cssi/SciSciGPT-SciSciNet huggingface dataset:
Preserving differential privacy in convolutional deep belief networks

The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural networks are built on users' personal and highly sensitive data, e.g., clinical records, user profiles, biomedical images, etc. However, only a few scientific studies on preserving privacy in deep learning have been conducted. In this paper, we focus on developing a private convolutional deep belief network (pCDBN), which essentially is a convolutional deep belief network (CDBN) under differential privacy. Our main idea of enforcing $$\epsilon $$∈-differential privacy is to leverage the functional mechanism to perturb the energy-based objective functions of traditional CDBNs, rather than their results. One key contribution of this work is that we propose the use of Chebyshev expansion to derive the approximate polynomial representation of objective functions. Our theoretical analysis shows that we can further derive the sensitivity and error bounds of the approximate polynomial representation. As a result, preserving differential privacy in CDBNs is feasible. We applied our model in a health social network, i.e., YesiWell data, and in a handwriting digit dataset, i.e., MNIST data, for human behavior prediction, human behavior classification, and handwriting digit recognition tasks. Theoretical analysis and rigorous experimental evaluations show that the pCDBN is highly effective. It significantly outperforms existing solutions.
Mesoscopic fluctuations of off-diagonal matrix elements of the angular momentum and orbital magnetism of free electrons in a rectangular box

We study, analytically and numerically, mesoscopic fluctuations of the off-diagonal matrix elements of the orbital angular momentum between the nearest energy levels $i=({n}_{x},{n}_{y})$ and $f=({k}_{x},{k}_{y})$ in a rectangular box with incommensurate sides. In the semiclassical regime, where the level number of $i$ is $\mathcal{N}⪢1$, our derivation gives $⟨{\ensuremath{\mid}{\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{L}}_{if}\ensuremath{\mid}}^{2}⟩\ensuremath{\sim}\sqrt{\mathcal{N}}$. Numerical simulations, using simultaneous ensemble averaging (over the aspect ratios of rectangles) and spectral averaging (over the energy interval), are in excellent agreement with this analytical prediction. Physically, the mean is dominated by the level pairs ${k}_{x}={n}_{x}\ifmmode\pm\else\textpm\fi{}1$ and ${k}_{y}={n}_{y}\ensuremath{\mp}1$. Also in a rectangular box, we investigate the mean orbital susceptibility of a free-electron gas and argue that it reduces, up to a coefficient, to the two-level Van Vleck susceptibility that involves the last occupied (Fermi) level $i$ and the first unoccupied level $f$. This result is confirmed numerically as well, albeit the effect of fluctuations being more pronounced for the susceptibility since it is due to large fluctuations in both $⟨{\ensuremath{\mid}{\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{L}}_{if}\ensuremath{\mid}}^{2}⟩$ and in level separations ${\ensuremath{\epsilon}}_{f}\ensuremath{-}{\ensuremath{\epsilon}}_{i}$ (level bunching).
Bad Company: Understanding negative peer effects in college achievement

Abstract Existing peer effects studies produce contradictory findings, including positive, negative, large, and small effects, despite similar contexts. We explore these results using U.S. Naval Academy data covering a 17-year history of the random assignment of students to peer groups. Coupled with students’ limited discretion over freshman-year courses, our setting affords an opportunity to better understand peer effects in different social contexts. We find negative effects at the broader “company” level – students’ social and residential group – and positive effects at the narrower course-company level within small peer groups. We suggest that peer spillovers change direction because of differences in the underlying mechanism of peer influence.
THE CEMENTLESS KNEE: AN EMERGENT GAME CHANGER – OPPOSES

Total knee arthroplasty (TKA) is reliable, durable, and reproducible in relieving pain and improving function in patients with arthritis of the knee joint. Cemented fixation is the gold standard with low rates of loosening and excellent survivorship in several large clinical series and joint registries. While cementless knee designs have been available for the past 3 decades, changing patient demographics (i.e. younger patients), improved implant designs and materials, and a shift towards TKA procedures being performed in ambulatory surgery centers has rekindled the debate of the role of cementless knee implants in TKA. The drive towards achieving biologic implant fixation in TKA is also driven by the successful transition from cemented hip implants to uncemented THA. However, new technologies and new techniques must be adopted as a result of an unmet need, significant improvement, and/or clinical advantage. Thus, the questions remain: 1) Why switch; and 2) Is cementless TKA more reliable, durable, or reproducible compared to cemented TKA? There are several advantages to using cement during TKA. First, the technique can be universally applied to all cases without exception and without concerns for bone health or structure. Second, cement can mask imprecisions in bone cuts and is a remarkably durable grout. Third, cement allows for antibiotic delivery at the time surrounding surgery which has been shown in some instances to reduce the risk of subsequent infection. Finally, cement fixation has provided successful and durable fixation across various types knee designs, surface finishes, and articulations. On the other hand, cementless knee implants have had an inconsistent track record throughout history. While some have fared very well, others have exhibited early failures and high revision rates. Behery et al. reported on a series of 70 consecutive cases of cementless TKA matched with 70 cemented TKA cases based on implant design and demographics and found that cementless TKA was associated with a greater risk of aseptic loosening and revision surgery at 5 years follow up. Finally, to date, there has not been a randomised controlled clinical trial demonstrating superiority of cementless fixation compared to cemented fixation in TKA. Improvements in materials and designs have definitely made cementless TKA designs viable. However, concerns with added cost, reproducibility, and durability remain. Cement fixation has withstood the test of time and is not the main cause of TKA failure. Therefore, until there is significant data showing that cementless TKA is more durable, reliable, and reproducible compared to cemented TKA, the widespread use of these implants cannot be recommended.
The fireball shock model of gamma ray bursts

Gamma-ray bursts are thought to be the outcome of a cataclysmic event leading to a relativistically expanding fireball, in which particles are accelerated at shocks and produce nonthermal radiation. We discuss the theoretical predictions of the fireball shock model and its general agreement with observations. Some of the recent work deals with the collimation of the outflow and its implications for the energetics, the production of prompt bright flashes at wavelengths much longer than gamma-rays, the time structure of the afterglow, its dependence on the central engine or progenitor system behavior, and the role of the environment on the evolution of the afterglow.
The AAA protein Msp1 mediates clearance of excess tail-anchored proteins from the peroxisomal membrane.

The phrase “finding a needle in a haystack” refers to the difficulty of locating a specific target among a large number of very similar objects. Living cells face a comparable challenge whenever they carry out seek and destroy missions aimed at broken or otherwise undesirable molecules. Scientists are still figuring out how these quality control systems can quickly and accurately pick out the few unwanted molecules that occasionally appear in crowds of normal molecules. Msp1 is a quality control protein that resides on the outer surfaces of two compartments within cells: mitochondria and peroxisomes. Previous work showed that when a protein called Pex15, which is normally found in peroxisomes, is mistakenly sent to mitochondria it is rapidly eliminated by Msp1. Weir et al. set out to understand if Msp1 can distinguish incorrectly localized Pex15 from correctly localized Pex15. Fluorescence microscopy was used to watch how Msp1 eliminates Pex15 from compartments within living yeast cells. Although Msp1 did not normally recognize Pex15 at peroxisomes, when Weir et al. attempted to over-load peroxisomes with Pex15 they saw that Msp1 provided a counterforce. Comparing how quickly cells eliminated excess Pex15 at peroxisomes with predictions from mathematical models showed that Pex15 “matures” from an Msp1-sensitive to an Msp1-insensitive state. Further experiments revealed that Pex15 binds to another protein found in peroxisomes, called Pex3, which protects Pex15 from Msp1. By contrast, occasional Pex15 molecules that reached mitochondria remained immature and sensitive to Msp1. Proteins similar to Msp1 are also found in humans, and Weir et al. hope that a better understanding of how Msp1 works in yeast will help scientists studying human disorders caused by defects in similar quality control systems. This could help to combat disease like cancer, neurodegenerative diseases and cystic fibrosis – which have all been linked to quality control systems that have started to target too few or too many proteins.
Contrasting Visions for Macroeconomic Theory: DSGE and OEE:

Dynamic stochastic general equilibrium (DSGE) modeling remains the workhorse of contemporary macroeconomics despite a growing number of critiques of its ability to explain the aggregate properties ...
Use of genetic mouse models in the study of diabetic nephropathy

The study of experimental diabetic nephropathy in rodent models has led to many changes in the clinical management of human diabetic nephropathy. With the development of technology to generate knockout and transgenic animals, the mouse has become a favored species in medical research. There are several genetic mouse models of diabetes, with the majority being models of type 2 diabetes mellitus. These include the hypoinsulinemic nonobese diabetic mouse, the KKAy mouse, the New Zealand obese mouse, the hyperinsulinemic ob/ob mouse, and the different strains of obese hyperinsulinemic db/db mouse. Each of these models displays some renal changes, but by far the best model of renal disease and the one that is the most studied is the db/db mouse. The db/db mouse displays substantial glomerular pathology, including mesangial matrix expansion and modest albuminuria. It has been reported that the db/db mouse has a decline in creatinine clearance after 5 months of age, but more specific approaches are warranted to confirm these findings. A number of intervention studies show renoprotection in this model. Although mice have many advantages, such as being able to be crossbred with genetically manipulated animals, in many ways they are not very similar to humans, and in some respects the rat may be a better choice, particularly in relation to some features of end-organ injury.
"Deadlines, Work Flows, Task Sorting, and Work Quality"

We examine deadlines-induced behavior using large-scale, high frequency data on about 5 million U.S. patents and published applications. We motivate the study with a model of rational agents facing discontinuous incentives around deadline thresholds, without using time-inconsistent preferences invoked in behavioral economics models of deadline-related behavior. Consistent with our model predictions, we find notable clustering of more complex patent applications around potential deadlines at month-, quarter- and year-ends, along with a small to moderate decline in work quality around those periods.
The Role of Assessment in a Learning Culture

of assessments used to give grades or to satisfy the accountability demands of an external authority, but rather the kind of assessment that can be used as a part of instruction to support and enhance learning. On this topic, I am especially interested in engaging the very large number of educational researchers who participate, in one way or another, in teacher education. The transformation of assessment practices cannot be accomplished in separate tests and measurement courses, but rather should be a central concern in teaching methods courses. The article is organized in three parts. I present, first, an historical framework highlighting the key tenets of social efficiency curricula, behaviorist learning theories, and "scientific measurement." Next, I offer a contrasting socialconstructivist conceptual framework that blends key ideas from cognitive, constructivist, and sociocultural theories. In the third part, I elaborate on the ways that assessment practices should change to be consistent with and support socialconstructivist pedagogy. The impetus for my development of an historical framework was the observation by Beth Graue (1993) that "assessment and instruction are often conceived as curiously separate in both time and purpose" (p. 291, emphasis added). As Graue notes, the measurement approach to classroom assessment, "exemplified by standardized tests and teacher-made emulations of those tests," presents a barrier to the implementation of more constructivist approaches to instruction. To understand the origins of Graue's picture of separation and to help explain its continuing power over presentday practice, I drew the chronology in Figure 1. A longerterm span of history helps us see that those measurement perspectives, now felt to be incompatible with instruction, came from an earlier, highly consistent theoretical framework (on the left) in which conceptions of "scientific measurement" were closely aligned with traditional curricula and beliefs about learning. To the right is an emergent, constructivist paradigm in which teachers' close assessment of students' understandings, feedback from peers, and student self-assessments would be a central part of the social processes that mediate the development of intellectual abilities, construction of knowledge, and formation of students' identities. The best way to understand dissonant current practices, shown in the middle of the figure, is to realize that instruction (at least in its ideal form) is drawn from the emergent paradigm, while testing is held over from the past. Historical Perspectives: Curriculum, Psychology, and Measurement
Computer security for data collection technologies

Many organizations in the developing world (e.g., NGOs), include digital data collection in their workflow. Data collected can include information that may be considered sensitive, such as medical or socioeconomic data, and which could be affected by computer security attacks or unintentional mishandling. The attitudes and practices of organizations collecting data have implications for confidentiality, availability, and integrity of data. This work, a collaboration between computer security and ICTD researchers, explores security and privacy attitudes, practices, and needs within organizations that use Open Data Kit (ODK), a prominent digital data collection platform. We conduct a detailed threat modeling exercise to inform our view on potential security threats, and then conduct and analyze a survey and interviews with technology experts in these organizations to ground this analysis in real deployment experiences. We then reflect upon our results, drawing lessons for both organizations collecting data and for tool developers.
Recent Police Killings in the United States: A Three-City Comparison:

Recent police killings of citizens in the United States have attracted massive coverage in the media, large-scale public protests, and demands for reform of police departments throughout the countr...
Unexplained Practice Variation in Primary Care Providers' Concern for Pediatric Obstructive Sleep Apnea.

Abstract Objective To examine primary care provider (PCP) screening practice for obstructive sleep apnea (OSA) and predictive factors for screening habits. A secondary objective was to describe the polysomnography completion proportion and outcome. We hypothesized that both provider and child health factors would predict PCP suspicion of OSA. Methods A computer decision support system that automated screening for snoring was implemented in 5 urban primary care clinics in Indianapolis, Indiana. We studied 1086 snoring children aged 1 to 11 years seen by 26 PCPs. We used logistic regression to examine the association between PCP suspicion of OSA and child demographics, child health characteristics, provider characteristics, and clinic site. Results PCPs suspected OSA in 20% of snoring children. Factors predicting PCP concern for OSA included clinic site ( P P P = .01; OR = 10.19), number of training years ( P = .01; OR = 4.26) and child age ( P Conclusions Results suggest unexplained small area practice variation in PCP concern for OSA among snoring children. It is likely that many children at risk for OSA remain unidentified. An important next step is to evaluate interventions to support PCPs in evidence-based OSA identification.
Layered Structure and Complex Mechanochemistry Underlie Strength and Versatility in a Bacterial Adhesive

ABSTRACT While designing synthetic adhesives that perform in aqueous environments has proven challenging, microorganisms commonly produce bioadhesives that efficiently attach to a variety of substrates, including wet surfaces. The aquatic bacterium Caulobacter crescentus uses a discrete polysaccharide complex, the holdfast, to strongly attach to surfaces and resist flow. The holdfast is extremely versatile and has impressive adhesive strength. Here, we used atomic force microscopy in conjunction with superresolution microscopy and enzymatic assays to unravel the complex structure of the holdfast and to characterize its chemical constituents and their role in adhesion. Our data support a model whereby the holdfast is a heterogeneous material organized as two layers: a stiffer nanoscopic core layer wrapped into a sparse, far-reaching, flexible brush layer. Moreover, we found that the elastic response of the holdfast evolves after surface contact from initially heterogeneous to more homogeneous. From a composition point of view, besides N-acetyl-d-glucosamine (NAG), the only component that had been identified to date, our data show that the holdfast contains peptides and DNA. We hypothesize that, while polypeptides are the most important components for adhesive force, the presence of DNA mainly impacts the brush layer and the strength of initial adhesion, with NAG playing a primarily structural role within the core. The unanticipated complexity of both the structure and composition of the holdfast likely underlies its versatility as a wet adhesive and its distinctive strength. Continued improvements in understanding of the mechanochemistry of this bioadhesive could provide new insights into how bacteria attach to surfaces and could inform the development of new adhesives. IMPORTANCE There is an urgent need for strong, biocompatible bioadhesives that perform underwater. To strongly adhere to surfaces and resist flow underwater, the bacterium Caulobacter crescentus produces an adhesive called the holdfast, the mechanochemistry of which remains undefined. We show that the holdfast is a layered structure with a stiff core layer and a polymeric brush layer and consists of polysaccharides, polypeptides, and DNA. The DNA appears to play a role in the structure of the brush layer and initial adhesion, the peptides in adhesive strength, and the polysaccharides in the structure of the core. The complex, multilayer organization and diverse chemistry described here underlie the distinctive adhesive properties of the holdfast and will provide important insights into the mechanisms of bacterial adhesion and bioadhesive applications.
If You Are Going to Pay Within the Next 24 Hours, Press 1: Automatic Planning Prompt Reduces Credit Card Delinquency

People often form intentions but fail to follow through on them. Mounting evidence suggests that such intention-action gaps can be narrowed with prompts to make concrete plans about when, where and how to act to achieve the intention. In this paper we pushed the notion of plan-concreteness to test the efficacy of a prompt under a minimalist automated calling setting, where respondents were only prompted to indicate a narrower duration within which they intent to act. In a field experiment this planning prompt significantly helped people to pay their past dues and get out of debt delinquency. These results suggest that minimalist automatic planning prompts are a scalable, cost-effective intervention.
Using Pinterest to stimulate student engagement, interest, and learning in managerial accounting courses

Abstract Managerial accounting is a course that typically suffers from a lack of student engagement. This paper presents a social media-based assignment that can increase student interest in and understanding of managerial accounting, particularly for English as a second language (ESL) students. For the assignment, students used Pinterest to share Internet-based resources with their class. The students were also required to comment on Pinterest “pins” created by their classmates. The assignment encouraged students to be engaged and active learners in the course, build interest in the managerial accounting topics covered, and develop a deeper understanding of managerial accounting by utilizing outside resources and real world examples. A survey of students’ attitudes indicates that approximately two-thirds of the students perceived the assignment had a positive impact on both their engagement in the course and their ability to better understand course topics. Student responses also suggest that the Pinterest assignment had some impact on their interest in managerial accounting. Mean survey responses were significantly more favorable for ESL students compared to non-ESL students.
Performance Assessment of Resonantly Driven Silicon Two-Qubit Quantum Gate

Two-qubit quantum gates play an essential role in quantum computing, whose operation critically depends on the entanglement between two qubits. Resonantly driven controlled-NOT (CNOT) gates based on silicon double quantum dots (DQDs) are studied theoretically. The physical mechanisms for effective gate modulation of the exchange coupling between two qubits are elucidated. Scaling behaviors of the singlet-triplet energy split, gate-switching speed, and gate fidelity are investigated as a function of the quantum dot spacing and modulation gate voltage. It is shown that the entanglement strength and gate-switching speed exponentially depend on the quantum dot spacing. A small spacing of ~10 nm can promise a CNOT gate delay of <1 ns and reliable gate switching in the presence of decoherence. The results show promising performance potential of the resonantly driven two-qubit quantum gates based on aggressively scaled silicon DQDs.
Study of impact of BTI's local layout effect including recovery effect on various standard-cells in 10nm FinFET

This paper presents an analysis methodology of the impact of Local Layout Effect (LLE) of bias temperature instability (BTI) on logic circuits by measuring Ring-Oscillators (RO) consist of many kinds of standard cells and shows its measurement result in a 10nm FinFET process. The measured delay degradations of all ROs are well correlated with estimated one without considering LLE of BTI and its maximum error rates is −16% and +13%. The LLE on BTI recovery effect is also evaluated and there is no obvious standard cell type dependency. This analysis would be useful for more accurate guideline to design BTI guard-band on logic circuits for high reliability required applications.
Solving equilibrium problems using extended mathematical programming

We introduce an extended mathematical programming framework for specifying equilibrium problems and their variational representations, such as generalized Nash equilibrium, multiple optimization problems with equilibrium constraints, and (quasi-) variational inequalities, and computing solutions of them from modeling languages. We define a new set of constructs with which users annotate variables and equations of the model to describe equilibrium and variational problems. Our constructs enable a natural translation of the model from one formulation to another more computationally tractable form without requiring the modeler to supply derivatives. In the context of many independent agents in the equilibrium, we facilitate expression of sophisticated structures such as shared constraints and additional constraints on their solutions. We define shared variables and demonstrate their uses for sparse reformulation, economic equilibrium problems sharing economic states, mixed pricing behavior of agents, and so on. We give some equilibrium and variational examples from the literature and describe how to formulate them using our framework. Experimental results comparing performance of various complementarity formulations for shared variables are provided. Our framework has been implemented and is available within GAMS/EMP.
Simultaneous multi-area recordings suggest a novel hypothesis about how attention improves performance

Visual attention dramatically improves subjects' ability to see and also modulates the responses of neurons in every known visual and oculomotor area, but whether those modulations can account for perceptual improvements remains unclear. We measured the relationship between populations of visual neurons, oculomotor neurons, and behavior, which was inconsistent with all published hypotheses about how attention improves perception. Our results support the novel hypothesis that attention reshapes the visual representation of attended stimuli to more effectively influence the premotor neurons that guide decisions without explicitly changing the readout or decision process. Our results suggest a path toward understanding the neural underpinnings of perception and cognition in health and disease by analyzing neuronal responses in ways that are constrained by behavior and interactions between brain areas.
21st Century Cures for the Opioid Crisis: Promise, Impact, and Missed Opportunities.

Signed into law in 2016, the landmark 21st Century Cures Act is as complex as it is divisive. For some stakeholders, including patient groups and representatives of regulated industries, the Act represented a major leap forward in pharmaceutical innovation, human subjects protections, and numerous other provisions. For other observers, this legislation was characterized as a major rollback in important regulations, which would leave patients worse off and the payers holding the bag. The one element of the Act that was relatively uncontroversial covered a number of provisions related to addressing the opioid crisis. This was by design. Provisions related to this issue were not part of the original legislation and were added to win over additional members of Congress who needed to be brought along to support the legislation. Many of the statute's provisions were intertwined with the Comprehensive Addiction Recovery Act (“CARA”) passed previously, but that legislation was stripped of much of its funding for opioid crisis response.
Configuration Space Metrics

When robot manipulators decide how to reach for an object, hand it over, or obey some task constraint, they implicitly assume a Euclidean distance metric in their configuration space. Their notion of what makes a configuration closer or further is dictated by this assumption. But different distance metrics will lead to different solutions. What is efficient under a Euclidean metric might not necessarily look the most efficient or natural to a person observing the robot. In this paper, we analyze the effect of the metric on robot behavior, examining both Euclidean, as well as non-Euclidean metrics - metrics that make certain joints cheaper, or that correlate different joints. Our user data suggests that tasks on a 3DOF arm and the Jaco 7DOF arm can typically be grouped into ones where a Euclidean metric works well, and tasks where that is no longer the case: there, surprisingly, penalizing elbow motion (and sometimes correlating the shoulder and wrist) leads to solutions that are more aligned with what users prefer.
Convergence of the augmented decomposition algorithm

We study the convergence of the augmented decomposition algorithm (ADA) proposed in Rockafellar et al. (Problem decomposition in block-separable convex optimization: ideas old and new, https://www.washington.edu/ , 2017) for solving multi-block separable convex minimization problems subject to linear constraints. We show that the global convergence rate of the exact ADA is $$o(1/\nu )$$ under the assumption that there exists a saddle point. We consider the inexact augmented decomposition algorithm and establish global and local convergence results under some mild assumptions, by providing a stability result for the maximal monotone operator $$\mathcal {T}$$ associated with the perturbation from both primal and dual perspectives. This result implies the local linear convergence of the inexact ADA for many applications such as the lasso, total variation reconstruction, exchange problem and many other problems from statistics, machine learning and engineering with $$\ell _1$$ regularization.
Ionic Tuning of Cobaltites at the Nanoscale

Author(s): Gilbert, DA; Grutter, AJ; Murray, PD; Chopdekar, RV; Kane, AM; Ionin, AL; Lee, MS; Spurgeon, SR; Kirby, BJ; Maranville, BB; N'Diaye, AT; Mehta, A; Arenholz, E; Liu, K; Takamura, Y; Borchers, JA | Abstract: Control of materials through custom design of ionic distributions represents a powerful new approach to develop future technologies ranging from spintronic logic and memory devices to energy storage. Perovskites have shown particular promise for ionic devices due to their high ion mobility and sensitivity to chemical stoichiometry. In this work, we demonstrate a solid-state approach to control of ionic distributions in (La,Sr)CoO3 thin films. Depositing a Gd capping layer on the perovskite film, oxygen is controllably extracted from the structure, up to 0.5 O/u.c. throughout the entire 36-nm thickness. Commensurate with the oxygen extraction, the Co valence state and saturation magnetization show a smooth continuous variation. In contrast, magnetoresistance measurements show no change in the magnetic anisotropy and a rapid increase in the resistivity over the same range of oxygen stoichiometry. These results suggest significant phase separation, with metallic ferromagnetic regions and oxygen-deficient, insulating, nonferromagnetic regions, forming percolated networks. Indeed, x-ray diffraction identifies oxygen-vacancy ordering, including transformation to a brownmillerite crystal structure. The unexpected transformation to the brownmillerite phase at ambient temperature is further confirmed by high-resolution scanning transmission electron microscopy which shows significant structural - and correspondingly chemical - phase separation. This work demonstrates room-temperature ionic control of magnetism, electrical resistivity, and crystalline structure in a 36-nm-thick film, presenting opportunities for ionic devices that leverage multiple material functionalities.
Cooperative Monetary and Fiscal Policies in the Euro Area

This article discusses the interaction of fiscal and monetary policy in the euro area. Though many observers suggest a fiscal union as the next step of euro‐area constitutional reform, a federal fiscal union does not appear politically feasible in the short run. We suggest moving forward with cooperative monetary and fiscal institutions and policies that allow for decentralized fiscal decisions, while taking federal stabilization policies into account. This approach will increase the probability of survival of the euro area compared with the current fiscal arrangements. Using a dynamic macro model, counterfactual simulation paths of our cooperative solution are contrasted with time‐series data for the euro area.
Rebalancing Growth in Asia

While many Asian emerging markets now run current account surpluses, reducing Asia’s overall excess savings is largely about modifying growth patterns and saving–investment balances in China. China accounts for about half of the total GDP in Asia ex-Japan but over two-thirds of the region’s total savings and current account surplus. One feature shared by all Asian economies is the surge in corporate savings over the past decade. Household saving rates, by contrast, have increased in China and India but declined sharply in Korea. Contrary to the popular characterization of China as relying on export-led growth, GDP growth in China has been dominated by investment growth. A comparative analysis reveals that China’s growth model has resulted in its having the lowest share of private consumption to GDP in the region and the lowest rate of employment growth relative to GDP growth.
Joint autoregressive and hierarchical priors for learned image compression

Recent models for learned image compression are based on autoencoders that learn approximately invertible mappings from pixels to a quantized latent representation. The transforms are combined with an entropy model, which is a prior on the latent representation that can be used with standard arithmetic coding algorithms to generate a compressed bitstream. Recently, hierarchical entropy models were introduced as a way to exploit more structure in the latents than previous fully factorized priors, improving compression performance while maintaining end-to-end optimization. Inspired by the success of autoregressive priors in probabilistic generative models, we examine autoregressive, hierarchical, and combined priors as alternatives, weighing their costs and benefits in the context of image compression. While it is well known that autoregressive models can incur a significant computational penalty, we find that in terms of compression performance, autoregressive and hierarchical priors are complementary and can be combined to exploit the probabilistic structure in the latents better than all previous learned models. The combined model yields state-of-the-art rate–distortion performance and generates smaller files than existing methods: 15.8% rate reductions over the baseline hierarchical model and 59.8%, 35%, and 8.4% savings over JPEG, JPEG2000, and BPG, respectively. To the best of our knowledge, our model is the first learning-based method to outperform the top standard image codec (BPG) on both the PSNR and MS-SSIM distortion metrics.
Energy-Efficient Decision Fusion for Distributed Detection in Wireless Sensor Networks

This paper proposes an energy-efficient counting rule for distributed detection by ordering sensor transmissions in wireless sensor networks. In the counting rule-based detection in an $N$ -sensor network, the local sensors transmit binary decisions to the fusion center, where the number of all $N$ local-sensor detections are counted and compared to a threshold. In the ordering scheme, sensors transmit their unquantized statistics to the fusion center in a sequential manner; highly informative sensors enjoy higher priority for transmission. When sufficient evidence is collected at the fusion center for decision making, the transmissions from the sensors are stopped. The ordering scheme achieves the same error probability as the optimum unconstrained energy approach (which requires observations from all the $N$ sensors) with far fewer sensor transmissions. The scheme proposed in this paper improves the energy efficiency of the counting rule detector by ordering the sensor transmissions: each sensor transmits at a time inversely proportional to a function of its observation. The resulting scheme combines the advantages offered by the counting rule (efficient utilization of the network's communication bandwidth, since the local decisions are transmitted in binary form to the fusion center) and ordering sensor transmissions (bandwidth efficiency, since the fusion center need not wait for all the $N$ sensors to transmit their local decisions), thereby leading to significant energy savings. As a concrete example, the problem of target detection in large-scale wireless sensor networks is considered. Under certain conditions the ordering-based counting rule scheme achieves the same detection performance as that of the original counting rule detector with fewer than $N/2$ sensor transmissions; in some cases, the savings in transmission approaches $(N-1)$ .
Who Reacts to News

We show that the positive relation between firm-level cash-flow news and institutional ownership documented by [Cohen et al., Journal of Financial Economics 66, 409–462.] is mostly driven by short-...
Using the Minnesota Multiphasic Personality Inventory-2-Restructured Form Cutoffs to Predict Lack of Pre-surgical Exercise

Previous studies suggest the importance of understanding what factors increase risk of lack of physical activity (PA) prior to bariatric surgery, which may increase risk of suboptimal postoperative outcomes. Therefore, the current study sought to explore which Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) scales were associated with lack of pre-surgical PA. The mean age of the sample (N = 1170) was 45.97 years [standard deviation (SD) = 11.59]. Bivariate correlations and relative risk ratios were utilized to examine associations between MMPI-2-RF scale scores and regular preoperative PA. Of the ten hypothesized associations, seven MMPI-2-RF scales in the internalizing and somatic domains were associated with increased risk of preoperative lack of PA. Interventions designed to increase levels of preoperative PA are especially important because individuals with higher levels of preoperative cardiorespiratory fitness experience less complications in surgery and greater weight loss postoperatively.
A methyl-sensitive element induces bidirectional transcription in TATA-less CpG island-associated promoters.

How TATA-less promoters such as those within CpG islands (CGI) control gene expression is still a subject of active research. Here, we have identified the “CGCG element”, a ten-base pair motif with a consensus sequence of TCTCGCGAGA present in a group of promoter-associated CGI-enriched in ribosomal protein and housekeeping genes. This element is evolutionarily conserved in vertebrates, found in DNase-accessible regions and employs RNA Pol II to activate gene expression. Through analysis of capped-nascent transcripts and supporting evidence from reporter assays, we demonstrate that this element activates bidirectional transcription through divergent start sites. Methylation of this element abrogates the associated promoter activity. When coincident with a TATA-box, directional transcription remains CGCG-dependent. Because the CGCG element is sufficient to drive transcription, we propose that its unmethylated form functions as a heretofore undescribed promoter element of a group of TATA-less CGI-associated promoters.
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset.

Generating musical audio directly with neural networks is notoriously difficult because it requires coherently modeling structure at many different timescales. Fortunately, most music is also highly structured and can be represented as discrete note events played on musical instruments. Herein, we show that by using notes as an intermediate representation, we can train a suite of models capable of transcribing, composing, and synthesizing audio waveforms with coherent musical structure on timescales spanning six orders of magnitude (~0.1 ms to ~100 s), a process we call Wave2Midi2Wave. This large advance in the state of the art is enabled by our release of the new MAESTRO (MIDI and Audio Edited for Synchronous TRacks and Organization) dataset, composed of over 172 hours of virtuosic piano performances captured with fine alignment (~3 ms) between note labels and audio waveforms. The networks and the dataset together present a promising approach toward creating new expressive and interpretable neural models of music.
Pharmacogenetics and Practice: Tailoring Prescribing for Safety and Effectiveness.

Abstract Precision medicine involves using information on the effect of DNA sequence variations, together with environmental and lifestyle exposures, to improve disease prevention and treatment. Advanced practice nurses can enhance patient outcomes by adopting a precision medicine approach to patient care, which includes effective implementation of pharmacogenetic test results. However, lack of familiarity with genetic test results is often a barrier to its implementation. To aid advanced practice nurses in the interpretation and application of the test results in patient care, this discussion illustrates the benefit of pharmacogenetic testing through a case-based learning mechanism.
Exploring gaze behavior to assess performance in digital game-based learning systems

The recent growth of sophisticated digital gaming technologies has spawned an $8.1B industry around using these games for pedagogical purposes. Though Digital Game-Based Learning Systems have been adopted by industries ranging from military to medical applications, these systems continue to rely on traditional measures of explicit interactions to gauge player performance which can be subject to guessing and other factors unrelated to actual performance. This study presents a novel implicit eye-tracking based metric for digital game-based learning environments. The proposed metric introduces a weighted eye-tracking measure of traditional in-game scoring to consider the mental schema of a player’s decision making. In order to validate the efficacy of this metric, we conducted an experiment with 25 participants playing a game designed to evaluate Chinese cultural competency and communication. This experiment showed strong correlation between the novel eye-tracking performance metric and traditional measures of in-game performance.
Optimized quantification of spin relaxation times in the hybrid state.

Purpose The optimization and analysis of spin ensemble trajectories in the hybrid state-a state in which the direction of the magnetization adiabatically follows the steady state while the magnitude remains in a transient state. Methods Numerical optimizations were performed to find spin ensemble trajectories that minimize the Cramer-Rao bound for T 1 -encoding, T 2 -encoding, and their weighted sum, respectively, followed by a comparison between the Cramer-Rao bounds obtained with our optimized spin-trajectories, Look-Locker sequences, and multi-spin-echo methods. Finally, we experimentally tested our optimized spin trajectories with in vivo scans of the human brain. Results After a nonrecurring inversion segment on the southern half of the Bloch sphere, all optimized spin trajectories pursue repetitive loops on the northern hemisphere in which the beginning of the first and the end of the last loop deviate from the others. The numerical results obtained in this work align well with intuitive insights gleaned directly from the governing equation. Our results suggest that hybrid-state sequences outperform traditional methods. Moreover, hybrid-state sequences that balance T 1 - and T 2 -encoding still result in near optimal signal-to-noise efficiency for each relaxation time. Thus, the second parameter can be encoded at virtually no extra cost. Conclusions We provided new insights into the optimal encoding processes of spin relaxation times in order to guide the design of robust and efficient pulse sequences. We found that joint acquisitions of T 1 and T 2 in the hybrid state are substantially more efficient than sequential encoding techniques.
Exposure to Immigration and Admission Preferences: Evidence from France

To what extent does exposure to immigration condition the types of immigrants citizens are willing to admit? Extending the conjoint approach adopted by Hainmueller and Hopkins (Am J Pol Sci 59(3):529–548, 2015), this study investigates whether the admission preferences of French natives vary based on personal exposure to immigration, as proxied by local demographics and self-reported social contact. Methodologically, we propose and apply new methods to compare attribute salience across different subgroups of respondents. We find that although an inflow of immigrants into respondents’ municipalities has a limited influence on how French natives evaluate prospective immigrants, social contact with immigrants matters. Specifically, French natives who do not frequently interact with immigrants are significantly less favorable toward immigrants from non-western countries, and more favorable toward immigrants from western countries. In contrast, natives who report frequent social interactions with immigrants place less weight on nationality as a criterion for immigrant admission. Although scholars have noted an increasing consensus in immigration attitudes across developed democracies, our findings suggest that individual experiences with immigration condition preferences for immigration policy at the national level.
Mentoring Nurse Faculty: Outcomes of a Three-Year Clinical Track Faculty Initiative.

Abstract Clinical track faculty often lack mentoring opportunities needed to develop their scholarship which may hinder their academic promotion. The Clinical Track Faculty Mentoring Initiative was designed to foster scholarship development and academic promotion of clinical assistant professors. Fifteen clinical assistant professors in two cohorts and their mentors participated in the Initiative. Each Cohort lasted two years with one overlapping year. Participating clinical assistant professors were required to attend five check-in meetings, a summer writing workshop, school and university promotion information sessions, and mentor-protege meetings. Program outcomes were assessed quarterly and they included knowledge of promotion processes, mentorship quality, scholarship productivity, and academic promotion. Scores on knowledge of promotion processes and perceived mentorship quality among participating clinical assistant professors were significantly increased. Participating clinical assistant professors published, on average, 3.33 papers and delivered 6.4 presentations in two years. The Initiative demonstrated an effective mentoring program that incorporated a multimethod approach with clear program goals, strong systems support, and high mentorship quality.
Chapter 11 – Pathology: The Clinical Description of Human Disease

Pathology is that field of science and medicine concerned with the study of diseases, specifically their initial causes (etiologies), their step-wise progressions (pathogenesis), and their effects on normal structure and function. This chapter will consider the history of relevant discoveries and technologies that have led to our current understanding of diseases, as well as the pathologist's current role in the diagnosis, prognosis, and prediction of response of human diseases.
Near-Optimal Distributed Estimation for a Network of Sensing Units Operating Under Communication Constraints

We study the problem of distributed state estimation in a network of sensing units that can exchange their measurements but the communication between the units is constrained. The units collect noisy, possibly only partial observations of the unknown state; they are assisted by a scheduler which organizes the exchange of measurements between the units. We consider the task of minimizing the total mean-square estimation error of the network while promoting balance between the individual units' performances. This problem is formulated as the maximization of a monotone objective function subject to a cardinality constraint. By leveraging the notion of weak submodularity, we develop an efficient greedy algorithm for the proposed formulation and show that the greedy algorithm achieves a constant factor approximation of the optimal objective. Our extensive simulation studies illustrate the efficacy of the proposed formulation and the greedy algorithm.