Layer-by-layer assembly of the dirhodium complex Rh
(O
CCH
)
(Rh
) with linear
,
'-bidentate ligands pyrazine (L
) or 1,2-bis(4-pyridyl)ethene (L
) on a gold substrate has developed two series of ...redox active molecular wires, (Rh
L
)
@Au and (Rh
L
)
@Au (
= 1-6). By controlling the number of assembling cycles, the molecular wires in the two series vary systematically in length, as characterized by UV-vis spectroscopy, cyclic voltammetry and atomic force microscopy. The current-voltage characteristics recorded by conductive probe atomic force microscopy indicate a mechanistic transition for charge transport from voltage-driven to electrical field-driven in wires with
= 4, irrespective of the nature and length of the wires. Whilst weak length dependence of electrical resistance is observed for both series, (Rh
L
)
@Au wires exhibit smaller distance attenuation factors (
) in both the tunneling (
= 0.044 Å
) and hopping (
= 0.003 Å
) regimes, although in (Rh
L
)
@Au the electronic coupling between the adjacent Rh
centers is stronger. DFT calculations reveal that these wires have a π-conjugated molecular backbone established through π(Rh
)-π(L) orbital interactions, and (Rh
L
)
@Au has a smaller energy gap between the filled π*(Rh
) and the empty π*(L) orbitals. Thus, for (Rh
L
)
@Au, electron hopping across the bridge is facilitated by the decreased metal to ligand charge transfer gap, while in (Rh
L
)
@Au the hopping pathway is disfavored likely due to the increased Coulomb repulsion. On this basis, we propose that the super-exchange tunneling and the underlying incoherent hopping are the dominant charge transport mechanisms for shorter (
≤ 4) and longer (
> 4) wires, respectively, and the Rh
L subunits in mixed-valence states alternately arranged along the wire serve as the hopping sites.
Parrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learning birds. They can imitate human speech, synchronize their ...body movements to a rhythmic beat, and understand complex concepts of referential meaning to sounds. However, little is known about the genetics of these traits. Elucidating the genetic bases would require whole genome sequencing and a robust assembly of a parrot genome.
We present a genomic resource for the budgerigar, an Australian Parakeet (Melopsittacus undulatus) -- the most widely studied parrot species in neuroscience and behavior. We present genomic sequence data that includes over 300× raw read coverage from multiple sequencing technologies and chromosome optical maps from a single male animal. The reads and optical maps were used to create three hybrid assemblies representing some of the largest genomic scaffolds to date for a bird; two of which were annotated based on similarities to reference sets of non-redundant human, zebra finch and chicken proteins, and budgerigar transcriptome sequence assemblies. The sequence reads for this project were in part generated and used for both the Assemblathon 2 competition and the first de novo assembly of a giga-scale vertebrate genome utilizing PacBio single-molecule sequencing.
Across several quality metrics, these budgerigar assemblies are comparable to or better than the chicken and zebra finch genome assemblies built from traditional Sanger sequencing reads, and are sufficient to analyze regions that are difficult to sequence and assemble, including those not yet assembled in prior bird genomes, and promoter regions of genes differentially regulated in vocal learning brain regions. This work provides valuable data and material for genome technology development and for investigating the genomics of complex behavioral traits.
•Research based on real-world smart electric vehicle charging network infrastructure.•More than 4 years data collection of historical charging records.•Adopted Latent Sematic Analysis to build ...mixture user model for behavior prediction.•Decentralized algorithm for smart charging and Vehicle to Grid with 20% cost saving.
With the rapidly growing electric vehicle adoption rate and increasing number of public electric vehicle charging stations in recent years, electric vehicle becomes more and more critical in the demand response programs. Development in Vehicle to Grid technology has converted electric vehicle to distributed energy resources. Using the Electric Vehicle Smart Charging Infrastructures on UCLA campus and city of Santa Monica as testbeds, we have collected real-world datasets of electric vehicle usage, based on which, we proposed optimal bi-directional charging control strategies to integrate electric vehicle in commercial and public parking facilities into the power grid as distributed energy resources for demand response programs by two-stage distributed optimization and water-filling algorithm. Driver behavioral uncertainties have been considered in our approach. Specifically, electric vehicle users are clustered by their behavioral patterns using a modified Latent Semantic Analysis. The first-stage optimization is performed to minimize energy cost using day-ahead wholesale energy price with predictions on energy demand and electric vehicle availability which generated by a mixture user model. Decentralized optimization (second-stage) is carried out on the next day in real-time to control individual electric vehicle so that the aggregated load can follow the first-stage optimal profile. As an alternative, a fast converging water filling algorithm is proposed and compared with two-stage optimization. Extensive simulation results show that proposed charging controls can utilize electric vehicle as distributed energy resource to accommodate demand response program while satisfying electric vehicle energy demands and providing significant energy cost savings.
The American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) uses Current Procedural Terminology (CPT) codes for risk-adjusted calculations. This study evaluates the ...inter-rater reliability of coding colorectal resections across Canada by ACS-NSQIP surgical clinical nurse reviewers (SCNR) and its impact on risk predictions.
SCNRs in Canada were asked to code simulated operative reports. Percent agreement and free-marginal kappa correlation were calculated. The ACS-NSQIP risk calculator was utilized to illustrate its impact on risk prediction.
Responses from 44 of 150 (29.3 %) SCNRs revealed 3 to 6 different codes chosen per case, with agreement ranging from 6.7 % to 62.3 %. Free-marginal kappa correlation ranged from moderate agreement (0.53) to high disagreement (−0.17). ACS-NSQIP risk calculator predicted large absolute differences in risk for serious complications (0.2 %–13.7 %) and mortality (0.2 %–6.3 %).
This study demonstrated low inter-rater reliability in coding ACS-NSQIP colorectal procedures in Canada among SCNRs, impacting risk predictions.
•This study demonstrated low inter-rater reliability across all ACS-NSQIP colorectal resection procedure coding in Canada among SCNRs.•Coding inconsistencies resulted in significant variation in predicted morbidity and mortality, when using the NSQIP risk prediction calculator.•These results highlight the importance of ongoing efforts to improve coding standardization and education among healthcare professionals.
Bats account for one-fifth of mammalian species, are the only mammals with powered flight, and are among the few animals that echolocate. The insect-eating Brandt's bat (Myotis brandtii) is the ...longest-lived bat species known to date (lifespan exceeds 40 years) and, at 4-8 g adult body weight, is the most extreme mammal with regard to disparity between body mass and longevity. Here we report sequencing and analysis of the Brandt's bat genome and transcriptome, which suggest adaptations consistent with echolocation and hibernation, as well as altered metabolism, reproduction and visual function. Unique sequence changes in growth hormone and insulin-like growth factor 1 receptors are also observed. The data suggest that an altered growth hormone/insulin-like growth factor 1 axis, which may be common to other long-lived bat species, together with adaptations such as hibernation and low reproductive rate, contribute to the exceptional lifespan of the Brandt's bat.
The blind mole rat (BMR), Spalax galili, is an excellent model for studying mammalian adaptation to life underground and medical applications. The BMR spends its entire life underground, protecting ...itself from predators and climatic fluctuations while challenging it with multiple stressors such as darkness, hypoxia, hypercapnia, energetics and high pathonecity. Here we sequence and analyse the BMR genome and transcriptome, highlighting the possible genomic adaptive responses to the underground stressors. Our results show high rates of RNA/DNA editing, reduced chromosome rearrangements, an over-representation of short interspersed elements (SINEs) probably linked to hypoxia tolerance, degeneration of vision and progression of photoperiodic perception, tolerance to hypercapnia and hypoxia and resistance to cancer. The remarkable traits of the BMR, together with its genomic and transcriptomic information, enhance our understanding of adaptation to extreme environments and will enable the utilization of BMR models for biomedical research in the fight against cancer, stroke and cardiovascular diseases.
With the increase in electric vehicle (EV) adoption in recent years, the impact of EV charging activity to the power grid has become increasingly significant. Although an EV is considered beneficial ...to the environment by reducing greenhouse gases, large amounts of un-coordinated EV charging could be detrimental to the power grid and thereby degrade power quality. Recent developments in Vehicle to Grid (V2G) technology has converted an EV to a distributed energy resource (DER). A modern smart grid with intelligent IoT devices, solar generation and battery storage provides additional opportunities but also additional challenges to the grid operator. To alleviate the negative effects of massive EV charging load and turn them into grid assets, the current dissertation performs research in designing and developing optimal EV charging strategies to integrate EVs into the smart power grid. Using the UCLA Smart Grid Energy Research Center (SMERC) smart EV charging network infrastructure as the testbed, data has been collected regarding EV driver charging behavior for five years. Based on historical charging records, both deterministic and generative EV user behavior models are proposed to combine statistical analysis and machine learning to predict day-ahead EV driver itinerary and energy demand. Optimal Vehicle Grid Integration strategy is designed to realize different objectives including EV charging cost minimization, power grid stabilization, computational burden decentralization, increasing convergence speed, mitigating solar over-generation, etc. A distributed optimal bi-directional charging scheduling algorithm with asynchronous converging feature has been designed for load curve flattening; A two-stage optimization and a distributed water-filling algorithm have been developed for aggregating EVs to participate in energy market and demand response program. Both large-scale simulation and real-world implementation are conducted to validate and evaluate the performance of these algorithms. Results show that the proposed distributed optimal bi-directional charging scheduling algorithm is able to flatten power peak load by 35% when implemented in a test-bed located within the parking structure 9 in UCLA. A daily energy cost saving of 18% is achieved when the two-stage optimization algorithm is performed to control the EVs in a parking structure in the Civic Center Garage of the City of Santa Monica to participate in wholesale energy markets. Smart meter data collected in the Santa Monica parking lot shows the proposed charging control algorithm is able to mitigate the solar over-generation in the building by 50% on a daily basis. It can be concluded that our Vehicle Grid Integration strategy is effective in stabilizing power grid load, reducing charging cost and solving solar power over-generation problem. In addition to the development of EV user behavior models and Vehicle Grid Integration strategy, this dissertation also solves practical engineering problems for a scalable, reliable and safe EV bi-directional smart charging infrastructure.
The role of chromosome rearrangements in driving evolution has been a long-standing question of evolutionary biology. Here we focused on ruminants as a model to assess how rearrangements may have ...contributed to the evolution of gene regulation. Using reconstructed ancestral karyotypes of Cetartiodactyls, Ruminants, Pecorans, and Bovids, we traced patterns of gross chromosome changes. We found that the lineage leading to the ruminant ancestor after the split from other cetartiodactyls was characterized by mostly intrachromosomal changes, whereas the lineage leading to the pecoran ancestor (including all livestock ruminants) included multiple interchromosomal changes. We observed that the liver cell putative enhancers in the ruminant evolutionary breakpoint regions are highly enriched for DNA sequences under selective constraint acting on lineage-specific transposable elements (TEs) and a set of 25 specific transcription factor (TF) binding motifs associated with recently active TEs. Coupled with gene expression data, we found that genes near ruminant breakpoint regions exhibit more divergent expression profiles among species, particularly in cattle, which is consistent with the phylogenetic origin of these breakpoint regions. This divergence was significantly greater in genes with enhancers that contain at least one of the 25 specific TF binding motifs and located near bovidae-to-cattle lineage breakpoint regions. Taken together, by combining ancestral karyotype reconstructions with analysis of
regulatory element and gene expression evolution, our work demonstrated that lineage-specific regulatory elements colocalized with gross chromosome rearrangements may have provided valuable functional modifications that helped to shape ruminant evolution.
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