Working Hours Reduction and Endogenous Growth

This paper formulates an endogenous growth model and uses it to inquire into the long-run impact of work-sharing arrangements on economic growth. We show that the styles of wage contract, namely salary-style and hourly-style contracts, are a key factor in determining the long-run growth effects of working time reduction. If the labor market is overwhelmingly salaried arrangement, then the extent of wage flexibility is relatively low; as a consequence, a policy of reducing working hours will deteriorate economic growth. On the contrary, if hourly pay predominates, then the wage system tends to increase the degree of wage flexibility. Thus, a cut in working time may favor the economy’s growth rate.Working hours reduction, Endogenous growth

Three-Phase Detection and Classification for Android Malware Based on Common Behaviors

Android is one of the most popular operating systems used in mobile devices. Its popularity also renders it a common target for attackers. We propose an efficient and accurate three-phase behavior-based approach for detecting and classifying malicious Android applications. In the proposed approach, the first two phases detect a malicious application and the final phase classifies the detected malware. The first phase quickly filters out benign applications based on requested permissions and the remaining samples are passed to the slower second phase, which detects malicious applications based on system call sequences. The final phase classifies malware into known or unknown types based on behavioral or permission similarities. Our contributions are three-fold: First, we propose a self-contained approach for Android malware identification and classification. Second, we show that permission requests from an Application are beneficial to benign application filtering. Third, we show that system call sequences generated from an application running inside a virtual machine can be used for malware detection. The experiment results indicate that the multi-phase approach is more accurate than the single-phase approach. The proposed approach registered true positive and false positive rates of 97% and 3%, respectively. In addition, more than 98% of the samples were correctly classified into known or unknown types of malware based on permission similarities.We believe that our findings shed some lights on future development of malware detection and classification

Ceftriaxone attenuates hypoxic-ischemic brain injury in neonatal rats

<p>Abstract</p> <p>Background</p> <p>Perinatal brain injury is the leading cause of subsequent neurological disability in both term and preterm baby. Glutamate excitotoxicity is one of the major factors involved in perinatal hypoxic-ischemic encephalopathy (HIE). Glutamate transporter GLT1, expressed mainly in mature astrocytes, is the major glutamate transporter in the brain. HIE induced excessive glutamate release which is not reuptaked by immature astrocytes may induce neuronal damage. Compounds, such as ceftriaxone, that enhance the expression of GLT1 may exert neuroprotective effect in HIE.</p> <p>Methods</p> <p>We used a neonatal rat model of HIE by unilateral ligation of carotid artery and subsequent exposure to 8% oxygen for 2 hrs on postnatal day 7 (P7) rats. Neonatal rats were administered three dosages of an antibiotic, ceftriaxone, 48 hrs prior to experimental HIE. Neurobehavioral tests of treated rats were assessed. Brain sections from P14 rats were examined with Nissl and immunohistochemical stain, and TUNEL assay. GLT1 protein expression was evaluated by Western blot and immunohistochemistry.</p> <p>Results</p> <p>Pre-treatment with 200 mg/kg ceftriaxone significantly reduced the brain injury scores and apoptotic cells in the hippocampus, restored myelination in the external capsule of P14 rats, and improved the hypoxia-ischemia induced learning and memory deficit of P23-24 rats. GLT1 expression was observed in the cortical neurons of ceftriaxone treated rats.</p> <p>Conclusion</p> <p>These results suggest that pre-treatment of infants at risk for HIE with ceftriaxone may reduce subsequent brain injury.</p

Improved Breath Phase and Continuous Adventitious Sound Detection in Lung and Tracheal Sound Using Mixed Set Training and Domain Adaptation

Previously, we established a lung sound database, HF_Lung_V2 and proposed convolutional bidirectional gated recurrent unit (CNN-BiGRU) models with adequate ability for inhalation, exhalation, continuous adventitious sound (CAS), and discontinuous adventitious sound detection in the lung sound. In this study, we proceeded to build a tracheal sound database, HF_Tracheal_V1, containing 11107 of 15-second tracheal sound recordings, 23087 inhalation labels, 16728 exhalation labels, and 6874 CAS labels. The tracheal sound in HF_Tracheal_V1 and the lung sound in HF_Lung_V2 were either combined or used alone to train the CNN-BiGRU models for respective lung and tracheal sound analysis. Different training strategies were investigated and compared: (1) using full training (training from scratch) to train the lung sound models using lung sound alone and train the tracheal sound models using tracheal sound alone, (2) using a mixed set that contains both the lung and tracheal sound to train the models, and (3) using domain adaptation that finetuned the pre-trained lung sound models with the tracheal sound data and vice versa. Results showed that the models trained only by lung sound performed poorly in the tracheal sound analysis and vice versa. However, the mixed set training and domain adaptation can improve the performance of exhalation and CAS detection in the lung sound, and inhalation, exhalation, and CAS detection in the tracheal sound compared to positive controls (lung models trained only by lung sound and vice versa). Especially, a model derived from the mixed set training prevails in the situation of killing two birds with one stone.Comment: To be submitted, 31 pages, 6 figures, 5 table

Analgesic and Anti-Inflammatory Activities of Methanol Extract of Ficus pumila L. in Mice

This study investigated possible analgesic and anti-inflammatory mechanisms of the methanol extract of Ficus pumila (FPMeOH). Analgesic effects were evaluated in two models including acetic acid-induced writhing response and formalin-induced paw licking. The results showed FPMeOH decreased writhing response in the acetic acid assay and licking time in the formalin test. The anti-inflammatory effect was evaluated by λ-carrageenan-induced mouse paw edema and histopathological analyses. FPMeOH significantly decreased the volume of paw edema induced by λ-carrageenan. Histopathologically, FPMeOH abated the level of tissue destruction and swelling of the edema paws. This study indicated anti-inflammatory mechanism of FPMeOH may be due to declined levels of NO and MDA in the edema paw through increasing the activities of SOD, GPx, and GRd in the liver. Additionally, FPMeOH also decreased the level of inflammatory mediators such as IL-1β, TNF-α, and COX-2. HPLC fingerprint was established and the contents of three active ingredients, rutin, luteolin, and apigenin, were quantitatively determined. This study provided evidence for the classical treatment of Ficus pumila in inflammatory diseases