A PCR-based subtractive hybridization technique was used to identify genes up-regulated in the hibernating bat brain to explore the molecular mechanism of hibernation. Three genes, Liprin-α2, PTP4A2 ...and CAMKKβ were differentially expressed in hibernating bat brain tissue compared to active bat brain tissue. One of them, Liprin-α2, which has recently been shown to have the key function in the organization of presynaptic and postsynaptic multiprotein complexes was studied in detail. We demonstrated that the expression level of Liprin-α2 was up-regulated almost 4-fold in hibernating bat brains by RT-PCR compared to levels in active bats. The differential expression pattern of Liprin-α2 was also detected in muscle, fat, brain and heart tissue of hibernating bats by real-time quantitative PCR. The result indicated that Liprin-α2 was over-expressed in brain and heart tissue and down-regulated in muscle and fat. In brain tissue of hibernating bats, Liprin-α2 expression was statistically significantly higher than in brain tissue of active controls （P = 0.029）. The precise control of transcriptional level and the distinctively differential expression pattern of Liprin-α2 in different organs during circannual hibernation may have important physiological significance, not only in maintaining normal function of many key organs but also in effectively conserving limited energy resources without physiological damage.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Pedestrian detection has achieved great improvements with the help of Convolutional Neural Networks (CNNs). CNN can learn high-level features from input images, but the insufficient spatial ...resolution of CNN feature channels (feature maps) may cause a loss of information, which is harmful especially to small instances. In this paper, we propose a new pedestrian detection framework, which extends the successful RPN+BF framework to combine handcrafted features and CNN features. RoI-pooling is used to extract features from both handcrafted channels (e.g. HOG+LUV, CheckerBoards or RotatedFilters) and CNN channels. Since handcrafted channels always have higher spatial resolution than CNN channels, we apply RoI-pooling with larger output resolution to handcrafted channels to keep more detailed information. Our ablation experiments show that the developed handcrafted features can reach better detection accuracy than the CNN features extracted from the VGG-16 net, and a performance gain can be achieved by combining them. Experimental results on Caltech pedestrian dataset with the original annotations and the improved annotations demonstrate the effectiveness of the proposed approach. When using a more advanced RPN in our framework, our approach can be further improved and get competitive results on both benchmarks.
Pedestrian detection is a fundamental component in many real-world applications such as automatic driving, intelligent surveillance, person re-identification and robotics. Therefore, it has attracted ...massive attention in the last decades. However, pedestrians in an images always exhibit different scales, which constitutes a significant mode of intra-class variability and affect the performance of pedestrian detection algorithm. To address this problem, we apply FPN (Feature Pyramid Network)for pedestrian detection. FPN exploits the inherent multi-scale structure of a deep convolutional network to construct a feature pyramid that has rich semantics at all levels and facilitates the detection of objects at different scales. To leverage the information from different levels of the feature pyramid, we extend the FPN-based pedestrian detection by fusing the feature of each level with adaptive feature pooling. Furthermore, we also integrate a Squeeze and Excitation module to the ROI pooled features from each level before the feature fusion. The experiment result on Caltech dataset shows that our approach outperforms the basic FPN-based pedestrian detection and robust towards to various scale of pedestrian.
The present study analyzed changes in the biochemical metabolites N-acetyl aspartate, choline, and creatine in a simple concussion rabbit model following quiet rest, hyperbaric oxygen therapy, or ...interference stimulation through the use of hydrogen proton magnetic resonance spectroscopy detection. Experimental findings showed that brain N-acetyl aspartate and choline peak values significantly decreased, while creatine peak values significantly increased following simple concussion. Following treatments, N-acetyl aspartate and choline peaks returned to normal levels in the quiet rest and hyperbaric oxygen therapy groups, but no changes were observed in the interference stimulation group. Results demonstrated abnormal changes in the brain biochemical metabolism environment following simple concussion. Quiet rest was shown to play an important role in restoration of biochemical metabolism following simple concussion.
Background Insulin resistance （IR） plays an important pathophysiological role in the development of diabetes,dyslipidemia,hypertension,and cardiovascular disease.Moreover,IR can occur even in ...non-obese people without diabetes.However,direct detection of IR is complicated.In order to find a simple surrogate marker of IR early in nonobese people,we investigate the association of commonly-used biochemical markers （liver enzymes and lipid profiles） with IR in urban middle-aged and older non-obese Chinese without diabetes.Methods This cross-sectional study included 1 987 subjects （1 473 women）.Fasting blood samples were collected for measurement of glucose,insulin,liver enzymes,lipid profiles and creatinine.Subjects whose homeostasis model of assessment-IR （HOMA-IR） index values exceeded the 75th percentile （2.67 for women and 2.48 for men） of the population were considered to have IR.The area under the receiver operating characteristic curve （ROC） was used to compare the power of potential markers in identifying IR.Results Triglycerides （TG） and ratio of TG to high-density lipoprotein cholesterol （TG/HDL-C） discriminated IR better than other indexes for both sexes; areas under the receiver operating characteristic （ROC） curves （AUC） values were 0.770 （95％ confidence interval 0.733-0.807） and 0.772 （0.736-0.809）,respectively,for women and 0.754 （0.664-0.844）and 0.756 （0.672-0.840）,respectively,for men.To identify IR,the optimal cut-offs for TG and TG/HDL-C ratio were 1.315 mmol/L （sensitivity 74.3％,specificity 71.0％） and 0.873 （sensitivity 70.1％,specificity 73.4％）,respectively,for women,and 1.275 mmol/L （sensitivity 66.7％,specificity 74.4％） and 0.812 （sensitivity 75.8％,specificity 69.2％）,respectively,for men.Conclusion TG and TG/HDL-C ratio could be used to identify IR in urban middle-aged and older non-obese Chinese without diabetes.
The new-type urbanization strategy proposed by the Chinese government is human-centered urbanization, which emphasizes the coordination of population, economy, society, and ecological environment. ...Despite extensive research on the impact of traditional urbanization, the impact of the new-type urbanization on energy efficiency is largely unknown. Based on the sample of 193 Chinese cities, this paper investigates the conditional convergence characteristics of energy intensity and explores the role of new-type urbanization on energy saving as well as its transmission channels. The results confirm the existence of condition β-convergence for energy intensity, and the new-type urbanization has a significant energy-saving effect with the effect being greater in resource-rich areas. Moreover, the mechanism analysis shows that the economic agglomeration effect, industrial structure effect, and technological progress effect are important transmission channels through which the new-type urbanization affects energy intensity. This paper adds new insights to understand the new-type urbanization process.
•Impact of the new-type urbanization on energy intensity is analyzed.•The new-type urbanization has a significant energy-saving effect.•Regional heterogeneity is found among different types of cities.•Three important transmission channels are identified.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To develop renewable energy as well as promote China's transition to a low-carbon economy, the government needs to pay attention to renewable energy technological innovation (RETI). Using China's ...provincial panel data from 2000 to 2015, and regarding the CO2 emissions as the proxy of climate change, this paper identifies the relationship between RETI and CO2 emissions as well as seeks to confirm the role of RETI on climate change. The linear regression model confirms that the RETI has a significant negative effect on CO2 emissions. In addition, considering the disparities of energy structure, the impacts of RETI on CO2 emissions may be distinct. We, therefore, construct a panel threshold model by taking into account the distinct effect of RETI under different energy structure. We find that the effect of RETI on curbing CO2 emissions decreases with the rising of coal-dominated energy consumption structure but in contrast, this effect increases with the growing proportion of renewable energy generation. This paper provides new insight into the relationship between technological innovation and climate change. Based on these findings, some relevant policy recommendations are proposed.
Display omitted
•We identify the relationship between renewable energy technological innovation (RETI) and CO2 emissions.•We find distinct effect of RETI on curbing CO2 under different energy structure.•The government should pay attention to the role of RETI.•More renewable energy should be encouraged in residential life and production process.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy ...technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000–2015 and panel data models, this paper regards the CO2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change.
•The drivers of the renewable energy technological innovation are explored.•There are significant differences in technological innovation across provinces.•Renewable energy technological innovation responds actively to climate changes.•R&D investment is conducive for promoting the technological innovation levels.•The government should give full play to the role of the energy price mechanism.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The green economy is considered as an efficient way for sustainability, but the connection between fiscal spending and green economic growth has not been systematically explained. This paper attempts ...to fill this research gap. Based on the panel data of 282 prefecture-level cities from 2005 to 2016, we first construct the green economic growth index by using the non-radial direction distance function. Then, by employing the System-GMM estimation, we further evaluate the effect of fiscal education spending and R&D spending on green economic growth. Finally, we explore the potential mechanism and discuss our findings. We obtain the following conclusions: (1) The green economic growth index fluctuated in the study period, we attribute it to the “political tournament” of local governments. (2) The System-GMM estimation results confirm the existence of composition effect and technique effect in the full sample, but the sub-sample analysis suggests that there is a heterogeneous effect in different areas with different resources abundant degree. (3) Mechanism analysis illustrates that fiscal R&D spending and education spending foster the green economic growth through technological activities and human-capital intensive activities, respectively, but they exhibit distinct roles in different areas. Based on these findings, we propose some targeted policy suggestions for promoting green economic growth.
•The effect of fiscal spending on green economic growth is analyzed.•The green economic growth index fluctuated in the study period.•We confirm the existence of composition effect and technique effect.•The heterogeneous effect exists in different type cities.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper first estimates the energy-related carbon dioxide (CO2) emissions and carbon intensity of China's 30 provinces from 2000 to 2015. By constructing a 4-variable Panel Vector Auto-regression ...(PVAR) model, the paper quantitatively analyzes the dynamic relationship among urbanization, industrial structure, energy and carbon intensity in China during urbanization and industrialization stage. The results show that urbanization process and the advancement of industrial structure are consistent with the optimization goals of energy and carbon intensity. In the long term, energy and carbon intensity will decline with the development of urbanization and the advancement of industrial structure. But urbanization process has an inverted U-shaped effect on energy and carbon intensity, while the influence of industrial structure advancement on energy and carbon intensity increases over time. In contrast, the positive impact of energy intensity on carbon intensity is mainly reflected in the short term. This paper confirms the importance of urbanization and upgrading of industrial structure in the goal of energy saving and emissions reduction. Thus, this paper suggests that each province should adopt the upgrading of industrial structure as one of the policy goals, and constantly promote new urbanization process, following their own development characteristics.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
