cssi/SciSciGPT-SciSciNet huggingface dataset:
CHARECTERIZATION of THE RADIATION PATTERN of a GPS ANTENNA MOUNTED on a SMALL T-TAIL AIRCRAFT in LANDING POSITION

This paper aims to characterize the radiation pattern of a Global Positioning System (GPS) antenna mounted on an aircraft at landing position. The antenna was mounted on the fuselage of the aircraft. Aircraft-level radiation pattern of a GPS antenna was simulated using the electromagnetic (EM) modeling abilities of the feldberechnung bei korpern mit beliebiger Oberflache (FEKO) software package. An aircraft Computer-aided Design (CAD) model was created to mimic the Bombardier Global 5000 commercial aircraft. FEKO was also used to design the stand-alone microstrip patch GPS antenna. Landing aircraft position was conceived via running simulations above Perfect Electric Conductor (PEC) medium. The Pitch and Roll planes radiation pattern of the GPS antenna are presented. Statistical analysis for the three dimensions (3D) radiation patterns is provided.
Observation of three-photon bound states in a quantum nonlinear medium

Bound states of massive particles, such as nuclei, atoms, or molecules, constitute the bulk of the visible world around us. By contrast, photons typically only interact weakly. We report the observation of traveling three-photon bound states in a quantum nonlinear medium where the interactions between photons are mediated by atomic Rydberg states. Photon correlation and conditional phase measurements reveal the distinct bunching and phase features associated with three-photon and two-photon bound states. Such photonic trimers and dimers possess shape-preserving wave functions that depend on the constituent photon number. The observed bunching and strongly nonlinear optical phase are described by an effective field theory of Rydberg-induced photon-photon interactions. These observations demonstrate the ability to realize and control strongly interacting quantum many-body states of light.
IceCube: the Discovery of High-Energy Cosmic Neutrinos

We review the rationale for building kilometer-scale neutrino detectors and briefly describe the first such instrument, IceCube. It has transformed one cubic kilometer of natural Antarctic ice into a Cherenkov detector that maps the light patterns radiated by the secondary particles produced in neutrino interactions. We discuss the discovery of cosmic neutrinos and reappraise the properties of the flux after the recent doubling of the data from two to four years. We conclude that the flux is isotropic with a flavor composition of 1:1:1 and therefore most likely extragalactic in origin. It is large by any measure and consistent with a neutrino flux from sources that release a similar amount of energy in photons and, possibly, cosmic rays. Strikingly, the photon flux accompanying IceCube neutrinos is, after cascading through the extragalactic background light, consistent with the high-energy gamma-ray flux observed by Fermi. This observation suggests common sources, which should ease the task of identifying the cosmic accelerators producing IceCube neutrinos. We will argue that event rates of hundreds rather than tens per year are desirable for launching a new era of astronomy. Building a detector that instruments ten cubic kilometers of ice is realistic and, as a result of the large absorption length of the ice revealed by IceCube, comparable in scope to the original project.
On the foundational equations of the classical theory of electrodynamics

A close examination of the Maxwell-Lorentz theory of electrodynamics reveals that polarization and magnetization of material media need not be treated as local averages over small volumes — volumes that nevertheless contain a large number of electric and/or magnetic dipoles. Indeed, Maxwell’s macroscopic equations are exact and self-consistent mathematical relations between electromagnetic fields and their sources, which consist of free charge, free current, polarization, and magnetization. When necessary, the discrete nature of the constituents of matter and the granularity of material media can be handled with the aid of special functions, such as Dirac’s delta-function. The energy of the electromagnetic field and the exchange of this energy with material media are treated with a single postulate that establishes the Poynting vector S = E × H as the rate of flow of electromagnetic energy under all circumstances. Similarly, the linear and angular momentum densities of the fields are simple functions of the Poynting vector that can be unambiguously evaluated at all points in space and time, irrespective of the type of material media, if any, that might reside at various locations. Finally, we examine the Einstein-Laub force- and torque-density equations, and point out the consistency of these equations with the preceding postulates, with the conservation laws, and with the special theory of relativity. The set of postulates thus obtained constitutes a foundation for the classical theory of electrodynamics.
Parameterized lattice strain models for REE partitioning between amphibole and silicate melt

The distribution of rare earth elements (REEs) between amphibole and silicate melt is important for understanding a wide variety of igneous and metamorphic processes in the lithosphere. In this study, we used published experimental REE and Y partitioning data between amphibole and silicate melt, the lattice strain model, and nonlinear least-squares regression method to parameterize key partitioning parameters in the lattice strain model ( D 0 , r 0 , and E ) as a function of pressure, temperature, and both amphibole and melt compositions. Two models, which give nearly identical results, are obtained in this study. In the first model, D 0 depends on temperature and amphibole composition: it positively correlates with Ti content and negative correlates with temperature and Mg, Na, and K contents in the amphibole. In the second model, D 0 depends solely on the melt composition: it positively correlates with Si content and negatively correlates with Ti and Ca contents in the melt. In both the mineral and melt composition models, r 0 negatively correlates with the ferromagnesian content in the M4 site of the amphibole, and E is a constant. The very similar coefficients in the equations for r 0 and best-fit values for E in the two models allow us to connect the two models through amphibole-melt phase equilibria. An application of our model to amphiboles in mantle xenoliths shows that observed major element compositional variations in amphibole alone can give rise to order of magnitude variations in amphibole-melt REE partition coefficients. Together with experimental data simulating fractional crystallization of arc magmas, out models suggest that: (1) REE partition coefficients between amphibole and melt can vary by an order of magnitude during arc magma crystallization due to variation in the temperature and composition of the amphibole and melt, and that (2) amphibole fractional crystallization plays a key role in depleting the middle REEs relative to heavy REEs and light REEs in arc magmas.
Gender, risk tolerance, and false consensus in asset allocation recommendations

Abstract We study the impact of gender on asset allocation recommendations. Graduate business students and professional wealth managers are randomly assigned a male or female client. Participants recommend an allocation and choose an allocation for themselves. Male students choose a riskier allocation than female students, consistent with existing evidence of a gender difference in risk tolerance, and recommend a riskier allocation. In contrast, male and female wealth managers choose and recommend the same allocation, indicating that male and female finance professionals feature similar risk preferences. In both samples, a subject's allocation choice is the strongest predictor of the recommendation provided.
The Effects of Genetic and Environmental Factors on Writing Development.

Abstract Researchers have identified sources of individual differences in writing across beginning and developing writers. The aim of the present study was to further clarify the sources of this variability by investigating the extent to which there are differences in genetic and environmental factors underlying the associations between lexical diversity, syntactic knowledge, and semantic cohesion knowledge in relation to writing. Differences were examined across two developmental phases of writing: beginning (i.e., elementary school) and developing (i.e., middle school). Participants included 262 twin pairs ( M age = 10.88 years) in elementary school and 247 twin pairs ( M age = 13.21 years) in middle school. Twins were drawn from the Florida Twin Project on Reading, Behavior, and Environment. Biometric models were conducted separately for subgroups defined by phase of writing development. Results indicated significant etiological differences in writing components across the two phases, such that effects associated with genes and non-shared environment were greater while effects associated with shared environment were lower in developing writers as compared to beginning writers. Furthermore, results showed that child-specific environment was the largest contributor to individual differences in writing components and their covariation for both beginning and developing writers. These results imply that even direct instruction about writing in schools may be having different effects on children based on their unique experiences.
Personal Lending Relationships

I identify the effects of personal relationships on loan contracting using executive deaths and retirements at other firms as a source of exogenous variation in executive turnover. After plausibly exogenous turnover, borrowers choose lenders with which their new executive's have personal relationships 4.1 times as frequently, and loans from these lenders have 20 basis points lower spreads and 12.5% larger amounts. Personal relationships benefit firms across loan terms, especially during macroeconomic downturns. Increased financial flexibility from personal relationships insulated firms from financial shocks during the recent financial crisis: they exhibited less constrained investment and were less likely to layoff employees. This article is protected by copyright. All rights reserved
On Non-Preemptive VM Scheduling in the Cloud

We study the problem of scheduling VMs (Virtual Machines) in a distributed server platform, motivated by cloud computing applications. The VMs arrive dynamically over time to the system, and require a certain amount of resources (e.g. memory, CPU, etc) for the duration of their service. To avoid costly preemptions, we consider non-preemptive scheduling: Each VM has to be assigned to a server which has enough residual capacity to accommodate it, and once a VM is assigned to a server, its service cannot be disrupted (preempted). Prior approaches to this problem either have high complexity, require synchronization among the servers, or yield queue sizes/delays which are excessively large. We propose a non-preemptive scheduling algorithm that resolves these issues. In general, given an approximation algorithm to Knapsack with approximation ratio r , our scheduling algorithm can provide rβ fraction of the throughput region for β
Natively oxidized amino acid residues in the spinach cytochrome b 6 f complex.

The cytochrome b 6 f complex of oxygenic photosynthesis produces substantial levels of reactive oxygen species (ROS). It has been observed that the ROS production rate by b 6 f is 10–20 fold higher than that observed for the analogous respiratory cytochrome bc1 complex. The types of ROS produced (O2•−, 1O2, and, possibly, H2O2) and the site(s) of ROS production within the b 6 f complex have been the subject of some debate. Proposed sources of ROS have included the heme b p , PQ p •− (possible sources for O2•−), the Rieske iron–sulfur cluster (possible source of O2•− and/or 1O2), Chl a (possible source of 1O2), and heme c n (possible source of O2•− and/or H2O2). Our working hypothesis is that amino acid residues proximal to the ROS production sites will be more susceptible to oxidative modification than distant residues. In the current study, we have identified natively oxidized amino acid residues in the subunits of the spinach cytochrome b 6 f complex. The oxidized residues were identified by tandem mass spectrometry using the MassMatrix Program. Our results indicate that numerous residues, principally localized near p-side cofactors and Chl a, were oxidatively modified. We hypothesize that these sites are sources for ROS generation in the spinach cytochrome b 6 f complex.
Streamlining of Bridge Piers as Scour Countermeasures: Effects of Curvature of Vertical Profiles

Pier streamlining is proposed as a flow-altering countermeasure to local scour for newly proposed piers. To obtain the optimal geometry, it is necessary to investigate the effect of the horizontal profile and vertical profile on the flow pattern around the piers. In a separate paper, the effect of the cross section was studied, and the optimal cross section was obtained. Continuing the effort, this paper investigates the effect of vertical profile curvatures. To achieve this goal, Bezier curves were used to parameterize the vertical curvatures. Fifty-one three-dimensional computational fluid dynamics models with different curvatures for the pier's vertical profile were constructed by varying the Bezier parameters and computed by COMSOL. All pier models in the flume had the same block ratio to ensure that results from test cases were comparable. Analysis and comparison of the simulation results showed that both a concave (or sloped) nose and a concave sidewall reduced the maximum shear stress around piers ...
Metacognitive self-reflectivity moderates the relationship between distress tolerance and empathy in schizophrenia.

Abstract Deficits in empathy seen in schizophrenia are thought to play a major role in the social dysfunction seen in the disorder. However, little work has investigated potential determinants of empathic deficits. This study aimed to fill that gap by examining the effects of two variables on empathy – distress tolerance and metacognitive self-reflectivity. Fifty-four people with schizophrenia-spectrum disorders receiving services at an urban VA or community mental health center were assessed for empathy, metacognition, and distress tolerance. Bivariate correlations and moderation methods were used to ascertain associations amongst these variables and examine interactions. Results revealed that, against hypotheses, empathy was not related at the bivariate level to either distress tolerance or metacognitive self-reflectivity. However, consistent with hypotheses, moderation analyses revealed that participants with higher self-reflectivity showed no relationship between distress tolerance and empathy, while those with lower self-reflectivity showed a relationship such that reduced ability to tolerate distress predicted reduced empathy. Taken together, results of this study suggest that lack of distress tolerance can negatively affect empathy in people with schizophrenia with lesser capacity for metacognitive self-reflection; thus, fostering self-reflectivity may help overcome that negative impact. Future work is needed investigating the impact of metacognitively-tailored interventions on empathy in this population.
Multidrug Binding Properties of the AcrB Efflux Pump Characterized by Molecular Dynamics Simulations

Multidrug resistance in Gram-negative bacteria, to which multidrug efflux pumps such as AcrB makes a major contribution, is becoming a major public health problem. Unfortunately only a few compounds have been cocrystallized with AcrB, and thus computational approaches are essential in elucidating the interaction between diverse ligands and the pump protein. We used molecular dynamics simulation to examine the binding of 9 substrates, 2 inhibitors, and 2 non-substrates to the distal binding pocket of AcrB, identified earlier by X-ray crystallography. This approach gave us more realistic views of the binding than the previously-used docking approach, as the explicit water molecules contributed to the process and the flexible binding site was often seen to undergo large structural changes. We analyzed the interaction in detail in terms of the binding energy, hydrophobic surface matching, and the residues mostly stabilizing the complex. We found that all substrates tested bound to the pocket, whereas the binding to this site was not preferred for the non-substrates. Interestingly, both inhibitors (Phe-Arg-β-naphthylamide and 1-(1-naphtylmethyl)-piperazine) tended to move out of the pocket at least partially, getting into contact with a glycine-rich loop that separates the distal pocket from the more proximal region of the protein and is thought to control the access of substrates to the distal pocket.
Utilization of Aspect Angle Information in Synthetic Aperture Images

Synthetic aperture sonar and synthetic aperture radar involve the creation of high-resolution images of a scene via scattered signals recorded at different locations. Each pixel of the reconstructed image includes information obtained from multiple aspects due to the changing position of the sources/receivers. In this paper, the aspect-dependent scattering at each pixel is exploited to provide additional information about the scene; this paper presents a framework for converting and utilizing multiaspect data, as well as several examples. For sonar data, as is presented here, the aspect dependence may be leveraged to separate objects of interest from the background, to understand the local bathymetry, or for visualizing acoustic shadowing in full circular synthetic aperture sonar images. Several examples of images of the seafloor containing objects of interest are presented for both circular and linear apertures. In addition, the aspect dependence of low-frequency elastic scattering from objects may be used to understand the underlying scattering physics, which is of potential use in fields such as target recognition and nondestructive testing; a laboratory example is presented.
The Lipid Layer and Stability of Tears in Human Newborns

We previously quantified the contributions of the basal and reflex tear systems to the tears of 70 neonates and found that both basal and reflex secretion increase from the preterm to the term period (Table 1).1 The low level of basal and reflex tear secretion found in preterms may mask the diagnosis of a nasolacrimal duct obstruction, permit higher concentrations of topically applied medications and allow corneas to dry during examination and treatment, especially for retinopathy of prematurity.
Reframing the Space Between: Teachers and Learners in Context.

New audiences, new theoretical understandings of cognitive development and teaching, and the moral imperative to reach all learners and teachers require reframing how we assess our effectiveness in...
Multiple sclerosis-associated changes in the composition and immune functions of spore-forming bacteria

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by adaptive and innate immune system dysregulation. Recent work has revealed moderate alteration of gut microbial communities in subjects with MS and in experimental, induced models. However, a mechanistic understanding linking the observed changes in the microbiota and the presence of the disease is still missing. Chloroform-resistant, spore-forming bacteria, which primarily belong to the classes Bacilli and Clostridia in the phylum Firmicutes, have been shown to exhibit immunomodulatory properties in vitro and in vivo, but they have not yet been characterized in the context of human disease. This study addresses the community composition and immune function of this bacterial fraction in MS. We identify MS-associated spore-forming taxa (primarily in the class Clostridia) and show that their presence correlates with impaired differentiation of IL-10-secreting, regulatory T lymphocytes in vitro. Colonization of antibiotic-treated mice with spore-forming bacteria allowed us to identify some bacterial taxa favoring IL-10+ lymphocyte differentiation and others inducing differentiation of proinflammatory, IFN-γ+ T lymphocytes. However, when fed into antibiotic-treated mice, both MS and control-derived spore-forming bacteria were able to induce similar IL-10-expressing Treg immunoregulatory responses, thus ameliorating symptoms of experimental allergic encephalomyelitis (EAE). Our analysis also identified Akkermansia muciniphila as a key organism that may interact either directly or indirectly with spore-forming bacteria to exacerbate the inflammatory effects of MS-associated gut microbiota. Thus, changes in the spore-forming fraction may influence T lymphocyte-mediated inflammation in MS. This experimental approach of isolating a subset of microbiota based on its functional characteristics may be useful to investigate other microbial fractions at greater depth. IMPORTANCE To address the impact of microbiome on disease development, it is essential to go beyond a descriptive study and evaluate the physiological importance of microbiome changes. Our study integrates computational analysis with in vitro and in vivo exploration of inflammatory properties of spore-forming microbial communities, revealing novel functional correlations. We specifically show that while small differences exist between the microbiomes of MS patients and healthy subjects, these differences are exacerbated in the chloroform-resistant fraction. We further demonstrate that, when purified from MS patients, this fraction is correlated with impaired immunomodulatory responses in vitro.
Procedural sensitivities of effect sizes for single-case designs with directly observed behavioral outcome measures

A wide variety of effect size indices have been proposed for quantifying the magnitude of treatment effects in single-case designs. Commonly used measures include parametric indices such as the standardized mean difference as well as nonoverlap measures such as the percentage of nonoverlapping data, improvement rate difference, and nonoverlap of all pairs. Currently, little is known about the properties of these indices when applied to behavioral data collected by systematic direct observation, even though systematic direct observation is the most common method for outcome measurement in single-case research. This study uses Monte Carlo simulation to investigate the properties of several widely used single-case effect size measures when applied to systematic direct observation data. Results indicate that the magnitude of the nonoverlap measures and of the standardized mean difference can be strongly influenced by procedural details of the study's design, which is a significant limitation to using these indices as effect sizes for meta-analysis of single-case designs. A less widely used parametric index, the log response ratio, has the advantage of being insensitive to sample size and observation session length, although its magnitude is influenced by the use of partial interval recording. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Kinetic Basis for DNA Target Specificity of CRISPR-Cas12a.

Summary Class 2 CRISPR-Cas nucleases are programmable genome editing tools with promising applications in human health and disease. However, DNA cleavage at off-target sites that resemble the target sequence is a pervasive problem that remains poorly understood mechanistically. Here, we use quantitative kinetics to dissect the reaction steps of DNA targeting by Acidaminococcus sp Cas12a (also known as Cpf1). We show that Cas12a binds DNA tightly in two kinetically separable steps. Protospacer-adjacent motif (PAM) recognition is followed by rate-limiting R-loop propagation, leading to inevitable DNA cleavage of both strands. Despite functionally irreversible binding, Cas12a discriminates strongly against mismatches along most of the DNA target sequence. This result implies substantial reversibility during R-loop formation—a late transition state—and defies common descriptions of a “seed” region. Our results provide a quantitative basis for the DNA cleavage patterns measured in vivo and observations of greater reported target specificity for Cas12a than for the Cas9 nuclease.
Adipose-derived stem cell conditioned medium impacts asymptomatic peripheral neuromuscular denervation in the mutant superoxide dismutase (G93A) transgenic mouse model of amyotrophic lateral sclerosis.

BACKGROUND Amyotrophic lateral sclerosis (ALS) is devastating, leading to paralysis and death. Disease onset begins pre-symptomatically through spinal motor neuron (MN) axon die-back from musculature at ∼47 days of age in the mutant superoxide dismutase 1 (mSOD1G93A) transgenic ALS mouse model. This period may be optimal to assess potential therapies. We previously demonstrated that post-symptomatic adipose-derived stem cell conditioned medium (ASC-CM) treatment is neuroprotective in mSOD1G93A mice. We hypothesized that early disease onset treatment could ameliorate neuromuscular junction (NMJ) disruption. OBJECTIVE To determine whether pre-symptom administration of ASC-CM prevents early NMJ disconnection. METHODS We confirmed the NMJ denervation time course in mSOD1G93A mice using co-labeling of neurofilament and post-synaptic acetylcholine receptors (AchR) by α-bungarotoxin. We determined whether ASC-CM ameliorates early NMJ loss in mSOD1G93A mice by systemically administering 200μl ASC-CM or vehicle medium daily from post-natal days 35 to 47 and quantifying intact NMJs through co-labeling of neurofilament and synaptophysin with α-bungarotoxin in gastrocnemius muscle. RESULTS Intact NMJs were significantly decreased in 47 day old mSOD1G93A mice (p < 0.05), and daily systemic ASC-CM prevented disease-induced NMJ denervation compared to vehicle treated mice (p < 0.05). CONCLUSIONS Our results lay the foundation for testing the long-term neurological benefits of systemic ASC-CM therapy in the mSOD1G93A mouse model of ALS.
Structural basis for ligand modulation of the CCR2 conformational landscape

CC chemokine receptor 2 (CCR2) is a part of the chemokine receptor family, an important class of therapeutic targets. These class A G-protein coupled receptors (GPCRs) are involved in mammalian signaling pathways and control cell migration toward endogenous CC chemokine ligands, named for the adjacent cysteine motif on their N terminus. Chemokine receptors and their associated ligands are involved in a wide range of diseases and thus have become important drug targets. CCR2, in particular, promotes the metastasis of cancer cells and is also implicated in autoimmunity-driven type-1 diabetes, diabetic nephropathy, multiple sclerosis, asthma, atherosclerosis, neuropathic pain, and rheumatoid arthritis. Although promising, CCR2 antagonists have been largely unsuccessful to date. Here, we investigate the effect of an orthosteric and an allosteric antagonist on CCR2 dynamics by coupling long-timescale molecular dynamics simulations with Markov-state model theory. We find that the antagonists shift CCR2 into several stable inactive conformations that are distinct from the crystal structure conformation and disrupt a continuous internal water and sodium ion pathway, preventing transitions to an active-like state. Several metastable conformations present a cryptic drug-binding pocket near the allosteric site that may be amenable to targeting with small molecules. Without antagonists, the apo dynamics reveal intermediate conformations along the activation pathway that provide insight into the basal dynamics of CCR2 and may also be useful for future drug design.
Videomatch: Matching based video object segmentation

Video object segmentation is challenging yet important in a wide variety of applications for video analysis. Recent works formulate video object segmentation as a prediction task using deep nets to achieve appealing state-of-the-art performance. Due to the formulation as a prediction task, most of these methods require fine-tuning during test time, such that the deep nets memorize the appearance of the objects of interest in the given video. However, fine-tuning is time-consuming and computationally expensive, hence the algorithms are far from real time. To address this issue, we develop a novel matching based algorithm for video object segmentation. In contrast to memorization based classification techniques, the proposed approach learns to match extracted features to a provided template without memorizing the appearance of the objects. We validate the effectiveness and the robustness of the proposed method on the challenging DAVIS-16, DAVIS-17, Youtube-Objects and JumpCut datasets. Extensive results show that our method achieves comparable performance without fine-tuning and is much more favorable in terms of computational time.
How Offshore Financial Competition Disciplines Exit Resistence by Incentive-Conflicted Bank Regulators

This paper studies the impact of technological change and regulatory competition on governmental efforts to generate rents for banks in two stylized regulatory environments. In the first environment, incentive-conflicted regulators attempt to create rents by restricting the size and scope of individual banking organizations. In the second, rents come from efforts to supply deposit guarantees to troubled banks. In both cases, innovations in financial technology and in competing domestic and offshore regulatory arrangements make the costs of delivering rents to banks more transparent to taxpayers and encourage customers to push rent-dependent banking systems into crisis. This analysis portrays the banking crises that have roiled world markets in recent years as information-producing events that identify and discredit inefficient strategies of regulating banking markets.
System-level analysis of metabolic trade-offs during anaerobic photoheterotrophic growth in Rhodopseudomonas palustris.

Living organisms need to allocate their limited resources in a manner that optimizes their overall fitness by simultaneously achieving several different biological objectives. Examination of these biological trade-offs can provide invaluable information regarding the biophysical and biochemical bases behind observed cellular phenotypes. A quantitative knowledge of a cell system’s critical objectives is also needed for engineering of cellular metabolism, where there is interest in mitigating the fitness costs that may result from human manipulation. To study metabolism in photoheterotrophs, we developed and validated a genome-scale model of metabolism in Rhodopseudomonas palustris, a metabolically versatile gram-negative purple non-sulfur bacterium capable of growing phototrophically on various carbon sources, including inorganic carbon and aromatic compounds. To quantitatively assess trade-offs among a set of important biological objectives during different metabolic growth modes, we used our new model to conduct an 8-dimensional multi-objective flux analysis of metabolism in R. palustris. Our results revealed that phototrophic metabolism in R. palustris is light-limited under anaerobic conditions, regardless of the available carbon source. Under photoheterotrophic conditions, R. palustris prioritizes the optimization of carbon efficiency, followed by ATP production and biomass production rate, in a Pareto-optimal manner. To achieve maximum carbon fixation, cells appear to divert limited energy resources away from growth and toward CO2 fixation, even in the presence of excess reduced carbon. We also found that to achieve the theoretical maximum rate of biomass production, anaerobic metabolism requires import of additional compounds (such as protons) to serve as electron acceptors. Finally, we found that production of hydrogen gas, of potential interest as a candidate biofuel, lowers the cellular growth rates under all circumstances. Photoheterotrophic metabolism of R. palustris is primarily regulated by the amount of light it can absorb and not the availability of carbon. However, despite carbon’s secondary role as a regulating factor, R. palustris’ metabolism strives for maximum carbon efficiency, even when this increased efficiency leads to slightly lower growth rates.
Spatial Concentration of Opioid Overdose Deaths in Indianapolis: An Application of the Law of Crime Concentration at Place to a Public Health Epidemic:

The law of crime concentration at place has become a criminological axiom and the foundation for one of the strongest evidence-based policing strategies to date. Using longitudinal data from three ...
Laser-Plasma Modeling using Perseus Extended-Mhd Simulation Code for Hed Plasmas

We discuss the use of the PERSEUS extended-MHD simulation code for high-energy-density (HED) plasmas in modeling power flow in coaxial transmission lines and in the Magnetized Liner Inertial Fusion (MagLIF) experiment at Sandia National Labs. By formulating the fluid equations as a relaxation system in which the current is semi-implicitly time-advanced using the Generalized Ohm's Law (GOL), PERSEUS enables modeling of two-fluid phenomena in dense plasmas without the need to resolve the smallest electron length and time scales. F or both coaxial transmission lines and a simple MagLIF load and feed section, we examine how power coupling is affected by the presence of electrode plasma, and the differences in power flow dynamics resulting from the Hall term in the GOL.
Leveraging Electronic Dental Record Data to Classify Patients Based on Their Smoking Intensity

Background Smoking is an established risk factor for oral diseases and, therefore, dental clinicians routinely assess and record their patients' detailed smoking status. Researchers have successfully extracted smoking history from electronic health records (EHRs) using text mining methods. However, they could not retrieve patients' smoking intensity due to its limited availability in the EHR. The presence of detailed smoking information in the electronic dental record (EDR) often under a separate section allows retrieving this information with less preprocessing. Objective To determine patients' detailed smoking status based on smoking intensity from the EDR. Methods First, the authors created a reference standard of 3,296 unique patients’ smoking histories from the EDR that classified patients based on their smoking intensity. Next, they trained three machine learning classifiers (support vector machine, random forest, and naive Bayes) using the training set (2,176) and evaluated performances on test set (1,120) using precision (P), recall (R), and F-measure (F). Finally, they applied the best classifier to classify smoking status from an additional 3,114 patients’ smoking histories. Results Support vector machine performed best to classify patients into smokers, nonsmokers, and unknowns (P, R, F: 98%); intermittent smoker (P: 95%, R: 98%, F: 96%); past smoker (P, R, F: 89%); light smoker (P, R, F: 87%); smokers with unknown intensity (P: 76%, R: 86%, F: 81%), and intermediate smoker (P: 90%, R: 88%, F: 89%). It performed moderately to differentiate heavy smokers (P: 90%, R: 44%, F: 60%). EDR could be a valuable source for obtaining patients’ detailed smoking information. Conclusion EDR data could serve as a valuable source for obtaining patients' detailed smoking information based on their smoking intensity that may not be readily available in the EHR.
Corporations as the Outgroup

Because the evolutionary competitive process found in the market selects firms whose practices most closely maximize profits, as in Alchian (1950), members of society correctly perceive that firms will defect when it aligns with their long-run profitability. This holds regardless of the intentions of those running the firm. But in terms of moral psychology, members of society subsequently consider firms to be members of the outgroup, deserving of ostracism. However, because conventional economic analysis already assumes that firms maximize profits, the observation that firms only act “ethically” when it is in their rational self-interest to do so does not have policy implications that are not already contained in neoclassical economics.
Early Sexual Trauma Exposure and Neural Response Inhibition in Adolescence and Young Adults: Trajectories of Frontal Theta Oscillations During a Go/No-Go Task.

Objective Trauma, particularly when experienced early in life, can alter neurophysiologic and behavioral development, thereby increasing risk for substance use disorders and related psychopathology. However, few studies have empirically examined trauma using well-characterized developmental samples that are followed longitudinally. Method The association of assaultive, non-assaultive, and sexual assaultive experiences before 10 years of age with developmental trajectories of brain function during response inhibition was examined by measuring electrophysiologic theta and delta oscillations during no-go and go conditions in an equal probability go/no-go task. Data were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort, composed of offspring who were aged 12 through 22 years at enrollment from high-risk and comparison families, with follow-ups at 2-year intervals since 2004. In addition, other important predictors of neurophysiologic functioning (eg, substance use, impulsivity, and parental alcohol use disorders) were investigated. Moreover, associations of neurophysiologic functioning with alcohol and cannabis use disorder symptom counts and externalizing and internalizing psychopathology were examined. Results Individuals exposed to sexual assaultive trauma before 10 years of age had slower rates of change in developmental trajectories of no-go frontal theta during response inhibition. Importantly, effects remained significant after accounting for exposure to other traumatic exposures, such as parental history of alcohol use disorder and participants’ substance use, but not measures of impulsivity. Further, slower rates of change in no-go frontal theta adolescent and young adult development were associated with increased risk for alcohol use disorder symptoms and internalizing psychopathology, but not for cannabis use disorder symptoms or externalizing psychopathology. Conclusion Childhood sexual assault is associated with atypical frontal neurophysiologic development during response inhibition. This could reflect alterations in frontal lobe development, synaptic pruning, and/or cortical maturation involving neural circuits for inhibitory control. These same areas could be associated with increased risk for young adult alcohol use disorder symptoms and internalizing psychopathology. These findings support the hypothesis that changes in neurocognitive development related to early sexual trauma exposure could increase the risk for mental health and substance use problems in young adulthood.
Flexible parsing

When people use natural language in natural settings, they often use it ungrammatically, leaving out or repeating words, breaking off and restarting, speaking in fragments, etc. Their human listeners are usually able to cope with these deviations with little difficulty. If a computer system is to accept natural language input from its users on a routine basis, it should be similarly robust. In this paper, we outline a set of parsing flexibilities that such a system should provide. We go on to describe FlexP, a bottom-up pattern matching parser that we have designed and implemented to provide many of these flexibilities for restricted natural language input to a limited-domain computer system.
Tubulin mRNA stability is sensitive to change in microtubule dynamics caused by multiple physiological and toxic cues.

The localization, mass, and dynamics of microtubules are important in many processes. Cells may actively monitor the state of their microtubules and respond to perturbation, but how this occurs outside mitosis is poorly understood. We used gene-expression analysis in quiescent cells to analyze responses to subtle and strong perturbation of microtubules. Genes encoding α-, β, and γ-tubulins (TUBAs, TUBBs, and TUBGs), but not δ- or e-tubulins (TUBDs or TUBEs), exhibited the strongest differential expression response to microtubule-stabilizing versus destabilizing drugs. Quantitative PCR of exon versus intron sequences confirmed that these changes were caused by regulation of tubulin mRNA stability and not transcription. Using tubulin mRNA stability as a signature to query the Gene Expression Omnibus (GEO) database, we find that tubulin genes respond to toxins known to damage microtubules. Importantly, we find many other experimental perturbations, including multiple signaling and metabolic inputs that trigger tubulin differential expression, suggesting their novel, to our knowledge, role in the regulation of the microtubule cytoskeleton. Mechanistic follow-up confirms that one important physiological signal, phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) activity, indeed regulates tubulin mRNA stability via changes in microtubule dynamics. We propose that tubulin gene expression is regulated as part of many coordinated biological responses, with wide implications in physiology and toxicology. Furthermore, we present a new way to discover microtubule regulation using transcriptomics.
So What Is Class Number 2

Using factorization properties, we give several characterizations for a ring of algebraic integers to have class number at most 2.
Factors that Contribute to Resident Teaching Effectiveness.

Background One of the key components of residency training is to become an educator. Resident physicians teach students, advanced practice providers, nurses, and even faculty on a daily basis. Objective The goal of this study was to identify the objective characteristics of residents, which correlate with perceived overall teaching effectiveness. Methods We conducted a one-year, retrospective study to identify factors that were associated with higher resident teaching evaluations. Senior emergency medicine (EM) teaching residents are evaluated by medical students following clinical teaching shifts. Eighteen factors pertaining to resident teaching effectiveness were chosen. Two items from the medical students' evaluations were analyzed against each factor: teaching effectiveness was measured on a five-point Likert scale and an overall teaching score (1-75). Results A total of 46 EM residents and 843 medical student evaluations were analyzed. The ACGME milestones for systems-based practice (p = 0.02) and accountability (p = 0.05) showed a statistically significant association with a rating of “five” on the Likert scale for teaching effectiveness. Three other ACGME milestones, systems-based practice (p = 0.01), task switching (p = 0.04), and team management (p = 0.03) also showed a statically significant association of receiving a score of 70 or greater on the overall teaching score. Conclusion Residents with higher performance associated with system management and accountability were perceived as highly effective teachers. USMLE and in-service exams were not predictive of higher teaching evaluations. Our data also suggest that effective teachers are working in both academic and community settings, providing a potential resource to academic departments and institutions.
Unsupervised Domain Adaptation with Feature Embeddings.

Representation learning is the dominant technique for unsupervised domain adaptation, but existing approaches often require the specification of "pivot features" that generalize across domains, which are selected by task-specific heuristics. We show that a novel but simple feature embedding approach provides better performance, by exploiting the feature template structure common in NLP problems.
Discriminative Models for Multi-Class Object Layout

Many state-of-the-art approaches for object recognition reduce the problem to a 0-1 classification task. This allows one to leverage sophisticated machine learning techniques for training classifiers from labeled examples. However, these models are typically trained independently for each class using positive and negative examples cropped from images. At test-time, various post-processing heuristics such as non-maxima suppression (NMS) are required to reconcile multiple detections within and between different classes for each image. Though crucial to good performance on benchmarks, this post-processing is usually defined heuristically. We introduce a unified model for multi-class object recognition that casts the problem as a structured prediction task. Rather than predicting a binary label for each image window independently, our model simultaneously predicts a structured labeling of the entire image (Fig. 1). Our model learns statistics that capture the spatial arrangements of various object classes in real images, both in terms of which arrangements to suppress through NMS and which arrangements to favor through spatial co-occurrence statistics. We formulate parameter estimation in our model as a max-margin learning problem. Given training images with ground-truth object locations, we show how to formulate learning as a convex optimization problem. We employ the cutting plane algorithm of Joachims et al. (Mach. Learn. 2009) to efficiently learn a model from thousands of training images. We show state-of-the-art results on the PASCAL VOC benchmark that indicate the benefits of learning a global model encapsulating the spatial layout of multiple object classes (a preliminary version of this work appeared in ICCV 2009, Desai et al., IEEE international conference on computer vision, 2009).
R^4 terms in 11 dimensions and conformal anomaly of (2,0) theory

Abstract Using AdS 7 /CFT 6 correspondence we compute a subleading O(N) term in the scale anomaly of ( 2,0 ) theory describing N coincident M5 branes. While the leading O(N 3 ) contribution to the anomaly is determined by the value of the supergravity action, the O(N) contribution comes from a particular R 4 term (8-d Euler density invariant) in the 11-dimensional effective action. This R 4 term is argued to be part of the same superinvariant as the P-odd C 3 R 4 term known to produce O(N) contribution to the R-symmetry anomaly of ( 2,0 ) theory. The known results for R-anomaly suggest that the total scale anomaly extrapolated to N=1 should be the same as the anomaly of a single free ( 2,0 ) tensor multiplet. A proposed explanation of this agreement is that the coefficient 4N 3 in the anomaly (which was found previously to be also the ratio of the 2-point and 3-point graviton correlators in the ( 2,0 ) theory and in the free tensor multiplet theory) is shifted to 4N 3 −3N .
Penalties, Manipulation, and Investment Efficiency

In this study, we examine whether imposing a penalty based on an earlier positive signal and a bad realized outcome can be welfare-improving. We find that imposing a penalty helps to improve invest...
Activating Group Recycling: A Fresh Approach to Arene Functionalization

Arene and alkene functionalizations are commonly employed in the synthesis of many important molecules. These transformations typically require an activating group, such as a halide or pseudohalide, to ensure reliable regioselectivity and reactivity. However, these groups are ultimately expelled from the final product after a single bond-forming event. A more attractive strategy could accomplish the desired reaction and retain the activating group in the final product. This ‘recycling’ tactic would permit additional bond-forming events to occur in the same reaction vessel, resulting in an increase in the complexity of the product and the atom economy of the reaction. This paper highlights recent examples of arene functionalization where an aryl activating group can be retained in the product. Particular emphasis is placed on methods that use the recycled activating group for further transformations, including examples from our lab that produce diverse molecular structures from simple styrenes.