Pulling cylindrical particles using a soft-nonparaxial tractor beam

In order to pull objects towards the light source a single tractor beam inevitably needs to be strongly nonparaxial. This stringent requirement makes such a tractor beam somewhat hypothetical. Here we reveal that the cylindrical shape of dielectric particles can effectively mitigate the nonparaxiality requirements, reducing the incidence angle of the partial plane waves of the light beam down to 45° and even to 30° for respectively dipole and dipole-quadrupole objects. The optical pulling force attributed to the interaction of magnetic dipole and magnetic quadrupole moments of dielectric cylinders occurs due to the TE rather than TM polarization. Therefore, the polarization state of the incident beam can be utilized as an external control for switching between the pushing and pulling forces. The results have application values towards optical micromanipulation, transportation and sorting of targeted particles

A machine learning-based model for predicting distant metastasis in patients with rectal cancer

BackgroundDistant metastasis from rectal cancer usually results in poorer survival and quality of life, so early identification of patients at high risk of distant metastasis from rectal cancer is essential.MethodThe study used eight machine-learning algorithms to construct a machine-learning model for the risk of distant metastasis from rectal cancer. We developed the models using 23867 patients with rectal cancer from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Meanwhile, 1178 rectal cancer patients from Chinese hospitals were selected to validate the model performance and extrapolation. We tuned the hyperparameters by random search and tenfold cross-validation to construct the machine-learning models. We evaluated the models using the area under the receiver operating characteristic curves (AUC), the area under the precision-recall curve (AUPRC), decision curve analysis, calibration curves, and the precision and accuracy of the internal test set and external validation cohorts. In addition, Shapley’s Additive explanations (SHAP) were used to interpret the machine-learning models. Finally, the best model was applied to develop a web calculator for predicting the risk of distant metastasis in rectal cancer.ResultThe study included 23,867 rectal cancer patients and 2,840 patients with distant metastasis. Multiple logistic regression analysis showed that age, differentiation grade, T-stage, N-stage, preoperative carcinoembryonic antigen (CEA), tumor deposits, perineural invasion, tumor size, radiation, and chemotherapy were-independent risk factors for distant metastasis in rectal cancer. The mean AUC value of the extreme gradient boosting (XGB) model in ten-fold cross-validation in the training set was 0.859. The XGB model performed best in the internal test set and external validation set. The XGB model in the internal test set had an AUC was 0.855, AUPRC was 0.510, accuracy was 0.900, and precision was 0.880. The metric AUC for the external validation set of the XGB model was 0.814, AUPRC was 0.609, accuracy was 0.800, and precision was 0.810. Finally, we constructed a web calculator using the XGB model for distant metastasis of rectal cancer.ConclusionThe study developed and validated an XGB model based on clinicopathological information for predicting the risk of distant metastasis in patients with rectal cancer, which may help physicians make clinical decisions. rectal cancer, distant metastasis, web calculator, machine learning algorithm, external validatio

Effect of vineyard soil variability on chlorophyll fluorescence, yield and quality of table grape as influenced by soil moisture, grown under double cropping system in protected condition

Environmental factors greatly influence grape quality. Among them, the effect of within-vineyard variability of soil in relation to soil moisture on table grape under protected condition has rarely been studied. In this present research, we investigated the influence of soil variability, in relation with soil moisture on chlorophyll fluorescence, yield and quality attributes of the “Summer Black” (Vitis vinifera L. × V. labruscana L.) table grape, popularly grown under double cropping system in protected covering in the southern part of China. The vineyard was divided vertically into three sites (lower, middle and upper, 192, 202 and 212 m above sea level, respectively) and data on soil moisture and other yield and quality parameters were recorded. Among the three vineyard sites, middle site resulted in higher yield compared to the upper and lower sites during winter and summer cropping cycles. However, compared to regular summer cycle, winter cycle provided grapevines with higher quality attributes. Polyphasic OJIP fluorescence transient exhibited a considerable increase in fluorescence intensity at J, I and P phase in the upper and middle sites compared to the lower site due to variation in soil moisture in both seasons. Values of fluorescence parameters including minimal fluorescence, relative variable fluorescence at phase J and I, the maximal quantum yield of photosystem II were also influenced by soil moisture in different sites. Different sites also exhibited a significant difference in total phenolics, flavonoid, antioxidant activity and individual anthocyanin which was influenced by available soil moisture. The present study shows that chlorophyll fluorescence OJIP transient can be used as a sensitive indicator to determine the moisture stress in grape grown in a varied soil. Double cropping proved to be a powerful technique to improve the fruit quality. This result may be useful for the table grape growers to better utilize the vineyard soil variability with water management to get higher yield and quality table grape under protected condition

Manipulating Steady Heat Conduction by Sensu-shaped Thermal Metamaterials

10.1038/srep10242Scientific Reports

Lead and copper-induced hormetic effect and toxicity mechanisms in lettuce (Lactuca sativa L.) grown in a contaminated soil

Lead (Pb) and copper (Cu) contamination seriously threatens agricultural production and food safety. This study aims to investigate Pb and Cu induced hormetic effect and toxicity mechanisms in lettuce (Lactuca sativa L.) and establish reliable empirical models of potentially toxic elements (PTEs) transfer in the soil–plant system. The content and distribution of Pb and Cu at subcellular levels in lettuce plants were examined using inductively coupled plasma-mass spectrometry, differential centrifugation and micro-X-ray fluorescence spectroscopy. The PTE-loaded capacity of Pb that ensures food safety was lower than that of Cu in the studied soil, but the PTE-loaded capacity of Pb that limits yield was higher than that of Cu. Lead in lettuce roots mainly accumulated in the cell wall (41%), while Cu mainly accumulated in the vacuoles (46%). The Pb and Cu were primarily distributed in the radicle of lettuce seeds under severe PTE stress, resulting in no seed development. Iron plaque formed on the root surface of lettuce seedlings and sequestered Pb and Cu via chelation. At the same concentration, lettuce was less tolerant to Cu in contaminated soil than Pb due to the higher activity of Cu ions in the soil. Lead was more phytotoxic to lettuce than Cu, however, since the radicle emerged from the seed under severe Cu levels, while it did not protrude under severe Pb levels. The potentially damaging effect of Pb in the visually healthy lettuce appeared to be higher than that of Cu under the same soil contamination level