS.</p

Participants, biographical data.

<p>Participants, biographical data.</p