Co-benefits of greenhouse gas mitigation: A review and classification by type, mitigation sector, and geography

The perceived inability of climate change mitigation goals alone to mobilize sufficient climate change mitigation efforts has, among other factors, led to growing research on the co-benefits of reducing greenhouse gas (GHG) emissions. This study conducts a systematic review (SR) of the literature on the co-benefits of mitigating GHG emissions resulting in 1554 papers. We analyze these papers using bibliometric analysis, including a keyword co-occurrence analysis. We then iteratively develop and present a typology of co-benefits, mitigation sectors, geographic scope, and methods based on the manual double coding of the papers resulting from the SR. We find that the co-benefits from GHG mitigation that have received the largest attention of researchers are impacts on ecosystems, economic activity, health, air pollution, and resource efficiency. The co-benefits that have received the least attention include the impacts on conflict and disaster resilience, poverty alleviation (or exacerbation), energy security, technological spillovers and innovation, and food security. Most research has investigated co-benefits from GHG mitigation in the agriculture, forestry and other land use (AFOLU), electricity, transport, and residential sectors, with the industrial sector being the subject of significantly less research. The largest number of co-benefits publications provide analysis at a global level, with relatively few studies providing local (city) level analysis or studying co-benefits in Oceanian or African contexts. Finally, science and engineering methods, in contrast to economic or social science methods, are the methods most commonly employed in co-benefits papers. We conclude that given the potential mobilizing power of understudied co-benefits (e.g. poverty alleviation) and local impacts, the magnitude of GHG emissions from the industrial sector, and the fact that Africa and South America are likely to be severely affected by climate change, there is an opportunity for the research community to fill these gaps

Dynamics of oppositely charged emulsion droplets

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Electron transport and band structure in phosphorus-doped polycrystalline silicon films

We study transport mechanisms, effective mass, and band structure by measuring the resistivity, Hall, and Seebeck and Nernst coefficients in heavily phosphorus-doped polycrystalline silicon films made by thermal crystallization of amorphous silicon. We observe a change in transport mechanism which results in an increase in electron mobility from 10% to 80% of the single-crystal silicon mobility as the carrier concentration increases from 1019 to 1020 cm-3. Our measurements of effective mass at the Fermi level indicate that as the carrier concentration increases, there is a shift from impurity-band transport to conduction-band transport, and that the electron effective mass is lower in the impurity band than in the conduction band of Si. The shift to conduction-band transport improves electron mobility with carrier density by improving intragrain carrier mean free path lengths and relaxation times. © 2009 American Institute of Physics.published_or_final_versio

A Poisson mixture model to identify changes in RNA polymerase II binding quantity using high-throughput sequencing technology

We present a mixture model-based analysis for identifying differences in the distribution of RNA polymerase II (Pol II) in transcribed regions, measured using ChIP-seq (chromatin immunoprecipitation following massively parallel sequencing technology). The statistical model assumes that the number of Pol II-targeted sequences contained within each genomic region follows a Poisson distribution. A Poisson mixture model was then developed to distinguish Pol II binding changes in transcribed region using an empirical approach and an expectation-maximization (EM) algorithm developed for estimation and inference. In order to achieve a global maximum in the M-step, a particle swarm optimization (PSO) was implemented. We applied this model to Pol II binding data generated from hormone-dependent MCF7 breast cancer cells and antiestrogen-resistant MCF7 breast cancer cells before and after treatment with 17β-estradiol (E2). We determined that in the hormone-dependent cells, ~9.9% (2527) genes showed significant changes in Pol II binding after E2 treatment. However, only ~0.7% (172) genes displayed significant Pol II binding changes in E2-treated antiestrogen-resistant cells. These results show that a Poisson mixture model can be used to analyze ChIP-seq data

Physical-layer Security of Uplink mmWave Transmissions in Cellular V2X Networks

In this paper, we investigate physical-layer security of the uplink millimeter wave communications for a cellular vehicle-to-everything (C-V2X) network comprised of a large number of base stations (BSs) and different categories of V2X nodes, including vehicles, pedestrians, and road side units. Considering the dynamic change and randomness of the topology of the C-V2X network, we model the roadways, the V2X nodes on each roadway, and the BSs by a Poisson line process, a 1D Poisson point process (PPP), and a 2D PPP, respectively. We propose two uplink association schemes for a typical vehicle, namely, the smallest-distance association (SDA) scheme and the largest-power association (LPA) scheme, and we establish a tractable analytical framework to comprehensively assess the security performance of the uplink transmission, by leveraging the stochastic geometry theory. Specifically, for each association scheme, we first obtain new expressions for the association probability of the typical vehicle, and then derive the overall connection outage probability and secrecy outage probability by calculating the Laplace transform of the aggregate interference power. Numerical results are presented to validate our theoretical analysis, and we also provide interesting insights into how the security performance is influenced by various system parameters, including the densities of V2X nodes and BSs. Moreover, we show that the LPA scheme outperforms the SDA scheme in terms of secrecy throughput

Retaining Expression on De-identified Faces

© Springer International Publishing AG 2017The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named k-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kSame fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.Peer reviewe

Photodynamic inactivation of Klebsiella pneumoniae biofilms and planktonic cells by 5-aminolevulinic acid and 5-aminolevulinic acid methyl ester

The treatment of Klebsiella pneumoniae, particularly extended-spectrum β-lactamase (ESBL)-producing K. pneumoniae, is currently a great challenge. Photodynamic antimicrobial chemotherapy is a promising approach for killing antibiotic-resistant bacteria. The aim of this study was to evaluate the capacity of 5-aminolevulinic acid (5-ALA) and its derivative 5-ALA methyl ester (MAL) in the presence of white light to cause photodynamic inactivation (PDI) of K. pneumoniae planktonic and biofilm cells. In the presence of white light, 5-ALA and MAL inactivated planktonic cells in a concentration-dependent manner. Biofilms were also sensitive to 5-ALA and MAL-mediated PDI. The mechanisms by which 5-ALA and MAL caused PDI of ESBL-producing K. pneumonia were also investigated. Exposure of K. pneumonia to light in the presence of either 5-ALA or MAL induced cleavage of genomic DNA and the rapid release of intracellular biopolymers. Intensely denatured cytoplasmic contents and aggregated ribosomes were also detected by transmission electron microscopy. Scanning electron microscopy showed that PDI of biofilms caused aggregated bacteria to detach and that the bacterial cell envelope was damaged. This study provides insights into 5-ALA and MAL-mediated PDI of ESBL-producing K. pneumoniae

Assessment of Cellular Estrogenic Activity Based on Estrogen Receptor-Mediated Reduction of Soluble-Form Catechol-O-Methyltransferase (COMT) Expression in an ELISA-Based System

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Effects of Glucose Concentration on Propofol Cardioprotection against Myocardial Ischemia Reperfusion Injury in Isolated Rat Hearts

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Controlling light-with-light without nonlinearity

According to Huygens' superposition principle, light beams traveling in a linear medium will pass though one another without mutual disturbance. Indeed, it is widely held that controlling light signals with light requires intense laser fields to facilitate beam interactions in nonlinear media, where the superposition principle can be broken. We demonstrate here that two coherent beams of light of arbitrarily low intensity can interact on a metamaterial layer of nanoscale thickness in such a way that one beam modulates the intensity of the other. We show that the interference of beams can eliminate the plasmonic Joule losses of light energy in the metamaterial or, in contrast, can lead to almost total absorbtion of light. Applications of this phenomenon may lie in ultrafast all-optical pulse-recovery devices, coherence filters and THz-bandwidth light-by-light modulators