The potential of Confocal micro-Raman spectroscopy in the quantitative analysis of pesticide (Chlorpyrifos, Omethoate) residues on orange surface is investigated in this work. Quantitative analysis models were established by partial least squares (PLS) using different preprocessing methods (Smoothing, First derivative, MSC, Baseline) for pesticide residues. For pesticide residues, the higher correlation coefficients (r) is 0.972 and 0.943, the root mean square error of prediction (RMSEP) is 2.05% and 2.36%, respectively. It is therefore clear that Confocal micro- Raman spectroscopy techniques enable rapid, nondestructive and reliable measurements, so Raman spectrometry appears to be a promising tool for pesticide residues.

Total green leaf area (GLA) is an important trait for agronomic studies. However, existing methods for estimating the GLA of individual rice plants are destructive and labor-intensive. A nondestructive method for estimating the total GLA of individual rice plants based on multiangle color images is presented. Using projected areas of the plant in images, linear, quadratic, exponential and power regression models for estimating total GLA were evaluated. Tests demonstrated that the side-view projected area had a stronger relationship with the actual total leaf area than the top-projected area. And power models fit better than other models. In addition, the use of multiple side-view images was an efficient method for reducing the estimation error. The inclusion of the top-view projected area as a second predictor provided only a slight improvement of the total leaf area estimation. When the projected areas from multi-angle images were used, the estimated leaf area (ELA) using the power model and the actual leaf area had a high correlation coefficient (R2 > 0:98), and the mean absolute percentage error (MAPE) was about 6%. The method was capable of estimating the total leaf area in a nondestructive, accurate and efficient manner, and it may be used for monitoring rice plant growth.

We proposed a new saccharides sensor developed by symmetrical optical waveguide (SOW)- based surface plasmon resonance (SPR). This unique MgF2/Au/MgF2/Analyte film structure results in longer surface plasmon wave (SPW) propagation lengths and depths, leading to an increment of resolution. In this paper, we managed to decorate the dielectric interface (MgF2 layer) by depositing a thin polydopamine film as surface-adherent that provides a platform for secondary reactions with the probe molecule. 3-Aminophenylboronic acid (3-PBA) is chosen to be the saccharides sense probe molecule in the present work. The aqueous humor of Diabetes and Cataract patient whose blood glucose level is normal are analyzed and the results demonstrated that this sensor shows great potential in monitoring the blood sugar and can be adapted in the field of biological monitoring in the future.

Breast cancer is one of the leading causes of cancer-related deaths in a global scenario. In the present study, biochemical changes exerted upon Pentoxifylline (PTX) treatment had been appraised in human breast cancer cells using Raman spectroscopy. There are no clinically approved methods to monitor such therapeutic responses available. The spectral profiling is suggestive of changes in DNA, protein and lipid contents showing a linear relationship with drug dosage. Further, multivariate analysis using principal-component based linear-discriminant-analysis (PC-LDA) was employed for classifying the control and the PTX treated groups. These findings support the feasibility of Raman spectroscopy as an alternate/adjunct label-free, objective method for monitoring drug-induced modifications against breast cancer cells.

In the human eye, accommodation is essential for functional vision. However, the mechanisms regulating accommodation and the ocular parameters affecting aberrations remain to be explored. In order to measure the alterations of ocular aberration and crystalline lens biometry during dynamic accommodative stimuli, we designed an optical coherence tomography with ultra-long penetration depth (UL-OCT) combined with a Shack–Hartmann wavefront sensor (SHWFS). This integrated set up measures human eye's anterior segment as well as monochromatic high-order aberrations (HOAs) with 6 μm resolution and (1/20) λ accuracy. A total of 10 healthy volunteers without ocular diseases were examined. Upon exposure to accommodative stimuli, the wavefront aberrations became larger. Among the anterior segment biometry, the anterior crystalline lens demonstrated significant curvature during accommodation and was the major cause of high-order aberration. These findings suggest that the front surface of the crystalline lens can significantly affect variation among aberrations, which is a key factor underlying the quality of human vision.

Focusing light though scattering media beyond the ballistic regime is a challenging task in biomedical optical imaging. This challenge can be overcome by wavefront shaping technique, in which a time-reversed (TR) wavefront of scattered light is generated to suppress the scattering. In previous TR optical focusing experiments, a phase-only spatial light modulator (SLM) has been typically used to control the wavefront of incident light. Unfortunately, although the phase information is reconstructed by the phase-only SLM, the amplitude information is lost, resulting in decreased peak-to-background ratio (PBR) of optical focusing in the TR wavefront reconstruction. A new method of TR optical focusing through scattering media is proposed here, which numerically reconstructs the full phase and amplitude of a simulated scattered light field by using a single phase-only SLM. Simulation results and the proposed optical setup show that the timereversal of a fully developed speckle field can be digitally implemented with both phase and amplitude recovery, affording a way to improve the performance of light focusing through scattering media.

Magnetic nanoparticle plays an important role in biomedical engineering, especially in tumor therapy. In this paper, a new technique has been developed by using the rapid moving magnetic nanoparticle under a low-frequency alternating magnetic field (LFAMF) to kill tumor cells. The LFAMF system which was used to drive magnetic nanoparticles (MNPs) was setup with the magnetic field frequency and power range at ~10–100 Hz and ~10–200mT, respectively. During the experiment, the LFAMF was adjusted at different frequencies and power levels. The experimental results show that the liver tumor cells (HepG2) mixed with MNPs (10 μg/mL) became partial fragments when exposed in the LFAMF with different frequencies (~10–100 Hz) and power (~10–200 mT), and the higher the frequency or the power, the more the tumor cells were killed at the same magnetic nanoparticle concentration. Conclusion: Tumor cells were effectively damaged by MNPs under LFAMF, which suggests that they had great potential to be applied in tumor therapy.

Noninvasive glucose monitoring development is critical for diabetic patient continuous monitoring. However, almost all the available devices are invasive and painful. Noninvasive methods such as using spectroscopy have shown some good results. Unfortunately, the drawback was that the tungsten halogen lamps usage that is impractical if applied on human skin. This paper compared the light emitting diode (LED) to traditional tungsten halogen lamps as light source for glucose detection where the type of light source plays an important role in achieving a good spectrum quality. Glucose concentration measurement has been developed as part of noninvasive technique using optical spectroscopy. Small change and overlapping in tungsten halogen results need to replace it with a more convenient light source such as LED. Based on the result obtained, the performance of LED for absorbance spectrum gives a significantly different and is directly proportional to the glucose concentration. The result shows a linear trend and successfully detects lowest at 60 to 160 mg/dL glucose concentration.

The purpose of this study was to develop a calibration model to evaluate the moisture content of tapioca starch using the near-infrared (NIR) spectral data in conjunction with partial least square (PLS) regression. The prediction ability was assessed using a separate prediction data set. Three groups of tapioca starch samples were used in this study: tapioca starch cake, dried tapioca starch and combined tapioca starch. The optimum model obtained from the baseline-offset spectra of dried tapioca starch samples at the outlet of the factory drying process provided a coefficient of determination (R2), standard error of prediction (SEP), bias and residual prediction deviation (RPD) of 0.974, 0.16%, -0.092% and 7.4, respectively. The NIR spectroscopy protocol developed in this study could be a rapid method for evaluation of the moisture content of the tapioca starch in factory laboratories. It indicated the possibility of real-time online monitoring and control of the tapioca starch cake feeder in the drying process. In addition, it was determined that there was a stronger influence of the NIR absorption of both water and starch on the prediction of moisture content of the model.

A recently proposed analytical hemodynamic model1 [S. Fantini, NeuroImage 85, 202–221 (2014)] is able to predict the changes of oxy, deoxy, and total hemoglobin concentrations (model outputs) given arbitrary changes in blood flow, blood volume, and rate of oxygen consumption (model inputs). One assumption of this model is that the capillary compartment is characterized by a single blood transit time. In this work, we have extended the original model by considering a distribution of capillary transit times and we have compared the outputs of both models (original and extended) for the case of sinusoidal input signals at different frequencies, which realizes the new technique of coherent hemodynamics spectroscopy (CHS). For the calculations with the original model, we have used the mean value of the distribution of capillary transit times considered in the extended model. We have found that, for distributions of capillary transit times having mean values around 1 s and a standard deviation less than about 45% of the mean value, the original and extended models yield the same CHS spectra (i.e., model outputs versus frequency of oscillation) within typical experimental errors. For wider capillary transit time distributions, the two models yield different CHS spectra. By assuming that Poiseuille's law is valid in the capillary compartment, we have related the distribution of capillary transit times to the distributions of capillary lengths and capillary speed of blood flow to calculate the average capillary and venous saturations. We have found that, for standard deviations of the capillary transit time distribution that are less than about 80% of the mean value, the average capillary saturation is always larger than the venous saturation. By contrast, the average capillary saturation may be less than the venous saturation for wider distributions of the capillary transit times.