Aspects of exchange rate determination : empirical evidence

The presence of a risk premium in foreign exchange markets for the floating exchange rate period has been examined by some researchers and the results obtained were not successful. In this thesis, we analyse a number of exchange rate models and assess their empirical performance. Using the data from the Group-S members in the post Bretton Woods period, we investigate the presence of the risk premium among different models. Our results are remarkably satisfactory.A 'new' random walk model is tested. It has been found that the null hypothesis of a unit coefficient with or without a constant cannot be rejected for several pairs of the countries. The statistically non-zero constant indicates the existence of the risk premium and/or transaction costs in the foreign exchange markets. Results of testing long run Real Interest Parity (RIP) show that such a condition holds in several cases, and this is explained by the existence of capital and exchange rate controls, and thus by the risk premium, rather than PPP and UIP conditions.One way to detect the existence of the risk premium is to test the significance of the semi-elasticity of bond supplies in a portfolio balance model. It has been shown that such a premium does exist in many cases. Thus the results support the view that the exchange rate is mainly determinated by investors' portfolio behaviour.Finally, a synthesis of monetary and portfolio balance models is also studied. We have been able to uncover evidence in support of the long run model of exchange rate determination for the floating exchange rate period. The evidence supports the synthesis model and a policy reaction function that manages the exchange rate by fully or partially offsetting systematic fluctuations in interest rate differentials

Retrospectively Analysis of Factors Influencing the Relapse (or Progression) of Newly Diagnosed Nonoperative Small Cell Lung Cancer

Background and objective Most small cell lung cancer (SCLC) patients relapse or progress and have low survival rate although they have significant response to initial chemotherapy and radiotherapy. This study intends to explore the factors affecting the relapse (or progression) of nonoperative SCLC and to explore the correlations between progression-free survival (PFS) and overall survival (OS). Methods Clinical data of 182 patients diagnosed with SCLC between January 2009 and December 2011 at Shanghai Chest Hospital has been reviewed and retrospectively analyzed. All of these patients accepted chemotherapy combined (or not combined) with radiotherapy, and relapsed or progressed after first-line therapy. Univariate Kaplan-Meier survival estimates as well as multivariate Cox regression survival analysis were used to locate the potential factors affecting PFS. The correlation between PFS and OS was analyzed via Bivariate Correlation Analysis method. Results The univariate estimates showed that the TNM stage, liver metastasis or not, brain metastasis or not, first-line chemotherapy cycles, effect of initial chemotherapy, and thoracic radiotherapy combined or not were the significant contributive factors to PFS. In the subgroup of the patients without brain metastases, those received prophylactic cranial irradiation (PCI) had longer PFS. Cox regression indicated that the three independent variables of first-line chemotherapy cycles, effect of initial chemotherapy and thoracic radiotherapy combined or not were closely related to PFS. In addition, significant positive correlation between PFS and OS had been observed. Conclusion PFS could be prolonged by having more first-line chemotherapy cycles (>4 cycles), obtaining better effect of initial chemotherapy (partial response or complete response), combining with thoracic radiotherapy and implementing PCI for patients without brain metastasis

HIV-Related High-Risk Behaviors among Chinese Migrant Construction Laborers in Nantong, Jiangsu

Background: HIV transmission in rural areas of China is being fueled in part by migrant workers who acquire HIV outside of their hometowns. Recent surveillance statistics indicate that HIV prevalence among returning migrants has increased significantly. Methods: We conducted a community-based cross-sectional study to assess HIV-related knowledge, attitudes and behaviors among migrant returnees in Nantong, Jiangsu Province, one of the largest exporters of migrant laborers. Results: A total of 1625 subjects were enrolled with a response rate of 89%. All participants were male and of the majority Han ethnicity. The mean age was 39.0 years (SD = 6.7; range: 18 to 63), and most had a stable partner (N = 1533, 94.3%). Most correctly identified the major modes of HIV transmission (68.9%–82.0%), but fewer were able to identify ways that HIV cannot be transmitted. Nearly one-third of participants held positive attitudes toward having multiple sex partners, and nearly half believed that sex work should be legalized. Multiple logistic regression analysis indicated that risky sexual behavior (defined as sex with a casual or commercial sex partner) was associated with no stable partner; working abroad; correct condom use; age,22 at first sex; higher coital frequency; and having a positive attitude towards multiple sex partners. Conclusions: We found high levels of reported sex with a casual or commercial sex partner and low levels of consisten

Caspase-8 and Caspase-9 Functioned Differently at Different Stages of the Cyclic Stretch-Induced Apoptosis in Human Periodontal Ligament Cells

<div><p>Background</p><p>Human periodontal ligament (PDL) cells underwent apoptosis after mechanical stretch loading. However, the exact signalling pathway remains unknown. This study aimed to elucidate how the apoptotic caspases functioned in the cyclic stretch-induced apoptosis in human PDL cells.</p><p>Materials and Methods</p><p>In the present study, 20% cyclic stretch was selected to load the cells for 6 or 24 h. The following parameters were analyzed: apoptotic rates, the protein levels of caspase-3, -7, -8 and -9 and the activities of caspase-8 and -9. Subsequently, the influences of caspase-8 and caspase-9 inhibitors on the apoptotic rate and the protein level of the activated caspase-3 were assessed as well.</p><p>Results</p><p>The apoptotic rates increased in response to cyclic stretch, but the cells entered different apoptotic stages after 6 and 24 h stretches. Caspase-3, -7, -8 and -9 were all activated after stretch loading. The stretch-induced apoptosis and the protein level of the activated caspase-3 were inhibited after inhibiting both caspase-8 and caspase-9 in both 6 and 24 h stretched cells and after inhibiting caspase-9 in 24 h stretched cells.</p><p>Conclusion</p><p>Caspase-8 and -9 functioned differently at different apoptotic stages in human PDL cells after cyclic stretch.</p></div

An Investigation of a Multidimensional CNN Combined with an Attention Mechanism Model to Resolve Small-Sample Problems in Hyperspectral Image Classification

The convolutional neural network (CNN) method has been widely used in the classification of hyperspectral images (HSIs). However, the efficiency and accuracy of the HSI classification are inevitably degraded when small samples are available. This study proposes a multidimensional CNN model named MDAN, which is constructed with an attention mechanism, to achieve an ideal classification performance of CNN within the framework of few-shot learning. In this model, a three-dimensional (3D) convolutional layer is carried out for obtaining spatial–spectral features from the 3D volumetric data of HSI. Subsequently, the two-dimensional (2D) and one-dimensional (1D) convolutional layers further learn spatial and spectral features efficiently at an abstract level. Based on the most widely used convolutional block attention module (CBAM), this study investigates a convolutional block self-attention module (CBSM) to improve accuracy by changing the connection ways of attention blocks. The CBSM model is used with the 2D convolutional layer for better performance of HSI classification purposes. The MDAN model is applied for classification applications using HSI, and its performance is evaluated by comparing the results with the support vector machine (SVM), 2D CNN, 3D CNN, 3D–2D–1D CNN, and CBAM. The findings of this study indicate that classification results from the MADN model show overall classification accuracies of 97.34%, 96.43%, and 92.23% for Salinas, WHU-Hi-HanChuan, and Pavia University datasets, respectively, when only 1% HSI data were used for training. The training and testing times of the MDAN model are close to those of the 3D–2D–1D CNN, which has the highest efficiency among all comparative CNN models. The attention model CBSM is introduced into MDAN, which achieves an overall accuracy of about 1% higher than that of the CBAM model. The performance of the two proposed methods is superior to the other models in terms of both efficiency and accuracy. The results show that the combination of multidimensional CNNs and attention mechanisms has the best ability for small-sample problems in HSI classification

Autonomous Detection of Spodoptera frugiperda by Feeding Symptoms Directly from UAV RGB Imagery

The use of digital technologies to detect, position, and quantify pests quickly and accurately is very important in precision agriculture. Imagery acquisition using air-borne drones in combination with the deep learning technique is a new and viable solution to replace human labor such as visual interpretation, which consumes a lot of time and effort. In this study, we developed a method for automatic detecting an important maize pest&mdash;Spodoptera frugiperda&mdash;by its gnawing holes on maize leaves based on convolution neural network. We validated the split-attention mechanism in the classical network structure ResNet50, which improves the accuracy and robustness, and verified the feasibility of two kinds of gnawing holes as the identification features of Spodoptera frugiperda invasion and the degree. In order to verify the robustness of this detection method against plant morphological changes, images at the jointing stage and heading stage were used for training and testing, respectively. The performance of the models trained with the jointing stage images has been achieved the validation accuracy of ResNeSt50, ResNet50, EfficientNet, and RegNet at 98.77%, 97.59%, 97.89%, and 98.07%, with a heading stage test accuracy of 89.39%, 81.88%, 86.21%, and 84.21%

Autonomous Detection of <i>Spodoptera frugiperda</i> by Feeding Symptoms Directly from UAV RGB Imagery

The use of digital technologies to detect, position, and quantify pests quickly and accurately is very important in precision agriculture. Imagery acquisition using air-borne drones in combination with the deep learning technique is a new and viable solution to replace human labor such as visual interpretation, which consumes a lot of time and effort. In this study, we developed a method for automatic detecting an important maize pest—Spodoptera frugiperda—by its gnawing holes on maize leaves based on convolution neural network. We validated the split-attention mechanism in the classical network structure ResNet50, which improves the accuracy and robustness, and verified the feasibility of two kinds of gnawing holes as the identification features of Spodoptera frugiperda invasion and the degree. In order to verify the robustness of this detection method against plant morphological changes, images at the jointing stage and heading stage were used for training and testing, respectively. The performance of the models trained with the jointing stage images has been achieved the validation accuracy of ResNeSt50, ResNet50, EfficientNet, and RegNet at 98.77%, 97.59%, 97.89%, and 98.07%, with a heading stage test accuracy of 89.39%, 81.88%, 86.21%, and 84.21%

Inhibition of caspase-8 and caspase-9 suppressed the apoptotic rate.

<p>The results of apoptotic analysis after inhibiting either caspase-8 or caspase-9 or both of them. (a-f) Dot plots of Annexin V and PI staining. (i, ii) Apoptotic rates in each group were calculated. In 6 h stretched cells, the apoptotic rates (including the early and the late apoptosis) were identified no statistical difference by using either caspase-8 inhibitor or caspase-9 inhibitor (P>0.05). However, inhibition of both caspase-8 and caspase-9 significantly reduced the apoptotic rates in 6 h stretched cells (P<0.01). In 24 h stretched cells, the apoptotic rate was significantly down-regulated by using caspase-9 inhibitor (P<0.01), while showed no change by using caspase-8 inhibitor (P>0.05). Inhibition of both caspase-8 and caspase-9 also significantly reduced the apoptotic rate in 24 h stretched cells (P<0.01). **: P<0.01 VS non-inhibiting cells.</p