cssi/SciSciGPT-SciSciNet huggingface dataset:
The role of the Rocky Mountains in the peopling of North America

Abstract This paper argues that the Rocky Mountains played a significantly more important role in the process of the peopling of the New World than archaeologists have traditionally recognized. Although First Americans did not reach the Rockies before they set foot in any other New World region—they could not have, regardless of their point of entry—by Clovis time, evidence suggests that Clovis people knew the Rocky Mountain landscape intimately. Archaeologists should have long anticipated this, given the many resources the Rocky Mountains offer that adjacent, albeit archaeologically better-known regions such as the Plains and some parts of the Far West do not; at least not as ubiquitously. These include plentiful water in the form of streams, lakes, snowpack, and glaciers; high-quality sources of obsidian, chert, quartzite and other knappable stone; and a vertically oriented landscape that maximizes floral and faunal diversity within comparatively condensed space. Two other non-economic characteristics likely contributed significantly to the appeal of the Rocky Mountains to some First Americans: the power and sanctity nearly all humans attribute to mountains, and the seemingly little-recognized fact that northeast Asian Upper Paleolithic people who populated the New World during the terminal Pleistocene occupied mountainous landscapes for some 45,000 years prior to their departure. For many First Americans, mountains—not the flat, windswept tundra of Siberian stereotypes—had always been home. Evidence for the familiarity of Clovis groups with the Rocky Mountain landscapes comes principally from three Clovis caches: Anzick, Fenn, and Mahaffy. All three caches are located in the Rockies, collectively contain artifacts made from ten of the highest-quality stone raw materials available in the Southern, Central and Northern Rockies, and at least one of the caches accompanies the burial of a young child who appears to have been interred intentionally on a prominent and likely sacred landform in a mountain valley. Bringing the paper's argument full circle, that same child's genetic profile shows a direct link to that of another youngster buried thousands of years earlier at the Late Glacial Maximum Mal'ta site in the mountainous Trans-Baikal region of Siberia.
Structural Transformation, Deep Downturns, and Government Policy

Most recessions are a result of some shock to the economic system, typically amplified by financial accelerators, and leading to large balance sheet effects of households and firms, which result in the effects persisting. But, over time, the balance sheets get restored. Even banks recover. But episodically, the “shock” is deeper. It is structural. Among advanced countries, the movement from agricultural to manufacturing in the last century, and the more recent movement from manufacturing to the service sector reflect such a large economic transformation. The associated downturns are longer lasting. The usual responses, in particular, monetary policy, are only of limited efficacy. Policies have to be designed to facilitate such transformations: markets on their own typically do not do well. This paper explains why such transformations are associated with persistently high unemployment, and describes the effects of particular government policies. It looks at the lessons of the Great Depression both for the advanced countries and the developing countries as they go through their structural transformations.
Dynamical tides in highly eccentric binaries: chaos, dissipation, and quasi-steady state

Highly eccentric binary systems appear in many astrophysical contexts, ranging from tidal capture in dense star clusters, precursors of stellar disruption by massive black holes, to high-eccentricity migration of giant planets. In a highly eccentric binary, the tidal potential of one body can excite oscillatory modes in the other during a pericenter passage, resulting in energy exchange between the modes and the binary orbit. These modes exhibit one of three behaviors over multiple passages: low-amplitude oscillations, large amplitude oscillations corresponding to a resonance between the orbital frequency and the mode frequency, and chaotic growth. We study these phenomena with an iterative map, fully exploring how the mode evolution depends on the pericenter distance and other parameters. In addition, we show that the dissipation of mode energy results in a quasi-steady state, with gradual orbital decay punctuated by resonances, even in systems where the mode amplitude would initially grow stochastically. A newly captured star around a black hole can experience significant orbital decay and heating due to the chaotic growth of the mode amplitude and dissipation. A giant planet pushed into a high-eccentricity orbit may experience a similar effect and become a hot or warm Jupiter.
CYP2D6 drug-gene and drug-drug-gene interactions among patients prescribed pharmacogenetically actionable opioids.

Abstract Purpose When codeine and tramadol are used for pain management, it is imperative that nurses are able to assess for potential drug-gene and drug-drug-gene interactions that could adversely impact drug metabolism and ultimately pain relief. Both drugs are metabolized through the CYP2D6 metabolic pathway which can be affected by medications as well the patient's own pharmacogenotype. The purpose of this brief report is to identify drug-gene and drug-drug-gene interactions in 30 adult patients prescribed codeine or tramadol for pain. Methods We used three data sources: (1) six months of electronic health record data on the number and types of medications prescribed to each patient; (2) each patient's CYP2D6 pharmacogenotype, and (3) published data on known CYP2D6 gene-drug and drug-drug-gene interactions. Results Ten patients (33%) had possible drug-gene or drug-drug-gene interactions. Five patients had CYP2D6 drug-gene interactions indicating they were not good candidates for codeine or tramadol. In addition, five patients had potential CYP2D6 drug-drug-gene interactions with either codeine or tramadol. Conclusion Our findings from this exploratory study underscores the importance of assessing and accounting for drug-gene and drug-drug-gene interactions in patients prescribed codeine or tramadol.
Visualization of Peripheral Neuron Sensitization in a Surgical Mouse Model of Osteoarthritis by In Vivo Calcium Imaging

Objective The purpose of this study was to develop a method for analyzing sensory neuron responses to mechanical stimuli in vivo, and to evaluate whether these neuronal responses change after destabilization of the medial meniscus (DMM). Methods DMM or sham surgery was performed in 10-week old male C57BL/6 wild-type or Pirt-GCaMP3+/- mice. All experiments were performed eight weeks after surgery. Knee and hind paw hyperalgesia were assessed in wild-type mice. The retrograde label DiI was injected into the ipsilateral knee to quantify the number of knee-innervating neurons in the L4 dorsal root ganglion (DRG) in wild-type mice. In vivo calcium imaging was performed on the ipsilateral L4 DRG of Pirt-GCaMP3+/- mice as mechanical stimuli (paw pinch, knee pinch, knee twist) were applied to the ipsilateral hind limb. Results Eight weeks after surgery, DMM mice had more hyperalgesia in the knee and hind paw compared to sham mice. Intra-articular injection of DiI labeled similar numbers of neurons in the L4 DRG of sham and DMM mice. Increased numbers of sensory neurons responded to all three mechanical stimuli in DMM mice, as assessed by in vivo calcium imaging. The majority of responses in sham and DMM mice were in small-to-medium-sized neurons, consistent with the size of nociceptors. The magnitude of responses was similar between sham and DMM mice. Conclusions We demonstrated that increased numbers of small-to-medium sized DRG neurons respond to mechanical stimuli 8 weeks after DMM surgery, suggesting that nociceptors have become sensitized by lowering the response threshold. This article is protected by copyright. All rights reserved.
Parametric Study of Alternating Flow Patterns in Non-Reacting Multiple-Swirl Flows

Multiple nozzle combustors, under certain conditions, may result in flowfields that differ between nozzles in an alternating pattern. Previous work has provided some clues on the parameters which govern the appearance of this behavior, but there is a lack of systematic studies. A series of non-reacting simulations of adjacent swirling flows is used to investigate the effect of nozzle exit flare angle and swirl number on the presence of the alternating flow pattern. Two-nozzle simulations are shown to accurately predict if an asymmetric flow characteristic appears and are therefore used in the parametric investigation. Alternating flow patterns are predicted at nozzle exit flare angles of 105 degrees (for a swirl number of 0.79) and 120 degrees (for a swirl number of 0.69 and 0.79). Under conditions close to the stability boundary between symmetric and asymmetric flows, the nozzle exit flare and increased swirl number push the shear layers against the dome wall so that the flows between each nozzle are largely opposite in direction. An increase in nozzle exit flare above 120∘ results in separated flows exiting from the inlet and a return to a symmetric flow state. This is consistent with a proposed physical mechanism based on hydrodynamic stability in turbulent opposed jets.
Optical and mechanical design of a “zipper” photonic crystal optomechanical cavity

Design of a doubly-clamped beam structure capable of localizing mechanical and optical energy at the nanoscale is presented. The optical design is based upon photonic crystal concepts in which patterning of a nanoscale-cross-section beam can result in strong optical localization to an effective optical mode volume of 0.2 cubic wavelengths ((λc)3). By placing two identical nanobeams within the near field of each other, strong optomechanical coupling can be realized for differential motion between the beams. Current designs for thin film silicon nitride beams at a wavelength of λ = 1.5 μ m indicate that such structures can simultaneously realize an optical Q -factor of 7 × 106, motional mass mu ~ 40 picograms, mechanical mode frequency ΩM/2π ~ 170 MHz, and an optomechanical coupling factor (gOM = dωc/dx = ωc/Lom) with effective length LOM ~ λ = 1.5 μm.
Follow-up of Mothers with Suspected Postpartum Depression from Pediatrics Clinics.

Purpose: Pediatric providers are increasingly screening for postpartum depression (PD), yet it unknown how often mothers comply with recommendations to seek treatment. The objectives were to describe the rate at which mothers with suspected PD seek treatment and explore factors that predict help-seeking behavior. Design and Methods: Mothers were recruited from 4 pediatric clinics after identification using the Child Health Improvement through Computer Automation (CHICA) system. Mothers with a positive screen were invited to participate in a telephone interview between January 2012 and December 2014. Mothers reported if they sought treatment or called a community resource. Results: 73 of 133 eligible mothers participated (55% response rate). Fifty women recalled a recommendation to seek help. Only 43.8% (32/73) made a follow up appointment with an adult provider and even fewer kept the appointment. Conclusions: A majority of mothers suspected of having PD recalled a referral for further intervention; yet, less than half took action. Further investigation of barriers of help-seeking behavior is warranted.
Calibrating Data to Sensitivity in Private Data Analysis.

We present an approach to differentially private computation in which one does not scale up the magnitude of noise for challenging queries, but rather scales down the contributions of challenging records. While scaling down all records uniformly is equivalent to scaling up the noise magnitude, we show that scaling records non-uniformly can result in substantially higher accuracy by bypassing the worst-case requirements of differential privacy for the noise magnitudes. This paper details the data analysis platform wPINQ, which generalizes the Privacy Integrated Query (PINQ) to weighted datasets. Using a few simple operators (including a non-uniformly scaling Join operator) wPINQ can reproduce (and improve) several recent results on graph analysis and introduce new generalizations (e.g., counting triangles with given degrees). We also show how to integrate probabilistic inference techniques to synthesize datasets respecting more complicated (and less easily interpreted) measurements.
Growth of face-homogeneous tessellations

A tessellation of the plane is face-homogeneous if for some integer k ≥ 3 there exists a cyclic sequence σ = [ p 0 , p 1 , …, p k − 1 ] of integers ≥ 3 such that, for every face f of the tessellation, the valences of the vertices incident with f are given by the terms of σ in either clockwise or counter-clockwise order. When a given cyclic sequence σ is realizable in this way, it may determine a unique tessellation (up to isomorphism), in which case σ is called monomorphic , or it may be the valence sequence of two or more non-isomorphic tessellations ( polymorphic ). A tessellation whose faces are uniformly bounded in the hyperbolic plane but not uniformly bounded in the Euclidean plane is called a hyperbolic tessellation . Such tessellations are well-known to have exponential growth. We seek the face-homogeneous hyperbolic tessellation(s) of slowest growth rate and show that the least growth rate of such monomorphic tessellations is the “golden mean,” γ = (1+√5)/2 , attained by the sequences [4, 6, 14] and [3, 4, 7, 4] . A polymorphic sequence may yield non-isomorphic tessellations with different growth rates. However, all such tessellations found thus far grow at rates greater than γ .
Understanding and forecasting lifecycle events in information cascades

Most social network sites allow users to reshare a piece of information posted by a user. As time progresses, the cascade of reshares grows, eventually saturating after a certain time period. While previous studies have focused heavily on one aspect of the cascade phenomenon, specifically predicting when the cascade would go viral, in this paper, we take a more holistic approach by analyzing the occurrence of two events within the cascade lifecycle—the period of maximum growth in terms of surge in reshares and the period where the cascade starts declining in adoption. We address the challenges in identifying these periods and then proceed to make a comparative analysis of these periods from the perspective of network topology. We study the effect of several node-centric structural measures on the reshare responses using Granger causality which helps us quantify the significance of the network measures and understand the extent to which the network topology impacts the growth dynamics. This evaluation is performed on a dataset of 7407 cascades extracted from the Weibo social network. Using our causality framework, we found that an entropy measure based on nodal degree causally affects the occurrence of these events in 93.95% of cascades. Surprisingly, this outperformed clustering coefficient and PageRank which we hypothesized would be more indicative of the growth dynamics based on earlier studies. We also extend the Granger causality Vector Autoregression model to forecast the times at which the events occur in the cascade lifecycle.
A formal approach for detection of security flaws in the android permission system

The ever increasing expansion of mobile applications into nearly every aspect of modern life, from banking to healthcare systems, is making their security more important than ever. Modern smartphone operating systems (OS) rely substantially on the permission-based security model to enforce restrictions on the operations that each application can perform. In this paper, we perform an analysis of the permission protocol implemented in Android, a popular OS for smartphones. We propose a formal model of the Android permission protocol in Alloy, and describe a fully automatic analysis that identifies potential flaws in the protocol. A study of real-world Android applications corroborates our finding that the flaws in the Android permission protocol can have severe security implications, in some cases allowing the attacker to bypass the permission checks entirely.
The rate of transient beta frequency events predicts behavior across tasks and species

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations.
Power, Status and Expectations: How Narcissism Manifests Among Women CEOs

Firms face mounting pressure to appoint ethical leaders who will avoid unnecessary risk, scandal and crisis. Alongside mounting evidence that narcissistic leaders place organizations at risk, there is a growing consensus that women are more ethical, transparent and risk-averse than men. We seek to interrogate these claims by analyzing whether narcissism is as prevalent among women CEOs as it is among men CEOs. We further analyze whether narcissistic women CEOs take the same types of risk as narcissistic men CEOs. Drawing on social role and token theories, we test hypotheses related to gender differences in the prevalence and impact of CEO narcissism on firm-level practices. Using a unique dataset that includes a large sample of CEOs of S&P 1500 companies from 1992 through 2014, we create a narcissism composite score for each CEO based on their photograph size in the annual report, and their cash earnings and non-cash earnings relative to the next highest paid executive. We find that women CEOs are less likely to exhibit narcissistic personality traits compared to men CEOs. Furthermore, we find that gender moderates the relationship between narcissistic CEOs and our outcome variables of risk-taking and questionable behaviors.
Constructing multidimensional differential addition chains and their applications

We propose new algorithms for constructing multidimensional differential addition chains and for performing multidimensional scalar point multiplication based on these chains. Our algorithms work in any dimension and offer some key efficiency and security features. In particular, our scalar point multiplication algorithm is uniform, it can be parallelized, and differential addition formulas can be deployed. It also allows trading speed for precomputation cost and storage requirements. These key features and our theoretical estimates indicate that this new algorithm may offer some performance advantages over the existing point multiplication algorithms in practice. We also report some experimental results and verify some of our theoretical findings, and a simplistic Magma implementation is provided.
Illuminant Spectra-Based Source Separation Using Flash Photography

Real-world lighting often consists of multiple illuminants with different spectra. Separating and manipulating these illuminants in post-process is a challenging problem that requires either significant manual input or calibrated scene geometry and lighting. In this work, we leverage a flash/no-flash image pair to analyze and edit scene illuminants based on their spectral differences. We derive a novel physics-based relationship between color variations in the observed flash/no-flash intensities and the spectra and surface shading corresponding to individual scene illuminants. Our technique uses this constraint to automatically separate an image into constituent images lit by each illuminant. This separation can be used to support applications like white balancing, lighting editing, and RGB photometric stereo, where we demonstrate results that outperform state-of-the-art techniques on a wide range of images.
Epitaxial Growth of III-Nitride Layers on Aluminum Nitride Substrates

High quality, epitaxial growth of AlN and AlxGa1−xN by OMVPE has been demonstrated on single-crystal AlN substrates. Here we report characterization of epitaxial layers on an a-face AlN substrate using Rutherford Backscattering/ion channeling, atomic force microscopy (AFM), x-ray rocking curves, and preliminary electrical characterization. Ion channeling along the [1020] axis gives a channeling minimum yield of 1.5% indicating a very high quality epitaxial layer.
How International Actors Help Enforce Domestic Deals

International actors at times seek to help bring peace, democracy, and human rights. Studies of how international actors help enforce political bargains between incumbent governments and their dome...
Simulation of inrush dynamics for unbalanced distribution systems using dynamic-phasor models

Microgrids are a possible solution to mitigate the extensive interruptions in service to end-use customers caused by abnormal events, such as major natural disasters. Microgrids can be formed by energizing portions of the distribution system to interconnect generators and critical loads. In this scenario, inrush dynamic currents can present a barrier for forming microgrids by preventing the necessary switching operations and/or damaging equipment. Modeling inrush dynamics, through electromagnetic transient tools, presents a challenge when the microgrid represents a large portion of a distribution feeder. This paper uses a dynamic-phasor approach to approximate the envelope of inrush dynamics, thus allowing simulations of large systems. The two main contributions of this paper are: a) a new formulation to solve a set of dynamic-phasor differential equations representing an unbalanced distribution system; and b) modeling of transformer saturation in the dynamic-phasor frame. These two contributions allow the inrush phenomena to be simulated on full-size microgrid and/or distribution feeder models. The new formulation and model are implemented in GridLAB-D, and tested on IEEE test systems. The simulations showed good approximation as compared with a more accurate, electromagnetic transient simulation in PSCAD software.
Mechanism of NMDA Receptor Channel Block by MK-801 and Memantine

The NMDA (N-methyl-d-aspartate) receptor transduces the binding of glutamate and glycine, coupling it to the opening of a calcium-permeable ion channel 1 . Owing to the lack of high-resolution structural studies of the NMDA receptor, the mechanism by which ion-channel blockers occlude ion permeation is not well understood. Here we show that removal of the amino-terminal domains from the GluN1–GluN2B NMDA receptor yields a functional receptor and crystals with good diffraction properties, allowing us to map the binding site of the NMDA receptor blocker, MK-801. This crystal structure, together with long-timescale molecular dynamics simulations, shows how MK-801 and memantine (a drug approved for the treatment of Alzheimer’s disease) bind within the vestibule of the ion channel, promote closure of the ion channel gate and lodge between the M3-helix-bundle crossing and the M2-pore loops, physically blocking ion permeation.
Diversity Thresholds: How Social Norms, Visibility, and Scrutiny Relate to Group Composition

Across a field study and four experiments, we examine how social norms and scrutiny affect decisions about adding members of underrepresented populations (e.g., women, racial minorities) to groups....
Printed Graphene Electrochemical Biosensors Fabricated by Inkjet Maskless Lithography for Rapid and Sensitive Detection of Organophosphates

Solution phase printing of graphene-based electrodes has recently become an attractive low-cost, scalable manufacturing technique to create in-field electrochemical biosensors. Here, we report a graphene-based electrode developed via inkjet maskless lithography (IML) for the direct and rapid monitoring of triple-O linked phosphonate organophosphates (OPs); these constitute the active compounds found in chemical warfare agents and pesticides that exhibit acute toxicity as well as long-term pollution to soils and waterways. The IML-printed graphene electrode is nano/microstructured with a 1000 mW benchtop laser engraver and electrochemically deposited platinum nanoparticles (dia. ∼25 nm) to improve its electrical conductivity (sheet resistance decreased from ∼10 000 to 100 Ω/sq), surface area, and electroactive nature for subsequent enzyme functionalization and biosensing. The enzyme phosphotriesterase (PTE) was conjugated to the electrode surface via glutaraldehyde cross-linking. The resulting biosensor was able to rapidly measure (5 s response time) the insecticide paraoxon (a model OP) with a low detection limit (3 nM), and high sensitivity (370 nA/μM) with negligible interference from similar nerve agents. Moreover, the biosensor exhibited high reusability (average of 0.3% decrease in sensitivity per sensing event), stability (90% anodic current signal retention over 1000 s), longevity (70% retained sensitivity after 8 weeks), and the ability to selectively sense OP in actual soil and water samples. Hence, this work presents a scalable printed graphene manufacturing technique that can be used to create OP biosensors that are suitable for in-field applications as well as, more generally, for low-cost biosensor test strips that could be incorporated into wearable or disposable sensing paradigms.
In vivo systems biology approaches to chronic immune/inflammatory pathophysiology

Systems biology offers an emphasis on integrative computational analysis of complex multi-component processes to enhance capability for predictive insights concerning operation of those processes. The immune system represents a prominent arena in which such processes are manifested for vital roles in physiology and pathology, encompassing dozens of cell types and hundreds of reciprocal interactions. Chronic, debilitating pathologies involving immune system dysregulation have become recognized as increasing in incidence over recent decades. While clinical consequences of immune dysregulation in such pathologies are well characterized, treatment options remain limited and focus on ameliorating symptoms. Because it is difficult to recapitulate more than a severely limited facet of the immune system in vitro, application of systems biology approaches to autoimmune and inflammatory pathophysiology in vivo has opened a new door toward discerning disease sub-groups and developing associated stratification strategies for patient treatment. In particular, early instances of these approaches have demonstrated advances in uncovering previously under-appreciated dysregulation of signaling networks between immune system and tissue cells, raising promise for improving upon current therapeutic approaches.
A Gradual Effects Model for Single-Case Designs

Single-case designs are a class of repeated measures experiments used to evaluate the effects of interventions for small or specialized populations, such as individuals with low-incidence disabilities. There has been growing interest in systematic reviews and syntheses of evidence from single-case designs, but there remains a need to further develop appropriate statistical models and effect sizes for data from the designs. We propose a novel model for single-case data that exhibit nonlinear time trends created by an intervention that produces gradual effects, which build up and dissipate over time. The model expresses a structural relationship between a pattern of treatment assignment and an outcome variable, making it appropriate for both treatment reversal and multiple baseline designs. It is formulated as a generalized linear model so that it can be applied to outcomes measured as frequency counts or proportions, both of which are commonly used in single-case research, while providing readily interpretable effect size estimates such as log response ratios or log odds ratios. We demonstrate the gradual effects model by applying it to data from a single-case study and examine the performance of proposed estimation methods in a Monte Carlo simulation of frequency count data.
Pendeo-epitaxial Growth and Characterization of GaN and related Materials on 6H-SiC(0001) and Si(111) Substrates

Discrete and coalesced monocrystalline GaN and AlxGa1−xN layers grown via Pendeoepitaxy (PE) [1] originated from side walls of GaN seed structures containing SiNx top masks have been grown via organometallic vapor phase deposition on GaN/AlN/6HSiC(0001) and GaN(0001)/AlN(0001)/3C-SiC(111)/Si(111) substrates. Scanning and transmission electron microscopies were used to evaluate the external microstructures and the distribution of dislocations, respectively. The dislocation densities in the PE grown films was reduced by at least five orders of magnitude relative to the initial GaN seed layers. Tilting in the coalesced GaN epilayers was observed via X-ray diffraction. A tilt of 0.2° was confined to areas of mask overgrowth; however, no tilting was observed in the material suspended above the SiC substrate. The strong, low-temperature PL band-edge peak at 3.45 eV with a FWHM of 17 meV was comparable to that observed in PE GaN films grown on 6H-SiC(0001). The band-edge in the GaN grown on AlN(0001)/SiC(111)Si(111) substrates was shifted to a lower energy by 10 meV, indicative of a greater tensile stress.
CONTROLLABILITY OF DAMPED SECOND-ORDER INITIAL VALUE PROBLEM FOR A CLASS OF DIFFERENTIAL INCLUSIONS WITH NONLOCAL CONDITIONS ON NONCOMPACT INTERVALS

In this short article, we investigate the controllability of damped second-order initial value problems for a class of differential inclusions with nonlocal conditions on unbounded real interval. We shall employ a theorem of Ma, which is an extension to multivalued maps on locally convex topological spaces, of Schaefer's theorem. Example is provided to illustrate the theory. This work is motivated by the papers of Benchohra and Ntouyas [10] and Benchohra, Gatsori and Ntouyas [8].
Engineering Nitrogen Fixation Activity in an Oxygenic Phototroph

Biological nitrogen fixation is catalyzed by nitrogenase, a complex metalloenzyme found only in prokaryotes. N2 fixation is energetically highly expensive, and an energy-generating process such as photosynthesis can meet the energy demand of N2 fixation. However, synthesis and expression of nitrogenase are exquisitely sensitive to the presence of oxygen. Thus, engineering nitrogen fixation activity in photosynthetic organisms that produce oxygen is challenging. Cyanobacteria are oxygenic photosynthetic prokaryotes, and some of them also fix N2 Here, we demonstrate a feasible way to engineer nitrogenase activity in the nondiazotrophic cyanobacterium Synechocystis sp. PCC 6803 through the transfer of 35 nitrogen fixation (nif) genes from the diazotrophic cyanobacterium Cyanothece sp. ATCC 51142. In addition, we have identified the minimal nif cluster required for such activity in Synechocystis 6803. Moreover, nitrogenase activity was significantly improved by increasing the expression levels of nif genes. Importantly, the O2 tolerance of nitrogenase was enhanced by introduction of uptake hydrogenase genes, showing this to be a functional way to improve nitrogenase enzyme activity under micro-oxic conditions. To date, our efforts have resulted in engineered Synechocystis 6803 strains that, remarkably, have more than 30% of the N2 fixation activity of Cyanothece 51142, the highest such activity established in any nondiazotrophic oxygenic photosynthetic organism. This report establishes a baseline for the ultimate goal of engineering nitrogen fixation ability in crop plants.IMPORTANCE Application of chemically synthesized nitrogen fertilizers has revolutionized agriculture. However, the energetic costs of such production processes and the widespread application of fertilizers have raised serious environmental issues. A sustainable alternative is to endow to crop plants the ability to fix atmospheric N2in situ One long-term approach is to transfer all nif genes from a prokaryote to plant cells and to express nitrogenase in an energy-producing organelle, chloroplast, or mitochondrion. In this context, Synechocystis 6803, the nondiazotrophic cyanobacterium utilized in this study, provides a model chassis for rapid investigation of the necessary requirements to establish diazotrophy in an oxygenic phototroph.
Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases.

Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the ‘no horizontal pleiotropy’ assumption can cause severe bias in MR. We developed the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that the MR-PRESSO test is best suited when horizontal pleiotropy occurs in 48% of causal relationships.
Dichotomies, structure, and concentration in normed spaces

Abstract We use probabilistic, topological and combinatorial methods to establish the following deviation inequality: For any normed space X = ( R n , ‖ ⋅ ‖ ) there exists an invertible linear map T : R n → R n with P ( | ‖ T G ‖ − E ‖ T G ‖ | > e E ‖ T G ‖ ) ≤ C exp ⁡ ( − c max ⁡ { e 2 , e } log ⁡ n ) , e > 0 , where G is the standard n-dimensional Gaussian vector and C , c > 0 are universal constants. It follows that for every e ∈ ( 0 , 1 ) and for every normed space X = ( R n , ‖ ⋅ ‖ ) there exists a k-dimensional subspace of X which is ( 1 + e ) -Euclidean and k ≥ c e log ⁡ n / log ⁡ 1 e . This improves by a logarithmic on e term the best previously known result due to G. Schechtman.
Aerothermodynamic Design Optimization of Hypersonic Vehicles

The objective of this study is to develop a reliable and efficient design optimization method for hypersonic vehicles focused on aerothermodynamic environments. Considering the nature of hypersonic...
Application of Optimized SFCL and STATCOM for the Transient Stability and LVRT Capability Enhancement of Wind Farms

In this paper, the combined superconducting fault current limiter (SFCL) and STATCOM are used to improve transient stability and low-voltage ride-through (LVRT) capability of the wind turbine generation system (WTGS). The SFCL absorbs the accelerating energy of the generator, and therefore, improves the WTGS transient stability. Also, STATCOM helps the restore connecting point voltage to improve LVRT capability by reactive power compensation (RPC) after fault clearing. The optimization problem of SFCL resistance and STATCOM capacity is formulated based on the transient stability and LVRT capability of WTGS. The Simulation study shows the superior improving LVRT capability of combined SFCL and STATCOM over individual SFCL or STATCOM. Also, the required capacity of STATCOM for RPC is significantly reduced. PSCAD/EMTDC software (V4.2) is used for simulation.
A Tree-based Decoder for Neural Machine Translation

Recent advances in Neural Machine Translation (NMT) show that adding syntactic information to NMT systems can improve the quality of their translations. Most existing work utilizes some specific types of linguistically-inspired tree structures, like constituency and dependency parse trees. This is often done via a standard RNN decoder that operates on a linearized target tree structure. However, it is an open question of what specific linguistic formalism, if any, is the best structural representation for NMT. In this paper, we (1) propose an NMT model that can naturally generate the topology of an arbitrary tree structure on the target side, and (2) experiment with various target tree structures. Our experiments show the surprising result that our model delivers the best improvements with balanced binary trees constructed without any linguistic knowledge; this model outperforms standard seq2seq models by up to 2.1 BLEU points, and other methods for incorporating target-side syntax by up to 0.7 BLEU.
Synthetic Genome Defenses against Selfish DNA Elements Stabilize Engineered Bacteria against Evolutionary Failure

Mobile genetic elements drive evolution by disrupting genes and rearranging genomes. Eukaryotes have evolved epigenetic mechanisms, including DNA methylation and RNA interference, that silence mobile elements and thereby preserve the integrity of their genomes. We created an artificial reprogrammable epigenetic system based on CRISPR interference to give engineered bacteria a similar line of defense against transposons and other selfish elements in their genomes. We demonstrate that this CRISPR interference against mobile elements (CRISPRi-ME) approach can be used to simultaneously repress two different transposon families in Escherichia coli, thereby increasing the evolutionary stability of costly protein expression. We further show that silencing a transposon in Acinetobacter baylyi ADP1 reduces mutation rates by a factor of 5, nearly as much as deleting all copies of this element from its genome. By deploying CRISPRi-ME on a broad-host-range vector, we have created a generalizable platform for stabiliz...
Constructing Trustworthy and Safe Communities on a Blockchain-Enabled Social Credits System

The emergence of big data and Artificial Intelligence (AI) technology is reshaping the world. While the technological revolution improves the quality of our life, new concerns are triggered. The superhuman capability enables AI to outperform human workers in many data-and/or computing-intensive tasks. Also, digital superpowers are showing arrogance towards individuals, which erodes the trust foundation of the society. In this position paper, we suggest to construct trustworthy and safe communities based on a BLockchain-Enabled Social credits System (BLESS) that rewards the residents who commit in socially beneficial activities. Human being's true value lies in serving other people. The BLESS system is considered as an efficient approach to promote the value and dignity in efforts focused on enhancing our communities and regulating business and private behaviors. The BLESS system leverages the decentralized architecture of the blockchain network, which not only allows grassroots individuals to participate rating process of a social credit system (SCS), but also provides tamper proof of transaction data in the trustless network environment. The anonymity in blockchain records also protects individuals from being targeted in the fight against powerful enterprises. Smart contract enabled authentication and authorization strategy prevents any unauthorized entity from accessing the credit system. The BLESS scheme is promising to offer a secure, transparent and decentralized SCS.
Efficiently testing local optimality and escaping saddles for ReLU networks

We provide a theoretical algorithm for checking local optimality and escaping saddles at nondifferentiable points of empirical risks of two-layer ReLU networks. Our algorithm receives any parameter value and returns: local minimum, second-order stationary point, or a strict descent direction. The presence of $M$ data points on the nondifferentiability of the ReLU divides the parameter space into at most $2^M$ regions, which makes analysis difficult. By exploiting polyhedral geometry, we reduce the total computation down to one convex quadratic program (QP) for each hidden node, $O(M)$ (in)equality tests, and one (or a few) nonconvex QP. For the last QP, we show that our specific problem can be solved efficiently, in spite of nonconvexity. In the benign case, we solve one equality constrained QP, and we prove that projected gradient descent solves it exponentially fast. In the bad case, we have to solve a few more inequality constrained QPs, but we prove that the time complexity is exponential only in the number of inequality constraints. Our experiments show that either benign case or bad case with very few inequality constraints occurs, implying that our algorithm is efficient in most cases.
NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video Classification

This paper introduces a fast and efficient network architecture, NeXtVLAD, to aggregate frame-level features into a compact feature vector for large-scale video classification. Briefly speaking, the basic idea is to decompose a high-dimensional feature into a group of relatively low-dimensional vectors with attention before applying NetVLAD aggregation over time. This NeXtVLAD approach turns out to be both effective and parameter efficient in aggregating temporal information. In the 2nd Youtube-8M video understanding challenge, a single NeXtVLAD model with less than 80M parameters achieves a GAP score of 0.87846 in private leaderboard. A mixture of 3 NeXtVLAD models results in 0.88722, which is ranked 3rd over 394 teams. The code is publicly available at https://github.com/linrongc/youtube-8m.
Digital Access amongst the Marginalized: Democracy and Internet Governance in Rio de Janeiro

This article examines how new modes of Internet governance and policies intended to expand Internet inclusion unfold in the marginalized communities of Rio de Janerio. In April 2014, Brazil enacted the Marco Civil da Internet (MCI), an “Internet Bill of Rights” that promotes democratic digital governance and regards Internet access as a requisite for civil rights. Rio’s favelas are territories where many of the intended beneficiaries of the Internet access policies live. Yet, drug gangs often control favela neighborhoods and censor the digital access of favela residents, which is just one example of how Internet access in disadvantaged communities is tied to a number of broader socio-political realities and risks. Because these risks index larger disjunctions in contemporary Brazilian democracy, I propose that violence and informal governance in urban favelas creates a corresponding disjunction in the MCI’s pledge of Internet access as a civil right.
Enter the Matrix: Safely Interruptible Autonomous Systems via Virtualization

Autonomous systems that operate around humans will likely always rely on kill switches that stop their execution and allow them to be remote-controlled for the safety of humans or to prevent damage to the system. It is theoretically possible for an autonomous system with sufficient sensor and effector capability that learn online using reinforcement learning to discover that the kill switch deprives it of long-term reward and thus learn to disable the switch or otherwise prevent a human operator from using the switch. This is referred to as the big red button problem. We present a technique that prevents a reinforcement learning agent from learning to disable the kill switch. We introduce an interruption process in which the agent's sensors and effectors are redirected to a virtual simulation where it continues to believe it is receiving reward. We illustrate our technique in a simple grid world environment.
Characterization of surface-solute interactions by diffusioosmosis

The accurate measurement of wall zeta potentials and solute-surface interaction length scales for electrolyte and non-electrolyte solutes, respectively, is critical to the design of many biomedical and microfluidic applications. We present a novel microfluidic approach using diffusioosmosis for measuring either the zeta potentials or the characteristic interaction length scales for surfaces exposed to, respectively, electrolyte or non-electrolyte solutes. When flows containing different solute concentrations merge in a junction, local solute concentration gradients can drive diffusioosmotic flow due to electrokinetic, steric, and other interactions between the solute molecules and solid surfaces. We demonstrate a microfluidic system consisting of a long, narrow pore connecting two large side channels in which solute concentration gradients drive diffusioosmosis within the pore, resulting in predictable fluid velocity/pressure and solute profiles. Furthermore, we present analytical results and a methodology to determine the zeta potential or interaction length scale for the pore surfaces based on the solute concentrations in the main side channels, the flow rate in the pore, and the pressure drop across the pore. We apply this method to the experimental data of Lee et al. to predict the zeta potentials of their system, and we use 3D numerical simulations to validate the theory and show that end effects caused by the junctions are negligible for a wide range of parameters. Because the dynamics in the proposed system are driven by diffusioosmosis, this technique does not suffer from certain disadvantages associated with the use of sensitive electronics in traditional zeta potential measurement approaches such as streaming potential, streaming current, or electroosmosis. To the best of our knowledge this is the first flow-based approach to characterize surface/solute interactions with non-electrolyte solutes.
Derivation of Louisville-Bratu-Gelfand Equation from Shift- or Scale-Invariance

Louisville-Bratu-Gelfand equation appears in many different physical situations ranging from combustion to explosions to astrophysics. The fact that the same equation appears in many different situations seems to indicate that this equation should not depend on any specific physical process, that it should be possible to derive it from general principles. This is indeed what we show in this paper: that this equation can be naturally derived from basic symmetry requirements.
The Bacterial Phosphoenolpyruvate-Sugar Phosphotransferase System*

The bacterial phosphotransferase system participates in diverse physiological phenomena; its best characterized function is in the group translocation of sugars that are substrates of the system. Such sugars are phosphorylated as they are translocated across the cell membrane. Isolation of different proteins of the phosphotransferase system and reconstitution of the complex shows that in the net transfer of the phosphoryl group from phosphoenolpyruvate to a given sugar the phosphoryl group is sequentially transferred from one protein to another. In all cases so far studied, with one important exception, the phosphoryl group is linked to the proteins through a nitrogen atom in the imidazole ring of a histidyl residue. In the exceptional protein, the phosphoryl group is linked to a carboxy group. An additional function of the phosphotransferase system is to regulate the uptake of sugars that cannot be phosphorylated.