cssi/SciSciGPT-SciSciNet huggingface dataset:
Are student ratings of instruction useful

Despite the lead article’s title “Validity Concerns and Usefulness of Student Ratings of Instruction” (Greenwald 1997) in the American Psychologist’’s special section on teacher ratings, the papers did not provide direct evidence on “usefulness.” There is no evidence that the use of teacher ratings improves learning in the long run. The papers do not show that the effects would improve the allocation of effort between teaching and research, or that the quality of the educational experience will be better, or that students and faculty will be happier. Given the evidence to date, the case for student ratings is weak. I raise some questions about usefulness, with a particular emphasis on the ratings’ effects on learning. Are teacher ratings related to learning? The correspondence of ratings to learning should be very close, otherwise, it is not clear what will change. When I was involved with worker incentive standards, the prevailing wisdom was that even modest departures from the desired measure created dysfunctional outcomes. Perhaps the most important finding from the special section is that teacher ratings and learning are not closely related. Furthermore, the ratings/learning relationship seems to be based heavily on studies involving rote learning. The studies provide no breakdown of evidence for studies where skill
The Fate of Former Authoritarian Elites Under Democracy

Why do some former authoritarian elites return to power after democratization through reelection or reappointment to political office, or by assuming board positions in state-owned or major private...
A random utility based estimation framework for the household activity pattern problem

Abstract This paper develops a random utility based estimation framework for the Household Activity Pattern Problem (HAPP). Based on the realization that outputs of complex activity-travel decisions form a continuous pattern in space-time dimension, the estimation framework is treated as a pattern selection problem. In particular, we define a variant of HAPP that has capabilities of forecasting activity selection and durations in addition to activity sequencing. The framework is comprised of three steps, (i) choice set generation, (ii) choice set individualization and (iii) model estimation. The estimation results show that utilities for work, shopping and disutilities for travel time, time outside home, and average tour delay are found to be significant in activity-travel decision making.
NK cells inhibit plasmodium falciparum growth in red blood cells via antibody-dependent cellular cytotoxicity

Malaria is a deadly disease caused by a parasite transmitted by mosquitoes. The parasite infects red blood cells, causing fever with flu-like symptoms. In some people, particularly pregnant women and children, the disease may be very serious and even lead to death. An effective malaria vaccine is urgently needed because malaria parasites are developing resistance to current drugs. People living in areas where malaria is common develop specific proteins called antibodies that protect them from malaria. Learning more about how the antibodies achieve this, could help to develop better vaccines. Scientists already know some antibodies bind to the malaria parasites and prevent them from entering red blood cells. Some vaccines have been based on these antibodies. Other antibodies bind to infected cells flagging them for destruction by cells of the immune system. Immune cells called natural killer cells can eliminate viruses or cancer cells this way, but it was not clear if they could also eliminate malaria parasite-infected red blood cells. Now, Arora et al. show that natural killer cells can selectively destroy malaria-infected red blood cells flagged with antibodies from people who live in areas where malaria is common. In laboratory experiments, natural killer cells from US volunteers, who were never exposed to malaria, did not kill normal or malaria-infected red blood cells. Adding antibodies collected from malaria-resistant volunteers from Africa allowed these natural killer cells from unexposed people to selectively seek out and destroy malaria-infected cells and leave uninfected red blood cells intact. Arora et al. also found that the antibodies from the malaria-resistant volunteers bound to parasite proteins on the surface of infected blood cells. The experiments suggest that vaccines designed to stimulate the production of antibodies to malaria proteins that are displayed on infected red blood cells, could destroy the parasite in infected people and help prevent disease and save lives.
Reputational economies of scale

Abstract For many years, most scholars have assumed that the strength of reputational incentives is positively correlated with firm size. Firms that sell more products or services were thought more likely to be trustworthy than those that sell less because larger firms have more to lose if consumers decide they have behaved badly. That assumption has been called into question by recent work that shows that, under the standard infinitely repeated game model of reputation, reputational economies of scale will occur only under special conditions, such as monopoly, because larger firms not only have more to lose from behaving badly, but also more to gain. This article shows that reputational economies of scale exist even when there is competition and without other special conditions, if the probability that low quality is detected is positively correlated with the quantity of the good or service sold. It also shows that reputational economies of scale exist, under some circumstances, in a finite-horizon model of reputation. Reputational economies of scale help explain why law and accounting firms can act as gatekeepers, why mass market products are more likely to be safe, why firms are less likely to exploit one-sided contracts than consumers, and why manufacturers market new products under the umbrella of established trademarks.
Running the Network Harder: Connection Provisioning Under Resource Crunch

Traditionally, networks operate at a small fraction of their capacities; however, recent technologies, such as software-defined networking, may let operators run their networks harder (i.e., at higher utilization levels). Higher utilization can increase the network operator’s revenue, but this gain comes at a cost: daily traffic fluctuations and failures might occasionally overload the network. We call such situations Resource Crunch . Dealing with Resource Crunch requires certain types of flexibility in the system. We focus on scenarios with flexible bandwidth requirements, e.g., some connections can tolerate reducing their bandwidth allocation. This may free capacity to provision new requests that would otherwise be blocked. For that, the network operator needs to make an informed decision, since reducing the bandwidth of a high-paying connection to allocate a low-value connection is not sensible. We propose a strategy to decide whether or not to provision a request (and which other connections to degrade) focusing on maximizing profits during Resource Crunch. To address this problem, we use an abstraction of the network state, called a connection adjacency graph (CAG). We propose an algorithm, called PROVISIONER, which integrates our CAG solution with an efficient linear program (LP). We compare our method to existing greedy approaches and to LP-only solutions, and show that our method outperforms them during Resource Crunch.
Information-Driven Adaptive Structured-Light Scanners

Sensor planning and active sensing, long studied in robotics, adapt sensor parameters to maximize a utility function while constraining resource expenditures. Here, we consider information gain as the utility function. While these concepts are often used to reason about 3D sensors, these are usually treated as a predefined black-box component. In this paper, we show how the same principles can be used as part of the 3D sensor. We describe the generative model for structured-light 3D scanning and show how adaptive pattern selection can maximize information gain in an open-loop-feedback manner. We then demonstrate how different choices of relevant variable sets (corresponding to the subproblems of localization and mapping) lead to different criteria for pattern selection and can be computed in an online fashion. We show results for both subproblems with several pattern dictionary choices and demonstrate their usefulness for pose estimation and depth acquisition.
Determining Relative Degrees in the Delegation of Executive Authority

Focuses on the determination of relative degrees in the delegation of executive authority. Components that must be considered in any attempt to determine the relative amounts of delegation present ...
Evaluation of Intersection Conflict Warning System: A Critical Gap Analysis:

Rural intersections account for around 30% of crashes in rural areas and 6% of all fatal crashes. An Intersection Conflict Warning System (ICWS) is a unique solution to address rural intersection s...
The impact of quality practices and employee empowerment in the performance of hospital units

Healthcare is a unique services environment with increasing demand for services coupled with widely diverse patient needs. In addition, hospitals are under increased pressure to provide quality car...
Model-Based Free-Breathing Cardiac MRI Reconstruction Using Deep Learned & Storm Priors: MODL-STORM

We introduce a model-based reconstruction framework with deep learned (DL) and smoothness regularization on manifolds (STORM) priors to recover free breathing and ungated (FBU) cardiac MRI from highly undersampled measurements. The DL priors enable us to exploit the local correlations, while the STORM prior enables us to make use of the extensive non-local similarities that are subject dependent. We introduce a novel model-based formulation that allows the seamless integration of deep learning methods with available prior information, which current deep learning algorithms are not capable of. The experimental results demonstrate the preliminary potential of this work in accelerating FBU cardiac MRI.
KERNEL-BASED LEARNING FOR SMART INVERTER CONTROL

Distribution grids are currently challenged by frequent voltage excursions induced by intermittent solar generation. Smart inverters have been advocated as a fast-responding means to regulate voltage and minimize ohmic losses. Since optimal inverter coordination may be computationally challenging and preset local control rules are subpar, the approach of customized control rules designed in a quasi-static fashion features as a golden middle. Departing from affine control rules, this work puts forth non-linear inverter control policies. Drawing analogies to multi-task learning, reactive control is posed as a kernel-based regression task. Leveraging a linearized grid model and given anticipated data scenarios, inverter rules are jointly designed at the feeder level to minimize a convex combination of voltage deviations and ohmic losses via a linearly-constrained quadratic program. Numerical tests using real-world data on a benchmark feeder demonstrate that nonlinear control rules driven also by a few non-local readings can attain near-optimal performance.
A Capacity Estimation Model for a Contraflow Left-Turn Pocket Lane at Signalized Intersections:

Alternative intersection designs are increasingly proposed and adopted by different agencies to meet the needs of growing traffic demand and constrained transportation resources. The left turn (LT)...
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets

A fundamental question in many data analysis settings is the problem of discerning the “natural” dimension of a data set. That is, when a data set is drawn from a manifold (possibly with noise), a meaningful aspect of the data is the dimension of that manifold. Various approaches exist for estimating this dimension, such as the method of Secant-Avoidance Projection (SAP). Intuitively, the SAP algorithm seeks to determine a projection which best preserves the lengths of all secants between points in a data set; by applying the algorithm to find the best projections to vector spaces of various dimensions, one may infer the dimension of the manifold of origination. That is, one may learn the dimension at which it is possible to construct a diffeomorphic copy of the data in a lower-dimensional Euclidean space. Using Whitney's embedding theorem, we can relate this information to the natural dimension of the data. A drawback of the SAP algorithm is that a data set with $T$ points has $O(T^{2})$ secants, making the computation and storage of all secants infeasible for very large data sets. In this paper, we propose a novel algorithm that generalizes the SAP algorithm with an emphasis on addressing this issue. That is, we propose a hierarchical secant-based dimensionality-reduction method, which can be employed for data sets where explicitly calculating all secants is not feasible.
Theta band network supporting human episodic memory is not activated in the seizure onset zone.

Abstract Episodic memory, everyday memory for events, is frequently impaired in patients with epilepsy. We tested patients undergoing intracranial electroencephalography (intracranial EEG) monitoring for the treatment of medically-refractory epilepsy on a well-characterized paradigm that requires episodic memory. We report that an anatomically diffuse network characterized by theta-band (4–7 Hz) coherence is activated at the time of target selection in a task that requires episodic memory. This distinct network of oscillatory activity is absent when episodic memory is not required. Further, the theta band synchronous network was absent in electrodes within the patient's seizure onset zone (SOZ). Our data provide novel empirical evidence for a set of brain areas that supports episodic memory in humans, and it provides a pathophysiologic mechanism for the memory deficits observed in patients with epilepsy.
Do Auditors Price Breach Risk in Their Audit Fees

ABSTRACT Data security breaches have been shown in the literature to negatively affect firm operations. Auditors serve as an important, external governance mechanism with respect to a firm's overal...
Occupational Classifications: A Machine Learning Approach

Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.
Nonnegative Eigenvectors of Symmetric Matrices

For matrices with all nonnegative entries, the Perron–Frobenius theorem guarantees the existence of an eigenvector with all nonnegative components. We show that the existence of such an eigenvector...
Clinical Diagnosis of Placenta Accreta and Clinicopathological Outcomes.

Objective To investigate the association between the intraoperative diagnosis of placenta accreta at the time of cesarean hysterectomy and pathological diagnosis. Study Design This is a retrospective cohort study of all patients undergoing cesarean hysterectomy for suspected placenta accreta from 2000 to 2016 at Barnes-Jewish Hospital. The primary outcome was the presence of invasive placentation on the pathology report. We estimated predictive characteristics of clinical diagnosis of placenta accreta using pathological diagnosis as the correct diagnosis. Results There were 50 cesarean hysterectomies performed for suspected abnormal placentation from 2000 to 2016. Of these, 34 (68%) had a diagnosis of accreta preoperatively and 16 (32%) were diagnosed intraoperatively at the time of cesarean delivery. Two patients had no pathological evidence of invasion, corresponding to a false-positive rate of 4% (95% confidence interval [CI]: 0.5%, 13.8%) and a positive predictive value of 96% (95% CI: 86.3%, 99.5%). There were no differences in complications among patients diagnosed intraoperatively compared with those diagnosed preoperatively. Conclusion Most patients undergoing cesarean hysterectomy for placenta accreta do have this diagnosis confirmed on pathology. However, since the diagnosis of placenta accreta was made intraoperatively in nearly a third of cesarean hysterectomies, intraoperative vigilance is required as the need for cesarean hysterectomy may not be anticipated preoperatively.
Super-Replication of the Best Pairs Trade in Hindsight

This paper derives a robust online equity trading algorithm that achieves the greatest possible percentage of the final wealth of the best pairs rebalancing rule in hindsight. A pairs rebalancing r...
Trust, Sexual Trust, and Sexual Health: An Interrogative Review

Trust is experienced almost constantly in all forms of social and interpersonal relationships, including sexual relationships, and may contribute both directly and indirectly to sexual health. The ...
Short-Term Cardiovascular Response to Short-Radius Centrifugation With and Without Ergometer Exercise.

Artificial gravity (AG) has often been proposed as an integrated multi-system countermeasure to physiological deconditioning associated with extended exposure to reduced gravity levels, particularly if combined with exercise. Twelve subjects underwent short-radius centrifugation along with bicycle ergometry to quantify the short-term cardiovascular response to AG and exercise across three AG levels (0G or no rotation, 1G, and 1.4G; referenced to the subject’s feet and measured in the centripetal direction) and three exercise intensities (25W, 50W, and 100W). Continuous cardiovascular measurements were collected during the centrifugation sessions using a non-invasive monitoring system. The cardiovascular responses were more prominent at higher levels of AG and exercise intensity. In particular, cardiac output, stroke volume, pulse pressure, and heart rate significantly increased with both AG level (in most of exercise group combinations, showing averaged increments across exercise conditions of 1.4 L/min/g, 7.6 mL/g, 5.22 mmHg/g, and 2.0 bpm/g, respectively), and workload intensity (averaged increments across AG conditions of 0.09 L/min/W, 0.17 mL/W, 0.22 mmHg/W, and 0.74 bpm/W respectively). These results suggest that the addition of artificial gravity to exercise can provide a greater cardiovascular benefit than exercise alone. Hierarchical regression models were fitted to the experimental data to determine dose-response curves of all cardiovascular variables as a function of AG-level or exercise intensity during short-radius centrifugation. These results can inform future studies, decisions, and trade-offs towards potential implementation of AG as a space countermeasure.
Counter Directional Optical Network using Ribbon Fiber

This ring optical network concept is meant for smaller platforms incorporating a source module and transmit / receive nodes. Source signals arise from a source bank. To transmit, a source fiber is connected with a receiving fiber in a node. The signal is modulated and then travels in the reverse direction. There is substantial flexibility in the source signal type, individual fiber type, none-to-node protocol, and modulation type.
Causal Inference Methods: Lessons from Applied Microeconomics

This paper discusses causal inference techniques for social scientists through the lens of applied microeconomics. We frame causal inference using the standard of the ideal experiment, emphasizing problems of omitted variable bias and reverse causality. We explore how laboratory and field experiments can succeed and fail to meet this ideal in practice. We then outline how different methods and the statistical assumptions behind them can lead to causal inference in non-experimental contexts. We explain when problems with omitted variables bias can and cannot be addressed using observed controls. We consider tools for studying natural experiments, including difference-in-differences, instrumental variables, and regression discontinuity techniques. Finally, we discuss additional concerns that may arise such as weighting, clustering, multiple inference, and external validity. We include Stata code for implementing each of these methods as well as a series of checklists for researchers detailing important robustness and design checks. Throughout, we emphasize the importance of understanding the context of a study and implementing analyses in a way that acknowledges strengths and limitations.
Cultural socialization and alcohol use: The mediating role of alcohol expectancies among racial/ethnic minority youth.

Abstract Introduction Cultural socialization is associated with reduced risk for several health outcomes among racial/ethnic minority youth. However, to date, less is known about its effect on substance use or the mechanisms through which this process may operate. The current study aimed to examine the effect of cultural socialization on alcohol use through alcohol expectancies among racial/ethnic minority youth. Methods 113 minority adolescents (69.9% African American; 13.3% Hispanic; 10.6% Multiracial; 2.7% American Indian/Alaskan Native) between ages 12 and 18 (mean age 15) were recruited from community-based after school centers. Participants completed measures on cultural socialization, four alcohol expectancy domains (i.e., positive social, wild and crazy, negative arousal, and sedation), and past year alcohol use. Results A significant indirect pathway between cultural socialization, alcohol expectancies and alcohol use was found for negative arousal expectancies (b = −0.160, Boot CI [95] = −0.413, −0.021). Indirect paths were non-significant for the other three alcohol expectancies. Conclusions Our findings suggest that cultural socialization can help reduce alcohol use among racial/ethnic minority adolescents, in part though influencing negative arousal expectancies. Given evidence that alcohol expectancies play an important and long-lasting role in alcohol use across development, incorporating cultural socialization into intervention programming for racial/ethnic minority youth may prove beneficial to reduce risk for alcohol use.
Ordinary Meaning and Empiricism

Statutory interpretation involves an interpreter determining the meaning of the text on the basis of various interpretive tools, all of which relate to the meaning of the words and their composition in light of the relevant context. Recently, with the increasing availability of scientific research tools such as corpus linguistics, advocates of such methods have stressed that statutory interpretation is an “empirical” inquiry. These claims fail to appreciate the contribution that context makes to meaning, both within and outside of law. Determinants of legal meaning must all relate in some way to the context of the relevant statute, whether the connection is to its language or the circumstances surrounding its enactment. Courts give (sometimes conclusive) weight to the statutory text, which implicates the systematicities of language and constrains the interpretations available to judges. Nevertheless, the ineliminably contextual nature of language, along with such legal features as the necessity of framing the interpretive inquiry in terms of an idealized interpreter, reveal legal interpretation to be a discretionary process, which should negate any claim that the determination of the meaning of a statute is primarily, or even largely, an empirical issue.
ICARUS' Implications for the Standard Model of Mind.

ICARUS is a cognitive architecture that shares many features with other theoretical frameworks, including a recent proposal for a standard model of human-like minds, but it also makes some distinctive assumptions. In this paper, we review ICARUS, discuss how it relates to this proposal, and propose extensions based on its novel features.
A Switch in Time Saves the Dime: A Model to Reduce Rental Cost in Cloud Computing

With the rapid growth of cloud computing, firms face a dizzying array of choices and pricing structures for performing their computing tasks on the cloud. Unlike captive computing resources, cloud ...
Identification of a nonseparable model under endogeneity using binary proxies for unobserved heterogeneity

In this paper, I study identification of a nonseparable model with endogeneity arising due to unobserved heterogeneity. Identification relies on the availability of binary proxies that can be used to control for the unobserved heterogeneity. I show that the model is identified in the limit as the number of proxies increases. The argument does not require an instrumental variable that is excluded from the outcome equation nor does it require the support of the unobserved heterogeneity to be finite. I then propose a nonparametric estimator that is consistent as the number of proxies increases with the sample size. I also show that, for a fixed number of proxies, nontrivial bounds on objects of interest can be obtained. Finally, I study two real data applications that illustrate computation of the bounds and estimation with a large number of items. Nonseparable model unobserved heterogeneity latent variable binary measurement error C14 C35 C38
Structural Equation Modeling: Checking Substantive Plausibility†

The process of construct validation involves a series of three steps, namely, concept definition, concept operationalization, and empirical confirmation. These steps lead to specifying and confirming a nomological network for the construct to be validated. Structural equation modeling efficiently confirms the substantive plausibility of the nomological network. Keywords: construct validity; nomological network; structural equation modeling; latent variables
Mobile ambients

This chapter introduces a calculus describing the movement of processes and devices, including movement through administrative domains.
Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times.
Model Primitive Hierarchical Lifelong Reinforcement Learning

Learning interpretable and transferable subpolicies and performing task decomposition from a single, complex task is difficult. Some traditional hierarchical reinforcement learning techniques enforce this decomposition in a top-down manner, while meta-learning techniques require a task distribution at hand to learn such decompositions. This paper presents a framework for using diverse suboptimal world models to decompose complex task solutions into simpler modular subpolicies. This framework performs automatic decomposition of a single source task in a bottom up manner, concurrently learning the required modular subpolicies as well as a controller to coordinate them. We perform a series of experiments on high dimensional continuous action control tasks to demonstrate the effectiveness of this approach at both complex single task learning and lifelong learning. Finally, we perform ablation studies to understand the importance and robustness of different elements in the framework and limitations to this approach.
Successes and Challenges of the “New” College- and Career-Ready Standards: Seven Implementation Trends:

This study identifies seven major trends in how states and districts are implementing college- and career-ready standards for general education students and for two special populations often the ta...
Effects of standing on lumbar spine alignment and intervertebral disc geometry in young, healthy individuals determined by positional magnetic resonance imaging.

Abstract Background Most diagnostic imaging of the spine is performed in supine, a relatively unloaded position. Although the spine is subjected to functional loading that changes the spinal alignment and intervertebral disc geometry, little data exists on how healthy spines adapt to standing. This study seeks to quantify the changes of the lumbar spine from supine to standing in young, back-healthy individuals using a positional magnetic resonance imaging system. Methods This is an observational study that examined the changes in the lumbar spine alignment and intervertebral disc geometry between supine and standing of forty participants (19 males/21 females) without a history of low back pain. The regional lumbar spinal alignment was measured by the sagittal Cobb angle. Segmental intervertebral disc measurements included the segmental Cobb angle, anterior-to-posterior height ratio, and intervertebral disc width measured at L1/L2 - L5/S1 levels. Intra-class correlation was performed for intra- and inter-observer measurements. Findings The intra-observer intra-class correlation consistency model ranged from 0.76 to 0.98 with the inter-observer correlation ranging from 0.68 to 0.99. The Cobb angle decreased in standing. The L5/S1 segmental Cobb angle decreased in standing. The L2/L3 and L3/L4 anterior-to-posterior height ratios increased and the L5/S1 anterior-to-posterior height ratio decreased in standing. No difference in intervertebral disc widths was observed from supine to standing. Interpretations We established normative data for a back-healthy population, using a positional magnetic resonance imaging system, that could inform future investigations that examine the standing-induced adaptations of the lumbar spine in individuals with spinal or intervertebral disc pathologies.
To Thine Own Self Be True: Asymmetric Information in Procurement Auctions

As procurement auctions increasingly move to digital platforms, more data and information is available (or can be made available) to bidders. Despite this trend, relatively little is known about the impact of information asymmetries in these settings. We investigate two such differences in first‐price sealed‐bid reverse auctions with a common value. In a design that mirrors real construction procurement auctions, our laboratory experiment tests the impact of the precision of a bidder's cost estimate and the degree to which bidders know the inherent cost estimate precisions in the auction. We find that more understanding of estimate precision decreases bidder profit, counter to our expectation; however, we also find evidence of strategic behavior from those bidders that ratchets up pressure on competitors and pushes competitors toward bankruptcy. Most notably, understanding just one's own precision can help avoid the winner's curse in some settings. The same result does not apply if bidders also know their competitor's precision; more information does not help. The implication from our realistic setting—that reduced uncertainty may not help the bidder—raises important questions about the degree of transparency that is optimal in procurement auctions.
Game-theoretic modeling of pre-disaster relocation

Sea-level rise due to climate change is clearly an important problem. This paper uses game theory in conjunction with discounting to explore strategies by which governments might encourage pre-disa...
Exploring Institutional Change in the Context of a Statewide Developmental Education Reform in Florida

We explore institutional change and organizational learning in higher education in the context of a large-scale reform of developmental education in Florida. We use statewide survey data to examine...
The Diurnal Rhythm of Insulin Receptor Substrate-1 (IRS-1) and Kir4.1 in Diabetes: Implications for a Clock Gene Bmal1

Purpose Diabetes leads to the downregulation of the retinal Kir4.1 channels and Muller cell dysfunction. The insulin receptor substrate-1 (IRS-1) is a critical regulator of insulin signaling in Muller cells. Circadian rhythms play an integral role in normal physiology; however, diabetes leads to a circadian dysrhythmia. We hypothesize that diabetes will result in a circadian dysrhythmia of IRS-1 and Kir4.1 and disturbed clock gene function will have a critical role in regulating Kir4.1 channels. Methods We assessed a diurnal rhythm of retinal IRS-1 and Kir4.1 in db/db mice. The Kir4.1 function was evaluated using a whole-cell recording of Muller cells. The rat Muller cells (rMC-1) were used to undertake in vitro studies using a siRNA. Results The IRS-1 exhibited a diurnal rhythm in control mice; however, with diabetes, this natural rhythm was lost. The Kir4.1 levels peaked and troughed at times similar to the IRS-1 rhythm. The IRS-1 silencing in the rMC-1 led to a decrease in Kir4.1 and BMAL1. The insulin treatment of retinal explants upregulated Kir4.1 possibly via upregulation of BMAL1 and phosphorylation of IRS-1 and Akt-1. Conclusions Our studies highlight that IRS-1, by regulating BMAL1, is an important regulator of Kir4.1 in Muller cells and the dysfunctional signaling mediated by IRS-1 may be detrimental to Kir4.1.
Sleep and daytime sleepiness in adolescents with and without ADHD: differences across ratings, daily diary, and actigraphy.

Background Children with attention-deficit/hyperactivity disorder (ADHD) experience greater sleep problems than their peers. Although adolescence is generally a developmental period characterized by insufficient sleep, few studies have used a multi-informant, multi-method design, to examine whether sleep differs in adolescents with and without ADHD. Methods Targeted recruitment was used to enroll an approximately equal number of eighth-grade adolescents (mean age = 13 years) with (n = 162) and without ADHD (n = 140). Adolescents and parents completed global ratings of sleep problems; adolescents, parents, and teachers completed ratings of daytime sleepiness. Adolescents wore actigraphs and completed a daily sleep diary for approximately 2 weeks. Results Adolescents with ADHD were more likely than adolescents without ADHD to obtain insufficient sleep on school days (per diary) and weekends (per diary and actigraphy). Adolescents with ADHD were also more likely to report falling asleep in class and to have stayed up all night at least twice in the previous 2 weeks (14% and 5% reported all-nighters for ADHD and comparison, respectively). In regression analyses controlling for a number of variables known to impact sleep (e.g. pubertal development, sex, medication use, having an externalizing, anxiety, or depression diagnosis), ADHD remained associated with shorter diary and actigraphy school night sleep duration, adolescent- and parent-reported daytime sleepiness, and parent-reported difficulties initiating and maintaining sleep and total sleep disturbance. Controlling for other variables, the odds of being classified with clinically elevated parent-reported sleep disturbance were 6.20 times greater for adolescents with ADHD. Conclusions Findings provide some of the clearest evidence yet that adolescents with ADHD experience more sleep problems and sleepiness than their peers without ADHD. It may be especially important to assess for sleep problems in adolescents with ADHD and to evaluate whether existing sleep interventions are effective, or can be optimized, for use in adolescents with ADHD who also have sleep problems.
Syntheses of Seven-Membered Rings: Ruthenium-Catalyzed Intramolecular [5+2] Cycloadditions

The Ru-catalyzed intramolecular [5+2] cycloaddition of cyclopropylenynes is investigated with respect to the regio- and diastereoselectivity as well as the functional group compatibility of the reaction. Evidence for the mechanism as occurring through a ruthenacyclopentene intermediate is elucidated from 1) the study of the diastereoselectivity of the cycloaddition; 2) the effect of variation of substituents on the regioselectivity of cyclopropyl bond cleavage in 1,2-trans- and 1,2-cis-disubstituted cyclopropanes and 3) examples that clearly do not involve ruthenacyclohexene as intermediates as products still incorporate the cyclopropyl moiety. The scope and limitations of the Ru-catalyzed cycloaddition are discussed and compared with the Rh-catalyzed reaction. The potential power of this methodology towards natural product total synthesis is demonstrated by the formation of several polycyclic systems with the chosen reaction conditions and readily available cyclopropylenyne substrates.
Terbium(III) Luminescence-Based Assay for Esterase Activity

Esterases catalyze the hydrolysis of esters to form a carboxylic acid and alcohol. These enzymes play a key role in both the detoxification of xenobiotic compounds and the metabolism of drugs and prodrugs. Numerous fluorogenic probes have been developed to monitor esterase activity. Most are based on an aromatic alcohol, and the others are based on an aromatic acid. These restrictions leave unexplored the specificity of esterases for aliphatic esters. Here, we report on the use of esters of thiopheneacetic acid coupled with the luminescence of terbium(III) as the basis for a continuous assay of esterase activity. This probe allows for a wide variation of the alcohol moiety and the detection of its hydrolysis at submicromolar concentrations. The assay verifies steady-state kinetic parameters for catalysis by pig liver esterase from either initial rates or the integration of progress curves, and its utility is evident with unpurified esterases in bacterial and human cell lysates.
A facile, one-pot procedure for the formation of benzimidazoles from esters using DABAL-Me3, an air stable source of AlMe3

Abstract A convenient, single-step, efficient synthesis of benzimidazoles from esters and diamines is reported. The methodology uses an air stable form of trimethylaluminum referred to as DABAL-Me3 and is compatible with a wide range of functional groups, including acid-sensitive protecting groups.
Genetic load makes cancer cells more sensitive to common drugs: evidence from Cancer Cell Line Encyclopedia

Genetic alterations initiate tumors and enable the evolution of drug resistance. The pro-cancer view of mutations is however incomplete, and several studies show that mutational load can reduce tumor fitness. Given its negative effect, genetic load should make tumors more sensitive to anticancer drugs. Here, we test this hypothesis across all major types of cancer from the Cancer Cell Line Encyclopedia, which provides genetic and expression data of 496 cell lines together with their response to 24 common anticancer drugs. We found that the efficacy of 9 out of 24 drugs showed significant association with genetic load in a pan-cancer analysis. The associations for some tissue-drug combinations were remarkably strong, with genetic load explaining up to 83% of the variance in the drug response. Overall, the role of genetic load depended on both the drug and the tissue type with 10 tissues being particularly vulnerable to genetic load. We also identified changes in gene expression associated with increased genetic load, which included cell-cycle checkpoints, DNA damage and apoptosis. Our results show that genetic load is an important component of tumor fitness and can predict drug sensitivity. Beyond being a biomarker, genetic load might be a new, unexplored vulnerability of cancer.
Application of the intramolecular Schmidt reaction to the asymmetric synthesis of (-)-indolizidine 209B from pulegone

A synthesis of enantiomerically pure indolizidine alkaloid 209B, beginning from naturally occurring pulegone, is described. The key step is the formation of a bicyclic lactam via the intramolecular Schmidt reaction of an alkyl azide with a cyclic ketone. The 11-pot synthesis was accomplished in an overall yield of 21.9%
Coppersmith's lattices and “focus groups”: An attack on small-exponent RSA

Abstract We present a principled technique for reducing the lattice and matrix size in some applications of Coppersmith's lattice method for finding roots of modular polynomial equations. It relies on extrapolating patterns from the actual behavior of Coppersmith's attack for smaller parameter sizes, which can be thought of as “focus group” testing. When applied to the small-exponent RSA problem, our technique reduces lattice dimensions and consequently running times, and hence can be applied to a wider range of exponents. Moreover, in many difficult examples our attack is not only faster but also more successful in recovering the RSA secret key. We include a discussion of subtleties concerning whether or not existing metrics (such as enabling condition bounds) are decisive in predicting the true efficacy of attacks based on Coppersmith's method. Finally, indications are given which suggest certain lattice basis reduction algorithms (such as Nguyen-Stehle's L2) may be particularly well-suited for Coppersmith's method.
Synthesis of 7-alkoxy-4-trifluoromethylcoumarins via the von Pechmann reaction catalyzed by molecular iodine

The synthesis of a series of 7-alkoxy-4-trifluoromethylcoumarins via the von Pechmann reaction catalyzed by molecular iodine is described. The reaction protocol is simple, inexpensive and leads to the formation of the corresponding coumarin derivatives in good yield and high purity. A key intermediate as well as several iodo byproducts were isolated.
Synthesis and preliminary use of naphthyl quinazoline and isoquinoline oxazolines for asymmetric allylic oxidation

This paper is dedicated to Professor Jerald S. Bradshaw, undergraduate mentor of MBA, with warmth and gratitude for his encouragement and outstanding leadership. Four new oxazoline ligands, 4-naphthyl-2-phenylquinazoline 4 and 1-naphthylisoquinoline 5 were made using Suzuki coupling, a Pictet-Gams reaction, and S-amino alcohol. Preliminary use as ligands for asymmetric copper catalyzed allylic oxidation with cyclohex-ene and perester showed promise providing S-cyclohexenyl benzoate product in moderate enantioselectivity (64%ee).
Stereoselective synthesis of 2,5,6-trisubstituted piperidines.

A short and efficient synthesis of 2,5,6-trisubstituted piperidines was achieved by a combination of an aza-Achmatowicz oxidation of a furyl benzenesulfonamide, conjugate addition to the resulting 2H-pyridinone, and subsequent addition of various nucleophiles to a transient N-sulfonyliminium ion. The steric bulk of the tosyl group directs attack of the nucleophile from its opposite side, thereby leading to the formation of cis-substituted products.
Enantioselective Reactions of Scalemic Acyclic α-(Alkoxy)alkyl- and α-(N-carbamoyl)alkylcuprates

Scalemic acyclic α-(alkoxy)alkyl- and α-(N-carbamoyl)alkylcuprates prepared from organostannanes via organolithium reagents react with vinyl iodides, propargyl mesylates, and α,β-enones to afford coupled products with enantioselectivities ranging from 0 to 99% ee depending upon cuprate reagent, substrate structure, solvent, and temperature. In general, lithium cuprates give higher chemical yields and lower enantioselectivities, while the trends are reversed for the corresponding zinc cuprate reagents.
MediaRank: Computational Ranking of Online News Sources

In the recent political climate, the topic of news quality has drawn attention both from the public and the academic communities. The growing distrust of traditional news media makes it harder to find a common base of accepted truth. In this work, we design and build MediaRank (urlwww.media-rank.com ), a fully automated system to rank over 50,000 online news sources around the world. MediaRank collects and analyzes one million news webpages and two million related tweets everyday. We base our algorithmic analysis on four properties journalists have established to be associated with reporting quality: peer reputation, reporting bias/breadth, bottomline financial pressure, and popularity. Our major contributions of this paper include: (i) Open, interpretable quality rankings for over 50,000 of the world's major news sources. Our rankings are validated against 35 published news rankings, including French, German, Russian, and Spanish language sources. MediaRank scores correlate positively with 34 of 35 of these expert rankings. (ii) New computational methods for measuring influence and bottomline pressure. To the best of our knowledge, we are the first to study the large-scale news reporting citation graph in-depth. We also propose new ways to measure the aggressiveness of advertisements and identify social bots, establishing a connection between both types of bad behavior. (iii) Analyzing the effect of media source bias and significance. We prove that news sources cite others despite different political views in accord with quality measures. However, in four English-speaking countries (US, UK, Canada, and Australia), the highest ranking sources all disproportionately favor left-wing parties, even when the majority of news sources exhibited conservative slants.
Epoxidation of bicyclo[2.2.1]hept-5-ene-2,3-endo- and exodicarboxylic acid N-arylimides

Epoxidation of endo- and exo-bicyclo[2.2.1]hept-5-ene-2,3-dicarboxylic acid N-arylimides with a solution of peracetic acid in anhydrous dioxane affords 5,6-exo-epoxybicycloheptanedicarboxylic acid N-arylimides. The epoxidation reaction is not sensitive to the configuration of the imide fragment, to the character and position of the substituent in the aromatic ring. The reaction is determined only by oxidation conditions.
Synthesis and biological activity of cyclic peptide inhibitors of ribonucleotide reductase.

A series of lactam-bridged peptide inhibitors (2−6) of mammalian ribonucleotide reductase (mRR) has been designed and synthesized on the basis of the heptapeptide N-AcFTLDADF (1), corresponding to the C-terminus of the R2 subunit of mRR. Inhibition studies revealed a direct relation between ring size and activity, with peptide 5 being 2.5 times more potent than peptide 1.
Synthesis of peri-Cyclobutarenes by Thermolysis of [Methoxy(trimethylsilyl)methyl]arenes

[Methoxy(trimethylsilyl)methyl]arenes are readily prepared by reactions of chlorotrimethylsilane with (α-methoxy)arenylmethyllithium reagents as obtained from (methoxymethyl)arenes and t-BuLi. The [methoxy(trimethylsilyl)methyl]arenes eliminate methoxytrimethylsilane at 525−675 °C/0.05−0.10 mm to yield peri-cyclobutarenes as derived from arenylcarbenes. Of importance is the fact that the initial arenylcarbenes generated insert into adjacent peri C−H bonds and/or isomerize to other arenylcarbenes that insert into their peri C−H bonds to give peri-cyclobutarenes. Thus, flash-vacuum pyrolysis of 1-[methoxy(trimethylsilyl)methyl]naphthalene (13) at 575−675 °C/0.05−0.10 mm yields 1H-cyclobuta[de]naphthalene (6, up to 39%) in practical quantities. 2-[Methoxy(trimethylsilyl)methyl]naphthalene (23) also affords 6 as a major thermolysis product. At 510 °C/0.05−0.10 mm 4-methoxy-1-[methoxy(trimethylsilyl)methyl]naphthalene (29) decomposes to 4-methoxy-1H-cyclobuta[de]naphthalene (31, 46%). Under similar conditions,...