Power Beacon-Assisted Millimeter Wave Ad Hoc Networks

Deployment of low cost power beacons (PBs) is a promising solution for dedicated wireless power transfer (WPT) in future wireless networks. In this paper, we present a tractable model for PB-assisted millimeter wave (mmWave) wireless ad hoc networks, where each transmitter (TX) harvests energy from all PBs and then uses the harvested energy to transmit information to its desired receiver. Our model accounts for realistic aspects of WPT and mmWave transmissions, such as power circuit activation threshold, allowed maximum harvested power, maximum transmit power, beamforming and blockage. Using stochastic geometry, we obtain the Laplace transform of the aggregate received power at the TX to calculate the power coverage probability. We approximate and discretize the transmit power of each TX into a finite number of discrete power levels in log scale to compute the channel and total coverage probability. We compare our analytical predictions to simulations and observe good accuracy. The proposed model allows insights into effect of system parameters, such as transmit power of PBs, PB density, main lobe beam-width and power circuit activation threshold on the overall coverage probability. The results confirm that it is feasible and safe to power TXs in a mmWave ad hoc network using PBs.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Disclosing the Leaching Behavior of Pd@CMK3 catalysts in Formic Acid Decomposition by Electron Tomography

Supported nanocatalysts exhibit different performance in batch and fixed bed reactors for a wide range of liquid phase catalytic reactions due to differences in metal leaching. To investigate this leaching process and its influence on the catalytic performance, a quantitative 3D characterization of the particle size and the particle distribution is important to follow the structural evolution of the active metal catalysts supported on porous materials during the reaction. In this work, electron tomography has been applied to uncover leaching and redeposition of a Pd@CMK3 catalyst during formic acid decomposition in batch and fixed bed reactors. The 3D distribution of Pd NPs on the mesoporous carbon CMK3 has been determined by a quantitative tomographic analysis and the determined structural changes are correlated with the observed differences in activity and stability of formic acid decomposition using batch and fixed bed reactors

Deep Convolution and Correlated Manifold Embedded Distribution Alignment for Forest Fire Smoke Prediction

This paper proposes the deep convolution and correlated manifold embedded distribution alignment (DC-CMEDA) model, which is able to realize the transfer learning classification between and among various small datasets, and greatly shorten the training time. First, pre-trained Resnet50 network is used for feature transfer to extract smoke features because of the difficulty in training small dataset of forest fire smoke; second, a correlated manifold embedded distribution alignment (CMEDA) is proposed to register the smoke features in order to align the input feature distributions of the source and target domains; and finally, a trainable network model is constructed. This model is evaluated in the paper based on satellite remote sensing image and video image datasets. Compared with the deep convolutional integrated long short-term memory (DC-ILSTM) network, DC-CMEDA has increased the accuracy of video images by 1.50 %, and the accuracy of satellite remote sensing images by 4.00 %. Compared the CMEDA algorithm with the ILSTM algorithm, the number of iterations of the former has decreased to 10 times or less, and the algorithm complexity of CMEDA is lower than that of ILSTM. DC-CMEDA has a great advantage in terms of convergence speed. The experimental results show that DC-CMEDA can solve the problem of small sample smoke dataset detection and recognition

Pd–In intermetallic nanoparticles with high catalytic selectivity for liquid-phase semi-hydrogenation of diphenylacetylene

Intermetallic nanoparticles (NPs) are highly interesting materials in catalysis due to their geometrically ordered structures and altered electronic properties, but the synthesis of defined intermetallic NPs remains a challenge. Here, we report a novel and facile approach for the synthesis of intermetallic Pd–In NPs in ionic liquids (ILs) at moderate temperatures. Depending on the molar ratio of the metal precursors and the reaction temperature, single-phase Pd$_3$In, PdIn and Pd$_3$In$_7$ NPs were obtained, which was confirmed, e.g. by powder X-ray diffraction, electron microscopy, and optical emission spectroscopy with inductively coupled plasma. The Pd–In NPs stabilized in ILs were used as catalysts in the liquid-phase semi-hydrogenation of diphenylacetylene (DPA). Highly ordered PdIn NPs with a CsCl type structure revealed both high activity and selectivity to cis-stilbene even at full DPA conversion. Intermetallic compounds such as PdIn can be used to isolate contiguous Pd atoms with another base metal into single Pd sites, thereby increasing the catalytic selectivity of Pd while stabilizing the individual sites in the intermetallic structures. This work may provide new pathways for the synthesis of single-phase intermetallic NPs and future insights into a more rational design of bimetallic catalysts with specific catalytic properties

Assessing the recent impact of COVID-19 on carbon emissions from China using domestic economic data

The outbreak of coronavirus disease 2019 (COVID-19) has caused tremendous loss to human life and economic decline in China and worldwide. It has significantly reduced gross domestic product (GDP), power generation, industrial activity and transport volume; thus, it has reduced fossil-related and cement-induced carbon dioxide (CO 2) emissions in China. Due to time delays in obtaining activity data, traditional emissions inventories generally involve a 2–3-year lag. However, a timely assessment of COVID-19's impact on provincial CO 2 emission reductions is crucial for accurately understanding the reduction and its implications for mitigation measures; furthermore, this information can provide constraints for modeling studies. Here, we used national and provincial GDP data and the China Emission Accounts and Datasets (CEADs) inventory to estimate the emission reductions in the first quarter (Q1) of 2020. We find a reduction of 257.7 Mt. CO 2 (11.0%) over Q1 2019. The secondary industry contributed 186.8 Mt. CO 2 (72.5%) to the total reduction, largely due to lower coal consumption and cement production. At the provincial level, Hubei contributed the most to the reductions (40.6 Mt) due to a notable decrease of 48.2% in the secondary industry. Moreover, transportation significantly contributed (65.1 Mt), with a change of −22.3% in freight transport and −59.1% in passenger transport compared with Q1 2019. We used a point, line and area sources (PLAS) method to test the GDP method, producing a close estimate (reduction of 10.6%). One policy implication is a change in people's working style and communication methods, realized by working from home and holding teleconferences, to reduce traffic emissions. Moreover, GDP is found to have potential merit in estimating emission changes when detailed energy activity data are unavailable. We provide provincial data that can serve as spatial disaggregation constraints for modeling studies and further support for both the carbon cycle community and policy makers

Observational constraints on Cosmic Reionization

Recent observations have set the first constraints on the epoch of reionization (EoR), corresponding to the formation epoch of the first luminous objects. Studies of Gunn-Peterson (GP) absorption, and related phenomena, suggest a qualitative change in the state of the intergalactic medium (IGM) at $z \sim 6$, indicating a rapid increase in the neutral fraction of the IGM, from $x_{HI} 10^{-3}$, perhaps up to 0.1, at $z \ge 6$. Conversely, transmission spikes in the GP trough, and the evolution of the \lya galaxy luminosity function indicate $x_{HI} < 0.5$ at $z\sim 6.5$, while the large scale polarization of the cosmic microwave background (CMB) implies a significant ionization fraction extending to higher redshifts, $z \sim 11 \pm 3$. The results suggest that reionization is less an event than a process, with the process beginning as early as $z \sim 14$, and with the 'percolation', or 'overlap' phase ending at $z \sim 6$. The data are consistent with low luminosity star forming galaxies as being the dominant sources of reionizing photons. Low frequency radio telescopes currently under construction should be able to make the first direct measurements of HI 21cm emission from the neutral IGM during the EoR, and upcoming measurements of secondary CMB temperature anisotropy will provide fine details of the dynamics of the reionized IGM.Comment: to appear in ARAA 2006, vol 44, page 415-462; latex. 84 pages. 15 fi

Pd–Au Bimetallic Catalysts for the Hydrogenation of Muconic Acid to Bio-Adipic Acid

The hydrogenation reaction of muconic acid, produced from biomass using fermentative processes, to bio-adipic acid is one of the most appealing green emerging chemical process. This reaction can be promoted by catalysts based on a metal belonging to the platinum group, and the use of a second metal can preserve and increase their activity. Pd–Au bimetallic nanoparticle samples supported on high-temperature, heat-treated carbon nanofibers were prepared using the sol immobilization method, changing the Pd–Au molar ratio. These catalysts were characterized by TEM, STEM, and XPS analysis and tested in a batch reactor pressurized with hydrogen, where muconic acid dissolved in water was converted to adipic acid. The synthesized Pd–Au bimetallic catalysts showed higher activity than monometallic Au and Pd material and better stability during the recycling tests. Moreover, the selectivity toward the mono-unsaturated changed by decreasing the Pd/Au molar ratio: the higher the amount of gold, the higher the selectivity toward the intermediates

Palladium-Based Bimetallic Nanocrystal Catalysts for the Direct Synthesis of Hydrogen Peroxide

The direct synthesis of H$_{2}$O$_{2}$ from H$_{2}$ and O$_{2}$ is a strongly desired reaction for green processes and a promising alternative to the commercialized anthraquinone process. The design of efficient catalysts with high activity and H$_{2}$O$_{2}$ selectivity is highly desirable and yet challenging. Metal dopants enhance the performance of the active phase by increasing reaction rates, stability, and/or selectivity. The identification of efficient dopants relies mostly on catalysts prepared with a random and non‐uniform deposition of active and promoter phases. To study the promotional effects of metal doping on Pd catalysts, we employ colloidal, bimetallic nanocrystals (NCs) to produce catalysts in which the active and doping metals are colocalized to a fine extent. In the absence of any acid and halide promotors, PdSn and PdGa NCs supported on acid‐pretreated TiO$_{2}$ (PdSn/s‐TiO$_{2}$, PdGa/s‐TiO$_{2}$) were highly efficient and outperformed the monometallic Pd catalyst (Pd/s‐TiO$_{2}$), whereas in the presence of an acid promotor, the overall H$_{2}$O$_{2}$ productivity was also further enhanced for the Ni‐, Ga‐, In‐, and Sn‐doped catalysts with respect to Pd/s‐TiO$_{2}$

Where to Seek Strategic Assets for Competitive Catch-up? A configurational study of emerging multinational enterprises expanding into foreign strategic factor markets

Emerging multinational enterprises (EMNEs) often engage in strategic-asset-seeking foreign direct investment (FDI) for competitive catch-up. This study explores the linkages between an EMNE’s competitive scenario consisting of a configuration of its awareness-motivation-capability (AMC) conditions and the comparative institutional advantages of its strategic-asset-seeking destination. Our configurational analyses of Chinese FDIs in the technology-intensive industries of OECD countries reveal a taxonomy of four distinct asset-seeking strategies of EMNEs. Our findings shed novel insights into the strategic variations within EMNEs based on a theoretically and methodologically extended AMC framework. This study also extends the varieties of capitalism literature by addressing the implications of comparative institutional advantages for foreign entrants, rather than domestic incumbent firms.The first author received funding support from the Australian Research Council (DE130100860) and the National Natural Science Foundation of China (71472038). The second author thanks financial support of Victoria University (RDGS 22-12) and Curtin University (CBS Journal Publication Support Round 1 2016 )

Aromatic Glucosinolate Biosynthesis Pathway in Barbarea vulgaris and its Response to Plutella xylostella Infestation

The inducibility of the glucosinolate resistance mechanism is an energy-saving strategy for plants, but whether induction would still be triggered by glucosinolate-tolerant Plutella xylostella (diamondback moth, DBM) after a plant had evolved a new resistance mechanism (e.g. saponins in Barbara vulgaris) was unknown. In B. vulgaris, aromatic glucosinolates derived from homo-phenylalanine are the dominate glucosinolates, but their biosynthesis pathway are unclear in this plant. In this study, we used G-type (pest-resistant) and P-type (pest-susceptible) B. vulgaris to compare glucosinolate levels and the expression profiles of their biosynthesis genes before and after infestation by DBM larvae. Two different stereoisomers of hydroxylated aromatic glucosinolates are dominant in G- and P-type B. vulgaris, respectively, and are induced by DBM. The transcripts of genes in the glucosinolate biosynthesis pathway and their corresponding transcription factors were identified from an Illumina dataset of G- and P-type B. vulgaris. Many genes involved or potentially involved in glucosinolate biosynthesis were induced in both plant types. The expression patterns of six DBM induced genes were validated by quantitative PCR (qPCR), while six long-fragment genes were validated by molecular cloning. The core structure biosynthetic genes showed high sequence similarities between the two genotypes. In contrast, the sequence identity of two apparent side chain modification genes, the SHO gene in the G-type and the RHO in P-type plants, showed only 77.50% identity in coding DNA sequences and 65.48% identity in deduced amino acid sequences. The homology to GS-OH in Arabidopsis, DBM induction of the transcript and a series of qPCR and glucosinolate analyses of G-type, P-type and F1 plants indicated that these genes control the production of S and R isomers of 2-hydroxy-2-phenylethyl glucosinolate. These glucosinolates were significantly induced by P. xylostella larvae in both the susceptiple P-type and the resistant G-type, even though saponins are the main DBM-resistance causing metabolites in G-type plants. Indol-3-ylmethylglucosinolate was induced in the G-type only. These data will aid our understanding of the biosynthesis and induction of aromatic glucosinolates at the molecular level and also increase our knowledge of the complex mechanisms underpinning defense induction in plants