Spin-dependent electron-hole capture kinetics in conjugated polymers

The recombination of electron-hole pairs injected in extended conjugated systems is modeled as a multi-pathway vibron-driven relaxation in monoexcited state-space. The computed triplet-to-singlet ratio of exciton formation times $r = \tau_T/\tau_S$ increases from 0.9 for a model dimer to 2.5 for a 32-unit chain, in excellent agreement with experiments. Therewith we rationalize recombination efficiency in terms of spin-dependent interstate vibronic coupling and spin- and conjugation-length-dependent exciton binding energies.Our model calculations for various length polymers indicate that the ratio of the singlet to triplet formation ratios, $r = \sigma_S/\sigma_T$, is inversely related to the ratio of the singlet and triplet binding energies, $\epsilon^b_S/\epsilon^b_T$

Quantitative atomic spectroscopy for primary thermometry

Quantitative spectroscopy has been used to measure accurately the Doppler-broadening of atomic transitions in $^{85}$Rb vapor. By using a conventional platinum resistance thermometer and the Doppler thermometry technique, we were able to determine $k_B$ with a relative uncertainty of $4.1\times 10^{-4}$, and with a deviation of $2.7\times 10^{-4}$ from the expected value. Our experiment, using an effusive vapour, departs significantly from other Doppler-broadened thermometry (DBT) techniques, which rely on weakly absorbing molecules in a diffusive regime. In these circumstances, very different systematic effects such as magnetic sensitivity and optical pumping are dominant. Using the model developed recently by Stace and Luiten, we estimate the perturbation due to optical pumping of the measured $k_B$ value was less than $4\times 10^{-6}$. The effects of optical pumping on atomic and molecular DBT experiments is mapped over a wide range of beam size and saturation intensity, indicating possible avenues for improvement. We also compare the line-broadening mechanisms, windows of operation and detection limits of some recent DBT experiments

Effectively Mapping Linguistic Abstractions for Message-passing Concurrency to Threads on the Java Virtual Machine

Efficient mapping of message passing concurrency (MPC) abstractions to Java Virtual Machine (JVM) threads is critical for performance, scalability, and CPU utilization; but tedious and time consuming to perform manually. In general, this mapping cannot be found in polynomial time, but we show that by exploiting the local characteristics of MPC abstractions and their communication patterns this mapping can be determined effectively. We describe our MPC abstraction to thread mapping technique, its realization in two frameworks (Panini and Akka), and its rigorous evaluation using several benchmarks from representative MPC frameworks. We also compare our technique against four default mapping techniques: thread-all, round-robin-task-all, random-task-all and work-stealing. Our evaluation shows that our mapping technique can improve the performance by 30%-60% over default mapping techniques. These improvements are due to a number of challenges addressed by our technique namely: i) balancing the computations across JVM threads, ii) reducing the communication overheads, iii) utilizing information about cache locality, and iv) mapping MPC abstractions to threads in a way that reduces the contention between JVM threads

Haplotype Network Branch Diversity, a New Metric Combining Genetic and Topological Diversity to Compare the Complexity of Haplotype Networks

A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network features to produce complexity values that cannot be defined in probabilistic terms, thereby obscuring the values’ implication for a sampled population, HBd uses frequencies of haplotype classes to incorporate topological information of networks, keeping the focus on the population and providing easy-to-interpret probabilistic values for randomly sampled individuals. The goal of this study is to introduce this more intuitive metric and provide an R script that allows researchers to calculate diversity and complexity indices from haplotype networks. A group of datasets, generated manually (model dataset) and based on published data (empirical dataset), were used to illustrate the behavior of HBd and both of its terms, haplotype diversity, and a new index called branch diversity. Results followed a predicted trend in both model and empirical datasets, from low metric values in simple networks to high values in complex networks. In short, the new combined metric joins genetic and topological diversity of haplotype networks, into a single complexity value. Based on our analysis, we recommend the use of HBd, as it makes direct comparisons of network complexity straightforward and provides probabilistic values that can readily discriminate situations that are difficult to resolve with available metrics

A Common Endocrine Signature Marks the Convergent Evolution of an Elaborate Dance Display in Frogs

Unrelated species often evolve similar phenotypic solutions to the same environmental problem, a phenomenon known as convergent evolution. But how do these common traits arise? We address this question from a physiological perspective by assessing how convergence of an elaborate gestural display in frogs (foot-flagging) is linked to changes in the androgenic hormone systems that underlie it. We show that the emergence of this rare display in unrelated anuran taxa is marked by a robust increase in the expression of androgen receptor (AR) messenger RNA in the musculature that actuates leg and foot movements, but we find no evidence of changes in the abundance of AR expression in these frogs’ central nervous systems. Meanwhile, the magnitude of the evolutionary change in muscular AR and its association with the origin of foot-flagging differ among clades, suggesting that these variables evolve together in a mosaic fashion. Finally, while gestural displays do differ between species, variation in the complexity of a foot-flagging routine does not predict differences in muscular AR. Altogether, these findings suggest that androgen-muscle interactions provide a conduit for convergence in sexual display behavior, potentially providing a path of least resistance for the evolution of motor performance

Use of Rollover Protective Structures -- Iowa, Kentucky, New York, and Ohio, 1992-1997

Agriculture has one of the highest occupational fatality rates of all industries in the United States (1). Tractors and other types of agricultural equipment account for a large proportion of these fatalities, and farm-tractor rollovers account for approximately 130 work-related deaths each year in the United States (2). Although rollover protective structures (ROPS) are effective in protecting tractor operators from fatal injuries during rollovers (3-5), most tractors in the United States are not equipped with ROPS (4-7). Beginning in 1985, tractor manufacturers in the United Sates agreed to sell only tractors with ROPS; however, many older tractors without ROPS remain in use. To determine the prevalence of the use of ROPS, beginning in 1992, the Farm Family Health and Hazard Surveillance (FFHHS) program * collected state-based data on tractor age and use of ROPS from selected states. As of August 1997, four states had completed collection and analysis of data on farm tractors. This report summarizes the results of that survey, which indicates that 80%-90% of tractors in use in the four states were manufactured before 1985 and that less than 40% are equipped with ROPS

Explaining Myanmar's Regime Transition: The Periphery is Central

In 2010, Myanmar (Burma) held its first elections after 22 years of direct military rule. Few compelling explanations for this regime transition have emerged. This article critiques popular accounts and potential explanations generated by theories of authoritarian ‘regime breakdown’ and ‘regime maintenance’. It returns instead to the classical literature on military intervention and withdrawal. Military regimes, when not terminated by internal factionalism or external unrest, typically liberalise once they feel they have sufficiently addressed the crises that prompted their seizure of power. This was the case in Myanmar. The military intervened for fear that political unrest and ethnic-minority separatist insurgencies would destroy Myanmar’s always-fragile territorial integrity and sovereignty. Far from suddenly liberalising in 2010, the regime sought to create a ‘disciplined democracy’ to safeguard its preferred social and political order twice before, but was thwarted by societal opposition. Its success in 2010 stemmed from a strategy of coercive state-building and economic incorporation via ‘ceasefire capitalism’, which weakened and co-opted much of the opposition. Having altered the balance of forces in its favour, the regime felt sufficiently confident to impose its preferred settlement. However, the transition neither reflected total ‘victory’ for the military nor secured a genuine or lasting peace

Reprogramming human T cell function and specificity with non-viral genome targeting.

Decades of work have aimed to genetically reprogram T cells for therapeutic purposes1,2 using recombinant viral vectors, which do not target transgenes to specific genomic sites3,4. The need for viral vectors has slowed down research and clinical use as their manufacturing and testing is lengthy and expensive. Genome editing brought the promise of specific and efficient insertion of large transgenes into target cells using homology-directed repair5,6. Here we developed a CRISPR-Cas9 genome-targeting system that does not require viral vectors, allowing rapid and efficient insertion of large DNA sequences (greater than one kilobase) at specific sites in the genomes of primary human T cells, while preserving cell viability and function. This permits individual or multiplexed modification of endogenous genes. First, we applied this strategy to correct a pathogenic IL2RA mutation in cells from patients with monogenic autoimmune disease, and demonstrate improved signalling function. Second, we replaced the endogenous T cell receptor (TCR) locus with a new TCR that redirected T cells to a cancer antigen. The resulting TCR-engineered T cells specifically recognized tumour antigens and mounted productive anti-tumour cell responses in vitro and in vivo. Together, these studies provide preclinical evidence that non-viral genome targeting can enable rapid and flexible experimental manipulation and therapeutic engineering of primary human immune cells

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

Proteomic fingerprint identification of Neotropical hard tick species (Acari: Ixodidae) using a self-curated mass spectra reference library

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used as biomarkers for taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both principal component analysis (PCA) and linear discriminant analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens. Author Summary Hard ticks (Ixodidae) are external parasites that feed on the blood of almost every species of terrestrial vertebrate on earth, including humans. Due to a complete dependency on blood, both sexes and even immature stages, are capable of transmitting disease agents to their hosts, causing distress and sometimes death. Despite the public health significance of ixodid ticks, accurate species identification remains problematic. Vector species identification is core to developing effective vector control schemes. Herein, we provide the first report of MALDI identification of several species of field-collected Neotropical tick specimens preserved in ethanol for up to four years. Our methodology shows that identification does not depend on a commercial reference library of lab-reared samples, but with the help of machine learning it can rely on a self-curated reference library. In addition, our approach offers greater accuracy and lower cost per sample than conventional and modern identification approaches such as morphology and molecular barcoding.Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used as biomarkers for taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both principal component analysis (PCA) and linear discriminant analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens. Author Summary Hard ticks (Ixodidae) are external parasites that feed on the blood of almost every species of terrestrial vertebrate on earth, including humans. Due to a complete dependency on blood, both sexes and even immature stages, are capable of transmitting disease agents to their hosts, causing distress and sometimes death. Despite the public health significance of ixodid ticks, accurate species identification remains problematic. Vector species identification is core to developing effective vector control schemes. Herein, we provide the first report of MALDI identification of several species of field-collected Neotropical tick specimens preserved in ethanol for up to four years. Our methodology shows that identification does not depend on a commercial reference library of lab-reared samples, but with the help of machine learning it can rely on a self-curated reference library. In addition, our approach offers greater accuracy and lower cost per sample than conventional and modern identification approaches such as morphology and molecular barcoding