cssi/SciSciGPT-SciSciNet huggingface dataset:
Pricing for online resource allocation: intervals and paths

We present pricing mechanisms for several online resource allocation problems which obtain tight or nearly tight approximations to social welfare. In our settings, buyers arrive online and purchase bundles of items; buyers' values for the bundles are drawn from known distributions. This problem is closely related to the so-called prophet-inequality of Krengel and Sucheston [23] and its extensions in recent literature. Motivated by applications to cloud economics, we consider two kinds of buyer preferences. In the first, items correspond to different units of time at which a resource is available; the items are arranged in a total order and buyers desire intervals of items. The second corresponds to bandwidth allocation over a tree network; the items are edges in the network and buyers desire paths.Because buyers' preferences have complementarities in the settings we consider, recent constant-factor approximations via item prices do not apply, and indeed strong negative results are known. We develop static, anonymous bundle pricing mechanisms.For the interval preferences setting, we show that static, anonymous bundle pricings achieve a sublogarithmic competitive ratio, which is optimal (within constant factors) over the class of all online allocation algorithms, truthful or not. For the path preferences setting, we obtain a nearly-tight logarithmic competitive ratio. Both of these results exhibit an exponential improvement over item pricings for these settings. Our results extend to settings where the seller has multiple copies of each item, with the competitive ratio decreasing linearly with supply. Such a gradual tradeoff between supply and the competitive ratio for welfare was previously known only for the single item prophet inequality.
François Viète’s revolution in algebra

Francios Viete (1540–1603) was a geometer in search of better techniques for astronomical calculation. Through his theorem on angular sections he found a use for higher-dimensional geometric magnitudes which allowed him to create an algebra for geometry. We show that unlike traditional numerical algebra, the knowns and unknowns in Viete’s logistice speciosa are the relative sizes of non-arithmetized magnitudes in which the “calculations” must respect dimension. Along with this foundational shift Viete adopted a radically new notation based in Greek geometric equalities. His letters stand for values rather than types, and his given values are undetermined. Where previously algebra was founded in polynomials as aggregations, Viete became the first modern algebraist in working with polynomials built from operations, and the notations reflect these conceptions. Viete’s innovations are situated in the context of sixteenth-century practice, and we examine the interpretation of Jacob Klein, the only historian to have conducted a serious inquiry into the ontology of Viete’s “species”.
Manifold properties of planar polygon spaces

Abstract We prove that the tangent bundle of a generic space of planar n-gons with specified side lengths, identified under isometry, plus a trivial line bundle is isomorphic to ( n − 2 ) times a canonical line bundle. We then discuss consequences for orientability, cobordism class, immersions, and parallelizability.
Redistributing the Gains from Trade through Progressive Taxation

Abstract Should a nation's tax system become more progressive as it opens to trade? Does opening to trade change the benefits of a progressive tax system? We answer these question within a standard incomplete markets model with frictional labor markets and Ricardian trade. Consistent with empirical evidence, adverse shocks to comparative advantage lead to labor income losses for import-competition-exposed workers; with incomplete markets, these workers are imperfectly insured and experience welfare losses. A progressive tax system is valuable, as it substitutes for imperfect insurance and redistributes the gains from trade. However, it also reduces the incentives for labor to reallocate away from comparatively disadvantaged locations. We find that optimal progressivity should increase with openness to trade with a ten percentage point increase in openness necessitating a five percentage point increase in marginal tax rates for those at the top of the income distribution.
Evidence Suppression by Prosecutors: Violations of the Brady Rule

We develop a model of individual prosecutors (and teams of prosecutors) to address the incentives for the suppression of exculpatory evidence. Our model assumes that each individual prosecutor trades off a desire for career advancement (by winning a case) and a disutility for knowingly convicting an innocent defendant. We assume a population of prosecutors that is heterogeneous with respect to this disutility, and each individual’s disutility rate is their own private information. A convicted defendant may later discover exculpatory information; a judge will then void the conviction and may order an investigation. Judges are also heterogeneous in their opportunity costs (which is each judge’s private information) of pursuing suspected misconduct. We show that the equilibrium information configuration within the team involves concentration of authority about suppressing/disclosing evidence. We further consider the effect of angst about teammate choices, office culture, and the endogenous choice of effort to suppress evidence.
Deep Learning Hyperspectral Image Classification using Multiple Class-Based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations

Herein, we present a system for hyperspectral image segmentation that utilizes multiple class-based denoising autoen-coders which are efficiently trained. Moreover, we present a novel hyperspectral data augmentation method for labelled HSI data using linear mixtures of pixels from each class, which helps the system with edge pixels which are almost always mixed pixels. Finally, we utilize a deep neural network and morphological hole-filling to provide robust image classification. Results run on the Salinas dataset verify the high performance of the proposed algorithm,
Flow-Grounded Spatial-Temporal Video Prediction from Still Images

Existing video prediction methods mainly rely on observing multiple historical frames or focus on predicting the next one-frame. In this work, we study the problem of generating consecutive multiple future frames by observing one single still image only. We formulate the multi-frame prediction task as a multiple time step flow (multi-flow) prediction phase followed by a flow-to-frame synthesis phase. The multi-flow prediction is modeled in a variational probabilistic manner with spatial-temporal relationships learned through 3D convolutions. The flow-to-frame synthesis is modeled as a generative process in order to keep the predicted results lying closer to the manifold shape of real video sequence. Such a two-phase design prevents the model from directly looking at the high-dimensional pixel space of the frame sequence and is demonstrated to be more effective in predicting better and diverse results. Extensive experimental results on videos with different types of motion show that the proposed algorithm performs favorably against existing methods in terms of quality, diversity and human perceptual evaluation.
Multidimensional Binary Search for Contextual Decision-Making

We consider a multidimensional search problem that is motivated by questions in contextual decision making, such as dynamic pricing and personalized medicine. Nature selects a state from a d-dimens...
A Decentralized Optimal Control Framework for Connected Automated Vehicles at Urban Intersections with Dynamic Resequencing

Earlier work has established a decentralized framework to optimally control Connected Automated Vehicles (CAVs) crossing an urban intersection without using explicit traffic signaling while following a strict First-In-First-Out (FIFO) queueing structure. The proposed solution minimizes energy consumption subject to a FIFO-based throughput maximization requirement. In this paper, we extend the solution to account for asymmetric intersections by relaxing the FIFO constraint and including a dynamic resequencing process so as to maximize traffic throughput. To investigate the tradeoff between throughput maximization and energy minimization objectives, we exploit several alternative problem formulations. In addition, the computational complexity of the resequencing process is analyzed and proved to be bounded, which makes the online implementation computationally feasible. The effectiveness of the dynamic resequencing process in terms of throughput maximization is illustrated through simulation.
Asynchronous stochastic price pump

Abstract We propose a model for equity trading in a population of agents where each agent acts to achieve his or her target stock-to-bond ratio, and, as a feedback mechanism, follows a market adaptive strategy. In this model only a fraction of agents participates in buying and selling stock during a trading period, while the rest of the group accepts the newly set price. Using numerical simulations we show that the stochastic process settles on a stationary regime for the returns. The mean return can be greater or less than the return on the bond and it is determined by the parameters of the adaptive mechanism. When the number of interacting agents is fixed, the distribution of the returns follows the log-normal density. In this case, we give an analytic formula for the mean rate of return in terms of the rate of change of agents’ risk levels and confirm the formula by numerical simulations. However, when the number of interacting agents per period is random, the distribution of returns can significantly deviate from the log-normal, especially as the variance of the distribution for the number of interacting agents increases.
Inequality in Reading and Math Skills Forms Mainly before Kindergarten: A Replication, and Partial Correction, of "Are Schools the Great Equalizer?".

When do children become unequal in reading and math skills? Some research claims that inequality grows mainly before school begins. Some research claims that schools cause inequality to grow. And s...
A Nationalist Backlash to International Refugee Law: Evidence from a Survey Experiment in Turkey

How do international laws affect citizens' willingness to accept refugees? In full and partial democracies, citizens' attitudes can influence national policy. A growing literature suggests international institutions can influence citizens' attitudes on foreign policy issues, and therefore lead to policy change. But those studies are almost entirely confined to domestic human rights and U.S.-based respondents; none consider refugee policy. Using data from a survey experiment administered in September 2017 via face-to-face interviews with 1335 Turkish citizens, we investigate how international norms affect citizens' willingness to accept refugees. Our findings are surprising: reminding people about the government's responsibility under the Refugee Convention to accept refugees triggers a backfire effect, \emph{decreasing} support for accepting them. This effect appears driven by respondents who support the nationalist-populist incumbent party and by lower-educated respondents. We therefore provide evidence that international refugee law -- and perhaps international institutions generally -- can trigger a political backlash, undermining the very policies that they promote.
Non-traditional biomarkers and incident diabetes in the Diabetes Prevention Program: comparative effects of lifestyle and metformin interventions.

We compared the associations of circulating biomarkers of inflammation, endothelial and adipocyte dysfunction and coagulation with incident diabetes in the placebo, lifestyle and metformin intervention arms of the Diabetes Prevention Program, a randomised clinical trial, to determine whether reported associations in general populations are reproduced in individuals with impaired glucose tolerance, and whether these associations are independent of traditional diabetes risk factors. We further investigated whether biomarker–incident diabetes associations are influenced by interventions that alter pathophysiology, biomarker concentrations and rates of incident diabetes. The Diabetes Prevention Program randomised 3234 individuals with impaired glucose tolerance into placebo, metformin (850 mg twice daily) and intensive lifestyle groups and showed that metformin and lifestyle reduced incident diabetes by 31% and 58%, respectively compared with placebo over an average follow-up period of 3.2 years. For this study, we measured adiponectin, leptin, tissue plasminogen activator (as a surrogate for plasminogen activator inhibitor 1), high-sensitivity C-reactive protein, IL-6, monocyte chemotactic protein 1, fibrinogen, E-selectin and intercellular adhesion molecule 1 at baseline and at 1 year by specific immunoassays. Traditional diabetes risk factors were defined as family history, HDL-cholesterol, triacylglycerol, BMI, fasting and 2 h glucose, HbA1c, systolic blood pressure, inverse of fasting insulin and insulinogenic index. Cox proportional hazard models were used to assess the effects of each biomarker on the development of diabetes assessed semi-annually and the effects of covariates on these. E-selectin, (HR 1.19 [95% CI 1.06, 1.34]), adiponectin (0.84 [0.71, 0.99]) and tissue plasminogen activator (1.13 [1.03, 1.24]) were associated with incident diabetes in the placebo group, independent of diabetes risk factors. Only the association between adiponectin and diabetes was maintained in the lifestyle (0.69 [0.52, 0.92]) and metformin groups (0.79 [0.66, 0.94]). E-selectin was not related to diabetes development in either lifestyle or metformin groups. A novel association appeared for change in IL-6 in the metformin group (1.09 [1.021, 1.173]) and for baseline leptin in the lifestyle groups (1.31 [1.06, 1.63]). These findings clarify associations between an extensive group of biomarkers and incident diabetes in a multi-ethnic cohort with impaired glucose tolerance, the effects of diabetes risk factors on these, and demonstrate differential modification of associations by interventions. They strengthen evidence linking adiponectin to diabetes development, and argue against a central role for endothelial dysfunction. The findings have implications for the pathophysiology of diabetes development and its prevention.
Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces

Steady-state visual evoked potential (SSVEP)-based brain computer-interfaces (BCIs) have shown its robustness in facilitating high-efficiency communication. State-of-the-art training-based SSVEP decoding methods such as extended Canonical Correlation Analysis (CCA) and Task-Related Component Analysis (TRCA) are the major players that elevate the efficiency of the SSVEP-based BCIs through a calibration process. However, due to notable human variability across individuals and within individuals over time, calibration (training) data collection is non-negligible and often laborious and time-consuming, deteriorating the practicality of SSVEP BCIs in a real-world context. This study aims to develop a cross-subject transferring approach to reduce the need for collecting training data from a test user with a newly proposed least-squares transformation (LST) method. Study results show the capability of the LST in reducing the number of training templates required for a 40-class SSVEP BCI. The LST method may lead to numerous real-world applications using near-zero-training/plug-and-play high-speed SSVEP BCIs.
Nicotine promotes neuron survival and partially protects from Parkinson's disease by suppressing SIRT6.

Parkinson’s disease is characterized by progressive death of dopaminergic neurons, leading to motor and cognitive dysfunction. Epidemiological studies consistently show that the use of tobacco reduces the risk of Parkinson’s. We report that nicotine reduces the abundance of SIRT6 in neuronal culture and brain tissue. We find that reduction of SIRT6 is partly responsible for neuroprotection afforded by nicotine. Additionally, SIRT6 abundance is greater in Parkinson’s patient brains, and decreased in the brains of tobacco users. We also identify SNPs that promote SIRT6 expression and simultaneously associate with an increased risk of Parkinson’s. Furthermore, brain-specific SIRT6 knockout mice are protected from MPTP-induced Parkinson’s, while SIRT6 overexpressing mice develop more severe pathology. Our data suggest that SIRT6 plays a pathogenic and pro-inflammatory role in Parkinson’s and that nicotine can provide neuroprotection by accelerating its degradation. Inhibition of SIRT6 may be a promising strategy to ameliorate Parkinson’s and neurodegeneration.
Attentional selectivity, automaticity, and self-efficacy predict simulator-acquired skill transfer to the clinical environment.

Abstract Introduction Several studies demonstrated that simulator-acquired skill transfer to the operating room is incomplete. Our objective was to identify trainee characteristics that predict the transfer of simulator-acquired skill to the operating room. Methods Trainees completed baseline assessments including intracorporeal suturing (IS) performance, attentional selectivity, self-reported use of mental skills, and self-reported prior clinical and simulated laparoscopic experience and confidence. Residents then followed proficiency-based laparoscopic skills training, and their skill transfer was assessed on a live-anesthetized porcine model. Predictive characteristics for transfer test performance were assessed using multiple linear regression. Results Thirty-eight residents completed the study. Automaticity, attentional selectivity, resident perceived ability with laparoscopy and simulators, and post-training IS performance were predictive of IS performance during the transfer test. Conclusions Promoting automaticity, self-efficacy, and attention selectivity may help improve the transfer of simulator-acquired skill. Mental skills training and training to automaticity may therefore be valuable interventions to achieve this goal.
Cyber Risk Economics Capability Gaps Research Strategy

This paper calls attention to a forthcoming publication produced by the Cyber Risk Economics Program within the U.S. Department of Homeland Security. It presents an overarching strategy for cyber security risk economics applied research and advanced development intended to address some of the most pressing capability gaps in government and industry.
Temporal starvation in multi-channel CSMA networks: an analytical framework

In this paper we consider a stochastic model for a frequencyagile CSMA protocol for wireless networks where multiple orthogonal frequency channels are available. Even when the possible interference on the different channels is described by different conflict graphs, we show that the network dynamics can be equivalently described as that of a single-channel CSMA algorithm on an appropriate virtual network. Our focus is on the asymptotic regime in which the network nodes try to activate aggressively in order to achieve maximum throughput. Of particular interest is the scenario where the number of available channels is not sufficient for all nodes of the network to be simultaneously active and the well-studied temporal starvation issues of the single-channel CSMA dynamics persist. For most networks we expect that a larger number of available channels should alleviate these temporal starvation issues. However, we prove that the aggregate throughput is a non-increasing function of the number of available channels. To investigate this trade-off that emerges between aggregate throughput and temporal starvation phenomena, we propose an analytical framework to study the transient dynamics of multi-channel CSMA networks by means of first hitting times. Our analysis further reveals that the mixing time of the activity process does not always correctly characterize the temporal starvation in the multi-channel scenario and often leads to pessimistic performance estimates.
Private Seeking of Private Monopoly in Early American Banking

In early nineteenth-century America, banks were chartered through legislative acts of incorporation. Most bank charters established local monopolies so that charters created economic rents. The public choice approach holds that governmental creation of artificial rents invites rent seeking and welfare losses, and more so the larger the potential rents. This chapter provides estimates of rents and potential welfare losses for Pennsylvania. The results suggest that local monopoly rents amounted to approximately 1–1.5% of gross domestic product. Pennsylvania adopted a number of policies, including price ceilings and tax policies, which reduced welfare losses and redistributed some of the rents. The chapter concludes with reflections on the evolving political economy of chartering policy, and why Pennsylvania was slow to reform its practices.
A Fundamental Performance Limitation for Adversarial Classification

Despite the widespread use of machine learning algorithms to solve problems of technological, economic, and social relevance, provable guarantees on the performance of these data-driven algorithms are critically lacking, especially when the data originates from unreliable sources and is transmitted over unprotected and easily accessible channels. In this letter, we take an important step to bridge this gap and formally show that, in a quest to optimize their accuracy, binary classification algorithms—including those based on machine-learning techniques—inevitably become more sensitive to adversarial manipulation of the data. Further, numerical evidence suggests that the accuracy-sensitivity tradeoff depends solely on the statistics of the data, and cannot be improved by tuning the algorithms or increasing their complexity.
School Bus Emissions, Student Health, and Academic Performance

Abstract Diesel emissions from school buses expose children to high levels of air pollution; retrofitting bus engines can substantially reduce this exposure. Using variation from 2656 retrofits across Georgia, we estimate effects of emissions reductions on district-level health and academic achievement. We demonstrate positive effects on respiratory health, measured by a statewide test of aerobic capacity. Placebo tests on body mass index show no impact. We also find that retrofitting districts experience significant test score gains in English and smaller gains in math. Our results suggest that engine retrofits can have meaningful and cost-effective impacts on health and cognitive functioning.
When self‐customization backfires: The role of a maximizing mindset

Self‐customization in online shopping contexts readily offers an abundance of options for consumers. However, the sheer amount of information can quickly become overwhelming. One way to give people the freedom to choose without overwhelming them with information is to simplify the decision process by breaking it down into a series of smaller steps. Contrary to a common assumption that simpler decisions increase choice likelihood, however, this study demonstrates that a simple by-attribute self‐customization process may activate a maximizing mindset, which increases people's desire to find better options and decreases their satisfaction with the ones available. Consequently, simplifying the self‐customization process can sometimes backfire by decreasing choice likelihood. Three studies suggest that although by‐attribute self‐customization formats are easier to choose from, compared with more complex matrix formats, they may sometimes—paradoxically—increase choice deferral. The findings suggest that a maximizing mindset mediates this effect, casting doubt on information‐based alternative explanations. The findings also suggest that whether by‐attribute self‐customization increases or decreases choice likelihood may depend on the presence of objective quality cues, which indicate that an objectively‐best option can be found. This study furthers the understanding of how decision difficulty and maximizing influence self‐customization decisions.
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images

Segmentation of ultra-high resolution images is increasingly demanded, yet poses significant challenges for algorithm efficiency, in particular considering the (GPU) memory limits. Current approaches either downsample an ultra-high resolution image, or crop it into small patches for separate processing. In either way, the loss of local fine details or global contextual information results in limited segmentation accuracy. We propose collaborative Global-Local Networks (GLNet) to effectively preserve both global and local information in a highly memory-efficient manner. GLNet is composed of a global branch and a local branch, taking the downsampled entire image and its cropped local patches as respective inputs. For segmentation, GLNet deeply fuses feature maps from two branches, capturing both the high-resolution fine structures from zoomed-in local patches and the contextual dependency from the downsampled input. To further resolve the potential class imbalance problem between background and foreground regions, we present a coarse-to-fine variant of GLNet, also being memory-efficient. Extensive experiments and analyses have been performed on three real-world ultra-high aerial and medical image datasets (resolution up to 30 million pixels). With only one single 1080Ti GPU and less than 2GB memory used, our GLNet yields high-quality segmentation results, and achieves much more competitive accuracy-memory usage trade-offs compared to state-of-the-arts.
Global supply chain networks and tariff rate quotas: equilibrium analysis with application to agricultural products

In this paper, we develop a global supply chain network model in which profit-maximizing firms engage in competition in the production and distribution of products in the presence of quantitative trade policy instruments in the form of tariff rate quotas. Tariff rate quotas are two-tiered tariffs, in which a lower in-quota tariff is applied to the units of imports until a quota or upper bound is attained and then a higher over-quota tariff is applied to all subsequent imports. They are utilized to protect domestic producers in the case of a wide range of products, from agricultural ones to fabrics and even steel, and can be challenging to formulate. We construct the governing set of novel equilibrium conditions associated with the product flows and Lagrange multipliers, which correspond to quota rent equivalents, and derive the variational inequality formulation. Qualitative properties are presented along with an effective algorithm, which is then applied to compute solutions to numerical examples comprising an agricultural product case study on avocados and global trade. This work is the first to model and solve general, competitive supply chain network problems consisting of oligopolistic firms with multiple production sites and demand markets in multiple countries subject to tariff rate quotas.
Synthesis of 1,8,11,12-Tetrachlorotricyclo[6.2.2.02,7]dodec-2-ene-4,5:9,10-bis(dicarboximides)

1,8,11,12-Tetrachlorotricyclo[6.2.2.02,7]dodec-11-ene-4,5:9,10-bis(dicarboximides) containing similar and different substituents on the nitrogen atoms were selectively synthesized by reactions of the corresponding dianhydride and imide anhydrides with aliphatic and aromatic amines in dimethylformamide. The structure of the resulting diimides was confirmed by independent synthesis via Diels-Alder reaction of N-substituted 1,2,3,4-tetrachlorobicyclo[4.4.0]deca-2,4-diene-8,9-carboximide with substituted maleimides.
A2CuP3S9 (A = K, Rb), Cs2Cu2P2S6, and K3CuP2S7: New Phases from the Dissolution of Copper in Molten Polythiophosphate Fluxes

The reaction of Cu with a molten mixture of A2S/P2S5 (A = K, Rb, Cs) produced the quaternary compounds A2CuP3S9 (A = K, Rb) and Cs2Cu2P2S6. The reaction of Cu with a molten mixture of K2S/P2S5/S pr...
Preparation of aromatic farnesol analogues via a Cu(I)-mediated Grignard coupling of THP ethers

Abstract A Cu(I)-mediated reaction of aromatic Grignard reagents with allylic tetrahydropyranyl ethers results in formation of the coupled products in good yields. This methodology allows facile synthetic manipulation of compounds with two reactive allylic positions.
Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression

By integrating Haar wavelets with Hidden Markov Models, we achieve drastically reduced running times for Bayesian inference using Forward-Backward Gibbs sampling. We show that this improves detection of genomic copy number variants (CNV) in array CGH experiments compared to the state-of-the-art, including standard Gibbs sampling. The method concentrates computational effort on chromosomal segments which are difficult to call, by dynamically and adaptively recomputing consecutive blocks of observations likely to share a copy number. This makes routine diagnostic use and re-analysis of legacy data collections feasible; to this end, we also propose an effective automatic prior. An open source software implementation of our method is available at http://schlieplab.org/Software/HaMMLET/ (DOI: 10.5281/zenodo.46262). This paper was selected for oral presentation at RECOMB 2016, and an abstract is published in the conference proceedings.
Structure and properties of the thorium vanadyl tellurate, Th(VO2)2(TeO6)(H2O)2.

The hydrothermal reaction of Th(NO3)4·xH2O with V2O5 and H6TeO6 at 200 °C under autogenously generated pressure results in the formation of Th(VO2)2(TeO6)(H2O)2 as a pure phase. The single-crystal X-ray data indicate that Th(VO2)2(TeO6)(H2O)2 possesses a three-dimensional structure constructed from ThO9 tricapped trigonal prisms, VO5 distorted square pyramids, VO4 distorted tetrahedra, and TeO6 distorted octahedra. Both of the vanadium polyhedra contain VO2+ vanadyl units with two short VO bond distances. The tellurate octahedron is tetragonally distorted and utilizes all of its oxygen atoms to bond to adjacent metal centers, sharing edges with ThO9 and VO5 units, and corners with two ThO9, one VO5, and two VO4 polyhedra. Crystallographic data: Th(VO2)2(TeO6)(H2O)2, orthorhombic, space group Pbca, a = 12.6921(7), b = 11.5593(7), c = 13.0950(8) A, Z = 8 (T = 193 K). The UV−vis diffuse reflectance spectrum of Th(VO2)2(TeO6)(H2O)2 shows vanadyl-based charge-transfer absorption features. Th(VO2)2(TeO6)(H2O)2...
GAPPadder: a sensitive approach for closing gaps on draft genomes with short sequence reads.

Closing gaps in draft genomes is an important post processing step in genome assembly. It leads to more complete genomes, which benefits downstream genome analysis such as annotation and genotyping. Several tools have been developed for gap closing. However, these tools don’t fully utilize the information contained in the sequence data. For example, while it is known that many gaps are caused by genomic repeats, existing tools often ignore many sequence reads that originate from a repeat-related gap. We compare GAPPadder with GapCloser, GapFiller and Sealer on one bacterial genome, human chromosome 14 and the human whole genome with paired-end and mate-paired reads with both short and long insert sizes. Empirical results show that GAPPadder can close more gaps than these existing tools. Besides closing gaps on draft genomes assembled only from short sequence reads, GAPPadder can also be used to close gaps for draft genomes assembled with long reads. We show GAPPadder can close gaps on the bed bug genome and the Asian sea bass genome that are assembled partially and fully with long reads respectively. We also show GAPPadder is efficient in both time and memory usage. In this paper, we propose a new approach called GAPPadder for gap closing. The main advantage of GAPPadder is that it uses more information in sequence data for gap closing. In particular, GAPPadder finds and uses reads that originate from repeat-related gaps. We show that these repeat-associated reads are useful for gap closing, even though they are ignored by all existing tools. Other main features of GAPPadder include utilizing the information in sequence reads with different insert sizes and performing two-stage local assembly of gap sequences. The results show that our method can close more gaps than several existing tools. The software tool, GAPPadder, is available for download at https://github.com/Reedwarbler/GAPPadder .
EpiAlignment: alignment with both DNA sequence and epigenomic data

Comparative epigenomics, which subjects both epigenome and genome to interspecies comparison, has become a powerful approach to reveal regulatory features of the genome. Thus elucidated regulatory features surpass the information derived from comparison of genomic sequences alone. Here, we present EpiAlignment, a web-based tool to align genomic regions with both DNA sequence and epigenomic data. EpiAlignment takes DNA sequence and epigenomic profiles derived by ChIP-seq from two species as input data, and outputs the best semi-global alignments. These alignments are based on EpiAlignment scores, computed by a dynamic programming algorithm that accounts for both sequence alignment and epigenome similarity. For timely response, the EpiAlignment web server automatically initiates up to 140 computing threads depending on the size of user input data. For users' convenience, we have pre-compiled the comparable human and mouse epigenome datasets in matched cell types and tissues from the Roadmap Epigenomics and ENCODE consortia. Users can either upload their own data or select pre-compiled datasets as inputs for EpiAlignment analyses. Results are presented in graphical and tabular formats where the entries can be interactively expanded to visualize additional features of these aligned regions. EpiAlignment is available at https://epialign.ucsd.edu/.
Spatial Tuning Shifts Increase the Discriminability and Fidelity of Population Codes in Visual Cortex.

Selective visual attention enables organisms to enhance the representation of behaviorally relevant stimuli by altering the encoding properties of single receptive fields (RFs). Yet we know little about how the attentional modulations of single RFs contribute to the encoding of an entire visual scene. Addressing this issue requires (1) measuring a group of RFs that tile a continuous portion of visual space, (2) constructing a population-level measurement of spatial representations based on these RFs, and (3) linking how different types of RF attentional modulations change the population-level representation. To accomplish these aims, we used fMRI to characterize the responses of thousands of voxels in retinotopically organized human cortex. First, we found that the response modulations of voxel RFs (vRFs) depend on the spatial relationship between the RF center and the visual location of the attended target. Second, we used two analyses to assess the spatial encoding quality of a population of voxels. We found that attention increased fine spatial discriminability and representational fidelity near the attended target. Third, we linked these findings by manipulating the observed vRF attentional modulations and recomputing our measures of the fidelity of population codes. Surprisingly, we discovered that attentional enhancements of population-level representations largely depend on position shifts of vRFs, rather than changes in size or gain. Our data suggest that position shifts of single RFs are a principal mechanism by which attention enhances population-level representations in visual cortex. SIGNIFICANCE STATEMENT Although changes in the gain and size of RFs have dominated our view of how attention modulates visual information codes, such hypotheses have largely relied on the extrapolation of single-cell responses to population responses. Here we use fMRI to relate changes in single voxel receptive fields (vRFs) to changes in population-level representations. We find that vRF position shifts contribute more to population-level enhancements of visual information than changes in vRF size or gain. This finding suggests that position shifts are a principal mechanism by which spatial attention enhances population codes for relevant visual information. This poses challenges for labeled line theories of information processing, suggesting that downstream regions likely rely on distributed inputs rather than single neuron-to-neuron mappings.
Ancestry and genetic associations with bronchopulmonary dysplasia in preterm infants.

Bronchopulmonary dysplasia in premature infants is a common and often severe lung disease with long-term sequelae. A genetic component is suspected but not fully defined. We performed an ancestry a...
Environmental high resolution electron microscopy of gas‐catalyst reactions

Environmental electron microscopy has become an important scientific method for fundamental studies of dynamic chemical reaction processes in heterogeneous catalysis and of catalytic growth of carbon nanotubes. Outstanding contributions are resulting from the ability to observe gas‐catalyst surface reactions in situ, on the atomic scale. A great deal of structural and chemical information including lattice modification of working catalysts is possible. This is key to understanding novel reaction processes, including release mechanism of structural oxygen in oxide catalysts in selective oxidation of hydrocarbons and to designing improved catalysts. This brief survey of the recent spectacular developments in environmental high resolution electron microscopy shows that new opportunities are being opened up in catalysis.
Generation of heritable germline mutations in the jewel wasp Nasonia vitripennis using CRISPR/Cas9.

The revolutionary RNA-guided endonuclease CRISPR/Cas9 system has proven to be a powerful tool for gene editing in a plethora of organisms. Here, utilizing this system we developed an efficient protocol for the generation of heritable germline mutations in the parasitoid jewel wasp, Nasonia vitripennis, a rising insect model organism for the study of evolution, development of axis pattern formation, venom production, haplo-diploid sex determination, and host–symbiont interactions. To establish CRISPR-directed gene editing in N. vitripennis, we targeted a conserved eye pigmentation gene cinnabar, generating several independent heritable germline mutations in this gene. Briefly, to generate these mutants, we developed a protocol to efficiently collect N. vitripennis eggs from a parasitized flesh fly pupa, Sarcophaga bullata, inject these eggs with Cas9/guide RNA mixtures, and transfer injected eggs back into the host to continue development. We also describe a flow for screening mutants and establishing stable mutant strains through genetic crosses. Overall, our results demonstrate that the CRISPR/Cas9 system is a powerful tool for genome manipulation in N. vitripennis, with strong potential for expansion to target critical genes, thus allowing for the investigation of several important biological phenomena in this organism.
A Facile Route to Cyclic and Acyclic Alkyl-Arginines

Abstract Treatment of commercially available alkyl and cycloalkyl thioureas with methyl iodide provides the corresponding S-alkylisothiouronium iodide which reacts directly with ornithine to yield the title compounds.
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes

The transfer of a neural network (CNN) trained to recognize objects to the task of scene classification is considered. A Bag-of-Semantics (BoS) representation is first induced, by feeding scene image patches to the object CNN, and representing the scene image by the ensuing bag of posterior class probability vectors (semantic posteriors). The encoding of the BoS with a Fisher vector (FV) is then studied. A link is established between the FV of any probabilistic model and the $Q$ Q -function of the expectation-maximization (EM) algorithm used to estimate its parameters by maximum likelihood. This enables 1) immediate derivation of FVs for any model for which an EM algorithm exists, and 2) leveraging efficient implementations from the EM literature for the computation of FVs. It is then shown that standard FVs, such as those derived from Gaussian or even Dirichlet mixtures, are unsuccessful for the transfer of semantic posteriors, due to the highly non-linear nature of the probability simplex. The analysis of these FVs shows that significant benefits can ensue by 1) designing FVs in the natural parameter space of the multinomial distribution, and 2) adopting sophisticated probabilistic models of semantic feature covariance. The combination of these two insights leads to the encoding of the BoS in the natural parameter space of the multinomial, using a vector of Fisher scores derived from a mixture of factor analyzers (MFA). A network implementation of the MFA Fisher Score (MFA-FS), denoted as the MFAFSNet, is finally proposed to enable end-to-end training. Experiments with various object CNNs and datasets show that the approach has state-of-the-art transfer performance. Somewhat surprisingly, the scene classification results are superior to those of a CNN explicitly trained for scene classification, using a large scene dataset (Places). This suggests that holistic analysis is insufficient for scene classification. The modeling of local object semantics appears to be at least equally important. The two approaches are also shown to be strongly complementary, leading to very large scene classification gains when combined, and outperforming all previous scene classification approaches by a sizable margin.
Single electron transfers in the reactions of carbanions

In assessing the possible role of single-electron-transfer processes in the preparation and reactions of Group 1 and Group 2 organometallic compounds we have proceeded from a discussion of the well-established and abundantly characterized Schlenk adducts to the more labile radical-anions generated and detected in solution and finally to a consideration of the likely role of SET processes in the mechanisms of a wide variety of carbanion reactions. As to the validity of our conclusions concerning such SET processes, it is well to remind ourselves that no mechanistic study proves any reaction mechanism beyond the shadow of reasonable doubt. All we can expect of a suggested reaction mechanism is that it explain all existing experimental data with a economy of speculation (Occam's razor) or that it be abandoned if it cannot account for every significant observation. It is in this sense that this chemist judges that the hypothesis of SET processes promises to be of continuing value in chemical research.
Facile synthesis of O6-alkyl-, O6-aryl-, and diaminopurine nucleosides from 2'-deoxyguanosine

The 3‘,5‘-bis-O-TBDMS derivative of 2‘-deoxyguanosine can be converted to its O6-alkyl and O6-aryl ethers as well as to N6-substituted diaminopurine nucleosides in two simple steps. Also described is a novel, nonaqueous, one-step O6-desulfonylation method that leads to deprotection of the carbonyl moiety of 2‘-deoxyguanosine.
High-pT hadron spectra at RHIC: an overview

Recent results on high transverse momentum (pT) hadron production in p+p, d+Au and Au+Au collisions at the relativistic heavy-ion collider (RHIC) are reviewed. Comparison of the nuclear modification factors, RdAu(pT) and RAA(pT), demonstrates that the large suppression in central Au+Au collisions is due to strong final-state effects. Theoretical models which incorporate jet quenching via gluon bremsstrahlung in the dense partonic medium that is expected in central Au+Au collisions at ultra-relativistic energies are shown to reproduce the shape and magnitude of the observed suppression over the range of collision energies so far studied at RHIC.
A convenient method for the conversion of N-acyloxazolidinones to hydroxamic acids.

Treatment of N-acyloxazolidinones with hydroxylamines using samarium triflate as a Lewis acid provides the corresponding hydroxamic acids in 50−98% yields at room temperature. The conversion proceeds with high degree of chemoselectivity and without racemization of chiral centers α- to the acyl group.
Physics at an upgraded Fermilab proton driver

In 2004 the Fermilab Long Range Planning Committee identified a new high intensity Proton Driver as an attractive option for the future, primarily motivated by the recent exciting developments in neutrino physics. Over the last few months a physics study has developed the physics case for the Fermilab Proton Driver. The potential physics opportunities are discussed.
Government as Landscape Designer: A Behavioral View of Industrial Policy

The strategic management literature has built rich and behaviorally plausible models of firms, yet the industrial policy literature has overlooked nuances in firm behavior. This paper bridges these...
3‐Substituted 2‐pyridinecarbaldoximes

A series of 2-pyridinecarbaldoximes and salts derived from them by methylation of the pyridine nitrogen, all of which are substituted at the 3-position with carbon (i.e., derivatives of nicotinic acid and its homologues) or oxygen, have been prepared.
ω-Halonitriles: Domino Cyclizations to Oxa- and Carbocyclic Nitriles

t-BuOK-induced deprotonation of omega-haloalkylnitriles generates remarkably stable potassiated nitriles. In situ deprotonation and alkylation of omega-chloroalkylnitriles with aldehyde electrophiles trigger sequential nucleophilic-electrophilic alkylations generating substituted tetrahydrofuranyl and tetrahydropyranyl nitriles. Redirecting the cyclization manifold with 5-iodopentanenitrile and a ketone causes a complementary electrophilic-nucleophilic cyclization to the corresponding carbonitrile. Collectively these cyclizations provide rapid assembly of five- and six-membered oxa- and carbocyclic nitriles demonstrating the utility of omega-halonitriles in domino alkylations.
Catalytic Palladium-Mediated Bisdiene Carbocyclizations: Bisdiene to Enediene Cycloisomerizations

The palladium-catalyzed cycloisomerization of acyclic bisdienes to cyclized enedienes defines a novel strategy for the stereoselective cyclization of certain unsymmetric bisdiene substrates to form functionalized five- and six-membered rings. The full details of our investigation into this novel cycloisomerization, including our observations on substrate requirements, stereoselectivity, the influence of the catalyst precursor, and some mechanistic insights drawn from deuterium labeling studies, are discussed.
Applications of highly enantioenriched alcohols bearing a phenylthio group in the preparation of ring compounds. The two-pot synthesis of an enantiopure spiroacetal pheromone bearing three chiral centers

Abstract The new chiron (S)-6-phenylthio-2-hexanol (3) was prepared in high enantiomeric excess by baker's yeast reduction of the corresponding ketone. Enantioenriched alcohols 1, 2 and 3, prepared previously by a similar procedure, or their racemic counterparts, were transformed into ring closed compounds 5-methyl-2-(phenylthio)tetrahydrofuran (9), 6-methyl-2-(phenylthio)tetrahydropyran (10), 2-methyl-1-phenylsulfonyl cyclopropane (14), cyclobutane (15), cyclopentane (16), and a bee pheromone, (2S,6R,8S)-2,8-dimethyl-1,7-dioxaspiro[5.5]undecane (20).
An Ab Initio Study of Lithium Diffusion in Titanium Disulfide Nanotubes

Using density functional theory (DFT), we have investigated the mobility and insertion potential of Li on single-walled TiS2 nanotubes as a function of radius. To explore large radii, the nanotube ...