New exact traveling wave solutions for the Klein–Gordon–Zakharov equations

AbstractBased on the extended hyperbolic functions method, we obtain the multiple exact explicit solutions of the Klein–Gordon–Zakharov equations. The solutions obtained in this paper include (a) the solitary wave solutions of bell-type for u and n, (b) the solitary wave solutions of kink-type for u and bell-type for n, (c) the solitary wave solutions of a compound of the bell-type and the kink-type for u and n, (d) the singular traveling wave solutions, (e) periodic traveling wave solutions of triangle function types, and solitary wave solutions of rational function types. We not only rederive all known solutions of the Klein–Gordon–Zakharov equations in a systematic way but also obtain several entirely new and more general solutions. The variety of structures of the exact solutions of the Klein–Gordon–Zakharov equations is illustrated

Thermodynamic Studies of Minerals under Mantle Conditions.

This dissertation is a contribution to the thermodynamic properties and phase equilibria of minerals under mantle conditions. For the first time, the heat capacity data of K-hollandite (KAlSi3O8), Si-wadeite (K2Si4O9) and γ-Fe2SiO4 in the temperature range of 5−303 K were measured using a Physical Properties Measurement System (PPMS). These high pressure phases were synthesized with multi-anvil and piston cylinder equipment at University of Minnesota. They were sent to Austria for the low-temperature heat capacity measurements after sample characterization with EMPA and XRD. These low-temperature heat capacity data are integrated to obtain the entropies of these phases. The entropy of K-hollandite at standard state is 166.2 ± 0.2 Jmol-1K-1, including an 18.7 Jmol-1K-1 contribution from the configurational entropy due to disorder of Al and Si in the octahedral sites. The entropy of Si-wadeite at standard state calculated from the measured heat capacity data is 253.8 ± 0.6 Jmol-1K-1, which is considerately larger than some of the previous estimates. Phase equilibria related to K-hollandite and Si-wadeite were calculated under mantle conditions with the help of the newly measured heat capacity data as well as other available thermodynamic properties. The calculated phase transition boundaries in the system K2O−Al2O3−SiO2 are generally consistent with previous experimental results. Thermodynamic calculation together with seven multi-anvil experiments at 1,400 K and 6.0−7.7 GPa suggests no stability field for kalsilite + coesite, in contrast to previous predictions. The low-temperature heat capacity of γ-Fe2SiO4 measured by PPMS shows a broad λ-transition at 11.8 K, which is presumably due to a paramagnetic−antiferromagnetic transition that represents the Néel temperature. The entropy and Gibbs free energy of γ-Fe2SiO4 at standard pressure and temperature are calculated to be 140.2 ± 0.4 Jmol-1K-1 and -1369.3 ± 2.7 Jmol-1K-1 based on the measured heat capacity and available enthalpy data. The phase boundary for the fayalite−γ-Fe2SiO4 transition at 298 K based on current thermodynamic data is located at 2.4 ± 0.6 GPa with a slope of 25.4 bars/K, consistent with extrapolated results of previous experimental studies.Ph.D.GeologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61681/1/wenjuny_1.pd

A Novel Compact Dual-Polarized Antenna

A novel compact dual-polarized antenna is proposed. The antenna has a 1.43% impedance bandwidth which is from 1801 MHz to 1827 MHz for return loss larger than 10 dB. The isolation between the two ports is above 28 dB in the bandwidth, and the gain is 6.6 dBi. The proposed antenna not only consists of a full-planar structure, but also is easy to be fabricated for its simple structure. Additionally, a section of slots and slits is cut on the radiation patch to reduce the area of it to 54% compared with the conventional square patch

Multi-Scale Object Detection Model for Autonomous Ship Navigation in Maritime Environment

Accurate detection of sea-surface objects is vital for the safe navigation of autonomous ships. With the continuous development of artificial intelligence, electro-optical (EO) sensors such as video cameras are used to supplement marine radar to improve the detection of objects that produce weak radar signals and small sizes. In this study, we propose an enhanced convolutional neural network (CNN) named VarifocalNet * that improves object detection in harsh maritime environments. Specifically, the feature representation and learning ability of the VarifocalNet model are improved by using a deformable convolution module, redesigning the loss function, introducing a soft non-maximum suppression algorithm, and incorporating multi-scale prediction methods. These strategies improve the accuracy and reliability of our CNN-based detection results under complex sea conditions, such as in turbulent waves, sea fog, and water reflection. Experimental results under different maritime conditions show that our method significantly outperforms similar methods (such as SSD, YOLOv3, RetinaNet, Faster R-CNN, Cascade R-CNN) in terms of the detection accuracy and robustness for small objects. The maritime obstacle detection results were obtained under harsh imaging conditions to demonstrate the performance of our network model

Fatigue Detection for Ship OOWs Based on Input Data Features, from The Perspective of Comparison with Vehicle Drivers: A Review

Ninety percent of the world’s cargo is transported by sea, and the fatigue of ship officers of the watch (OOWs) contributes significantly to maritime accidents. The fatigue detection of ship OOWs is more difficult than that of vehicles drivers owing to an increase in the automation degree. In this study, research progress pertaining to fatigue detection in OOWs is comprehensively analysed based on a comparison with that in vehicle drivers. Fatigue detection techniques for OOWs are organised based on input sources, which include the physiological/behavioural features of OOWs, vehicle/ship features, and their comprehensive features. Prerequisites for detecting fatigue in OOWs are summarised. Subsequently, various input features applicable and existing applications to the fatigue detection of OOWs are proposed, and their limitations are analysed. The results show that the reliability of the acquired feature data is insufficient for detecting fatigue in OOWs, as well as a non-negligible invasive effect on OOWs. Hence, low-invasive physiological information pertaining to the OOWs, behaviour videos, and multisource feature data of ship characteristics should be used as inputs in future studies to realise quantitative, accurate, and real-time fatigue detections in OOWs on actual ships

The Changing Patterns in Grasslands and Soil Fertility along the Eastern Eurasian Steppe Transect across China–Mongolia–Russia

This paper analyses the adaptation and change in species along the north-south Eastern Eurasian Steppe Transect across China – Mongolia – Russia and considers the implications for climate change and management. The plant community diversity, above-ground biomass, N:P ratios of community and of dominant species, soil N (nitrogen), soil P (phosphorus) and AP (available phosphorus) contents were studied along a 1400 km north-south transect. The main findings were: (1) the community diversity and productivity decreased with the increase in latitude and a significant negative correlation was found between the many plant characteristics and latitude (P \u3c 0.05) – decreasing diversity, biomass and N:P ratios; (2) soil AP content was lowest in Inner Mongolia, whereas no significant change in soil total P with latitude was found in China-Mongolia-Russia transect, a significant positive correlation was detected between the soil nutrient (N and AP) and latitude (P \u3c 0.05); (3) a significant positive correlation was evident between plant community P content and soil AP content (P \u3c 0.01), but a negative correlation was found between community N:P ratio and soil AP content (P \u3c 0.05). The soil AP content can be used as a soil properties indicator to reflect the plant communities P content and N: P ratio. It is suggested that greater human activities in Inner Mongolia may be an important factor affecting soil AP content, community N:P and plant growth

Calorie restriction and endurance exercise share potent anti-inflammatory function in adipose tissues in ameliorating diet-induced obesity and insulin resistance in mice

<p>Abstract</p> <p>Background</p> <p>Calorie restriction (CR) and endurance exercise are known to attenuate obesity and improve the metabolic syndrome. The aim of this study was to directly compare the effects of CR and endurance exercise in a mouse model of diet-induced obesity and insulin resistance.</p> <p>Methods</p> <p>Adult male C57BL/6N mice were randomly assigned and subjected to one of the six interventions for 8 weeks: low-fat diet (LC, 10% fat), low-fat diet with 30% calorie restriction (LR), high-fat diet (HC, 60% fat), high-fat diet with 30% calorie restriction (HR), high-fat diet with voluntary running exercise (HE), and high-fat diet with a combination of 30% calorie restriction and exercise (HRE). The impacts of the interventions were assessed by comprehensive metabolic analyses and pro-inflammatory cytokine gene expression.</p> <p>Results</p> <p>Endurance exercise significantly attenuated high-fat diet-induced obesity. CR dramatically prevented high-fat diet-induced metabolic abnormalities. A combination of CR and endurance exercise further reduced obesity and insulin resistance under the condition of high-fat diet. CR and endurance exercise each potently suppressed the expression of inflammatory cytokines in white adipose tissues with additive effects when combined, but the effects of diet and exercise interventions in the liver were moderate to minimal.</p> <p>Conclusions</p> <p>CR and endurance exercise share a potent anti-inflammatory function in adipose tissues in ameliorating diet-induced obesity and insulin resistance.</p

Effects on global warming by microbial methanogenesis in alkaline lakes during the Late Paleozoic Ice Age (LPIA)

This work was jointly funded by the National Natural Science Foundation of China (Grant Nos . 42230808, 42203055 and 41830425) and PetroChina Science and Technology Major project (Grant No. 20 21DJ0108).Methane (CH4) is an important greenhouse gas, but its behavior and influencing factors over geological time scales are not sufficiently clear. This study investigated the Late Paleozoic Ice Age (LPIA), which is thought to have experienced an interval of rapid warming at ca. 304 Ma, that may have been analogous to modern warming. To explore possible causes of this warming event, we investigated ancient alkaline lakes in the Junggar Basin, northwestern China. Results show that microbial CH4 cycling here was strong, as evidenced by carbonate δ13C (δ13Ccarb) values of &gt;5‰, ∼+0.6‰ offsets between pristane δ13C (δ13CPr) and phytane δ13C (δ13CPh) values, a 3β-methylhopane index of 9.5% ± 3.0%, and highly negative δ13C values of hopanes (−44‰ to −61‰). Low sulfate concentrations in the alkaline lakes made methanogenic archaea more competitive than sulfate-reducing bacteria, and the elevated levels of dissolved inorganic carbon promoted methanogenesis. Biogenic CH4 emissions from alkaline lakes, in addition to CO2, may have contributed to rapid climate warming.PostprintPeer reviewe