The Relation Between the CO

Carbon dioxide can change the heat balance of the atmosphere. To study the relationship between CO2 and temperature change, we use the given CO2 concentrations to implement linear regression model, gray time series forecasting model, back-propagation model, and auto-regressive and moving average model to establish the growth function of CO2 concentration. Errors are evaluated to choose the most suitable model. then we use the most suitable model in step one to further predict future land-ocean temperature. Finally, we use grey relational analysis to analyze the relationship between CO2 concentrations and land-ocean temperatures since 1959

Distance spectral radius of series-reduced trees with parameters

For a connected graph G, the distance matrix is a real-symmetric matrix where the (u, v)-entry is the distance between vertex u and vertex v in G. The distance spectral radius of G is the largest eigenvalue of the distance matrix of G. A series-reduced tree is a tree with at least one internal vertex and all internal vertices having degree at least three. Those series-reduced trees that maximize the distance spectral radius are determined over all series-reduced trees with fixed order and maximum degree and over all series-reduced trees with fixed order and number of leaves, respectively

Label-Free Anomaly Detection Using Distributed Optical Fiber Acoustic Sensing

Deep learning anomaly detection is important in distributed optical fiber acoustic sensing (DAS). However, anomaly detection is more challenging than traditional learning tasks, due to the scarcity of true-positive data and the vast imbalance and irregularity within datasets. Furthermore, it is impossible to catalog all types of anomalies, therefore, the direct application of supervised learning is deficient. To overcome these problems, an unsupervised deep learning method that only learns the normal data features from ordinary events is proposed. First, a convolutional autoencoder is used to extract DAS signal features. A clustering algorithm then locates the feature center of the normal data, and the distance to the new signal is used to determine whether it is an anomaly. The efficacy of the proposed method was evaluated in a real high-speed rail intrusion scenario, and considered all behaviors that may threaten the normal operation of high-speed trains as abnormal. The results show that the threat detection rate of this method reaches 91.5%, which is 5.9% higher than that of the state-of-the-art supervised network and, at 7.2%, the false alarm rate is 0.8% lower than the supervised network. Moreover, using a shallow autoencoder reduces the parameters to 1.34 K, which is significantly lower than the 79.55 K of the state-of-the-art supervised network

In situ N-, P- and Ca-codoped biochar derived from animal bones to boost the electrocatalytic hydrogen evolution reaction

The development of highly efficient and inexpensive carbon-based catalysts for the production of hydrogen from water electrolysis is a considerable challenge in the field of sustainable energy transformation. Herein, an in situ N-, P- and Ca-codoped biochar was successfully fabricated from animal bone by thermal treatment at 800 degrees C. This in situ N-, P- and Ca-codoped catalyst exhibits high atomic contents with synergistic effects of N, P and Ca, a large electrochemically active surface area, a low charge-transfer resistance, high conductivity, and a large specific area. These characteristics lead to an outstanding hydrogen evolution reaction (HER) activity and good stability in a H2SO4 acidic solution, with an onset potential of 80 +/- 3 mV, an overpotential of 162 +/- 3 mV at a current density of 10 mA/cm(2), a Tafel slope of 80 mV/dec, and an exchange current density of 52.5 mu A/cm(2), which are comparable to or even better than those of synthetic hetematom-doped or transition metal-doped carbon-based catalysts. These findings demonstrate that animal bone is a useful material for the preparation of N-, P- and Ca-codoped carbon materials as effective electrocatalysts for the HER

Study on Microwave Deicing Efficiency of Microwave-Absorbing Concrete Pavements and Its Influencing Factors

Microwave deicing technology, as a new environmentally friendly deicing technology, can effectively solve the problem of the frequent icing of road surfaces in the winter, which affects the safety of traffic. To improve the efficiency of microwave deicing on cement concrete pavement, this study proposed the use of magnetite, iron sulfide slag, steel slag, lead–zinc slag, and graphite as microwave-absorbing materials, and conducted microwave deicing tests under the influence of five factors, namely the form of the pavement surface structure, the content of the microwave-absorbing material, microwave power, the shielding state, and dry and wet conditions. Layer by layer, we selected the combination of pavement surface structure, microwave-absorbing material content, microwave power, shielding state, and dry and wet conditions on the bottom surface of the concrete slab with the optimal deicing effect. The results showed that the 2 cm scattered microwave-absorbing surface concrete structure has the fastest heating rate; the higher the magnetite content and microwave power, the higher the deicing efficiency; the maximum heating rate can be increased by 17.6% when the shielding layer is set at the bottom of the cement concrete slab; and the heating rate of the microwave-absorbing concrete slab in the wet state is increased by 20.8% relative to the dry state. In summary, 7000 W of power, a magnetite content of 60 vol % in the scattered microwave-absorbing surface, a shielding layer set at the bottom surface, and wet conditions can greatly improve the efficiency of microwave deicing compared with the microwave ice melting effects of plain cement concrete and other microwave-absorbing materials mixed into the concrete. In addition, the temperature uniformity of the microwave-absorbing materials is essential to improve the deicing efficiency of microwave-absorbing concrete, so it is essential to explore it further

Enhancing hydrogen evolution by photoelectrocatalysis of water splitting over a CdS flowers-loaded TiO2 nanotube array film on the Ti foil substrate

This study is devoted to the scalable fabrication of a high-performance composite photocatalyst by incorporation of the visible-light-active CdS flowers (with sharp edges exposed) onto a TiO2 nanotube array (TNA) film on the Ti foil substrate. To evaluate the visible-light-harvesting performance of the prepared hierarchical architecture consisting of the CdS flowers, TNAs, and Ti foil, we subsequently assembled a photoelectrochemical (PEC) cell with membrane electrode assemblies fabricated innovatively by thermocompression. The CdS flowers can efficiently harvest the visible light energy, while TiO2 collects photoelectrons, effectively separating of the photoexcited electron-hole pairs and hence enhancing the photocatalysis efficiency in the photoelectrochemical conversion and yield of hydrogen production from water splitting. An impressive hydrogen production rate of 22.44 mu mol square h(-1)square cm(-2) was obtained in the PEC cell with the CdS flowers-sensitized TNA film under simulated solar light with an active irradiation area of around 42 cm(2), thus showing great potential for practical applications

Alfalfa Leaf-Derived Porous Heteroatom-Doped Carbon Materials as Efficient Cathodic Catalysts in Microbial Fuel Cells

Heteroatom-doped lamellar-structured carbon with a high surface area synthesized from alfalfa leaves is utilized as a cathode catalyst in this study to improve the power output of microbial fuel cells (MFCs). Different chemical activation agents are used to treat alfalfa leaf-derived carbon (ALC). It is found that chemical activation agents substantially affect the catalytic activities of the alfalfa leaf-derived carbon materials in the power output of MFCs and the oxygen reduction reaction (ORR). ALC materials activated by KOH (ALC-K) exhibit the best electrochemical activity compared with those of materials activated by FeCl3 (ALC-Fe) or ZnCl2 (ALC-Zn). A high limiting current density and excellent long-term stability can be seen with ALC-K as the cathode catalyst, which gives superior results to those of Pt/C. Moreover, a maximum power density of approximately 1328.9 mW/m(2) is obtained from an MFC equipped with an ALC-K cathode, offering performance characteristics comparable to those of a Pt/C cathode as well. This work demonstrates a new method for the production of inexpensive natural resources that exhibit high performance in MFCs

Pomelo peel-derived, N-doped biochar microspheres as an efficient and durable metal-free ORR catalyst in microbial fuel cells

Microbial fuel cells (MFCs) are widely explored for promising green and renewable energy generation; however, their strong reliance on noble metal-based catalysts causes high fabrication costs and thus limits their widespread applications. Herein, metal-free alternatives derived from naturally abundant, renewable pomelo peels are explored. Two kinds of pomelo peel-derived novel N-doped carbocatalysts are presented, i.e., biochar microspheres (BCMs) and their activated porous counterpart (a-BCMs). In comparison with BCMs, the thermal activation processing endowed a-BCMs with significantly enhanced porosity, an elevated N doping content (2.41 vs. 0.51 at%), a 5-fold increased specific surface area (314.3 vs. 62.8 m(2) g(-1)), and a much improved electrical conductivity (0.13 vs. 0.006 S cm(-1)). This metal-free a-BCM catalyst is subsequently employed to construct an MFC cathode for the oxygen reduction reaction (ORR), and an impressive electrocatalytic activity is achieved in 0.1 mol L-1 phosphate-buffered saline (PBS) buffer. The maximum power density reaches as high as 907.2 mW m(-2), comparable to that of the costly Pt/C counterpart (1022.9 mW m(-2)). The long-term durability of the a-BCM electrocatalyst is also demonstrated by continuous running for 90 days, even superior to that of Pt/C. The origin of this excellent electrocatalytic performance of a-BCMs is deeply analyzed and discussed. Furthermore, the 4e(-) reduction pathway is also unraveled for the efficient and durable carbocatalysis of the ORR over a-BCMs in MFCs

Lysine-modified TiO2 nanotube array for optimizing bioelectricity generation in microbial fuel cells

As the carrier of electroactive bacteria and part of the electron migration path, the anode is a restricting factor for the power density of microbial fuel cells (MFCs). In this study, carbon-coated TiO2 nanotube array (TNT/HL) was synthesized by anodization and thermal treatment, for use as anodes in MFCs to promote power production. Due to the sucker structure and the carbon attachment, the TNT/HL anode increased the bacterial loading capacity when exposed under lamplight or natural light. Single-chamber MFCs with the TNT/HL anode achieved a maximum power density of 0.88 W/m(2), which is much higher than that of MFCs using the common commercial carbon cloth (CC) anode (0.61 W/m(2)). Further investigation attributed such superior results to the better biocompatibility, enlarged electroactive surface, decreased electric resistance and Tafel slope of the as-prepared TNT/HL anode. This study introduces a promising anode material for MFCs with high conductivity, high current density, and fast extracellular electron transfer (EET). (C) 2019 Elsevier Ltd. All rights reserved