cssi/SciSciGPT-SciSciNet huggingface dataset:
Quantitation of Renal Function With Static Imaging Agents

DMSA is an excellent static imaging agent. Approximately 50% of the injected dose remains bound to the cortical tubules of the kidney up to 24 hr after injection. During this time, 30% of the dose is excreted in the urine, background activity drops significantly, and kidney-to-background ratio is enhanced markedly. A 5 mCi dose is adequate for static imaging even out to 24 hr and the 5 mCi dose can be reduced for 1–4 hr post injection images. Patients should be adequately hydrated prior to a DMSA study since adequate hydration may enhance the excretion of DMSA, decrease background activity, improve the kidney-to-background ratio, and lower the radiation dose to the patient. A number of studies have shown that the relative uptake of DMSA correlates well with the relative ERPF and GFR in patients with both normal and asymmetrically functioning kidneys however, there are only a limited number of comparison studies in patients with severely compromised renal function. In this group of patients, comparison and validation studies are complicated by the fact that measuring the relative renal uptake of hippurate or DTPA during the first 1–3 min post-injection can be statistically less accuarate than determining the relative uptake of DMSA. A few investigators have reported DMSA scanning may be misleading in patients with obstruction due to retention of DMSA in the renal pelvis. This conclusion is based on a discrepancy in the relative renal function determined using DMSA and 131 I-hippurate or DTPA. Since obstructed kidneys generally have diminished function, this discrepancy may be related to the problem of region of interest assignment and background substraction during the first 1–3 min after hippurate or DTPA injection. While other investigators have not observed obstruction to be a problem, it is probably safer to confirm DMSA results in patients with obstruction with an additional study using hippurate or DTPA until more comparison data become available. After reconstitution with 99m Tc pertechnetate, the DMSA preparation is quite sensitive to oxidation and air should not be introduced into the reaction vial. If more than one dose is to be obtained from a single vial, the two or more doses should be drawn immediately after each other and administered as soon as possible. Oxidation will degrade the DMSA complex, decrease uptake in the kidney and increase liver background activity. It also is important to note that acidification of the urine in rats with ammonium chloride doubled the liver uptake of DMSA and decreased the renal uptake by 50%. Acidification of the urine in patients may also alter the biodistribution and, in theory, may also alter the relative distribution of DMSA between asymmetrically functioning kidneys. These possibilities need to be further evaluated. Finally, since a number of variables can affect the total renal accumulation of DMSA, DMSA should not be quantitated as an absolute index of renal function unless it is done by experienced investigators under carefully controlled conditions.
Vancomycin Therapy in Patients with Impaired Renal Function: A Nomogram for Dosage

The relation between vancomycin clearance and renal function was studied in 22 patients with various degrees of renal functional impairment and in four normal volunteers. Clearance of vancomycin and creatinine were highly correlated (r = 0.92) among 17 persons not on dialysis. In five dialysis patients vancomycin clearance averaged 0.086 mL/min . kg of body weight (+/- SEM = 0.025). These relations enabled us to construct a nomogram for vancomycin dosage adjustment (based on a mean steady-state serum vancomycin concentration of 15 micrograms/mL) in patients with various degrees of renal functional impairment.
The Use of Pelvic Ultrasonography in the Evaluation of Adolescents With Pelvic Inflammatory Disease

• To evaluate the use of pelvic ultrasonography in the diagnosis and management of female adolescents with pelvic inflammatory disease (PID), sonograms of 60 patients with PID were compared with those of 40 age-matched controls. Sonograms were evaluated for adnexal volume, adnexal adherence, uterine size, and the presence of cul-de-sac fluid. Eleven (19.3%) of the 57 patients with PID, in whom adequate sonograms were obtained, had tubo-ovarian abscesses; in seven of these patients, the abscesses were diagnosed ultrasonographically before suspected clinically. Even in those patients without tubo-ovarian abscesses, the mean (±SD) adnexal volume in the PID group was significantly larger than that of the control group (11.0±6.8 cm3vs 5.2± 2.7 cm,3respectively). Adnexal adherence, uterine size, and the presence of cul-de-sac fluid were not useful in differentiating patients with PID from normal controls. Pelvic ultrasonography can be a useful adjunct in the diagnosis and management of PID in adolescents and may, in some instances, provide diagnoses in the abscence of clinical findings. (AJDC1987;141:1235-1238)
Does the choice between fixed price and make whole call provisions reflect differential agency costs

Abstract Bonds with either fixed price or make whole call provisions allow for the efficient recontracting of claims, but they differ in terms of their ability to mitigate debt agency costs. Controlling for the influence of bondholder-shareholder conflicts on both the level of covenant protection and selection of a particular type of call provision, we show that firms select call provisions with greater sensitivity to changes in the option-free value of the bond when agency problems are more severe. Our findings are consistent with the Barnea, Haugen and Senbet (1980) theorem that firms select fixed price callable debt to mitigate bondholder-shareholder conflicts.
WHOLESALE DEMAND FOR USDA QUALITY GRADED BOXED BEEF AND EFFECTS OF SEASONALITY

This study estimates wholesale demand for pork, chicken, and quality differentiated beef. We estimate meat retailer own- and cross-price demand elasticities for USDA Choice and Select boxed beef. Results indicate that meat retailers have more elastic demand for lower quality graded beef. Retail beef price has a strong positive relationship with Choice and Select boxed beef demand, and a strong negative relationship with wholesale pork and chicken demand. Seasonal analysis reveals demand for both beef quality grades becomes highly price inelastic during the summer months. The two beef quality grades are substitutes during the winter; however, Select beef is not a substitute for Choice beef in the spring and summer.
Task-based End-to-end Model Learning in Stochastic Optimization

With the increasing popularity of machine learning techniques, it has become common to see prediction algorithms operating within some larger process. However, the criteria by which we train these algorithms often differ from the ultimate criteria on which we evaluate them. This paper proposes an end-to-end approach for learning probabilistic machine learning models in a manner that directly captures the ultimate task-based objective for which they will be used, within the context of stochastic programming. We present three experimental evaluations of the proposed approach: a classical inventory stock problem, a real-world electrical grid scheduling task, and a real-world energy storage arbitrage task. We show that the proposed approach can outperform both traditional modeling and purely black-box policy optimization approaches in these applications.
Ultraviolet Hyperspectral Interferometric Microscopy

We present ultraviolet hyperspectral interferometric microscopy, a method that provides molecular information based on absorption and dispersion properties of biological samples, with subcellular resolution, in the ultraviolet region of the spectrum.
Motivating Supplier Social Responsibility Under Incomplete Visibility

Problem definition: We examine how a profit-driven firm (she) can motivate better social responsibility (SR) practices by a supplier (he) when these practices cannot be perfectly observed by the fi...
Financial Heterogeneity and the Investment Channel of Monetary Policy

We study the role of financial frictions and firm heterogeneity in determining the investment channel of monetary policy. Empirically, we find that firms with low default risk—those with low debt burdens and high “distance to default”— are the most responsive to monetary shocks. We interpret these findings using a heterogeneous firm New Keynesian model with default risk. In our model, low‐risk firms are more responsive to monetary shocks because they face a flatter marginal cost curve for financing investment. The aggregate effect of monetary policy may therefore depend on the distribution of default risk, which varies over time.
Chemopreventative celecoxib fails to prevent schwannoma formation or sensorineural hearing loss in genetically engineered murine model of neurofibromatosis type 2.

// Benjamin M. Wahle 1, 2 , Eric T. Hawley 1 , Yongzheng He 1 , Abbi E. Smith 1 , Jin Yuan 1 , Andi R. Masters 3 , David R. Jones 3 , Jeffrey R. Gehlhausen 1 , Su-Jung Park 1 , Simon J. Conway 1 , D. Wade Clapp 1 and Charles W. Yates 1, 2 1 Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA 2 Department of Otolaryngology/Head and Neck Surgery, Indiana University School of Medicine, Indianapolis, Indiana, USA 3 Clinical Pharmacology Analytical Core, Indiana University Simon Cancer Center, Indianapolis, Indiana, USA Correspondence to: D. Wade Clapp, email: dclapp@iu.edu Charles W. Yates, email: cwyates@iupui.edu Keywords: neurofibromatosis type 2; vestibular schwannoma; cyclooxygenase 2; non-steroidal anti-inflammatory agents; transgenic mice Abbreviations: COX-2 (cyclooxygenase-2), NSAID (nonsteroidal antiinflamatory drug) Received: March 31, 2017 Accepted: October 02, 2017 Published: October 24, 2017 ABSTRACT Mutations in the tumor suppressor gene NF2 lead to Neurofibromatosis type 2 (NF2), a tumor predisposition syndrome characterized by the development of schwannomas, including bilateral vestibular schwannomas with complete penetrance. Recent work has implicated the importance of COX-2 in schwannoma growth. Using a genetically engineered murine model of NF2, we demonstrate that selective inhibition of COX-2 with celecoxib fails to prevent the spontaneous development of schwannomas or sensorineural hearing loss in vivo , despite elevated expression levels of COX-2 in Nf2 -deficient tumor tissue. These results suggest that COX-2 is nonessential to schwannomagenesis and that the proposed tumor suppressive effects of NSAIDs on schwannomas may occur through COX-2 independent mechanisms.
Name Disambiguation in Anonymized Graphs using Network Embedding

In real-world, our DNA is unique but many people share names. This phenomenon often causes erroneous aggregation of documents of multiple persons who are namesake of one another. Such mistakes deteriorate the performance of document retrieval, web search, and more seriously, cause improper attribution of credit or blame in digital forensic. To resolve this issue, the name disambiguation task is designed which aims to partition the documents associated with a name reference such that each partition contains documents pertaining to a unique real-life person. Existing solutions to this task substantially rely on feature engineering, such as biographical feature extraction, or construction of auxiliary features from Wikipedia. However, for many scenarios, such features may be costly to obtain or unavailable due to the risk of privacy violation. In this work, we propose a novel name disambiguation method. Our proposed method is non-intrusive of privacy because instead of using attributes pertaining to a real-life person, our method leverages only relational data in the form of anonymized graphs. In the methodological aspect, the proposed method uses a novel representation learning model to embed each document in a low dimensional vector space where name disambiguation can be solved by a hierarchical agglomerative clustering algorithm. Our experimental results demonstrate that the proposed method is significantly better than the existing name disambiguation methods working in a similar setting.
ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information

Object detection in wide area motion imagery (WAMI) has drawn the attention of the computer vision research community for a number of years. WAMI proposes a number of unique challenges including extremely small object sizes, both sparse and densely-packed objects, and extremely large search spaces (large video frames). Nearly all state-of-the-art methods in WAMI object detection report that appearance-based classifiers fail in this challenging data and instead rely almost entirely on motion information in the form of background subtraction or frame-differencing. In this work, we experimentally verify the failure of appearance-based classifiers in WAMI, such as Faster R-CNN and a heatmap-based fully convolutional neural network (CNN), and propose a novel two-stage spatio-temporal CNN which effectively and efficiently combines both appearance and motion information to significantly surpass the state-of-the-art in WAMI object detection. To reduce the large search space, the first stage (ClusterNet) takes in a set of extremely large video frames, combines the motion and appearance information within the convolutional architecture, and proposes regions of objects of interest (ROOBI). These ROOBI can contain from one to clusters of several hundred objects due to the large video frame size and varying object density in WAMI. The second stage (FoveaNet) then estimates the centroid location of all objects in that given ROOBI simultaneously via heatmap estimation. The proposed method exceeds state-of-the-art results on the WPAFB 2009 dataset by 5-16% for moving objects and nearly 50% for stopped objects, as well as being the first proposed method in wide area motion imagery to detect completely stationary objects.
A Note on the Isomorphism Problem for Monomial Digraphs

Let p be a prime e be a positive integer, q=pe, and let Fq denote the finite field of q elements. Let m,n, 1≤m,n≤q−1, be integers. The monomial digraph D=D(q;m,n) is defined as follows: the vertex set of D is Fq2, and ((x1,x2),(y1,y2)) is an arc in D if x2+y2=x1my1n. In this note we study the question of isomorphism of monomial digraphs D(q;m1,n1) and D(q;m2,n2). Several necessary conditions and several sufficient conditions for the isomorphism are found. We conjecture that one simple sufficient condition is also a necessary one.
The Impact of a Surprise Donation Ask

Abstract Individuals frequently exploit “flexibility” built into decision environments to give less. They use uncertainty to justify options benefiting themselves over others, they avoid information that may encourage them to give, and they avoid the ask itself. In this paper, we examine whether a reluctance to give may arise even when such explicit flexibility is absent. We investigate whether merely alerting individuals to an upcoming prosocial ask — that is neither avoided nor occurs in an environment with flexibility — results in reduced prosocial behavior. That is, we investigate whether individuals use time to quickly find ways to decline prosocial asks and thus whether surprising individuals with prosocial asks increases compliance. Results from a field study and complementary online studies provide a clear answer: yes.
Next generation aircraft design considering airline operations and economics

Traditional approaches to design and optimization of a new system often use a system-centric objective and do not take into consideration how the operator will use this new system alongside other existing systems. When the new system design is incorporated into the broader group of systems, the performance of the operator-level objective can be sub-optimal due to the unmodeled interaction between the new system and the other systems. Among the few available references that describe attempts to address this disconnect, most follow an MDO (Multidisciplinary Design Optimization)-motivated sequential decomposition approach of first designing a very good system and then providing this system to the operator who, decides the best way to use this new system along with the existing systems. This paper addresses this issue by including aircraft design, airline operations, and revenue management "subspaces"; and presents an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem rather than the traditional approach described above. The monolithic approach makes the problem an expensive Mixed Integer Non-Linear Programming problem, which are extremely difficult to solve. To address the problem, we use a recently developed optimization framework that simultaneously solves the subspaces to capture the "synergy" in the problem that the previous decomposition approaches did not exploit, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. This approach solves an 11-route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. Simultaneously solving the subspaces leads to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach.
Reynolds-Stress Budgets in an Impinging Shock-Wave/Boundary-Layer Interaction

Wall-resolved large-eddy simulations of an impinging shock-wave/boundary-layer interaction (SBLI) are performed to investigate the evolution of Reynolds stresses. After an assessment of accuracy by...
Next-Generation Sequencing to Detect Deletion of RB1 and ERBB4 Genes in Chromophobe Renal Cell Carcinoma: A Potential Role in Distinguishing Chromophobe Renal Cell Carcinoma from Renal Oncocytoma.

Overlapping morphologic, immunohistochemical, and ultrastructural features make it difficult to diagnose chromophobe renal cell carcinoma (ChRCC) and renal oncocytoma (RO). Because ChRCC is a malignant tumor, whereas RO is a tumor with benign behavior, it is important to distinguish these two entities. We aimed to identify genetic markers that distinguish ChRCC from RO by using next-generation sequencing (NGS). NGS for hotspot mutations or gene copy number changes was performed on 12 renal neoplasms, including seven ChRCC and five RO cases. Matched normal tissues from the same patients were used to exclude germline variants. Rare hotspot mutations were found in cancer-critical genes ( TP53 and PIK3CA ) in ChRCC but not RO. The NGS gene copy number analysis revealed multiple abnormalities. The two most common deletions were tumor-suppressor genes RB1 and ERBB4 in ChRCC but not RO. Fluorescence in situ hybridization was performed on 65 cases (ChRCC, n = 33; RO, n = 32) to verify hemizygous deletion of RB1 (17/33, 52%) or ERBB4 (11/33, 33%) in ChRCC, but not in RO (0/32, 0%). In total, ChRCCs (23/33, 70%) carry either a hemizygous deletion of RB1 or ERBB4 . The combined use of RB1 and ERBB4 fluorescence in situ hybridization to detect deletion of these genes may offer a highly sensitive and specific assay to distinguish ChRCC from RO.
Polariton chemistry: controlling molecular dynamics with optical cavities

Molecular polaritons are the optical excitations which emerge when molecular transitions interact strongly with confined electromagnetic fields. Increasing interest in the hybrid molecular-photonic materials that host these excitations stems from recent observations of their novel and tunable chemistry. Some of the remarkable functionalities exhibited by polaritons include the ability to induce long-range excitation energy transfer, enhance charge conductivity, and inhibit or accelerate chemical reactions. In this review, we explain the effective theories of molecular polaritons which form a basis for the interpretation and guidance of experiments at the strong coupling limit. The theoretical discussion is illustrated with the analysis of innovative applications of strongly coupled molecular-photonic systems to chemical phenomena of fundamental importance to future technologies.
Transport Costs and Rural Development

Innovations that reduce costs of transport from rural locations may also reduce transport costs to rural areas. As transport costs fall, producers can afford to concentrate and achieve economies of scale. This paper explains an initially negative, but ultimately positive, relationship between reductions in transport costs and rural develop- ment. A two-region general equilibrium model with firm and worker spatial mobility highlights the firm and household location implications of costly transport-service use by both industry and agriculture in the context of scale economies and product differentiation. The computable general equilibrium model is initialized and verified with a bi-regional social accounting matrix and then used for simulations. Changes in relative transport costs are shown to affect relative regional wage rates, thus also determining the location of "production-cost-oriented" firms.
Sequential Maximum Margin Classifiers for Partially Labeled Data

In many real-world applications, data is not collected as one batch, but sequentially over time, and often it is not possible or desirable to wait until the data is completely gathered before analyzing it. Thus, we propose a framework to sequentially update a maximum margin classifier by taking advantage of the Maximum Entropy Discrimination principle. Our maximum margin classifier allows for a kernel representation to represent large numbers of features and can also be regularized with respect to a smooth sub-manifold, allowing it to incorporate unlabeled observations. We compare the performance of our classifier to its non-sequential equivalents in both simulated and real datasets.
The phonetics of register in Takhian Thong Chong

The Chong language uses a combination of different acoustic correlates to distinguish among its four contrastive registers (phonation types). Electroglottographic (EGG) and acoustic data were examined from original fieldwork on the Takhian Thong dialect. EGG data shows high open quotient (OQ) values for the breathy register, low OQ values for the tense register, intermediate OQ values for the modal register, and rapidly changing high to low OQ values for the breathy-tense register. Acoustic correlates indicate that H1-A3 best distinguishes between breathy and non-breathy phonation, but measures like H1-H2 and pitch are necessary to discriminate between tense and non-tense phonation. A comparison of spectral tilt and OQ measures shows the greatest correlation between OQ and H1-H2, suggesting that changes in the relative amplitude of frequencies in the upper spectrum are not directly related to changes in the open period of the glottal cycle. OQ is best correlated with changes in the degree of glottal tension.
S&P 500 Index‐Futures Price Jumps and Macroeconomic News

This study examines the influence of macroeconomic news on price discontinuities in the S&P 500 index futures. Results document a strong association between macro news and price jumps. Over three-fourths of the price jumps between 8:30 am and 8:35 am and over three-fifths of the jumps between 10:00 am and 10:05 am are related to news released at 8:30 am and 10:30 am, respectively. Notably, among several types of news releases considered, Non-farm Payroll and Consumer Confidence are found to be significantly related to price jumps. Our findings also provide insights into the speed of news absorption and the influence of alternative trading platforms on the jump return behavior. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:980–1001, 2014
Single Image Reflection Separation with Perceptual Losses

We present an approach to separating reflection from a single image. The approach uses a fully convolutional network trained end-to-end with losses that exploit low-level and high-level image information. Our loss function includes two perceptual losses: a feature loss from a visual perception network, and an adversarial loss that encodes characteristics of images in the transmission layers. We also propose a novel exclusion loss that enforces pixel-level layer separation. We create a dataset of real-world images with reflection and corresponding ground-truth transmission layers for quantitative evaluation and model training. We validate our method through comprehensive quantitative experiments and show that our approach outperforms state-of-the-art reflection removal methods in PSNR, SSIM, and perceptual user study. We also extend our method to two other image enhancement tasks to demonstrate the generality of our approach.
Poor Sleep and Obesity: Concurrent Epidemics in Adolescent Youth

Poor sleep and obesity are both extraordinarily common in the US adolescent population and often occur simultaneously. This review explores the links between obesity and sleep, outlining what is known about the relationships between sleep characteristics, obesity, and cardiometabolic risk factors in youth. Sleep duration is less than optimal in teens, and decreases as age increases. This is detrimental to overall well-being and is associated with obesity in children, adolescents, and young adults. Accordingly, inadequate sleep duration is associated with poor diet quality, decreased insulin sensitivity, hyperglycemia, and prevalent cardiometabolic risk factors. Evidence suggests that poor sleep quality and altered circadian timing characterized by a preferred later sleep onset, known as “adolescent chronotype,” contributes to shortened sleep duration. Obstructive sleep apnea (OSA) occurs more frequently among youth with obesity, and is associated with autonomic nervous system activity promoting higher blood pressure, increased markers of cardiovascular disease risk, and insulin resistance. While there is a clear association between OSA and type 2 diabetes in adults, whether or not this association is prevalent in youth is unclear at this time. Interventions to improve both sleep duration and quality, and obesity in adolescents are scarce and more evidence is needed to determine if such interventions can improve obesity-related health outcomes.
Author-based analysis of conference versus journal publication in computer science

Conference publications in computer science (CS) have attracted scholarly attention due to their unique status as a main research outlet, unlike other science fields where journals are dominantly used for communicating research findings. One frequent research question has been how different conference and journal publications are, considering an article as a unit of analysis. This study takes an author‐based approach to analyze the publishing patterns of 517,763 scholars who have ever published both in CS conferences and journals for the last 57 years, as recorded in DBLP. The analysis shows that the majority of CS scholars tend to make their scholarly debut, publish more articles, and collaborate with more coauthors in conferences than in journals. Importantly, conference articles seem to serve as a distinct channel of scholarly communication, not a mere preceding step to journal publications: coauthors and title words of authors across conferences and journals tend not to overlap much. This study corroborates findings of previous studies on this topic from a distinctive perspective and suggests that conference authorship in CS calls for more special attention from scholars and administrators outside CS who have focused on journal publications to mine authorship data and evaluate scholarly performance.
What Happened: Financial Factors in the Great Recession

Abstract At the onset of the recent global financial crisis, the workhorse macroeconomic models assumed frictionless financial markets. These frameworks were thus not able to anticipate the crisis, nor to analyze how the disruption of credit markets changed what initially appeared like a mild downturn into the Great Recession. Since that time, an explosion of both theoretical and empirical research has investigated how the financial crisis emerged and how it was transmitted to the real sector. The goal of this paper is to describe what we have learned from this new research and how it can be used to understand what happened during the Great Recession. In the process, we also present some new empirical work. We argue that a complete description of the Great Recession must take account of the financial distress facing both households and banks and, as the crisis unfolded, nonfinancial firms as well. Exploiting both panel data and time series methods, we analyze the contribution of the house price decline, v...
Time-lagged Ordered Lasso for network inference

Accurate gene regulatory networks can be used to explain the emergence of different phenotypes, disease mechanisms, and other biological functions. Many methods have been proposed to infer networks from gene expression data but have been hampered by problems such as low sample size, inaccurate constraints, and incomplete characterizations of regulatory dynamics. Since expression regulation is dynamic, time-course data can be used to infer causality, but these datasets tend to be short or sparsely sampled. In addition, temporal methods typically assume that the expression of a gene at a time point depends on the expression of other genes at only the immediately preceding time point, while other methods include additional time points without any constraints to account for their temporal distance. These limitations can contribute to inaccurate networks with many missing and anomalous links. We adapted the time-lagged Ordered Lasso, a regularized regression method with temporal monotonicity constraints, for de novo reconstruction. We also developed a semi-supervised method that embeds prior network information into the Ordered Lasso to discover novel regulatory dependencies in existing pathways. R code is available at https://github.com/pn51/laggedOrderedLassoNetwork . We evaluated these approaches on simulated data for a repressilator, time-course data from past DREAM challenges, and a HeLa cell cycle dataset to show that they can produce accurate networks subject to the dynamics and assumptions of the time-lagged Ordered Lasso regression.
Differential HDAC6 Activity Modulates Ciliogenesis and Subsequent Mechanosensing of Endothelial Cells Derived from Pluripotent Stem Cells

Summary The role of primary cilia in mechanosensation is essential in endothelial cell (EC) shear responsiveness. Here, we find that venous, capillary, and progenitor ECs respond to shear stress in vitro in a cilia-dependent manner. We then demonstrate that primary cilia assembly in human induced pluripotent stem cell (hiPSC)-derived ECs varies between different cell lines with marginal influence of differentiation protocol. hiPSC-derived ECs lacking cilia do not align to shear stress, lack stress fiber assembly, have uncoordinated migration during wound closure in vitro, and have aberrant calcium influx upon shear exposure. Transcriptional analysis reveals variation in regulatory genes involved in ciliogenesis among different hiPSC-derived ECs. Moreover, inhibition of histone deacetylase 6 (HDAC6) activity in hiPSC-ECs lacking cilia rescues cilia formation and restores mechanical sensing. Taken together, these results show the importance of primary cilia in hiPSC-EC mechano-responsiveness and its modulation through HDAC6 activity varies among hiPSC-ECs.
A multiscale neural network based on hierarchical nested bases

In recent years, deep learning has led to impressive results in many fields. In this paper, we introduce a multiscale artificial neural network for high-dimensional nonlinear maps based on the idea of hierarchical nested bases in the fast multipole method and the $$\mathcal {H}^2$$ -matrices. This approach allows us to efficiently approximate discretized nonlinear maps arising from partial differential equations or integral equations. It also naturally extends our recent work based on the generalization of hierarchical matrices (Fan et al. arXiv:1807.01883 ), but with a reduced number of parameters. In particular, the number of parameters of the neural network grows linearly with the dimension of the parameter space of the discretized PDE. We demonstrate the properties of the architecture by approximating the solution maps of nonlinear Schrodinger equation, the radiative transfer equation and the Kohn–Sham map.
Social Cohesion in Autonomous Driving

Autonomous cars can perform poorly for many reasons. They may have perception issues, incorrect dynamics models, be unaware of obscure rules of human traffic systems, or follow certain rules too conservatively. Regardless of the exact failure mode of the car, often human drivers around the car are behaving correctly. For example, even if the car does not know that it should pull over when an ambulance races by, other humans on the road will know and will pull over. We propose to make socially cohesive cars that leverage the behavior of nearby human drivers to act in ways that are safer and more socially acceptable. The simple intuition behind our algorithm is that if all the humans are consistently behaving in a particular way, then the autonomous car probably should too. We analyze the performance of our algorithm in a variety of scenarios and conduct a user study to assess people's attitudes towards socially cohesive cars. We find that people are surprisingly tolerant of mistakes that cohesive cars might make in order to get the benefits of driving in a car with a safer, or even just more socially acceptable behavior.
A Single Mechanism of Biogenesis, Initiated and Directed by PIWI Proteins, Explains piRNA Production in Most Animals.

Summary In animals, PIWI-interacting RNAs (piRNAs) guide PIWI proteins to silence transposons and regulate gene expression. The mechanisms for making piRNAs have been proposed to differ among cell types, tissues, and animals. Our data instead suggest a single model that explains piRNA production in most animals. piRNAs initiate piRNA production by guiding PIWI proteins to slice precursor transcripts. Next, PIWI proteins direct the stepwise fragmentation of the sliced precursor transcripts, yielding tail-to-head strings of phased precursor piRNAs (pre-piRNAs). Our analyses detect evidence for this piRNA biogenesis strategy across an evolutionarily broad range of animals, including humans. Thus, PIWI proteins initiate and sustain piRNA biogenesis by the same mechanism in species whose last common ancestor predates the branching of most animal lineages. The unified model places PIWI-clade Argonautes at the center of piRNA biology and suggests that the ancestral animal—the Urmetazoan—used PIWI proteins both to generate piRNA guides and to execute piRNA function.
Thermal conductivity reduction by acoustic Mie resonance in nanoparticles

We evaluate the impact of acoustic Mie resonance in nanoparticles on the thermal conductivity of semiconductor and polymer composites. By appropriately choosing the bulk modulus and density, and selecting the size of the nanoparticle to align the Mie resonances with the dominant portion of the thermal conductivity spectrum, we show that large reductions in thermal conductivity are achievable with a dilute concentration of nanoparticles. This can be useful for enhancing ZT for thermoelectric applications, since a dilute loading of particles will minimally impact electrical conductivity. We apply the model to explain the steep reduction in thermal conductivity observed previously in semiconductor alloys and then show that acoustic Mie resonance in polysiloxane nanoparticles can be used to reduce the thermal conductivity of an amorphous polymer by nearly a factor of two.We evaluate the impact of acoustic Mie resonance in nanoparticles on the thermal conductivity of semiconductor and polymer composites. By appropriately choosing the bulk modulus and density, and selecting the size of the nanoparticle to align the Mie resonances with the dominant portion of the thermal conductivity spectrum, we show that large reductions in thermal conductivity are achievable with a dilute concentration of nanoparticles. This can be useful for enhancing ZT for thermoelectric applications, since a dilute loading of particles will minimally impact electrical conductivity. We apply the model to explain the steep reduction in thermal conductivity observed previously in semiconductor alloys and then show that acoustic Mie resonance in polysiloxane nanoparticles can be used to reduce the thermal conductivity of an amorphous polymer by nearly a factor of two.
Insider trading ahead of cyber breach announcements

Abstract Stock market reactions to cybersecurity breach announcements are generally negative. We find significant evidence of opportunistic insider trading, with insiders saving an average of $35,009 due to timely selling in the three months before the announcement of a cybersecurity breach. Late filing violations by insiders are more likely to occur near the announcement of a cyber breach. The bulk of opportunistic trading tends to occur 55–72 days before the public announcement. The results lend support to the U.S. Security and Exchange Commission’s recently announced goal of tightening restrictions on insider trading ahead of cyber breach announcements.
Noise at sea: Characterization of extended shift noise exposures among U.S. Navy aircraft carrier support personnel.

The purpose of this investigation was to characterize 12-hr on-duty, 12-hr off-duty, and 24-hr noise exposures among U.S. Navy aircraft carrier support personnel. Noise dosimetry samples were colle...
A Research Framework for Business Models: What Is Common Among Fast Fashion, E-Tailing, and Ride Sharing?

Every firm has a business model, which is the collection of strategic decisions that determine how the firm generates a sustainable enterprise through the creation of enough value (its supply model...
Scientific visualization

Using visual display methods to examine scientific data and information is a time-honored technique (Tufte, 1983). Electronic or digital scientific visualization is a younger field, 10-20 years old. Scientific visualization applies techniques from the convergent fields of computer animation, computer graphics, image processing, computer vision (q.v.), computer-aided design and manufacturing (CAD/CAM--q.v.), signal processing, and user interface (q.v.) design studies (MacCormick et al., 1987).
Queries revisited

We begin with a brief tutorial on the problem of learning a finite concept class over a finite domain using membership queries and/or equivalence queries. We then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension, the sample exclusion dimension, the Vapnik-Chervonenkis dimension, the abstract identification dimension, and the general dimension.
Adversarial Variational Bayes Methods for Tweedie Compound Poisson Mixed Models

The Tweedie Compound Poisson-Gamma model is routinely used for modeling non-negative continuous data with a discrete probability mass at zero. Mixed models with random effects account for the covariance structure related to the grouping hierarchy in the data. An important application of Tweedie mixed models is pricing the insurance policies, e.g. car insurance. However, the intractable likelihood function, the unknown variance function, and the hierarchical structure of mixed effects have presented considerable challenges for drawing inferences on Tweedie. In this study, we tackle the Bayesian Tweedie mixed-effects models via variational inference approaches. In particular, we empower the posterior approximation by implicit models trained in an adversarial setting. To reduce the variance of gradients, we reparameterize random effects, and integrate out one local latent variable of Tweedie. We also employ a flexible hyper prior to ensure the richness of the approximation. Our method is evaluated on both simulated and real-world data. Results show that the proposed method has smaller estimation bias on the random effects compared to traditional inference methods including MCMC; it also achieves a state-of-the-art predictive performance, meanwhile offering a richer estimation of the variance function.
A sparse random projection-based test for overall qualitative treatment effects

In contrast to the classical “one-size-fits-all” approach, precision medicine proposes the customization of individualized treatment regimes to account for patients’ heterogeneity in response to tr...
The Role of Strategic Uncertainty in Area-wide Pest Management Decisions of Florida Citrus Growers

We elicit a measure of strategic uncertainty from growers by using an experimental game grounded on the theory of global games. This allows us to achieve the following: propose a mechanism for measuring strategic uncertainty aversion; compare growers’ risk aversion to their strategic uncertainty aversion; explore how growers’ strategic uncertainty aversion is affected by changes in group size and coordination requirement; and relate a strategic uncertainty aversion measure to growers’ actual decisions to participate in an area-wide pest management program. In our experimental setting, we found that when the coordination requirement for a successful outcome is low, most growers see the strategic uncertainty posed by human interaction as more favorable in terms of expected payoffs relative to a game against nature. In contrast, when the coordination requirement is high, most growers expect lower payoffs and choose to coordinate less. We also found evidence that growers’ strong beliefs about neighbors not coordinating negatively impacted their choices to coordinate. Our measure of strategic uncertainty was also found to influence the likelihood of growers to actually coordinate sprays. Our findings help explain why participation in area-wide pest management to control the vector of citrus greening across Florida has not been as widespread as expected; the strategic uncertainty involved in relying on neighbors has made many growers choose self-reliance in spraying despite the lower payoff.
Embedding Content or Interring Copyright: Does the Internet Need the “Server Rule”?

The “server rule” holds that online displays or performances of copyrighted content accomplished through “in-line” or “framing” hyperlinks do not trigger the exclusive rights of public display or performance unless the linker also possesses a copy of the underlying work. As a result, the rule shields a vast array of online activities from claims of direct copyright infringement, effectively exempting those activities from the reach of the Copyright Act. While the server rule has enjoyed relatively consistent adherence since its adoption in 2007, some courts have recently suggested a departure from that precedent, noting the doctrinal and statutory inconsistencies underlying it. Authors and copyright owners have long lamented that the server rule’s immunization of certain online activities eviscerates their ability to control how their works are disseminated on the Internet. But many Internet users and commercial actors have incorporated the rule’s liability shield into their expectations about how the Internet does (and should) function. Accordingly, while authors and copyright owners foresee improved prospects for remuneration, many commentators and advocacy groups have expressed concerns regarding the recent judicial doubt about the validity of the server rule. They contend that, without the server rule, the Internet would cease to function as it does today. However, these concerns overlook the applicable defenses—in particular, the defenses of safe harbor under § 512 of the Digital Millennium Copyright Act and express license—which, we expect, would take on a more significant role in a post- server rule world. In this Article, we explore the likely effect of the potential reversal of the server rule, taking into account these defenses. We conclude that the principal difference between copyright law with and without the server rule comes down to the author’s ability to obtain the removal of links to infringing content, and to authorize embedding of content from a source to which the public had lawful access. Moreover, while the reversal of the server rule may interrupt a handful of online services that rely entirely on the unauthorized appropriation of copyrighted works, most online practices would likely continue unaltered in the post-server rule world.
Maternal choline supplementation mitigates alcohol-induced fetal cranio-facial abnormalities detected using an ultrasonographic examination in a sheep model

Abstract Early detection of prenatal alcohol exposure is critical for designing and testing effectiveness of interventional therapeutics. Choline supplementation during and after prenatal alcohol exposure has shown promising benefits in improving outcomes in rodent models and clinical studies. A sheep model of first trimester-equivalent binge alcohol exposure was used in this study to model the dose of maternal choline supplementation used in an ongoing prospective clinical trial involving pregnancies at risk for FASD. Pregnant sheep were randomly assigned to six groups: Saline + Placebo control, Saline + Choline, binge Alcohol + Placebo (light binging), binge Alcohol + Choline, Heavy binge Alcohol + Placebo (heavy binging), and Heavy binge Alcohol + Choline. Ewes received intravenous alcohol or saline on three consecutive days per week from gestation day (GD) 4–41 to mimic a first trimester-equivalent weekend binge-drinking paradigm. Choline (10 mg/kg in the daily food ration) was administered from GD 4 until term. On GD 76, 11 fetal ultrasonographic measurements were collected transabdominally. Heavy binge alcohol exposure reduced fetal Frontothalamic Distance (FTD), Mean Orbital Diameter (MOD), and Mean Lens Diameter (MLD), and increased Interorbital Distance (IOD) and Thalamic Width (TW). Maternal choline supplementation mitigated most of these alcohol-induced effects. Maternal choline supplementation also improved overall fetal femur and humerus bone lengths, compared to their respective placebo groups. Taken together, these results indicate a potential dose-dependent effect that could impact the sensitivity of these ultrasonographic measures in predicting prenatal alcohol exposure. This is the first study in the sheep model to identify biomarkers of prenatal alcohol exposure in utero with ultrasound and co-administration of maternal choline supplementation.
On the Role of a Market Maker in Networked Cournot Competition

We study Cournot competition among firms in a networked marketplace that is centrally managed by a market maker. In particular, we study a situation in which a market maker facilitates trade betwee...