Refugees: Achievement and Conflict

Currently, there are more than 30 million refugees and internally displaced people in the world. Since the 1970s, after the Vietnam War, international organizations and many countries have supported refugees financially, however, they all have different definitions for a refugee. Refugees who desire peace or freedom and resettle in new countries have had remarkable economic, social, and educational achievement, especially Indochinese people in the US. However, refugees who flee from conflicts have often faced new conflicts in their host society. Both refugees and the host countries experience economic and social burden, however, refugees struggle and try to escape from their economic dependency from the local government. If refugee achievements continue, they could exceed the US educational and social norm in the future

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Tea trees are kept in shaded locations to increase their chlorophyll content, which influences green tea quality. Therefore, monitoring change in chlorophyll content under low light conditions is important for managing tea trees and producing high-quality green tea. Hyperspectral remote sensing is one of the most frequently used methods for estimating chlorophyll content. Numerous studies based on data collected under relatively low-stress conditions and many hyperspectral indices and radiative transfer models show that shade-grown tea performs poorly. The performance of four machine learning algorithms—random forest, support vector machine, deep belief nets, and kernel-based extreme learning machine (KELM)—in evaluating data collected from tea leaves cultivated under different shade treatments was tested. KELM performed best with a root-mean-square error of 8.94 ± 3.05 μg cm−2 and performance to deviation values from 1.70 to 8.04 for the test data. These results suggest that a combination of hyperspectral reflectance and KELM has the potential to trace changes in the chlorophyll content of shaded tea leaves

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

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Quantifying chlorophyll-a and b content in tea leaves using hyperspectral reflectance and deep learning

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Unilateral abnormality of initial motor-evoked potential in the upper limb detected during lumbar spine surgery: a case report

Abstract Background We present a case with abnormal findings of initial motor-evoked potential (MEP) in the left upper limb after prone positioning during lumbar spine surgery. Case presentation A 71-year-old man with bilateral lower extremity numbness without a history of preexisting motor weakness underwent L3–5 spinal fenestration. Initial MEP monitoring after prone positioning revealed markedly prolonged latency and lower amplitude in the left abductor pollicis brevis (APB). Because the left upper limb somatosensory-evoked potentials had normal values, a position-related impending peripheral nerve injury located between the neck and the forearm was excluded. Postoperative examination revealed that MEP abnormality in the left APB was caused by carpal tunnel syndrome. Conclusions Abnormal initial MEP from the upper limb was unexpectedly detected after prone positioning during lumbar spine surgery. The condition was caused by preexisting carpal tunnel syndrome