cssi/SciSciGPT-SciSciNet huggingface dataset:
Pharmacological or genetic targeting of Transient Receptor Potential (TRP) channels can disrupt the planarian escape response.

In response to noxious stimuli, planarians cease their typical ciliary gliding and exhibit an oscillatory type of locomotion called scrunching. We have previously characterized the biomechanics of scrunching and shown that it is induced by specific stimuli, such as amputation, noxious heat, and extreme pH. Because these specific inducers are known to activate Transient Receptor Potential (TRP) channels in other systems, we hypothesized that TRP channels control scrunching. We found that chemicals known to activate TRPA1 (allyl isothiocyanate (AITC) and hydrogen peroxide) and TRPV (capsaicin and anandamide) in other systems induce scrunching in the planarian species Dugesia japonica and, except for anandamide, in Schmidtea mediterranea. To confirm that these responses were specific to either TRPA1 or TRPV, respectively, we tried to block scrunching using selective TRPA1 or TRPV antagonists and RNA interference (RNAi) mediated knockdown. Unexpectedly, co-treatment with a mammalian TRPA1 antagonist, HC-030031, enhanced AITC-induced scrunching by decreasing the latency time, suggesting an agonistic relationship in planarians. We further confirmed that TRPA1 in both planarian species is necessary for AITC-induced scrunching using RNAi. Conversely, while co-treatment of a mammalian TRPV antagonist, SB-366791, also enhanced capsaicin-induced reactions in D. japonica, combined knockdown of two previously identified D. japonica TRPV genes (DjTRPVa and DjTRPVb) did not inhibit capsaicin-induced scrunching. RNAi of DjTRPVa/DjTRPVb attenuated scrunching induced by the endocannabinoid and TRPV agonist, anandamide. Overall, our results show that although scrunching induction can involve different initial pathways for sensing stimuli, this behavior’s signature dynamical features are independent of the inducer, implying that scrunching is a stereotypical planarian escape behavior in response to various noxious stimuli that converge on a single downstream pathway. Understanding which aspects of nociception are conserved or not across different organisms can provide insight into the underlying regulatory mechanisms to better understand pain sensation.
Activation of Distinct Channelrhodopsin Variants Engages Different Patterns of Network Activity

Several recently developed Channelrhodopsin (ChR) variants are characterized by rapid kinetics and reduced desensitization in comparison to the widely used ChR2. However, little is known about how varying opsin properties may regulate their interaction with local network dynamics. We compared evoked cortical activity in mice expressing three ChR variants with distinct temporal profiles under the CamKII promoter: Chronos, Chrimson, and ChR2. We assessed overall neural activation by measuring the amplitude and temporal progression of evoked spiking. Using γ-range (30-80 Hz) local field potential (LFP) power as an assay for local network engagement, we examined the recruitment of cortical network activity by each tool. All variants caused light-evoked increases in firing in vivo, but each demonstrated different temporal patterning of evoked activity. In addition, the three ChRs had distinct effects on cortical γ-band activity. Our findings suggest the properties of optogenetic tools can substantially affect their efficacy in vivo, as well their engagement of circuit resonance.
Schadenfreude, rivalry antecedents, and the role of perceived sincerity in sponsorship of sport rivalries

Abstract Emotion impacts fans' information processing and evaluation of sport sponsors. This paper examines the emotion of schadenfreude (joy at others' misfortune) within rivalry contests under a cognition-emotion theoretical framework. Study 1 assesses the relationships between appraisals of 11 rivalry antecedents and schadenfreude using survey data from 5,459 fans across six sport leagues. Results show that unfairness and cultural difference have the strongest association with schadenfreude. Study 2 utilizes an experimental design involving 543 fans of professional teams in four US-based rivalries. Findings show positive effects of schadenfreude on fans' reactions to the sponsor, mediated by perceived sincerity of the sponsoring brand. Specifically, emotionally-engaged fans (based on heightened schadenfreude) see sponsor support as more sincere, which enhances fan interest, favorability, and intended consumption of the brand. Implications for sponsors include recognizing how activation tactics in affiliation with rivalry games may circumvent the drawbacks of sponsoring just one side of a rivalry.
On the estimation of correlation in a binary sequence model

Abstract We consider a binary sequence generated by thresholding a hidden continuous sequence. The hidden variables are assumed to have a compound symmetry covariance structure with a single parameter characterizing the common correlation. We study the parameter estimation problem under such one-parameter models. We demonstrate that maximizing the likelihood function does not yield consistent estimates for the correlation. We then formally prove the nonestimability of the parameter by deriving a non-vanishing minimax lower bound. This counter-intuitive phenomenon provides an interesting insight that one-bit information of each latent variable is not sufficient to consistently recover their common correlation. On the other hand, we further show that trinary data generated from the hidden variables can consistently estimate the correlation with parametric convergence rate. Thus we reveal a phase transition phenomenon regarding the discretization of latent continuous variables while preserving the estimability of the correlation. Numerical experiments are performed to validate the conclusions.
BLiMP: The Benchmark of Linguistic Minimal Pairs for English

We introduce The Benchmark of Linguistic Minimal Pairs (BLiMP),1 a challenge set for evaluating the linguistic knowledge of language models (LMs) on major grammatical phenomena in English. BLiMP co...
A Study of Interference Distributions in Millimeter Wave Cellular Networks

We study the distribution of the interference power in a millimeter wave (mmWave) cellular network. Such interference is random and highly dependent on the employed transmission technique, as well as the varying channel conditions and the varying association between users and base stations. Traditional networks at lower frequencies usually employ omnidirectional transmission which creates an (almost) equal amount of interference in any direction. MmWave networks, however, must employ directional beamforming transmission in order to compensate for the high path loss in mmWave frequency bands. These directional transmissions drastically change the network interference structure. We examine the interference power distributions in an mmWave network employing beamforming transmission under different user association schemes, and contrast with those under omnidirectional transmission. Numerical results using an analytical mmWave channel model and a measurement-based channel generator, NYUSIM, show that beamforming not only reduces the amount of strong interference and hence significantly enhances network throughput, but also user association can considerably alter network interference and throughput structures.
In Vitro Evaluation of Antifungal Drug Combinations against Multidrug-Resistant Candida auris Isolates from New York Outbreak.

Since 2016, New York hospitals and health care facilities have faced an unprecedented outbreak of the pathogenic yeast Candida auris We tested over 1,000 C. auris isolates from affected facilities and found high resistance to fluconazole (MIC > 256 mg/liter) and variable resistance to other antifungal drugs. Therefore, we tested if two-drug combinations are effective in vitro against multidrug-resistant C. auris Broth microdilution antifungal combination plates were custom manufactured by TREK Diagnostic System. We used 100% inhibition endpoints for the drug combination as reported earlier for the intra- and interlaboratory agreements against Candida species. The results were derived from 12,960 readings, for 15 C. auris isolates tested against 864 two-drug antifungal combinations for nine antifungal drugs. Flucytosine (5FC) at 1.0 mg/liter potentiated the most combinations. For nine C. auris isolates resistant to amphotericin B (AMB; MIC ≥ 2.0 mg/liter), AMB-5FC (0.25/1.0 mg/liter) yielded 100% inhibition. Six C. auris isolates resistant to three echinocandins (anidulafungin [AFG], MIC ≥ 4.0 mg/liter; caspofungin [CAS], MIC ≥ 2.0 mg/liter; and micafungin [MFG], MIC ≥ 4.0 mg/liter) were 100% inhibited by AFG-5FC and CAS-5FC (0.0078/1 mg/liter) and MFG-5FC (0.12/1 mg/liter). None of the combinations were effective for C. auris 18-1 and 18-13 (fluconazole [FLC] > 256 mg/liter, 5FC > 32 mg/liter) except MFG-5FC (0.1/0.06 mg/liter). Thirteen isolates with a high voriconazole (VRC) MIC (>2 mg/liter) were 100% inhibited by the VRC-5FC (0.015/1 mg/liter). The simplified two-drug combination susceptibility test format would permit laboratories to provide clinicians and public health experts with additional data to manage multidrug-resistant C. auris.
The Decline of the U.S. Labor Share Across Sectors

This paper provides novel insights on the changing functional distribution of income in the post–war US economy. We present a Divisia index decomposition of the US labor share (1948–2017) by fourteen sectors. The decomposition method furnishes exact contributions from four components towards aggregate changes of the labor share: sectoral real compensation, sectoral labor productivity, the structure of the economy as measured by employment shares, and the structure of markets as measured by relative prices. Results are presented for the entire period as well as the “golden age” (1948–1979) and a “neoliberal era” (1979–2017), painting a rich and detailed picture of structural changes in the US economy. The manufacturing sector plays a dominant role: despite its continuously falling employment share, growth of real compensation matches that of labor productivity in the early period but falls far behind during the neoliberal era. Further, employment shifts towards stagnant sectors with relatively low real wages and productivity. We discuss these results in the context of Baumol’s and Lewis’s seminal contributions on dual economies. While the cost disease is apparent—employment shifts towards stagnant sectors, their relative prices rise, and the aggregate growth rate (of productivity) decreases—the originally suggested mechanism of upward real wage convergence is muted. The observed changes are instead compatible with a “reverse-Lewis” shift, where stagnant sectors act as a labor surplus sink, and dynamic sector labor experiences slowing real wage growth.
A lower bound on cycle-finding in sparse digraphs

We consider the problem of finding a cycle in a sparse directed graph G that is promised to be far from acyclic, meaning that the smallest feedback arc set in G is large. We prove an information-theoretic lower bound, showing that for N-vertex graphs with constant outdegree any algorithm for this problem must make [MATH HERE] queries to an adjacency list representation of G. In the language of property testing, our result is an [MATH HERE] lower bound on the query complexity of one-sided algorithms for testing whether sparse digraphs with constant outdegree are far from acyclic. This is the first improvement on the [MATH HERE] lower bound, implicit in Bender and Ron [BR02], which follows from a simple birthday paradox argument.
Radiofrequency ablation of malignant liver tumors.

Background: Radiofrequency ablation (RFA) is being used to treat primary and metastatic liver tumors. The indications, treatment planning, and limitations of hepatic RFA must be defined and refined by surgeons treating hepatic malignancies.
Quantitation of phenanthrene dihydrodiols in the urine of smokers and non-smokers by gas chromatography-negative ion chemical ionization-tandem mass spectrometry.

Abstract Polycyclic aromatic hydrocarbons (PAH) are well-established environmental carcinogens likely to be causative agents for some human cancers. Bay-region diol epoxides are ultimate carcinogenic metabolites of multiple PAH. Dihydrodiols are the important intermediate products of this pathway and can be further oxidized to form diol epoxides. We quantified two dihydrodiol metabolites of phenanthrene (Phe), the simplest PAH with a bay-region, in the 6 h urine of smokers (N = 25) and non-smokers (N = 25) using a newly developed and validated analytical method. After hydrolysis by s-glucuronidase and sulfatase, and solid phase extraction, the sample was silylated and analyzed by gas chromatography-negative ion chemical ionization-tandem mass spectrometry (GC-NICI-MS/MS). Levels (nmol/6h urine) of Phe-1,2-dihydrodiol (Phe-1,2-D) and Phe-3,4-dihydrodiol (Phe-3,4-D) were 2.04 ± 1.52 and 0.51 ± 0.35 , respectively, in smokers, significantly higher than those in non-smokers (1.35 ± 1.11 of Phe-1,2-D, p
Machine Learning Strategy That Leverages Large Data sets to Boost Statistical Power in Small-Scale Experiments

Machine learning methods have proven invaluable for increasing the sensitivity of peptide detection in proteomics experiments. Most modern tools, such as Percolator and PeptideProphet, use semisupervised algorithms to learn models directly from the data sets that they analyze. Although these methods are effective for many proteomics experiments, we suspected that they may be suboptimal for experiments of smaller scale. In this work, we found that the power and consistency of Percolator results were reduced as the size of the experiment was decreased. As an alternative, we propose a different operating mode for Percolator: learn a model with Percolator from a large data set and use the learned model to evaluate the small-scale experiment. We call this a “static modeling” approach, in contrast to Percolator’s usual “dynamic model” that is trained anew for each data set. We applied this static modeling approach to two settings: small, gel-based experiments and single-cell proteomics. In both cases, static mo...
Diffeomorphic Registration With Intensity Transformation and Missing Data: Application to 3D Digital Pathology of Alzheimer's Disease

This paper examines the problem of diffeomorphic image registration in the presence of differing image intensity profiles and sparsely sampled, missing, or damaged tissue. Our motivation comes from the problem of aligning 3D brain MRI with 100-micron isotropic resolution to histology sections at 1 × 1 × 1,000-micron resolution with multiple varying stains. We pose registration as a penalized Bayesian estimation, exploiting statistical models of image formation where the target images are modeled as sparse and noisy observations of the atlas. In this injective setting, there is no assumption of symmetry between atlas and target. Cross-modality image matching is achieved by jointly estimating polynomial transformations of the atlas intensity. Missing data is accommodated via a multiple atlas selection procedure where several atlas images may be of homogeneous intensity and correspond to "background" or "artifact." The two concepts are combined within an Expectation-Maximization algorithm, where atlas selection posteriors and deformation parameters are updated iteratively and polynomial coefficients are computed in closed form. We validate our method with simulated images, examples from neuropathology, and a standard benchmarking dataset. Finally, we apply it to reconstructing digital pathology and MRI in standard atlas coordinates. By using a standard convolutional neural network to detect tau tangles in histology slices, this registration method enabled us to quantify the 3D density distribution of tauopathy throughout the medial temporal lobe of an Alzheimer's disease postmortem specimen.
Super-Resolution Limit of the ESPRIT Algorithm

The problem of imaging point objects can be formulated as estimation of an unknown atomic measure from its ${M}+1$ consecutive noisy Fourier coefficients. The standard resolution of this inverse problem is $1/{M}$ and super-resolution refers to the capability of resolving atoms at a higher resolution. When any two atoms are less than $1/{M}$ apart, this recovery problem is highly challenging and many existing algorithms either cannot deal with this situation or require restrictive assumptions on the sign of the measure. ESPRIT is an efficient method which does not depend on the sign of the measure. This paper provides an explicit error bound on the support matching distance of ESPRIT in terms of the minimum singular value of Vandermonde matrices. When the support consists of multiple well-separated clumps and noise is sufficiently small, the support error by ESPRIT scales like $\text {SRF}^{2\lambda -2} \times \text {Noise}$ , where the Super-Resolution Factor (SRF) governs the difficulty of the problem and $\lambda $ is the cardinality of the largest clump. Our error bound matches the min-max rate of a special model with one clump of closely spaced atoms up to a factor of $M$ in the small noise regime, and therefore establishes the near-optimality of ESPRIT. Our theory is validated by numerical experiments.
Physics-Informed Artificial Neural Network Approach for Axial Compression Buckling Analysis of Thin-Walled Cylinder

Unstable buckling leads to the failure of thin-walled cylinders under axial compression. Because of the manufacturing and loading imperfections, a significant variation was observed between experim...
Global convergence of neuron birth-death dynamics

Neural networks with a large number of parameters admit a mean-field description, which has recently served as a theoretical explanation for the favorable training properties of "overparameterized" models. In this regime, gradient descent obeys a deterministic partial differential equation (PDE) that converges to a globally optimal solution for networks with a single hidden layer under appropriate assumptions. In this work, we propose a non-local mass transport dynamics that leads to a modified PDE with the same minimizer. We implement this non-local dynamics as a stochastic neuronal birth-death process and we prove that it accelerates the rate of convergence in the mean-field limit. We subsequently realize this PDE with two classes of numerical schemes that converge to the mean-field equation, each of which can easily be implemented for neural networks with finite numbers of parameters. We illustrate our algorithms with two models to provide intuition for the mechanism through which convergence is accelerated.
Special zeta values using tensor powers of Drinfeld modules

We study tensor powers of rank 1 sign-normalized Drinfeld A-modules, where A is the coordinate ring of an elliptic curve over a finite field. Using the theory of vector valued Anderson generating functions, we give formulas for the coefficients of the logarithm and exponential functions associated to these A-modules. We then show that there exists a vector whose bottom coordinate contains a Goss zeta value, whose evaluation under the exponential function is defined over the Hilbert class field. This allows us to prove the transcendence of Goss zeta values and periods of Drinfeld modules as well as the transcendence of certain ratios of those quantities.
Hierarchical Coding to Enable Scalability and Flexibility in Heterogeneous Cloud Storage

In order to accommodate the ever-growing data from various, possibly independent, sources and the dynamic nature of data usage rates in practical applications, modern cloud data storage systems are required to be scalable, flexible, and heterogeneous. Codes with hierarchical locality have been intensively studied due to their effectiveness in reducing the average reading time in cloud storage. In this paper, we present the first codes with hierarchical locality that achieve scalability and flexibility in heterogeneous cloud storage using small field size. We propose a double- level construction utilizing so-called Cauchy Reed-Solomon codes. We then develop a triple-level construction based on this double-level code; this construction can be easily generalized into any hierarchical structure with a greater number of layers since it naturally achieves scalability in the cloud storage systems.
Random-Coefficients Logit Demand Estimation with Zero-Valued Market Shares

This paper provides a new estimator to address the zero-valued market shares in the BLP random-coefficient logit demand estimation.
A Mathematical Justification for Exponentially Distributed NLOS Bias

In the past few decades, the localization literature has seen many models attempting to characterize the non-line-of-sight (NLOS) bias error commonly experienced in range measurements. These models have either been based on specific measurement data or chosen due to attractive features of a particular distribution, yet to date, none have been backed by rigorous analysis. Leveraging tools from stochastic geometry, this paper attempts to fill this void by providing the first analytical backing for an NLOS bias error model. Using a Boolean model to statistically characterize the random locations, orientations, and sizes of reflectors, and assuming first-order (i.e., single-bounce) reflections, the distance traversed by the first-arriving NLOS path is characterized. Under these assumptions, this analysis reveals that NLOS bias exhibits an exponential form and can in fact be well approximated by an exponential distribution - a result consistent with previous NLOS bias error models in the literature. This analytically derived distribution is then compared to a common exponential model from the literature, revealing this distribution to be a close match in some cases and a lower bound in others. Lastly, the assumptions under which these results were derived suggest this model is aptly suited to characterize NLOS bias in 5G millimeter wave systems as well.
Cyber Threat Impact Analysis to Air Traffic Flows Through Dynamic Queue Networks

Air traffic control (ATC) increasingly depends on information and communication technology to manage traffic flow through highly congested and increasingly interdependent airspace regions. Although these systems are critical to ensuring the efficiency and safety of our airspace, they are also increasingly vulnerable to cyber threats that could potentially lead to reduction in capacity and/or reorganization of traffic flows. In this article, we model various cyber threats to ATC systems and analyze how these attacks could impact the flow of aircraft through the airspace. To perform this analysis, we consider a model for wide-area air traffic based on a dynamic queuing network model. Then we introduce three different attacks (Route Denial of Service, Route Selection Tampering, and Sector Denial of Service) to the ATC system and explore how these attacks manipulate the sector flows by evaluating the queue backlogs for each sector’s outflows. Furthermore, we explore graph-level vulnerability metrics to identify the sectors that are most vulnerable to various flow manipulations and compare them to case-study simulations of the various attacks. The results suggest that Route Denial of Service attacks have a significant impact on the target sector and lead to the largest degradation to the overall air traffic flows. Furthermore, the impact of Sector Denial of Service attack impacts are primarily confined to the target sector, whereas Route Selection Tampering impacts are mostly confined to certain aircraft.
Eigenvector delocalization for non‐Hermitian random matrices and applications

Improving upon results of Rudelson and Vershynin, we establish delocalization bounds for eigenvectors of independent-entry random matrices. In particular, we show that with high probability every eigenvector is delocalized, meaning any subset of its coordinates carries an appropriate proportion of its mass. Our results hold for random matrices with genuinely complex as well as real entries. In both cases, our bounds match numerical simulations, up to lower order terms, indicating the optimality of our results. As an application of our methods, we also establish delocalization bounds for normal vectors to random hyperplanes. The proofs of our main results rely on a least singular value bound for genuinely complex rectangular random matrices, which generalizes a previous bound due to the first author, and may be of independent interest.
Nonparametric universal copula modeling

To handle the ubiquitous problem of "dependence learning," copulas are quickly becoming a pervasive tool across a wide range of data-driven disciplines encompassing neuroscience, finance, econometrics, genomics, social science, machine learning, healthcare and many more. Copula (or connection) functions were invented in 1959 by Abe Sklar in response to a query of Maurice Frechet. After 60 years, where do we stand now? This article provides a history of the key developments and offers a unified perspective.
Shift in worker physiology and gene expression pattern from reproductive to diapause-like with colony age in the bumble bee Bombus impatiens

Insects maximize their fitness by exhibiting predictable and adaptive seasonal patterns in response to changing environmental conditions. These seasonal patterns are often expressed even when insects are kept in captivity, suggesting they are functionally and evolutionarily important. In this study, we examined whether workers of the eusocial bumble bee Bombus impatiens maintained a seasonal signature when kept in captivity. We used an integrative approach and compared worker egg laying, ovarian activation, body size and mass, lipid content in the fat body, cold tolerance and expression of genes related to cold tolerance, metabolism and stress throughout colony development. We found that bumble bee worker physiology and gene expression patterns shift from reproductive-like to diapause-like as the colony ages. Workers eclosing early in the colony cycle had increased egg laying and ovarian activation, and reduced cold tolerance, body size, mass and lipid content in the fat body, in line with a reproductive-like profile, while late-eclosing workers exhibited the opposite characteristics. Furthermore, expression patterns of genes associated with reproduction and diapause differed between early- and late-eclosing workers, partially following the physiological patterns. We suggest that a seasonal signature, innate to individual workers, the queen or the colony, is used by workers as a social cue determining the phenology of the colony and discuss possible implications for understanding reproductive division of labor in bumble bee colonies and the evolutionary divergence of female castes in the genus Bombus.
A conjoint analysis study on self-sampling for human papillomavirus (HPV) testing characteristics among black women in Indiana

Self-sampling for HPV testing may be a method to increase overall cervical cancer screening rates among Black women, who are underscreened for cervical cancer in parts of the US. The purpose of this study was to assess preferred characteristics for delivery of HPV self-sampling kits, return of HPV self-sampling kits, and communication of HPV test results and explore sociodemographic factors (income, education, and marital status) associated with acceptability of self-sampling for HPV testing. Survey data were gathered at an Indiana minority health fair. Participants evaluated 9 scenarios that varied along 3 dimensions: HPV self-sampling kit delivery (mail, pharmacy pick-up, or clinic pick-up), HPV self-sampling kit return (mail, pharmacy drop-off, or clinic drop-off), and HPV test results (mail, phone call, or text message). The 9 scenarios were produced from a fractional factorial design and rated on a 0 to 100 scale. Ratings-based conjoint analysis (RBCA) determined how each dimension influenced ratings. A measure for acceptability of self-sampling was obtained from the ratings of all 9 scenarios. The acceptability measure was regressed on sociodemographics. The 98 participants ranged in age from 21 to 65 (M = 45). Across the 9 scenarios, overall acceptability to self-sample had a mean of 60.9 (SD = 31.3). RBCA indicated that HPV self-sampling kit return had the most influence on ratings, followed by HPV self-sampling kit delivery, and finally, HPV test result communication. Thirty-six percent of participants rated all self-sampling scenarios the same. Sociodemographic characteristics were not associated with acceptability of self-sampling. Self-sampling for HPV testing was found to be generally acceptable to Black women in this pilot survey study. This information could be used by researchers developing self-sampling interventions and the implementation of self-sampling among providers.
Anticipating changes in wildlife habitat induced by private forest owners' adaptation to climate change and carbon policy.

Conserving forests to provide ecosystem services and biodiversity will be a key environmental challenge as society strives to adapt to climate change. The ecosystem services and biodiversity that forests provide will be influenced by the behaviors of numerous individual private landowners as they alter their use of forests in response to climate change and any future carbon pricing policies that emerge. We evaluated the impact of forest landowners’ likely adaptation behaviors on potential habitat for 35 terrestrial, forest-dependent vertebrates across three U.S. Pacific states. In particular, we couple a previously estimated empirical-economic model of forest management with spatially explicit species’ range and habitat associations to quantify the effects of adaptation to climate change and carbon pricing on potential habitat for our focal species (amphibians, birds and mammals) drawn from state agency lists of species of conservation concern. We show that both climate change and carbon pricing policies would likely encourage adaptation away from currently prevalent coniferous forest types, such as Douglas-fir, largely through harvest and planting decisions. This would reduce potential habitat for a majority of the focal species we studied across all three vertebrate taxa. The total anticipated habitat loss for amphibians, birds and mammals considered species of state concern would exceed total habitat gained, and the net loss in habitat per decade would accelerate over time. Carbon payments to forest landowners likely would lead to unintended localized habitat losses especially in Douglas-fir dominant forest types, and encourage more hardwoods on private forest lands. Our study highlights potential tradeoffs that could arise from pricing one ecosystem service (e.g., carbon) while leaving others (e.g., wildlife habitat) unpriced. Our study demonstrates the importance of anticipating potential changes in ecosystem services and biodiversity resulting from forest landowners’ climate adaptation behavior and accounting for a broader set of environmental benefits and costs when designing policies to address climate change.
SpecCFI: Mitigating Spectre Attacks using CFI Informed Speculation

Spectre attacks and their many subsequent variants are a new vulnerability class affecting modern CPUs. The attacks rely on the ability to misguide speculative execution, generally by exploiting the branch prediction structures, to execute a vulnerable code sequence speculatively. In this paper, we propose to use Control-Flow Integrity (CFI), a security technique used to stop control-flow hijacking attacks, on the committed path, to prevent speculative control-flow from being hijacked to launch the most dangerous variants of the Spectre attacks (Spectre-BTB and Spectre-RSB). Specifically, CFI attempts to constrain the possible targets of an indirect branch to a set of legal targets defined by a pre-calculated control-flow graph (CFG). As CFI is being adopted by commodity software (e.g., Windows and Android) and commodity hardware (e.g., Intel’s CET and ARM’s BTI), the CFI information becomes readily available through the hardware CFI extensions. With the CFI information, we apply CFI principles to also constrain illegal control-flow during speculative execution. Specifically, our proposed defense, SpecCFI, ensures that control flow instructions target legal destinations to constrain dangerous speculation on forward control-flow paths (indirect calls and branches). We augment this protection with a precise speculation-aware hardware stack to constrain speculation on backward control-flow edges (returns). We combine this solution with existing solutions against branch target predictor attacks (Spectre-PHT) to close all known non-vendor-specific Spectre vulnerabilities. We show that SpecCFI results in small overheads both in terms of performance and additional hardware complexity.
Misallocation Costs of Digging Deeper into the Central Bank Toolkit

Abstract Central bank large-scale asset purchases, such as the purchase of securities of nonfinancial firms, can induce a misallocation of resources through their heterogeneous effect on firm cost of capital. First, we analytically demonstrate the mechanism in a two-period model. We then evaluate the misallocation of resources induced by corporate security purchases and the associated output losses in a calibrated heterogeneous firm New Keynesian DSGE model. The calibrated model suggests misallocation effects from corporate security purchases can be large enough to make them less effective in increasing output than government bond buys.
Trade in Technology: A Potential Solution to the Food Security Challenges of the 21st Century

Abstract The recent rise in caloric undernutrition in Sub-Saharan Africa (SSA) demonstrates the continued relevance of the Malthusian footrace between food availability and population. Sluggish growth in farm productivity in SSA has brought to the fore the key role of agricultural technology in alleviating future food insecurity. We develop a model of technology, food security and international trade with three distinct channels for technology reduce food insecurity in SSA. The first is via greater domestic R&D investment. An alternative is to import technologies from other countries with significant knowledge capital. The third role for technology to resolve the Malthusian dilemma in SSA is that of ‘virtual technology trade’, i.e., importing technological investments undertaken elsewhere through cheaper imported food. To assess the relative contribution of each channel to food security in Africa, we employ a partial equilibrium, quantitative trade model, augmented by a temporal relationship between R&D investments, knowledge capital and agricultural productivity. Over the historical period: 1991-2011 we find that direct R&D investments in SSA have been the dominant vehicle for lowering food prices in Africa. Looking forward to 2050, we find that virtual technology trade will be the most important vehicle for reducing non-farm undernutrition in Africa.
Enumerating anchored permutations with bounded gaps

Abstract Say that a permutation of 1 , 2 , … , n is k -bounded if every pair of consecutive entries in the permutation differs by no more than k . Such a permutation is anchored if the first entry is 1 and the last entry is n . We show that the generating function for the enumeration of k -bounded anchored permutations is always rational, mirroring the known result on (non-anchored) k -bounded permutations due to Avgustinovich and Kitaev. We then explicitly determine the recursive formulas of minimal depth for the number of anchored k -bounded permutations of n for k = 2 and k = 3 , resolving a conjecture listed on the Online Encyclopedia of Integer Sequences (entry A249665). We additionally show that, asymptotically, the number of anchored k -bounded permutations of n is O k n as a function of n for a given k .
Hormone-induced transformation of receptor proteins☆

Publisher Summary This chapter describes hormone-induced transformation of receptor proteins. During the course of steroid-induced translocation to the nuclei of their respective target cells, extra nuclear receptor proteins for estrogenic and androgenic hormones undergo temperature-dependent alteration that can be recognized both by a change in sedimentation properties and the acquisition of an ability to bind to isolated nuclei or chromatin. Warming the uterine cytosol receptor with estradiol increases the sedimentation coefficient of the complex from 3–8 S to 5–3 S, whereas similar incubation of the prostatic cytosol receptor with dihydrotestosterone decreases the sedimentation coefficient from 3–8 S to 3–0 S. Treatment of isolated uterine nuclei with transformed estradiol–receptor complex not only increases their RNA polymerase activity but also changes the nearest neighbor frequency spectrum of the RNA produced, in the same manner as does estradiol administered in vivo.
Law, medicine, and trust.

There is a stark dichotomy between the significance of trust in medical relationships and the lack of attention paid to trust in existing legal analyses. Health care law lacks a developed vocabulary, analytical framework, or body of empirical information for focusing on the psychological realities of trust, vulnerability and illness. This article seeks to give legal and public policy analysts the tools and information they need to begin thinking clearly and constructively about trust by establishing the following foundational features of medical care delivery: (1) Trust is essential and unavoidable in medical relationships. Patients need and want to trust, and without trust medical relationships never form or are entirely dysfunctional. (2) Beyond the mechanics of forming and conducting treatment relationships, trust may confer therapeutic benefit by activating non-specific or self-healing mechanisms, or by enhancing the effects of active therapies. Medical trust has this unique instrumental value because of its strong emotional content, which results from the deep vulnerability of illness that gives rise to trust. (3) Law can (and does) enforce trust-related expectations, punish violations of trust, facilitate the psychology of trust, and undermine trust. These effects occur both through direct regulation and through the law's expressive function and its relationship with social and professional norms. (4) These legal attitudes toward trust sometimes come into conflict because enforcing trust or punishing its violations can also weaken the psychological foundations of trust. (5) Striking the best compromise among competing legal stances toward trust often requires subtlety, complexity, and detailed empirical information about the psychology of trust. (6) Honoring these principles may require that formal legal rights be softened somewhat with the therapeutic reality of trust. Recognizing these points does not require us to jettison or rework entire sections of the field, however, since most of existing law is broadly consistent with the psychology of trust. Seeing this demonstrates that a therapeutic perspective can reconcile many of the tensions between a strong patient rights orientation and a more enlightened version of professionalism.
Current status of droplet and liquid combustion

Abstract The present understanding of spray combustion in rocket engine, gas turbine, Diesel engine and industrial furnace applications is reviewed. In some cases, spray combustion can be modeled by ignoring the details of spray evaporation and treating the system as a gaseous diffusion flame; however, in many circumstances, this simplification is not adequate and turbulent two-phase flow must be considered. The behavior of individual droplets is a necessary component of two-phase models and recent work on transient droplet evaporation, ignition and combustion is considered, along with a discussion of important simplifying assumptions involved with modeling these processes. Methods of modeling spray evaporation and combustion processes are also discussed including: one-dimensional models for rocket engine and prevaporized combustion systems, lumped zone models (utilizing well-stirred reactor and plug flow regions) for gas turbine and furnace systems, locally homogeneous turbulent models, and two-phase models. The review highlights the need for improved injector characterization methods, more information of droplet transport characteristics in turbulent flow and continued development of more complete two-phase turbulent models.
Mitochondrial Medicine Arrives to Prime Time in Clinical Care: Nutritional Biochemistry and Mitochondrial Hyperpermeability ("Leaky Mitochondria") Meet Disease Pathogenesis and Clinical Interventions.

MITOCHONDRIAL MEDICINE ARRIVES TO GENERAL PRACTICE AND ROUTINE PATIENT CARE Mitochondrial disorders were once relegated to “orphan” status as topics for small paragraphs in pathology textbooks and the hospital-based practices of subspecialists. With the increasing appreciation of the high frequency and ease of treatment of mitochondrial dysfunction, this common cause and consequence of many conditions seen in both primary and specialty care deserves the attention of all practicing clinicians. We all know that mitochondria are the intracellular organelles responsible for the production of the currency of cellular energy in the form of the molecule adenosine triphosphate (ATP); by this time, contemporary clinicians should be developing an awareness of the other roles that mitochondria play in (patho)physiology and clinical practice. Beyond being simple organelles that make ATP, mitochondria play clinically significant roles in autoimmunity, inflammation, cancer, insulin resistance, cardiometabolic disease such as hypertension and heart failure, and neurologic disorders such as Alzheimer’s and Parkinson’s diseases. As I stated during the recent International Conference on Human Nutrition and Functional Medicine1 in Portland, Oregon, in September 2013, we have collectively arrived at a time when mitochondrial therapeutics and the contribution of mitochondrial dysfunction to clinical diseases must be considered on a routine basis in clinical practice. Mitochondrial medicine is no longer an orphan topic, nor is it a superfluous consideration relegated to boutique practices. Mitochondrial medicine is ready for prime time—now—both in the general practice of primary care as well as in specialty and subspecialty medicine. What I describe here as the “new” mitochondrial medicine is the application of assessments and treatments to routine clinical practice primarily for the treatment of secondary/acquired forms of mitochondrial impairment that contribute to common conditions such as fatigue, depression, fibromyalgia, diabetes mellitus, hypertension, neuropsychiatric and neurodegenerative conditions, and other inflammatory and dysmetabolic conditions such as allergy and autoimmunity.
On the Frobenius complexity of Stanley–Reisner rings

The Frobenius complexity of a local ring R measures asymptotically the abundance of Frobenius operators of order e on the injective hull of the residue field of R. It is known that, for Stanley–Rei...
Convergence results for implicit–explicit general linear methods

Abstract This paper studies fixed-step convergence of implicit-explicit general linear methods. We focus on a subclass of schemes that is internally consistent, has high stage order, and favorable stability properties. Classical, index-1 differential algebraic equation, and singular perturbation convergence analyses results are given. For all these problems IMEX GLMs from the class of interest converge with the full theoretical orders under general assumptions. The convergence results require the time steps to be sufficiently small, with upper bounds that are independent on the stiffness of the problem.
An investigation of switching behaviors of bimetallic-disk thermostats

Abstract : Thermostatic switches that use a bimetallic, curved disk as the control element have been known to exhibit, on occasion, anomalous switching behaviors, such as a gradual drift of or sudden deviation from the original switching temperatures. A detailed analysis is presented in this report to show that a class of these switching anomalies can be attributed to an improperly designed interaction between the disk and the elastic switching armature. The analysis is based on Wittrick's theory of thermoelastic stability of the bimetallic disk, extended to include the effects of a central force. The resulting nonlinear problem was solved numerically on a digital computer with the aid of an existing solution routine for two-point boundary-value problems. Numerical results indicate that under certain combinations of geometrical, mechanical and thermal conditions, the thermostat may fail to respond to temperature changes with positive snap actions of the disk, thus resulting in the so-called temperature creepage or dithering phenomenon. Such events are usually characterized by a series of openings and closings of the contacts with reduced travel but greatly increased frequency, which can induce excessive arcing or fatigue damage that would cause the thermostat to malfunction.
Sensitivity of collective outcomes identifies pivotal components

A social system is susceptible to perturbation when its collective properties depend sensitively on a few pivotal components. Using the information geometry of minimal models from statistical physi...
Nearly orthogonal vectors and small antipodal spherical codes

How can d+k vectors in ℝd be arranged so that they are as close to orthogonal as possible? In particular, define θ(d, k) := minX maxx≠y∈X |〈x, y〉 | where the minimum is taken over all collections of d + k unit vectors X ⊆ ℝd. In this paper, we focus on the case here k is fixed and d → ∞. In establishing bounds on θ(d, k), we find an intimate connection to the existence of systems of $$\left(\begin{array}{c}k+1\\ 2\end{array}\right)$$ equiangular lines in ℝk. Using this connection, we are able to pin down θ(d, k) whenever k ∈ {1, 2, 3, 7, 23} and establish asymptotics for general k. The main tool is an upper bound on $$\mathbb{E}_{x,y\sim\mu}|\langle{x,y}\rangle|$$ whenever μ is an isotropic probability mass on ℝk, which may be of independent interest. Our results translate naturally to the analogous question in ℂd. In this case, the question relates to the existence of systems of k2 equiangular lines in ℂk, also known as SIC-POVM in physics literature.
Isotopic Composition of Cosmic-Ray Nitrogen at 1.5 GeV/amu

We have determined the cosmic-ray $^{15}\mathrm{N}$/($^{14}\mathrm{N}$ + $^{15}\mathrm{N}$) ratio with a detector sensitive to velocities of particles in the penumbra of Earth's magnetic field. Our instrument was flown twice on high-altitude balloons from Palestine, Texas, obtaining an exposure factor of 20 ${\mathrm{m}}^{2}$ sr h. We measure the fraction of $^{15}\mathrm{N}$ to be 0.45 \ifmmode\pm\else\textpm\fi{} 0.07 at 1.5 GeV/amu consistent with an origin for nitrogen primarily due to spallation in the interstellar medium.
Dedekind sums arising from newform Eisenstein series

For primitive nontrivial Dirichlet characters χ1 and χ2, we study the weight zero newform Eisenstein series Eχ1,χ2(z,s) at s = 1. The holomorphic part of this function has a transformation rule tha...
What is Learned in Visually Grounded Neural Syntax Acquisition

Visual features are a promising signal for learning bootstrap textual models. However, blackbox learning models make it difficult to isolate the specific contribution of visual components. In this analysis, we consider the case study of the Visually Grounded Neural Syntax Learner (Shi et al., 2019), a recent approach for learning syntax from a visual training signal. By constructing simplified versions of the model, we isolate the core factors that yield the model’s strong performance. Contrary to what the model might be capable of learning, we find significantly less expressive versions produce similar predictions and perform just as well, or even better. We also find that a simple lexical signal of noun concreteness plays the main role in the model’s predictions as opposed to more complex syntactic reasoning.