cssi/SciSciGPT-SciSciNet huggingface dataset:
Interior point search for nonparametric image segmentation

Precise object boundary detection for automatic image segmentation is critical for image analysis, including that used in computer-aided diagnosis. However, such detection traditionally uses active contour or snake models requiring accurate initialization and parameter optimization. Identifying optimal parameter values requires time-consuming multiple runs and provides results that vary by user expertise, limiting the use of these models in high-throughput or real-time situations. Thus, we developed a nonparametric snake model using an interior point search method applied in iterations to find and improve the set of snake points forming the edge of a shape. At each iteration, one or more snake points are replaced by others in the edge map. We validated the model using binary and continuous edge images of single and multiple objects, and noisy and real images, comparing the results to those obtained using traditional snake models. The proposed model not only provides better results on all image types tested but is more robust than traditional snake models. Unlike traditional snake models, the proposed model requires no user interaction for initializing snakes and no preprocessing of noisy images. Thus, our method offers robust automatic image segmentation that is simpler to use and less time-consuming than traditional snake models.
Functional Genomics Approach Identifies Novel Signaling Regulators of TGFα Ectodomain Shedding

Ectodomain shedding of cell-surface precursor proteins by metalloproteases generates important cellular signaling molecules. Of importance for disease is the release of ligands that activate the EGFR, such as TGFα, which is mostly carried out by ADAM17 [a member of the A-disintegrin and metalloprotease (ADAM) domain family]. EGFR ligand shedding has been linked to many diseases, in particular cancer development, growth and metastasis, as well as resistance to cancer therapeutics. Excessive EGFR ligand release can outcompete therapeutic EGFR inhibition or the inhibition of other growth factor pathways by providing bypass signaling via EGFR activation. Drugging metalloproteases directly have failed clinically because it indiscriminately affected shedding of numerous substrates. It is therefore essential to identify regulators for EGFR ligand cleavage. Here, integration of a functional shRNA genomic screen, computational network analysis, and dedicated validation tests succeeded in identifying several key signaling pathways as novel regulators of TGFα shedding in cancer cells. Most notably, a cluster of genes with NFκB pathway regulatory functions was found to strongly influence TGFα release, albeit independent of their NFκB regulatory functions. Inflammatory regulators thus also govern cancer cell growth-promoting ectodomain cleavage, lending mechanistic understanding to the well-known connection between inflammation and cancer.Implications: Using genomic screens and network analysis, this study defines targets that regulate ectodomain shedding and suggests new treatment opportunities for EGFR-driven cancers. Mol Cancer Res; 16(1); 147-61. ©2017 AACR.
Archaic Skeletal Remains from the Central Plains: Demography and Burial Practices

Recently a number of reports on Plains Archaic skeletal material have been published which quadruple the number of burials described and analyzed in the literature. Although the total number of burials is still relatively small, it is large enough to allow research to begin in paleodemographic aspects of the central part of the Plains and the suggestion of burial patterns for these materials. By combining all Archaic burials from the Plains a demographic profile has been developed. It is compared with other Archaic populations from the eastern United States, and with a Plains population dating after A.D. 1000. The results of the analysis show that with few exceptions burial patterns and the demographic picture of the Plains are quite stable over time, although differences are found in metric and non-metric variations in both the time and space continua. The analysis further shows that certain anomalous conditions in the skeleton appear to be much more prevalent in Archaic material than in recent material from the same area. The results finally suggest that Archaic people in the demographic and burial practice continua are quite similar to later populations, at least through Middle Mississippian populations in the Plains.
When Is the Averaging Effect Present in Auditor Judgments

Auditing standards task auditors with collecting sufficient appropriate evidence to form audit judgments. Yet, cognitive psychology documents a robust finding in which people evaluate a bundle of relevant, directionally consistent evidence as though averaging the strength of the components. In consequence, a bundle of evidence may be viewed as weaker evidence than the bundle's strongest evidence item alone. We experimentally examine whether this averaging effect occurs in an audit context, and we test a potential moderator. In three independent mini‐cases, we ask auditor participants to make judgments about going concern, internal controls, and fraud risk. We present auditors with unfavorable audit evidence relevant to each judgment, manipulating whether we present a single strong evidence item or bundle it with a weaker evidence item. We also manipulate the auditor's initial impression of the client's state. We find that experienced auditors succumb to the averaging effect, making more strongly unfavorable judgments in response to the single evidence item than the bundle, and that this bias is reduced when the observed evidence is inconsistent with the auditor's initial impression. We interpret our results as consistent with the dual‐processing theory of cognition. Quand les effets de moyenne se manifestent‐ils dans les jugements des auditeurs? Les normes d'audit assignent aux auditeurs la tâche de colliger des elements probants appropries suffisants pour porter des jugements d'audit. Or, les recherches en psychologie cognitive font etat d'une constatation robuste selon laquelle les gens evaluent des groupes d’elements pertinents pointant dans la meme direction comme s'ils etablissaient une moyenne de la solidite de ces elements. En consequence, un groupe d’elements peut etre considere comme etant moins probant que l’element le plus probant du groupe. Les auteures procedent a une experience visant a determiner si cet effet de moyenne se produit dans un contexte d'audit et testent un moderateur potentiel. Dans trois mini‐cas independants, elles demandent aux auditeurs participants de porter des jugements sur le risque lie a la continuite de l'exploitation, au controle interne et a la fraude. Elles soumettent aux auditeurs des elements probants defavorables pertinents a chaque jugement et manipulent un parametre en leur presentant soit un element probant unique fort soit cet element probant associe a un element moins probant. Elles manipulent egalement l'impression initiale de l'auditeur quant a la situation du client. Les auteures constatent que les auditeurs experimentes cedent a la tentation d’etablir une moyenne, en portant des jugements plus nettement defavorables en reaction a l’element probant unique qu'en reaction aux elements groupes, et que cette distorsion s'attenue lorsque l’element observe ne cadre pas avec l'impression initiale de l'auditeur. Les auteures interpretent ces resultats comme etant conformes a la theorie du traitement parallele de l'information en psychologie cognitive.
Managerial ability, information quality, and the design and pricing of corporate debt

We examine if managerial ability affects the efficiency of the contracting environment with lenders. We find that higher ability alters the balance of information-sensitive covenants demanded by outside investors, increases the issuance of bonds with longer maturity, and decreases the issuance of senior secured debt. We also document higher ability reduces the risk premium demanded by investors on information-sensitive debt. These results are collectively consistent with the premise that the mitigation of information risk is an important dimension of managerial ability that has a direct bearing on the structure and pricing of corporate debt.
Growth is required for perception of water availability to pattern root branches in plants.

Water availability is a potent regulator of plant development and induces root branching through a process termed hydropatterning. Hydropatterning enables roots to position lateral branches toward regions of high water availability, such as wet soil or agar media, while preventing their emergence where water is less available, such as in air. The mechanism by which roots perceive the spatial distribution of water during hydropatterning is unknown. Using primary roots of Zea mays (maize) we reveal that developmental competence for hydropatterning is limited to the growth zone of the root tip. Past work has shown that growth generates gradients in water potential across an organ when asymmetries exist in the distribution of available water. Using mathematical modeling, we predict that substantial growth-sustained water potential gradients are also generated in the hydropatterning competent zone and that such biophysical cues inform the patterning of lateral roots. Using diverse chemical and environmental treatments we experimentally demonstrate that growth is necessary for normal hydropatterning of lateral roots. Transcriptomic characterization of the local response of tissues to a moist surface or air revealed extensive regulation of signaling and physiological pathways, some of which we show are growth-dependent. Our work supports a “sense-by-growth” mechanism governing hydropatterning, by which water availability cues are rendered interpretable through growth-sustained water movement.
Visualizations for an Explainable Planning Agent

In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making. Imposing transparency and explainability requirements on such agents is especially important in order to establish trust and common ground with the end-to-end automated planning system. Visualizing the agent's internal decision-making processes is a crucial step towards achieving this. This may include externalizing the "brain" of the agent -- starting from its sensory inputs, to progressively higher order decisions made by it in order to drive its planning components. We also show how the planner can bootstrap on the latest techniques in explainable planning to cast plan visualization as a plan explanation problem, and thus provide concise model-based visualization of its plans. We demonstrate these functionalities in the context of the automated planning components of a smart assistant in an instrumented meeting space.
A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks

ABSTRACTGiven different types of constraints on human life, people must make decisions that satisfy social activity needs. Minimizing costs (i.e. distance, time, or money) associated with travel plays an important role in perceived and realized social quality of life. Identifying optimal interaction locations on road networks when there are multiple moving objects (MMO) with space–time constraints remains a challenge. In this research, we formalize the problem of finding dynamic ideal interaction locations for MMO as a spatial optimization model and introduce a context-based geoprocessing heuristic framework to address this problem. As a proof of concept, a case study involving identification of a meetup location for multiple people under traffic conditions is used to validate the proposed geoprocessing framework. Five heuristic methods with regard to efficient shortest-path search space have been tested. We find that the R* tree-based algorithm performs the best with high quality solutions and low comput...
Resource theory of non-Gaussian operations

Non-Gaussian states and operations are crucial for various continuous-variable quantum information processing tasks. To quantitatively understand non-Gaussianity beyond states, we establish a resource theory for non-Gaussian operations. In our framework, we consider Gaussian operations as free operations, and non-Gaussian operations as resources. We define entanglement-assisted non-Gaussianity generating power and show that it is a monotone that is nonincreasing under the set of free superoperations, i.e., concatenation and tensoring with Gaussian channels. For conditional unitary maps, this monotone can be analytically calculated. As examples, we show that the non-Gaussianity of ideal photon-number subtraction and photon-number addition equal the non-Gaussianity of the single-photon Fock state. Based on our non-Gaussianity monotone, we divide non-Gaussian operations into two classes: (i) the finite non-Gaussianity class, e.g., photon-number subtraction, photon-number addition, and all Gaussian-dilatable non-Gaussian channels; and (ii) the diverging non-Gaussianity class, e.g., the binary phase-shift channel and the Kerr nonlinearity. This classification also implies that not all non-Gaussian channels are exactly Gaussian dilatable. Our resource theory enables a quantitative characterization and a first classification of non-Gaussian operations, paving the way towards the full understanding of non-Gaussianity.
Kourami: graph-guided assembly for novel human leukocyte antigen allele discovery

Accurate typing of human leukocyte antigen (HLA) is important because HLA genes play important roles in immune responses and disease genesis. Previously available computational methods are database-matching approaches and their outputs are inherently limited by the completeness of already known types, making them unsuitable for discovery of novel alleles. We have developed a graph-guided assembly technique for classical HLA genes, which can construct allele sequences given high-coverage whole-genome sequencing data. Our method delivers highly accurate HLA typing, comparable to the current state-of-the-art methods. Using various data, we also demonstrate that our method can type novel alleles.
Population Structure Promotes the Evolution of Intuitive Cooperation and Inhibits Deliberation

Spatial structure is one of the most studied mechanisms in evolutionary game theory. Here, we explore the consequences of spatial structure for a question which has received considerable empirical and theoretical attention in recent years, but has not yet been studied from a network perspective: whether cooperation relies on intuitive predispositions or deliberative self-control. We examine this question using a model which integrates the “dual-process” framework from cognitive science with evolutionary game theory, and considers the evolution of agents who are embedded within a social network and only interact with their neighbors. In line with past work in well-mixed populations, we find that selection favors either the intuitive defector strategy which never deliberates, or the dual-process cooperator strategy which intuitively cooperates but uses deliberation to switch to defection when doing so is payoff-maximizing. We find that sparser networks (i.e., smaller average degree) facilitate the success of dual-process cooperators over intuitive defectors, while also reducing the level of deliberation that dual-process cooperators engage in; and that these results generalize across different kinds of networks. These observations demonstrate the important role that spatial structure can have not just on the evolution of cooperation, but on the co-evolution of cooperation and cognition.
High-throughput live-imaging of embryos in microwell arrays using a modular specimen mounting system

High-throughput live-imaging of embryos is an essential technique in developmental biology, but it is difficult and costly to mount and image embryos in consistent conditions. Here, we present OMMAwell, a simple, reusable device to easily mount dozens of embryos in arrays of agarose microwells with customizable dimensions and spacing. OMMAwell can be configured to mount specimens for upright or inverted microscopes, and includes a reservoir to hold live-imaging medium to maintain constant moisture and osmolarity of specimens during time-lapse imaging. All device components can be fabricated by cutting pieces from a sheet of acrylic using a laser cutter or by making them with a 3D printer. We demonstrate how to design a custom mold and use it to live-image dozens of embryos at a time. We include descriptions, schematics, and design files for 13 additional molds for nine animal species, including most major traditional laboratory models and a number of emerging model systems. Finally, we provide instructions for researchers to customize OMMAwell inserts for embryos or tissues not described herein.
The Audit of Organizational Communication

A conceptual and methodological structure is presented for examination of communication processes in organizations. Components of the communication system are identified, a taxonomical table of act...
Fighting Fake News: Image Splice Detection via Learned Self-Consistency

Advances in photo editing and manipulation tools have made it significantly easier to create fake imagery. Learning to detect such manipulations, however, remains a challenging problem due to the lack of sufficient amounts of manipulated training data. In this paper, we propose a learning algorithm for detecting visual image manipulations that is trained only using a large dataset of real photographs. The algorithm uses the automatically recorded photo EXIF metadata as supervisory signal for training a model to determine whether an image is self-consistent — that is, whether its content could have been produced by a single imaging pipeline. We apply this self-consistency model to the task of detecting and localizing image splices. The proposed method obtains state-of-the-art performance on several image forensics benchmarks, despite never seeing any manipulated images at training. That said, it is merely a step in the long quest for a truly general purpose visual forensics tool.
Repetitive Stimulation Enhances V1 Encoding Efficiency

Repeated stimulus presentations reduce neuronal responses across many brain areas (repetition suppression) while improving performance in associated tasks (repetition priming). The neuronal mechanisms that enhance performance in the face of reduced brain activity are unknown. Here we demonstrate that stimulus repetition increases encoding efficiency among cortical neurons, which enhances stimulus representations despite reduced spiking activity. Using a repetition priming-evoking stimulus sequence, we recorded laminar responses in monkey primary visual cortex (V1). We found that repetition suppression is most pronounced outside the V1 layers that receive retinogeniculate input and is robust to alternating stimuli between the two eyes, suggesting that repetition suppression is of cortical origin. This V1 spiking suppression is accompanied by sharpened neural tuning as well as increased neuronal synchrony, however not by decreased response latency. These results suggest that repetition priming and repetition suppression arise from modulated cortical neuronal processing that enhances encoding efficiency as stimuli repeat.
Planarity and street network representation in urban form analysis

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in...
Data-Driven Modeling of Aircraft Engine Fuel Burn in Climb Out and Approach:

Fuel burn is a key driver of aircraft performance, and contributes to airline costs and emissions. Low-altitude fuel burn and emissions, such as those that occur during climb out and approach, have...
The Internet of Things: Secure Distributed Inference

The growth in the number of devices connected to the Internet of Things (IoT) poses major challenges in security. The integrity and trustworthiness of data and data analytics are increasingly important concerns in IoT applications. These are compounded by the highly distributed nature of IoT devices, making it infeasible to prevent attacks and intrusions on all data sources. Adversaries may hijack devices and compromise their data. As a result, reactive countermeasures, such as intrusion detection and resilient analytics, become vital components of security. This article overviews algorithms for secure distributed inference in IoT.
Tissue-specific degradation of essential centrosome components reveals distinct microtubule populations at microtubule organizing centers.

Non-centrosomal microtubule organizing centers (ncMTOCs) are found in most differentiated cells, but how these structures regulate microtubule organization and dynamics is largely unknown. We optimized a tissue-specific degradation system to test the role of the essential centrosomal microtubule nucleators γ-tubulin ring complex (γ-TuRC) and AIR-1/Aurora A at the apical ncMTOC, where they both localize in Caenorhabditis elegans embryonic intestinal epithelial cells. As at the centrosome, the core γ-TuRC component GIP-1/GCP3 is required to recruit other γ-TuRC components to the apical ncMTOC, including MZT-1/MZT1, characterized here for the first time in animal development. In contrast, AIR-1 and MZT-1 were specifically required to recruit γ-TuRC to the centrosome, but not to centrioles or to the apical ncMTOC. Surprisingly, microtubules remain robustly organized at the apical ncMTOC upon γ-TuRC and AIR-1 co-depletion, and upon depletion of other known microtubule regulators, including TPXL-1/TPX2, ZYG-9/ch-TOG, PTRN-1/CAMSAP, and NOCA-1/Ninein. However, loss of GIP-1 removed a subset of dynamic EBP-2/EB1–marked microtubules, and the remaining dynamic microtubules grew faster. Together, these results suggest that different microtubule organizing centers (MTOCs) use discrete proteins for their function, and that the apical ncMTOC is composed of distinct populations of γ-TuRC-dependent and -independent microtubules that compete for a limited pool of resources.
Towards More Reliable Transfer Learning

Multi-source transfer learning has been proven effective when within-target labeled data is scarce. Previous work focuses primarily on exploiting domain similarities and assumes that source domains are richly or at least comparably labeled. While this strong assumption is never true in practice, this paper relaxes it and addresses challenges related to sources with diverse labeling volume and diverse reliability. The first challenge is combining domain similarity and source reliability by proposing a new transfer learning method that utilizes both source-target similarities and inter-source relationships. The second challenge involves pool-based active learning where the oracle is only available in source domains, resulting in an integrated active transfer learning framework that incorporates distribution matching and uncertainty sampling. Extensive experiments on synthetic and two real-world datasets clearly demonstrate the superiority of our proposed methods over several baselines including state-of-the-art transfer learning methods. Code related to this paper is available at: https://github.com/iedwardwangi/ReliableMSTL.
Extending the bounds of morphology instruction: teaching Latin roots facilitates academic word learning for English Learner adolescents

This study investigated the hypothesis that academic vocabulary instruction infused with morphological analysis of bound Latin roots-such as analysis of the relation between innovative and its bound root, nov (meaning “new”)-will enhance word learning outcomes for English Learner (EL) adolescents. Latinate words with bound roots comprise a majority of general academic vocabulary words in English and are ubiquitous in texts across content areas. However, the effect of instruction in this area of morphology is unclear. Theory suggests that morphological knowledge is a critical component of lexical representations, binding a word’s phonological, orthographic and semantic features. We hypothesized that instruction in bound Latin roots would (a) produce stronger outcomes for learning academic words by strengthening semantic and orthographic representations, and (b) equip students with morphological analysis skills to problem-solve new words. Employing a within-subjects design, 84 EL students participated in both of two counterbalanced conditions: vocabulary intervention without roots (comparison) and vocabulary intervention with roots (treatment). Effects on learning meanings of academic words were similar across conditions. However, the “with roots” condition showed large treatment effects for morphological problem-solving of unfamiliar words, and also suggested positive treatment effects on lexical access, lending partial support to our hypothesis that instruction about bound Latin roots contributes to EL adolescents’ academic vocabulary learning.
Using the maximum entropy distribution to describe electrons in reconnecting current sheets

Particle distributions in weakly collisional environments such as the magnetosphere have been observed to show deviations from the Maxwellian distribution. These can often be reproduced in kinetic simulations, but fluid models, which are used in global simulations of the magnetosphere, do not necessarily capture any of this. We apply the maximum entropy fluid closure of Levermore, which leads to well posed moment equations, to reconstruct particle distributions from a kinetic simulation in a reconnection region. Our results show that without information other than the moments, the model can reproduce the general structure of the distributions but not all of the finer details. The advantages of the closure over the traditional Grad closure are also discussed.
Corporate Tax Avoidance and Firm Value Discount

We analyze the valuation-tax avoidance relation and find there is, in fact, a market value discount for tax avoidance. We identify several channels for the adverse valuation effects of tax avoidanc...
Generalization Bounds for Uniformly Stable Algorithms

Uniform stability of a learning algorithm is a classical notion of algorithmic stability introduced to derive high-probability bounds on the generalization error (Bousquet and Elisseeff, 2002). Specifically, for a loss function with range bounded in $[0,1]$, the generalization error of $\gamma$-uniformly stable learning algorithm on $n$ samples is known to be at most $O((\gamma +1/n) \sqrt{n \log(1/\delta)})$ with probability at least $1-\delta$. Unfortunately, this bound does not lead to meaningful generalization bounds in many common settings where $\gamma \geq 1/\sqrt{n}$. At the same time the bound is known to be tight only when $\gamma = O(1/n)$. Here we prove substantially stronger generalization bounds for uniformly stable algorithms without any additional assumptions. First, we show that the generalization error in this setting is at most $O(\sqrt{(\gamma + 1/n) \log(1/\delta)})$ with probability at least $1-\delta$. In addition, we prove a tight bound of $O(\gamma^2 + 1/n)$ on the second moment of the generalization error. The best previous bound on the second moment of the generalization error is $O(\gamma + 1/n)$. Our proofs are based on new analysis techniques and our results imply substantially stronger generalization guarantees for several well-studied algorithms.
THE DISTRIBUTION OF EXCHANGE RATES IN THE EMS

Exchange rates of currencies in the Exchange Rate Mechanism (ERM) of the European Monetary System (EMS) are characterized by long periods of stability interrupted by periods of extreme volatility. The periods of volatility appear at times of realignments of the central parities and at times when the exchange rate is within the ERM bands. We begin by considering a procedure for finding outliers based on measuring distance as a quadratic form. The evidence suggests that the exchange rates of the EMS can be described by a mixture of two distributions. We therefore model the exchange rate as switching between two distributions--one that holds in stable times and the other that holds in volatile times. In particular, we use Hamilton's Markov-switching model. In addition, we extend Hamilton's model by allowing the probability of switching from one state to another to depend on the position of the exchange rate within its EMS band. This model has the interesting implication that near the edge of the band, large movements--either realignments or large jumps to the centre of the band--are more likely if the move to the edge of the band has been precipitous. Copyright @ 1996 by John Wiley & Sons, Ltd. All rights reserved.
Validation and Uncertainty Quantification for Wall Boiling Closure Relations in Multiphase-CFD Solver

Two-fluid model-based multiphase computational fluid dynamics (MCFD) has been considered one of the most promising tools to investigate a two-phase flow and boiling system for engineering purposes....
Advanced application of statistical and fuzzy control to textile processes

A new control strategy is proposed to optimize the slasher control parameters and the slashing operation during normal, transient and creep speed. An expert system detects and identifies off-limits or failure conditions and generates command signals for low level control of slasher components such as creel, size box drying section and beamer drive. It also addresses the issues of system integration between warping and weaving at a hierarchical level. Simple process models for each section of a slasher are simulated on computers. Simulated results from these models demonstrate that the control strategy is efficient and robust. >
Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina

High-acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible organisms lack a fovea, its specialized function and its dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >60 cell types match between the two regions but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved. In contrast, projection neuron types and programs diverge, despite exhibiting conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 7 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species.
Identity Politics and Trade Policy

We characterize trade policies that result from political competition when assessments of well-being include both material and psychosocial components. The material component reflects, as usual, satisfaction from consumption. Borrowing from social identity theory, we take the psychosocial component as combining the pride and self-esteem an individual draws from the status of groups with which she identifies and a dissonance cost she bears from identifying with those that are different from herself. In this framework, changes in social identification patterns that may result, for example, from increased income inequality or heightened class or ethnic tensions, lead to pronounced changes in trade policy. We analyse the nature of these policy changes.
User Perceptions of Smart Home IoT Privacy

Smart home Internet of Things (IoT) devices are rapidly increasing in popularity, with more households including Internet-connected devices that continuously monitor user activities. In this study, we conduct eleven semi-structured interviews with smart home owners, investigating their reasons for purchasing IoT devices, perceptions of smart home privacy risks, and actions taken to protect their privacy from those external to the home who create, manage, track, or regulate IoT devices and/or their data. We note several recurring themes. First, users' desires for convenience and connectedness dictate their privacy-related behaviors for dealing with external entities, such as device manufacturers, Internet Service Providers, governments, and advertisers. Second, user opinions about external entities collecting smart home data depend on perceived benefit from these entities. Third, users trust IoT device manufacturers to protect their privacy but do not verify that these protections are in place. Fourth, users are unaware of privacy risks from inference algorithms operating on data from non-audio/visual devices. These findings motivate several recommendations for device designers, researchers, and industry standards to better match device privacy features to the expectations and preferences of smart home owners.
Comparison of In Vitro Stereoselective Metabolism of Bupropion in Human, Monkey, Rat, and Mouse Liver Microsomes

Bupropion is an atypical antidepressant and smoking cessation aid associated with wide intersubject variability. This study compared the formation kinetics of three phase I metabolites (hydroxybupropion, threohydrobupropion, and erythrohydrobupropion) in human, marmoset, rat, and mouse liver microsomes. The objective was to establish suitability and limitations for subsequent use of nonclinical species to model bupropion central nervous system (CNS) disposition in humans. Hepatic microsomal incubations were conducted separately for the R- and S-bupropion enantiomers, and the formation of enantiomer-specific metabolites was determined using LC-MS/MS. Intrinsic formation clearance (CLint) of metabolites across the four species was determined from the formation rate versus substrate concentration relationship. The total clearance of S-bupropion was higher than that of R-bupropion in monkey and human liver microsomes. The contribution of hydroxybupropion to the total racemic bupropion clearance was 38%, 62%, 17%, and 96% in human, monkey, rat, and mouse, respectively. In the same species order, threohydrobupropion contributed 53%, 23%, 17%, and 3%, and erythrohydrobupropion contributed 9%, 14%, 66%, and 1.3%, respectively, to racemic bupropion clearance. The results demonstrate that phase I metabolism in monkeys best approximates that observed in humans, and support the preferred use of this species to investigate possible pharmacokinetic factors that influence the CNS disposition of bupropion and contribute to its high intersubject variability.
The Labor Market Effects of Offshoring by U.S. Multinational Firms

We use firm-level data on U.S. multinationals to show how offshoring affects domestic employment within and across firms. We introduce a new instrument for offshoring: Bilateral Tax Treaties, which...
Bitcoin: Rube Goldberg Machine, Antique Throwback, Gigantic Distraction, Entertainment, Ripoff or New Money?

A means of exchange and preservation of value is likely as old as our species. Global economic trade is often argued to be as old as trade. The question of the nature of the exchange, of who creates the value and how it is regulated is the issue. While tin from England may have reached Sumeria 4 000 years ago, or Phoenicians' ships entered the Africa area of Cape Palmas at about the same time, the problem of exchange is a central issue. Ideas of money are as diverse as the cultures that produce them, yet today global trade is experiencing modifications of the satisfaction of exchange with new platforms of electronic money. Blockchain technology is touted as foolproof, such claims have appeared in the past with various financial innovations. Such abstractions of value may not be new, but as a product of technology and complexity they create psychological novelty and a form of mesmerizing fetishism (Douglas, M. and Isherwood, B., ed.: The World of Goods: Towards an Anthropology of Consumption. Routledge, London, 1978). Manias of value are also not new, from stock (South Seas Corporation) to tulips (MacKay, C.: Extraordinary Popular Delusions and the Madness of Crowds. Crown Press, London, 1841). The form of the mania is defined and expressed culturally but is often associated with technological change and distance of exchange of partners and clients (Baric, L.: Some aspects of credit, saving and investment in a 'non-monetary' economy (Rossel Island). In: Firth, R. and Yamey, B.S., eds.: Capital, Saving and Credit in Peasant Societies. Aldine Publishing, Chicago, pp.35-52, 1964.). Inequality is also a feature, embedded in economic and technological disruption of trade and exchange. The role of redistribution and taxation are essential in maintaining social credit and equality. We can relate such behaviour to other systems of animal societies.
JOINT TRAJECTORIES OF COGNITION AND FRAILTY, AND ASSOCIATED BURDEN OF PATIENT-REPORTED OUTCOMES

Abstract Objectives To evaluate joint trajectories of cognition and frailty and their association with the cumulative burden of patient-reported outcomes, including hospitalization, nursing home admission, and disability. Design Longitudinal study of 754 community-living persons aged 70 or older. Participants 690 participants who had a baseline and at least one follow-up assessment of cognition and frailty between 1998 and 2009. Measurements Cognition was assessed using the Mini-Mental State Examination (MMSE). Frailty was defined by the 5 criteria for the Fried phenotype: muscle weakness, exhaustion, low physical activity, shrinking, and slow walking speed. A group-based, mixture modeling approach was used to fit the joint trajectories of cognition and frailty. The cumulative burden of hospitalization, nursing home admission, and disability over 141 months associated with the joint trajectories was evaluated using a series of generalized estimating equation Poisson models. Results Four joint trajectories were identified, including No cognitive frailty (27.8%), Slow cognitive decline and progressive frailty (45.5%), Rapid cognitive decline and progressive frailty (20.2%), and Cognitive frailty (6.5%). For each joint trajectory group, the interval-specific incidence density rates of all patient-reported outcomes tended to increase over time, with the exception of hospitalization for which the increasing trend was apparent only for the Slow cognitive decline and progressive frailty group. The No cognitive frailty group had the lowest cumulative burden of all patient-reported outcomes [eg, nursing home admissions, 7.5/1000 person-months, 95% confidence interval (CI): 4.8-11.7], whereas the Cognitive frailty group had the highest cumulative burden (eg, nursing home admissions, 381.1/1000 person-months, 95% CI: 294.5-493.1), with the exception of hospitalization. Compared with the No cognitive frailty group, the 3 other joint trajectory groups all had significantly greater burden of the patient-reported outcomes. Conclusion Community-living older persons exhibit distinct joint trajectories of cognition and frailty and experience an increasing burden of nursing home admission and disability as they age, with the greatest burden for those on a cognitive frailty trajectory.
Quantum Efficiency of Charge Transfer Competing against Nonexponential Processes: The Case of Electron Transfer from CdS Nanorods to Hydrogenase

Photoexcited charge transfer from semiconductor nanocrystals to charge acceptors is a key step for photon energy conversion in semiconductor nanocrystal-based light-harvesting systems. Charge transfer competes against relaxation processes within the nanocrystals, and this competition determines the quantum efficiency of charge transfer. The quantum efficiency is a critical design element in photochemistry, but in nanocrystal–acceptor systems its extraction from experimental data is complicated by sample heterogeneity and intrinsically nonexponential excited-state decay pathways. In this manuscript, we systematically explore these complexities using TA spectroscopy over a broad range of timescales to probe electron transfer from CdS nanorods to the redox enzyme hydrogenase. To analyze the experimental data, we build a model that quantifies the quantum efficiency of charge transfer in the presence of competing, potentially nonexponential, relaxation processes. Our approach can be applied to calculate the ef...
Revisiting Non-Malleable Secret Sharing

A threshold secret sharing scheme (with threshold t) allows a dealer to share a secret among a set of parties such that any group of t or more parties can recover the secret and no group of at most \(t-1\) parties learn any information about the secret. A non-malleable threshold secret sharing scheme, introduced in the recent work of Goyal and Kumar (STOC’18), additionally protects a threshold secret sharing scheme when its shares are subject to tampering attacks. Specifically, it guarantees that the reconstructed secret from the tampered shares is either the original secret or something that is unrelated to the original secret.
Paying attention to social media stocks

Abstract Social media has reshaped business models, economies, politics, and culture around the world. In this paper, we identified social media stocks from various sectors by using a strict, academic definition and then studied their performance and return characteristics. Multivariate regression results demonstrate that being recognized as a social media firm yields extra return. The performance of social media stocks is not associated with macro-level sentiment, but rather with firm-level attention paid by potential investors. Causality tests indicate that the default risk premium and volatility have incremental power in explaining the performance of social media stocks.
Smoking Cessation Before and After Total Joint Arthroplasty – An Uphill Battle

Abstract Background Patients actively smoking at the time of primary total joint arthroplasty (TJA) are at increased risk of perioperative complications. Employing strategies for smoking cessation has therefore become routine. A potential benefit of cessation in anticipation of TJA may be long-term cessation. However, success rates and the longevity of successful smoking cessation attempts before TJA have yet to be presented. Methods Our institution’s total joint registry documents self-reported smoking status. As such, all patients who underwent TJA from 2007 to 2018 were identified and grouped as nonsmokers, smokers (regularly smoking within 1 year before surgery), and former smokers (those who quit smoking within 1 year before surgery). Thereafter, postoperative smoking status was assessed with special attention to former smokers to see who remained smoke-free. Results From the 28,758 primary TJAs identified, 91.3% (26,244) were nonsmokers, 7.3% (2109) were smokers, and 1.4% (405) had quit smoking before surgery. Among former smokers, 86% were abstinent 1 year postoperatively but only 45% were still abstinent 8 years postoperatively. Conversely, 7% of smokers at the time of surgery eventually quit and 6% of prior nonsmokers started smoking over the same time period. Conclusion Despite concerted efforts to help patients stop smoking before TJA, 7.3% remain smokers. Among those who are successful, less than half (45%) remain smoke-free after surgery. Compared to current smokers, however, patients who managed to quit before surgery are more likely to remain smoke-free after surgery. These findings demonstrate the tremendous challenge smoking represents in contemporary TJA practices. Level of Evidence Therapeutic level III.
Bank Contagion Risk through Fire-Sales: A Heterogeneous Agent Model

This paper studies the impact of interbank risk exposures due to fire sales in the interbank lending market. We incorporate fire sale behaviors in a large-scale agent-based model that represents dynamic U.S. interbank lending system. We compare the simulated interbank networks with and without fire sales. The model shows that fire sales reduce the number of bank defaults due to financial shocks, while increasing the likelihood of contagion. Moreover, we investigate the implications of the capital requirements imposed by the Basel regulation by conducting a sensitivity test on capital ratios. We find the higher capital requirements may result in larger number of bank defaults.
Dopamine Depletion Affects Vocal Acoustics and Disrupts Sensorimotor Adaptation in Songbirds.

Abstract Dopamine is hypothesized to convey error information in reinforcement learning tasks with explicit appetitive or aversive cues. However, during motor skill learning feedback signals arise from an animal’s evaluation of sensory feedback resulting from its own behavior, rather than any external reward or punishment. It has previously been shown that intact dopaminergic signaling from the ventral tegmental area/substantia nigra pars compacta (VTA/SNc) complex is necessary for vocal learning when songbirds modify their vocalizations to avoid hearing distorted auditory feedback (playbacks of white noise). However, it remains unclear whether dopaminergic signaling underlies vocal learning in response to more naturalistic errors (pitch-shifted feedback delivered via headphones). We used male Bengalese finches ( Lonchura striata var. domestica ) to test the hypothesis that the necessity of dopamine signaling is shared between the two types of learning. We combined 6-hydroxydopamine (6-OHDA) lesions of dopaminergic terminals within Area X, a basal ganglia nucleus critical for song learning, with a headphones learning paradigm that shifted the pitch of auditory feedback and compared their learning to that of unlesioned controls. We found that 6-OHDA lesions affected song behavior in two ways. First, over a period of days lesioned birds systematically lowered their pitch regardless of the presence or absence of auditory errors. Second, 6-OHDA lesioned birds also displayed severe deficits in sensorimotor learning in response to pitch-shifted feedback. Our results suggest roles for dopamine in both motor production and auditory error processing, and a shared mechanism underlying vocal learning in response to both distorted and pitch-shifted auditory feedback.
Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database

Objective This article documents wide‐ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods Two k‐fold cross‐validations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results The cross‐validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality data sets. Conclusion Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross‐national research on income inequality.
A simple method for the direct arylation of indoles

Abstract The scope and limitations are described for a powerful new method to access indoles bearing a quaternary center at C-3 using easily accessible bisaryl λ3-iodanes and a cheap organic base.
(S)- or (R)-3-(E-enoyl)-4-phenyl-1,3-oxazolidin-2-ones: Ideal Michael acceptors to afford a virtually complete control of simple and face diastereoselectivity in addition reactions with glycine derivatives

[formula: see text] Enantiomerically pure (S)- or (R)-3-(E-enoyl)-4-phenyl-1,3-oxazolidin-2-ones were found to serve as ideal Michael acceptors in addition reactions with achiral Ni(II) complexes of glycine Schiff bases. Virtually complete control of simple and face diastereoselectivity, observed in these reactions, combined with quantitative chemical yields renders this methodology synthetically superior to the previous methods.