cssi/SciSciGPT-SciSciNet huggingface dataset:
Long Non-Coding RNA Expression Levels Modulate Cell-Type-Specific Splicing Patterns by Altering Their Interaction Landscape with RNA-Binding Proteins.

Recent developments in our understanding of the interactions between long non-coding RNAs (lncRNAs) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein–RNA interaction networks. Analysis of alternative splicing events across 39 lncRNA knockdown and wildtype RNA-sequencing datasets from three human cell lines—HeLa (cervical cancer), K562 (myeloid leukemia), and U87 (glioblastoma)—resulted in the high-confidence (false discovery rate (fdr) < 0.01) identification of 11,630 skipped exon events and 5895 retained intron events, implicating 759 genes to be impacted at the post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockdown were specific to the cell type. In tandem, the functions annotated to the genes affected by alternative splicing across each lncRNA knockdown also displayed cell-type specificity. To understand the mechanism behind this cell-type-specific alternative splicing pattern, we analyzed RNA-binding protein (RBP)–RNA interaction profiles across the spliced regions in order to observe cell-type-specific alternative splice event RBP binding preference. Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron–exon junctions in a cell-type-specific manner. The cellular functions affected by alternative splicing were also affected in a cell-type-specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs and their downstream functions. We propose that such lncRNA sponges can extensively rewire post-transcriptional gene regulatory networks by altering the protein–RNA interaction landscape in a cell-type-specific manner.
Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals

Insects and hummingbirds exhibit extraordinary flight performance and can simultaneously master seemingly conflicting goals: stable hovering and aggressive maneuvering, which are unmatched by conventional small scale man-made vehicles. Flapping Wing Micro Air Vehicles (FWMAVs) hold great promise for closing this performance gap. However, design and control of such systems remain challenging. Here, we present an open source high fidelity dynamic simulation for FWMAVs. The simulator serves as a testbed for the design, optimization and flight control of FWMAVs. To validate the simulation, we recreated the at-scale hummingbird robot developed in our lab in the simulation. System identification was performed to obtain the model parameters. Force generation and dynamic response of open-loop and closed loop systems between simulated and experimental flights were compared. The unsteady aerodynamics and the highly nonlinear flight dynamics present challenging control problems for conventional and learning control algorithms such as Reinforcement Learning. The interface of the simulation is fully compatible with OpenAI Gym environment. As a benchmark study, we present a linear controller for hovering stabilization and a Deep Reinforcement Learning control policy for goal-directed maneuvering. Finally, we demonstrate direct simulation-to-real transfer of both control policies onto the physical robot, further demonstrating the fidelity of the simulation.
Does institutional trading affect underwriting

Abstract This paper investigates the impact of institutional trading on SEO lead underwriter choice. We measure the trading intensity of the lead investment bank in several different ways and find that bank trading has a significant effect on underwriter choice. A bank that concentrates its trading in particular stocks has an improved probability of earning the underwriting mandate in those stocks. We also find that the trading intensity of the lead bank has a significant effect on SEO underpricing and the composition of the underwriting syndicate. We attribute these results to the fact that banks that are large and active traders in an issuer's stock have a competitive advantage in marketing to the current shareholder base. For smaller banks, we show that concentrating the bank's own trading in the issuer's stock produces similar effects.
Critical Reflections on Visualization Authoring Systems

An emerging generation of visualization authoring systems support expressive information visualization without textual programming. As they vary in their visualization models, system architectures, and user interfaces, it is challenging to directly compare these systems using traditional evaluative methods. Recognizing the value of contextualizing our decisions in the broader design space, we present critical reflections on three systems we developed —Lyra, Data Illustrator, and Charticulator. This paper surfaces knowledge that would have been daunting within the constituent papers of these three systems. We compare and contrast their (previously unmentioned) limitations and trade-offs between expressivity and learnability. We also reflect on common assumptions that we made during the development of our systems, thereby informing future research directions in visualization authoring systems.
Inverting Deep Generative models, One layer at a time

We study the problem of inverting a deep generative model with ReLU activations. Inversion corresponds to finding a latent code vector that explains observed measurements as much as possible. In most prior works this is performed by attempting to solve a non-convex optimization problem involving the generator. In this paper we obtain several novel theoretical results for the inversion problem. We show that for the realizable case, single layer inversion can be performed exactly in polynomial time, by solving a linear program. Further, we show that for two layers, inversion is NP-hard to recover binary latent code (even for the realizable case) and the pre-image set can be non-convex. For generative models of arbitrary depth, we show that exact recovery is possible in polynomial time with high probability, if the layers are expanding and the weights are randomly selected. Very recent work analyzed the same problem for gradient descent inversion. Their analysis requires significantly higher expansion (logarithmic in the latent dimension) while our proposed algorithm can provably reconstruct even with constant factor expansion. We also provide provable error bounds for different norms for reconstructing noisy observations. Our empirical validation demonstrates that we obtain better reconstructions when the latent dimension is large.
Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts

Sports broadcasters inject drama into play-by-play commentary by building team and player narratives through subjective analyses and anecdotes. Prior studies based on small datasets and manual coding show that such theatrics evince commentator bias in sports broadcasts. To examine this phenomenon, we assemble FOOTBALL, which contains 1,455 broadcast transcripts from American football games across six decades that are automatically annotated with 250K player mentions and linked with racial metadata. We identify major confounding factors for researchers examining racial bias in FOOTBALL, and perform a computational analysis that supports conclusions from prior social science studies.
Poisson metrics on flat vector bundles over non-compact curves

Let (E,D,P) be a flat vector bundle with a parabolic structure over a punctured Riemann surface, (M,g). We consider a deformation of the harmonic metric equation which we call the Poisson metric equation. This equation arises naturally as the dimension reduction of the Hermitian-Yang-Mills equation for holomorphic vector bundles on K3 surfaces in the large complex structure limit. We define a notion of slope stability, and show that if the flat connection D has regular singularities, and the Riemannian metric g has finite volume then E admits a Poisson metric with asymptotics determined by the parabolic structure if and only if (E,D,P) is slope polystable.
Progressive image transmission over space-time coded OFDM systems with adaptive modulation

This paper considers a progressive image transmission system over wireless channels by combining joint source-channel coding (JSCC), space-time coding and orthogonal frequency division multiplexing (OFDM) and evaluate its performance. The BER performance of space-time coded OFDM is first evaluated analytically by assuming perfect channel state information at the receiver for coherent detection. Then for a given average SNR (hence BER), a fast local search algorithm is applied to optimize the unequal error protection design in JSCC. With this end-to-end system performance measurement, an adaptive modulation scheme is proposed by assigning different constellation sizes to various SNR ranges to achieve the best image quality. Simulation results confirm the effectiveness of our proposed adaptive modulation scheme.
Superimposed training for doubly selective channels

We adopt a basis expansion approach to model the time and frequency (i.e., doubly) selective fading channel and employ a superimposed training technique to acquire the channel state information. Specifically, we add a known periodic sequence onto, instead of multiplexing it into, the information sequence. There is no reduction in transmission rate, and it is possible to estimate the time-varying channel without requiring receiver diversity. We propose a novel Doppler frequency estimator and describe two equalizers for symbol recovery. Bit error rate performance is demonstrated for the iterative joint data-channel estimator. Tradeoffs regarding power allocation to the pilot and to the symbols are also explored.
Exposing DeepFake Videos By Detecting Face Warping Artifacts

In this work, we describe a new deep learning based method that can effectively distinguish AI-generated fake videos (referred to as {\em DeepFake} videos hereafter) from real videos. Our method is based on the observations that current DeepFake algorithm can only generate images of limited resolutions, which need to be further warped to match the original faces in the source video. Such transforms leave distinctive artifacts in the resulting DeepFake videos, and we show that they can be effectively captured by convolutional neural networks (CNNs). Compared to previous methods which use a large amount of real and DeepFake generated images to train CNN classifier, our method does not need DeepFake generated images as negative training examples since we target the artifacts in affine face warping as the distinctive feature to distinguish real and fake images. The advantages of our method are two-fold: (1) Such artifacts can be simulated directly using simple image processing operations on a image to make it as negative example. Since training a DeepFake model to generate negative examples is time-consuming and resource-demanding, our method saves a plenty of time and resources in training data collection; (2) Since such artifacts are general existed in DeepFake videos from different sources, our method is more robust compared to others. Our method is evaluated on two sets of DeepFake video datasets for its effectiveness in practice.
Bivariate Kolchin-type dimension polynomials of non-reflexive prime difference-differential ideals. The case of one translation

Abstract We use the method of characteristic sets with respect to two term orderings to prove the existence and obtain a method of computation of a bivariate Kolchin-type dimension polynomial associated with a non-reflexive difference-differential ideal in the algebra of difference-differential polynomials with several basic derivations and one translation. In particular, we obtain a new proof and a method of computation of the dimension polynomial of a non-reflexive prime difference ideal in the algebra of difference polynomials over an ordinary difference field. As a consequence, it is shown that the reflexive closure of a prime difference polynomial ideal is the inverse image of this ideal under a power of the basic translation. We also discuss applications of our results to the analysis of systems of algebraic difference-differential equations.
Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance.

Evolved resistance to one antibiotic may be associated with "collateral" sensitivity to other drugs. Here, we provide an extensive quantitative characterization of collateral effects in Enterococcus faecalis, a gram-positive opportunistic pathogen. By combining parallel experimental evolution with high-throughput dose-response measurements, we measure phenotypic profiles of collateral sensitivity and resistance for a total of 900 mutant–drug combinations. We find that collateral effects are pervasive but difficult to predict because independent populations selected by the same drug can exhibit qualitatively different profiles of collateral sensitivity as well as markedly different fitness costs. Using whole-genome sequencing of evolved populations, we identified mutations in a number of known resistance determinants, including mutations in several genes previously linked with collateral sensitivity in other species. Although phenotypic drug sensitivity profiles show significant diversity, they cluster into statistically similar groups characterized by selecting drugs with similar mechanisms. To exploit the statistical structure in these resistance profiles, we develop a simple mathematical model based on a stochastic control process and use it to design optimal drug policies that assign a unique drug to every possible resistance profile. Stochastic simulations reveal that these optimal drug policies outperform intuitive cycling protocols by maintaining long-term sensitivity at the expense of short-term periods of high resistance. The approach reveals a new conceptual strategy for mitigating resistance by balancing short-term inhibition of pathogen growth with infrequent use of drugs intended to steer pathogen populations to a more vulnerable future state. Experiments in laboratory populations confirm that model-inspired sequences of four drugs reduce growth and slow adaptation relative to naive protocols involving the drugs alone, in pairwise cycles, or in a four-drug uniform cycle.
Non-LTE Models and Theoretical Spectra of Accretion Disks in Active Galactic Nuclei

We present self-consistent models of the vertical structure and emergent spectrum of active galactic nucleus (AGN) accretion disks. The central object is assumed to be a supermassive Kerr black hole. We demonstrate that non-LTE (NLTE) effects and the effects of a self-consistent vertical structure of a disk play a very important role in determining the emergent radiation and therefore should be taken into account. In particular, NLTE models exhibit a largely diminished H I Lyman discontinuity when compared to LTE models, and the He II discontinuity appears strongly in emission for NLTE models. Consequently, the number of ionizing photons in the He II Lyman continuum predicted by NLTE disk models is 1-2 orders of magnitude higher than that following from the blackbody approximation. This prediction has important implications for ionization models of AGN broad-line regions and for models of the intergalactic radiation field and the ionization of helium in the intergalactic medium.
Investigation of spin orbit torque driven dynamics in ferromagnetic heterostructures

Abstract We use time-resolved (TR) measurements based on the polar magneto-optical Kerr effect (MOKE) to study the magnetization dynamics excited by spin orbit torques in Py (Permalloy)/Pt and Ta/CoFeB bilayers. The analysis reveals that the field-like (FL) spin orbit torque (SOT) dominates the amplitude of the first oscillation cycle of the magnetization precession and the damping-like (DL) torque determines the final steady-state magnetization. In our bilayer samples, we have extracted the effective fields, hFL and hDL, of the two SOTs from the time-resolved magnetization oscillation spectrum. The extracted values are in good agreement with those extracted from time-integrated DCMOKE measurements, suggesting that the SOTs do not change at high frequencies. We also find that the amplitude ratio of the first oscillation to steady state is linearly proportional to the ratio hFL/hDL. The first oscillation amplitude is inversely proportional to, whereas the steady state value is independent of, the applied external field along the current direction.
Four-volume cutoff measure of the multiverse

Predictions in an eternally inflating multiverse are meaningless unless we specify the probability measure. The scale-factor cutoff is perhaps the simplest and most successful measure which avoids catastrophic problems such as the youngness paradox, runaway problem, and Boltzmann brain problem, but it is not well defined in contracting regions with a negative cosmological constant. In this paper, we propose a new measure with properties similar to the scale-factor cutoff which is well-defined everywhere. The measure is defined by a cutoff in the four volume spanned by infinitesimal comoving neighborhoods in a congruence of timelike geodesics. The probability distributions for the cosmological constant and for the curvature parameter in this measure are similar to those for the scale-factor cutoff and are in a good agreement with observations.
Comparative-effectiveness of pembrolizumab vs. nivolumab for patients with metastatic melanoma

Background: Pembrolizumab (P) and nivolumab (N) are commonly used therapies for advanced melanoma. However, their effectiveness has never been directly compared, leaving little guidance for clinici...
A Simple Approach for Vortex Core Visualization

We propose a method to visualize vortex cores based on manipulation of the pressure field produced by isolated vortices in incompressible flow. Under ideal conditions the function $D=2|\nabla P|/\nabla^2 P$ yields an approximate distance to vortex centerlines. As opposed to local methods to identify coherent structures, isosurfaces of $D$ produce a field of vortex tubes equidistant to the vortex core center which, ideally, are independent of vortex intensity or size. In contrast to other line-vortex identification methods, which typically rely on algorithms to detect vortex core lines and frequently need complex implementations, the proposed method can be computed from the local Eulerian velocity and pressure fields as easily as vortex identification methods such as the $Q$ and $\lambda_2$ criteria. $2|\nabla P|/\nabla^2 P$ results in the exact distance to the core center for a Rankine vortex and is in general valid for the region of a vortex where there is pure rotation, yielding an approximation to the distance farther from the core in other simple one-dimensional vortex models. The methodology performs well in all tests we attempted, though limitations are presented and discussed. The method is demonstrated for a canonical Burgers vortex, a Bodewadt vortex, homogeneous isotropic turbulent flow, the wake of a propeller, a heaving plate, a turning containership and the airwake of a surface combatant. The proposed method helps to better visualize vortical flow fields by displaying vortex cores, complementing methods like $Q$ and $\lambda_2$ which display vortical volumes.
Receptor-based mechanism of relative sensing and cell memory in mammalian signaling networks

Detecting relative rather than absolute changes in extracellular signals enables cells to make decisions in constantly fluctuating environments. It is currently not well understood how mammalian signaling networks store the memories of past stimuli and subsequently use them to compute relative signals, that is perform fold change detection. Using the growth factor-activated PI3K-Akt signaling pathway, we develop here computational and analytical models, and experimentally validate a novel non-transcriptional mechanism of relative sensing in mammalian cells. This mechanism relies on a new form of cellular memory, where cells effectively encode past stimulation levels in the abundance of cognate receptors on the cell surface. The surface receptor abundance is regulated by background signal-dependent receptor endocytosis and down-regulation. We show the robustness and specificity of relative sensing for two physiologically important ligands, epidermal growth factor (EGF) and hepatocyte growth factor (HGF), and across wide ranges of background stimuli. Our results suggest that similar mechanisms of cell memory and fold change detection may be important in diverse signaling cascades and multiple biological contexts.
Motion Decoupling and Composition via Reduced Order Model optimization for Dynamic Humanoid Walking with CLF-QP based Active Force Control

In this paper, 3D humanoid walking is decoupled into periodic and transitional motion, each of which is decoupled into planar walking in the sagittal and lateral plane. Reduced order models (ROMs), i.e. actuated Spring-loaded Inverted Pendulum (aSLIP) models and Hybrid-Linear Inverted Pendulum (H-LIP) models, are utilized for motion generation on the desired center of mass (COM) dynamics for each type of planar motion. The periodic motion is planned via point foot (underactuated) ROMs for dynamic motion with minimum ankle actuation, while the transitional motion is planned via foot-actuated ROMs for fast and smooth transition. Composition of the planar COM dynamics yields the desired COM dynamics in 3D, which is embedded on the humanoid via control Lyapunov function based Quadratic programs (CLF-QPs). Additionally, the ground reaction force profiles of the aSLIP walking are used as desired references for ground contact forces in the CLF-QPs for smooth domain transitions. The proposed framework is realized on a lower-limb exoskeleton in simulation wherein different walking motions are achieved.
Local structure order parameters and site fingerprints for quantification of coordination environment and crystal structure similarity

Structure characterization and classification is frequently based on local environment information of all or selected atomic sites in the crystal structure. Therefore, reliable and robust procedures to find coordinated neighbors and to evaluate the resulting coordination pattern (e.g., tetrahedral, square planar) are critically important for both traditional and machine learning approaches that aim to exploit site or structure information for predicting materials properties. Here, we introduce new local structure order parameters (LoStOPs) that are specifically designed to rapidly detect highly symmetric local coordination environments (e.g., Platonic solids such as a tetrahedron or an octahedron) as well as less symmetric ones (e.g., Johnson solids such as a square pyramid). Furthermore, we introduce a Monte Carlo optimization approach to ensure that the different LoStOPs are comparable with each other. We then apply the new local environment descriptors to define site and structure fingerprints and to measure similarity between 61 known coordination environments and 40 commonly studied crystal structures, respectively. After extensive testing and optimization, we determine the most accurate structure similarity assessment procedure to compute all 2.45 billion structure similarities between each pair of the ≈70 000 materials that are currently present in the Materials Project database.
An examination of longitudinal study typologies for business research

Longitudinal studies have become a standard methodology for academic research that examines issues in the ever-changing, complex global world of business. In business research, longitudinal studies are particularly effective for measuring how business policies and strategies affect the performance of a business firm over time. The literature's call for more longitudinal studies runs up against a rather incoherent and potentially confusing use of terminology and typology undermining the accessibility for business academics and practitioners who are not familiar with this area. This study provides a thorough review of longitudinal study typologies, including an annotated, illustrated methodological framework integrating the key facets of observational longitudinal studies. Although the framework is generalisable beyond the behavioural or business context, it refrains from dealing with the specific nuances of areas such as medicine. This review and framework should be beneficial to academics and other researchers in properly describing, setting up, and understanding longitudinal studies.
The Multispecies Coalescent Model Outperforms Concatenation Across Diverse Phylogenomic Data Sets

A statistical framework of model comparison and model validation is essential to resolving the debates over concatenation and coalescent models in phylogenomic data analysis. A set of statistical tests are here applied and developed to evaluate and compare the adequacy of substitution, concatenation, and multispecies coalescent (MSC) models across 47 phylogenomic data sets collected across tree of life. Tests for substitution models and the concatenation assumption of topologically congruent gene trees suggest that a poor fit of substitution models, rejected by 44% of loci, and concatenation models, rejected by 38% of loci, is widespread. Logistic regression shows that the proportions of GC content and informative sites are both negatively correlated with the fit of substitution models across loci. Moreover, a substantial violation of the concatenation assumption of congruent gene trees is consistently observed across six major groups (birds, mammals, fish, insects, reptiles, and others, including other invertebrates). In contrast, among those loci adequately described by a given substitution model, the proportion of loci rejecting the MSC model is 11%, significantly lower than those rejecting the substitution and concatenation models. Although conducted on reduced data sets due to computational constraints, Bayesian model validation and comparison both strongly favor the MSC over concatenation across all data sets; the concatenation assumption of congruent gene trees rarely holds for phylogenomic data sets with more than 10 loci. Thus, for large phylogenomic data sets, model comparisons are expected to consistently and more strongly favor the coalescent model over the concatenation model. We also found that loci rejecting the MSC have little effect on species tree estimation. Our study reveals the value of model validation and comparison in phylogenomic data analysis, as well as the need for further improvements of multilocus models and computational tools for phylogenetic inference. [Bayes factor; Bayesian model validation; coalescent prior; congruent gene trees; independent prior; Metazoa; posterior predictive simulation.].
A converse to a theorem of Gross, Zagier, and Kolyvagin

Let $E$ be a semistable elliptic curve over $\mathbb{Q}$. We prove that if $E$ has non-split multiplicative reduction at at least one odd prime or split multiplicative reduction at at least two odd primes and if the rank of $E(\mathbb{Q})$ is one and the Tate-Shafarevich group of $E$ has finite order, then $\mathrm{ord}_{s=1}L(E,s)=1$. We also prove the corresponding result for the abelian variety associated with a weight two newform $f$ of trivial character. These, and other related results, are consequences of our main theorem, which establishes criteria for $f$ and $H^1_f(\mathbb{Q},V)$, where $V$ is the $p$-adic Galois representation associated with $f$, that ensure that $\mathrm{ord}_{s=1}L(f,s)=1$. The main theorem is proved using the Iwasawa theory of $V$ over an imaginary quadratic field to show that the $p$-adic logarithm of a suitable Heegner point is non-zero.
Groundwater Management in the Borderlands of Mexico and Texas: The Beauty of the Unknown, the Negligence of the Present, and the Way Forward

Over the last decade, transboundary aquifers traversing the Mexico‐Texas border have generated growing interest of federal institutions on the Mexico side and state and federal institutions on the Texas side. Notwithstanding this, binational efforts to understand, assess, and manage shared groundwater resources remain limited and politically sensitive. On the Mexico side, long‐standing centralized groundwater governance structures have created institutional barriers at the local level to the expansion of knowledge and cooperation over these transboundary resources. On the Texas side, property rights related to groundwater resources limit the scope of options available for cooperative management of cross‐border aquifers. This paper examines stakeholders' perspectives on the borderland between Mexico and Texas through 44 surveys and personal interviews. Findings show that stakeholders appear to support a binational groundwater agreement as a means for assuring the sound long‐term management of transboundary groundwater resources in the border region; however, the majority of stakeholders also suggest that short‐term local or regional arrangements may be preferable over binational agreements as local/regional approaches may be more achievable or realistic. Second, participants identified leadership and individual personalities as key factors for success at the local level but noted that such influence had limited sustainability and limited regional‐systemic effects. Third, the stakeholders indicated that water quality, rather than water quantity, is the main driver of transboundary cooperation efforts in the region. Fourth, participants suggested that failures and successes in groundwater cooperation efforts are based more on fear and political lobbying than on understanding of scientific facts.
Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Turbulence governs the development and erosion of wind farm wakes, which can deplete the offshore wind resource. Therefore, an accurate understanding of atmospheric turbulence is required to support the rapid growth of offshore wind energy. Using 13 months of lidar observations off the coast of Massachusetts, we find that offshore wind plants at the site will experience very low turbulence, quantified as lidar turbulence intensity, especially in summer, when the wind flows from the open ocean. Moreover, the lowest turbulence regimes are often associated with large wind veer conditions, which can impact the effectiveness of wake steering solutions.
DAF-16 and SMK-1 Contribute to Innate Immunity During Adulthood in Caenorhabditis elegans

Aging is accompanied by a progressive decline in immune function termed "immunosenescence". Deficient surveillance coupled with the impaired function of immune cells compromises host defense in older animals. The dynamic activity of regulatory modules that control immunity appears to underlie age-dependent modifications to the immune system. In the roundworm Caenorhabditis elegans levels of PMK-1 p38 MAP kinase diminish over time, reducing the expression of immune effectors that clear bacterial pathogens. Along with the PMK-1 pathway, innate immunity in C. elegans is regulated by the insulin signaling pathway. Here we asked whether DAF-16, a Forkhead box (FOXO) transcription factor whose activity is inhibited by insulin signaling, plays a role in host defense later in life. While in younger C. elegans DAF-16 is inactive unless stimulated by environmental insults, we found that even in the absence of acute stress the transcriptional activity of DAF-16 increases in an age-dependent manner. Beginning in the reproductive phase of adulthood, DAF-16 upregulates a subset of its transcriptional targets, including genes required to kill ingested microbes. Accordingly, DAF-16 has little to no role in larval immunity, but functions specifically during adulthood to confer resistance to bacterial pathogens. We found that DAF-16-mediated immunity in adults requires SMK-1, a regulatory subunit of the PP4 protein phosphatase complex. Our data suggest that as the function of one branch of the innate immune system of C. elegans (PMK-1) declines over time, DAF-16-mediated immunity ramps up to become the predominant means of protecting adults from infection, thus reconfiguring immunity later in life.
An amygdalo-parabrachial pathway regulates pain perception and chronic pain

The parabrachial (PB) complex mediates both ascending nociceptive signaling and descending pain modulatory information in the affective/emotional pain pathway. We have recently reported that chronic pain is associated with amplified activity of PB neurons in a rat model of neuropathic pain. Here we demonstrate that similar activity amplification occurs in mice, and that this is related to suppressed inhibition to lateral parabrachial (LPB) neurons from the CeA in animals of either sex. Animals with pain after chronic constriction injury of the infraorbital nerve (CCI-Pain) displayed higher spontaneous and evoked activity in PB neurons, and a dramatic increase in after-discharges, responses that far outlast the stimulus, compared with controls. LPB neurons in CCI-Pain animals showed a reduction in inhibitory, GABAergic inputs. We show that, in both rats and mice, LPB contains few GABAergic neurons, and that most of its GABAergic inputs arise from CeA. These CeA GABA neurons express dynorphin, somatostatin, and/or corticotropin releasing hormone. We find that the efficacy of this CeA-LPB pathway is suppressed in chronic pain. Further, optogenetically stimulating this pathway suppresses acute pain, and inhibiting it, in naive animals, evokes pain behaviors. These findings demonstrate that the CeA-LPB pathway is critically involved in pain regulation, and in the pathogenesis of chronic pain. SIGNIFICANCE STATEMENT We describe a novel pathway, consisting of inhibition by dynorphin, somatostatin, and corticotropin-releasing hormone-expressing neurons in the CeA that project to the parabrachial nucleus. We show that this pathway regulates the activity of pain-related neurons in parabrachial nucleus, and that, in chronic pain, this inhibitory pathway is suppressed, and that this suppression is causally related to pain perception. We propose that this amygdalo-parabrachial pathway is a key regulator of both chronic and acute pain, and a novel target for pain relief.
On the spectrum of finite, rooted homogeneous trees

Abstract In this paper we study the adjacency spectrum of families of finite rooted trees with regular branching properties. In particular, we show that in the case of constant branching, the eigenvalues are realized as the roots of a family of generalized Fibonacci polynomials and produce a limiting distribution for the eigenvalues as the tree depth goes to infinity. We indicate how these results can be extended to periodic branching patterns and also provide a generalization to higher order simplicial complexes.
Cross-coupling polymerization at iodophenyl thin films prepared by spontaneous grafting of a diazonium salt

Development of a method for the surface-initiated Kumada cross-coupling polymerization based on 4-iodophenyldiazonium salt thin films. Studies of the kinetics of chain termination and polymer film growth, and use of this method to make polythiophene brushes.
Fast Acoustic Scattering Using Convolutional Neural Networks

Diffracted scattering and occlusion are important acoustic effects in interactive auralization and noise control applications, typically requiring expensive numerical simulation. We propose training a convolutional neural network to map from a convex scatterer’s crosssection to a 2D slice of the resulting spatial loudness distribution. We show that employing a full-resolution residual network for the resulting image-to-image regression problem yields spatially detailed loudness fields with a root-mean-squared error of less than 1 dB, at over 100x speedup compared to full wave simulation.
Nanophotonic particle simulation and inverse design using artificial neural networks

We propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find the network needs to be trained on only a small sampling of the data in order to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used solve nanophotonic inverse design problems by using back-propogation - where the gradient is analytical, not numerical.
Practical numerical integration on NISQ devices

This paper addresses the practical aspects of quantum algorithms used in numerical integration, specifically their implementation on Noisy Intermediate-Scale Quantum (NISQ) devices. Quantum algorithms for numerical integration utilize Quantum Amplitude Estimation (QAE) (Brassard et al., 2002) in conjunction with Grover’s algorithm. However, QAE is daunting to implement on NISQ devices since it typically relies on Quantum Phase Estimation (QPE), which requires many ancilla qubits and controlled operations. To mitigate these challenges, a recently published QAE algorithm (Suzuki et al., 2020), which does not rely on QPE, requires a much smaller number of controlled operations and does not require ancilla qubits. We implement this new algorithm for numerical integration on IBM quantum devices using Qiskit and optimize the circuit on each target device. We discuss the application of this algorithm on two qubits and its scalability to more than two qubits on NISQ devices.
Yeast DNA replication.

In this review, we will summarize new approaches to the study of DNA replication in yeast made possible by recombinant DNA technology, and in particular, survey results obtained with in vitro replication systems. Other recent reviews that summarize previous yeast replication studies are those of Fangman and Zakian and Petes. A more general review of replication is found in Kornberg Article de synthese sur la replication de l'ADN de levure in vivo et in vitro, l'organisation des elements chromosomiques et extrachromosomiques: plasmide 2 μm et sequences a replication autonome, l'enzymologie de la replication. Resume des etudes faites par les techniques de clonage
Chapter 10 – Structured Systems Analysis and Design; Systems Acquisition

Publisher Summary A computer-based system is a collection of hardware and software components that work together to reach a common goal. The systems life cycle consists of the requirements definition, systems analysis, systems design, implementation, and operation phases. The requirements document is a description of new capabilities needed by a user group. It is written by computer users from a non-technical and applications viewpoint. Systems designers specify how the system is to be built to meet its specification, a clearly stated description of what the system is supposed to do. A management information system is an organization's set of systems. Systems analysts and systems designers perform cost/benefit analysis to help choose between alternative systems and designs on the basis of their anticipated costs and benefits. The implementation team acquires hardware and software; programs, tests, and debugs the system; and trains the users. Most systems are built as program modules that interact with one another. This makes it easier to program, debug, and modify the system.
BOARD STRUCTURE, ANTITAKEOVER PROVISIONS, AND STOCKHOLDER WEALTH

This paper’s regression analyses from a sample of 261 firms that adopted 486 antitakeover provisions (supermajority, classified boards, fair-price, reduction in cumulative voting, antigreenmail and poison pills) in the 1984‐88 period indicate that the negative market reactions to antitakeover provisions vary depending on firms’ board structures. This paper’s empirical evidence indicates that while separating the positions of CEO and chairperson of the board reduces the negative effect, increased outsider representation increases negative market reactions. © 1997 by John Wiley & Sons, Ltd.
Assessing the effect of school days and absences on test score performance

Abstract While instructional time is viewed as crucial to learning, little is known about the effectiveness of reducing absences relative to increasing the number of school days. Using administrative data from North Carolina public schools, this paper jointly estimates the effect of absences and length of the school calendar on test score performance. We exploit a state policy that provides variation in the number of school days prior to standardized testing and find substantial differences between these two effects. Extending the school calendar by ten days increases math and reading test scores by only 1.7% and 0.8% of a standard deviation, respectively. A similar reduction in absences would lead to gains of 5.5% in math and 2.9% in reading. We perform a number of robustness checks including utilizing flu data to instrument for absences, family-year fixed effects, distinguishing between excused and unexcused absences, and controlling for a contemporaneous measure of student disengagement. Our results are robust to these alternative specifications. In addition, our findings indicate considerable heterogeneity across student ability, suggesting that targeting absenteeism among low performing students could aid in narrowing current gaps in performance.
Chapter 13 – Hepatic Function

Publisher Summary This chapter describes the biochemical mechanisms responsible for the cardinal clinical manifestations of hepatic insufficiency. The chapter also describes biochemical tests used in the clinical diagnosis of liver disease and to assess hepatic function. The liver plays an essential role in: nutrient metabolism, including the control and maintenance of the blood glucose level; detoxification and excretion of hydrophobic metabolites and xenobiotics; synthesis of most plasma proteins; and in digestion through synthesis, biliary secretion, and conservation of bile acids that are essential both for digestion and intestinal absorption of fats and other lipids including fat-soluble vitamins. The clinical manifestations of hepatic disease are directly attributable to alterations in the metabolic, excretory, synthetic, and digestive functions of the liver. Conventional tests for hepatic disease provide information about the integrity of the hepatocytes and the status of the biliary system. Hepatic function can be assessed by estimating the excretory capacity and synthetic functions of the liver. This chapter explains in detail the functional anatomy of liver. The chapter also elaborates clinical manifestations of hepatic insufficiency and laboratory assessment of hepatic function.
Low-Power 16 x 10 Gb/s Bi-Directional Single Chip CMOS Optical Transceivers Operating at < 5 mW/Gb/s/link

We report here on a parallel optical transceiver based on a single 0.13 μm CMOS amplifier chip with 16 transmitter and 16 receiver channels. The transceiver is designed to support very low-power, chip-to-chip optical data buses on printed circuit boards at data rates up to 10 Gb/s/channel. Optical interfaces to the chip are provided by 16-channel photodiode (PD) and VCSEL arrays directly flip-chip soldered to the CMOS IC. The resulting complete transceivers, or Optochips, are low-cost, low-profile highly-integrated chip-scale components. The packaging approach, dense hybrid-integration of optical devices with CMOS, facilitates further scaling to even larger 2-D arrays for future massively parallel optical data buses. Comparison with a previously reported high-speed transceiver Optochip is provided to provide insight into the design space of dense CMOS-based parallel optical transceivers. All of the Optochip transmitter and receiver channels operate at 10 Gb/s for an aggregate bi-directional data rate of 160 Gb/s. Direct measurements of inter-channel crosstalk at 10 Gb/s indicate negligible power penalties. The transceiver measures 3.25 x 5.25 mm and consumes 708 mW of power with all channels fully operational. The area efficiency achieved by the Optochip is 9.4 Gb/s/mm 2 per link, and the per-bit power consumption of 4.44 mW/Gb/s is unprecedented for parallel optical modules.
Congressional Vote Options

Numerous accounts reveal that congressional leaders often secure �hip-pocket votes� or �if you need me� pledges from rank-and-file legislators. These are essentially options on votes. Leaders exercise sufficient options�pay legislators to convert to favorable votes�when those options will yield victory. Otherwise, they release the options. A model shows that this optimal strategy for leaders produces many small victories, few small losses, and losses that are, on average, larger than victories. We find precisely these patterns, hence strong evidence for vote options, in Congressional Quarterly key votes from 1975 through 2001 and in non-key votes from the 106th Congress (1999�2000).
Understanding international portfolio diversification and turnover rates

Abstract This paper argues that international trading costs of a fixed type can help explain home bias in international equities markets. While the stylized fact of high trading turnover in foreign holdings has been interpreted as evidence against international trading costs, we show that this argument only applies to costs that are proportional to trade, and not to fixed costs of entering the foreign market. After documenting that the home bias and turnover stylized facts remain valid in recent data, the paper constructs a simple portfolio allocation model with various configurations of trading costs. A configuration with per-unit costs heterogeneous among agents and a homogeneous fixed cost is found to replicate the pair of stylized facts.
Symbolic vector analysis in plasma physics

Many problems in plasma physics involve substantial amounts of analytical vector calculation. The complexity usually originates from both the vector operations themselves and the underlying coordinate systems. A computer algebra package for symbolic vector analysis in general coordinate systems, GeneralVectorAnalysis (GVA), is developed using Mathematica. The modern viewpoint for 3D vector calculus, differential forms on 3-manifolds, is adopted to unify and systematize the vector calculus operations in general coordinate systems. Besides the basic vector analysis functions, the package provides asymptotic capabilities, 2D vector analysis notation, and a simple interface for users to define their own coordinate systems. These features will benefit physicists and applied mathematicians in their research where complicated vector analysis in complicated coordinate systems is required. Several applications of this symbolic vector analysis package to plasma physics are also given.