cssi/SciSciGPT-SciSciNet huggingface dataset:
Stat3 in osteocytes mediates osteogenic response to loading

Abstract Signal transducer and activator of transcription 3 (Stat3) is a member of the Stat family of proteins involved in signaling in many different cell types, including osteocytes. Osteocytes are considered major mechanosensing cells in bone due to their intricate dendritic networks able to sense changes in physical force and to orchestrate the response of osteoclasts and osteoblasts. We examined the role of Stat3 in osteocytes by generating mice lacking Stat3 in these cells using the Dmp-1(8kb)-Cre promoter (Stat3cKO mice). Compared to age-matched littermate controls, Stat3cKO mice of either sex (18 weeks old) exhibit reduced bone formation indices, decreased osteoblasts and increased osteoclasts, and altered material properties, without detectable changes in bone mineral density (BMD) or content of either trabecular or cortical bone. In addition, Stat3cKO mice of either sex show significantly decreased load-induced bone formation. Furthermore, pharmacologic inhibition of Stat3 in osteocytes in vitro with WP1066 blocked the increase in cytosolic calcium induced by ATP, a mediator of the cellular responses to sheer stress. WP1066 also increased reactive oxygen species (ROS) production in cultured MLO-Y4 osteocytes. These data demonstrate that Stat3 is a critical mediator of mechanical signals received by osteocytes and suggest that osteocytic Stat3 is a potential therapeutic target to stimulate bone anabolism.
Dropping Pixels for Adversarial Robustness

Deep neural networks are vulnerable against adversarial examples. In this paper, we propose to train and test the networks with randomly subsampled images with high drop rates. We show that this approach significantly improves robustness against adversarial examples in all cases of bounded L0, L2 and L∞ perturbations, while reducing the standard accuracy by a small value. We argue that subsampling pixels can be thought to provide a set of robust features for the input image and, thus, improves robustness without performing adversarial training.
Effects of Five Silvicultural Treatments on Loblolly Pine in the Georgia Piedmont at Age 20

Age 20data from a designed experir7zental study installed on 24plorsat one location in the Lower Piediizont in Jones County, Georgia, tilere used to evaluate the effect of six silviculrural treatments on survival, growth, and yield of cutover site-pi-epared lobloll~1 pine plantations in the Georgia Piedmont. The following silvicultural treatnzeizts were included in the study: ( I ) clearcut only, (2 ) clearcut with all residual treesgreater than I inch dbh removed by chairzsn~~, (3) slzear and chop, (4) shear, rootrake, burn, and disk, and (5) shear, rootrake, burn, disk, fertilize, and herbicide. Treatment sigizificanrly affected all tree aizd stand characteristics at age 20. The slzear, rootrake, burn, disk, fertilize, and herbicide rrearnlent ranked best in all categories with the exception ofsuwival aizd basal area, which were Izighestfor the shear, rootrake, burn, and disk treatmenr. The shear and chop trearrnent was 1701 sigizifcanrly lower rlzan the ~izost intensive treatment in any measured category. Sourh. J . Appl. For. 28(1):35-40.
Cube is a Strict Local Maximizer for the Illumination Number

It was conjectured by Levi, Hadwiger, Gohberg and Markus that the boundary of any convex body in $${\mathbb R}^n$$ can be illuminated by at most $$2^n$$ light sources, and, moreover, $$2^n-1$$ light sources suffice unless the body is a parallelotope. We show that if a convex body is close to the cube in the Banach–Mazur metric, and it is not a parallelotope, then indeed $$2^n-1$$ light sources suffice to illuminate its boundary. Equivalently, any convex body sufficiently close to the cube, but not isometric to it, can be covered by $$2^n-1$$ smaller homothetic copies of itself.
Effects of VR Gaming and Game Genre on Player Experience

With the increasing availability of modern virtual reality (VR) headsets, the use and applications of VR technology for gaming purposes have become more pervasive than ever. Despite the growing popularity of VR gaming, user studies into how it might affect the player experience (PX) during the gameplay are scarce. Accordingly, the current study investigated the effects of VR gaming and game genre on PX. We compared PX metrics for two game genres, strategy (more interactive) and racing (less interactive), across two gaming platforms, VR and traditional desktop gaming. Participants were randomly assigned to one of the gaming platforms, played both a strategy and racing game on their corresponding platform, and provided PX ratings. Results revealed that, regardless of the game genre, participants in the VR gaming condition experienced a greater level of sense of presence than did those in the desktop gaming condition. That said, results showed that the two gaming platforms did not significantly differ from one another in PX ratings. As for the effect of game genre, participants provided greater PX ratings for the strategy game than for the racing game, regardless of whether the game was played on a VR headset or desktop computer. Collectively, these results indicate that although VR gaming affords a greater sense of presence in the game environment, this increase in presence does not seem to translate into a more satisfactory PX when playing either a strategy or racing game.
Percutaneous Nephrolithotomy in the 80 Years of Age and Older Population.

Abstract Objective To evaluate feasibility of percutaneous nephrolithotomy (PCNL) for complex nephrolithiasis in patients 80 years of age and older compared to younger individuals. Methods From an institutional IRB-approved database, 1,647 patients were identified who underwent PCNL from 1999 to 2019. Patients were stratified by age: group 1 (20-59), group 2 (60-79), and group 3 (>80). Statistics were performed using chi-square and ANOVA to compare outcomes. Results Of the 1,647 patients, median age was 46, 66, and 83, respectively (P Conclusion PCNL is feasible in the extremely elderly; however with a higher rate of complications and longer hospitalizations. No long-term sequelae or deaths in the 80 and older cohort were seen. This study allows us to appropriately counsel older patients on a realistic postoperative course and supports use of PCNL as the best means of long-term survival.
Molecular phenotyping using networks, diffusion, and topology: soft tissue sarcoma

Many biological datasets are high-dimensional yet manifest an underlying order. In this paper, we describe an unsupervised data analysis methodology that operates in the setting of a multivariate dataset and a network which expresses influence between the variables of the given set. The technique involves network geometry employing the Wasserstein distance, global spectral analysis in the form of diffusion maps, and topological data analysis using the Mapper algorithm. The prototypical application is to gene expression profiles obtained from RNA-Seq experiments on a collection of tissue samples, considering only genes whose protein products participate in a known pathway or network of interest. Employing the technique, we discern several coherent states or signatures displayed by the gene expression profiles of the sarcomas in the Cancer Genome Atlas along the TP53 (p53) signaling network. The signatures substantially recover the leiomyosarcoma, dedifferentiated liposarcoma (DDLPS), and synovial sarcoma histological subtype diagnoses, and they also include a new signature defined by activation and inactivation of about a dozen genes, including activation of serine endopeptidase inhibitor SERPINE1 and inactivation of TP53-family tumor suppressor gene TP73.
Improving Prediction Accuracy in Building Performance Models Using Generative Adversarial Networks (GANs)

Building performance discrepancies between building design and operation are one of the causes that lead many new designs fail to achieve their goals and objectives. A main factor contributing to the discrepancy is occupant behaviors. Occupants responding to a new design are influenced by several factors. Existing building performance models (BPMs) ignore or partially address those factors (called contextual factors) while developing BPMs. To potentially reduce the discrepancies and improve the prediction accuracy of BPMs, this paper proposes a computational framework for learning mixture models by using Generative Adversarial Networks (GANs) that appropriately combining existing BPMs with knowledge on occupant behaviors to contextual factors in new designs. Immersive virtual environments (IVEs) experiments are used to acquire data on such behaviors. Performance targets are used to guide appropriate combination of existing BPMs with knowledge on occupant behaviors. The resulting model obtained is called an augmented BPM. Two different experiments related to occupants lighting behaviors are shown as case study. The results reveal that augmented BPMs significantly outperformed existing BPMs with respect to achieving specified performance targets. The case study confirmed the potential of the computational framework for improving prediction accuracy of BPMs during design.
The Arab inequality puzzle: the role of income sources in Egypt and Tunisia

Egypt and Tunisia are perceived to have high levels of inequality, yet based on standard measures, inequality in these two countries is not unusually high. In this study we explore a different dime...
Topologically-Guided Color Image Enhancement

Enhancement is an important step in post-processing digital images for personal use, in medical imaging, and for object recognition. Most existing manual techniques rely on region selection, similarity, and/or thresholding for editing, never really considering the topological structure of the image. In this paper, we leverage the contour tree to extract a hierarchical representation of the topology of an image. We propose 4 topology-aware transfer functions for editing features of the image using local topological properties, instead of global image properties. Finally, we evaluate our approach with grayscale and color images.
Negative frequency‐dependent selection maintains coexisting genotypes during fluctuating selection

Natural environments are rarely static; rather selection can fluctuate on timescales ranging from hours to centuries. However, it is unclear how adaptation to fluctuating environments differs from adaptation to constant environments at the genetic level. For bacteria, one key axis of environmental variation is selection for planktonic or biofilm modes of growth. We conducted an evolution experiment with Burkholderia cenocepacia, comparing the evolutionary dynamics of populations evolving under constant selection for either biofilm formation or planktonic growth with populations in which selection fluctuated between the two environments on a weekly basis. Populations evolved in the fluctuating environment shared many of the same genetic targets of selection as those evolved in constant biofilm selection, but were genetically distinct from the constant planktonic populations. In the fluctuating environment, mutations in the biofilm-regulating genes wspA and rpfR rose to high frequency in all replicate populations. A mutation in wspA first rose rapidly and nearly fixed during the initial biofilm phase but was subsequently displaced by a collection of rpfR mutants upon the shift to the planktonic phase. The wspA and rpfR genotypes coexisted via negative frequency-dependent selection around an equilibrium frequency that shifted between the environments. The maintenance of coexisting genotypes in the fluctuating environment was unexpected. Under temporally fluctuating environments, coexistence of two genotypes is only predicted under a narrow range of conditions, but the frequency-dependent interactions we observed provide a mechanism that can increase the likelihood of coexistence in fluctuating environments.
Rules without Commitment: Reputation and Incentives

This paper studies the optimal design of rules in a dynamic model when there is a time inconsistency problem and uncertainty about whether the policy maker can commit to follow the rule ex post. The policy maker can either be a commitment type, which can always commit to follow rules, or an optimizing type, which sequentially decides whether to follow rules or not. This type is unobservable to private agents, who learn about it through the actions of the policy maker. Higher beliefs that the policy maker is the commitment type (the policy maker's reputation) help promote good behavior by private agents. We show that in a large class of economies, preserving uncertainty about the policy maker's type is preferable from an ex-ante perspective. If the initial reputation is not too high, the optimal rule is the strictest one that is incentive compatible for the optimizing type. We show that reputational considerations imply that the optimal rule is more lenient than the one that would arise in a static environment. Moreover, opaque rules are preferable to transparent ones if reputation is high enough. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Transcription factor NF-κB in a basal metazoan, the sponge, has conserved and unique sequences, activities, and regulation

Herein, we characterize transcription factor NF-κB from the demosponge Amphimedon queenslandica (Aq). Aq-NF-κB is most similar to NF-κB p100/p105 among vertebrate proteins, with an N-terminal DNA-binding domain, a C-terminal Ankyrin (ANK) repeat domain, and a DNA binding-site profile akin to human NF-κB proteins. Like mammalian NF-κB p100, C-terminal truncation allows nuclear translocation of Aq-NF-κB and increases its transcriptional activation activity. Expression of IκB kinases (IKKs) induces proteasome-dependent C-terminal processing of Aq-NF-κB in human cells, and processing requires C-terminal serines in Aq-NF-κB. Unlike NF-κB p100, C-terminal sequences of Aq-NF-κB do not inhibit its DNA-binding activity. Tissue of a black encrusting demosponge contains NF-κB site DNA-binding activity, as well as nuclear and processed NF-κB. Treatment of sponge tissue with LPS increases both DNA-binding activity and processing of NF-κB. A. queenslandica transcriptomes contain homologs to upstream NF-κB pathway components. This is first functional characterization of NF-κB in sponge, the most basal multicellular animal.
Effects Of Ultraviolet-a And Riboflavin On The Interaction Of Collagen And Proteoglycans During Corneal Cross-linking

Corneal cross-linking using riboflavin and ultraviolet-A (RFUVA) is a clinical treatment targeting the stroma in progressive keratoconus. The stroma contains keratocan, lumican, mimecan, and decorin, core proteins of major proteoglycans (PGs) that bind collagen fibrils, playing important roles in stromal transparency. Here, a model reaction system using purified, non-glycosylated PG core proteins in solution in vitro has been compared with reactions inside an intact cornea, ex vivo, revealing effects of RFUVA on interactions between PGs and collagen cross-linking. Irradiation with UVA and riboflavin cross-links collagen α and β chains into larger polymers. In addition, RFUVA cross-links PG core proteins, forming higher molecular weight polymers. When collagen type I is mixed with individual purified, non-glycosylated PG core proteins in solution in vitro and subjected to RFUVA, both keratocan and lumican strongly inhibit collagen cross-linking. However, mimecan and decorin do not inhibit but instead form cross-links with collagen, forming new high molecular weight polymers. In contrast, corneal glycosaminoglycans, keratan sulfate and chondroitin sulfate, in isolation from their core proteins, are not cross-linked by RFUVA and do not form cross-links with collagen. Significantly, when RFUVA is conducted on intact corneas ex vivo, both keratocan and lumican, in their natively glycosylated form, do form cross-links with collagen. Thus, RFUVA causes cross-linking of collagen molecules among themselves and PG core proteins among themselves, together with limited linkages between collagen and keratocan, lumican, mimecan, and decorin. RFUVA as a diagnostic tool reveals that keratocan and lumican core proteins interact with collagen very differently than do mimecan and decorin.
Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms

Abstract Media platforms, technological systems, and search engines act as conduits and gatekeepers for all kinds of information. They often influence, reflect, and reinforce gender stereotypes, in...
Mucinous cystic neoplasms of the liver: presence of biliary communication.

A 35-year-old woman was referred for a symptomatic liver mass. Diagnostic workup detected a septated cyst located centrally in the liver measuring 10 × 7 cm. The cyst had gradually increased in size from previous studies with new intrahepatic biliary dilation. Due to concern for malignancy and symptomatic presentation of the patient, a partial central hepatectomy was performed. Pathology revealed a smooth-walled, multiloculated cyst lined with mucinous epithelium and ovarian-type stroma. The diagnosis of low-grade mucinous cystic neoplasm of the liver (MCN-L) was made. Characteristics of MCN-L have not been elucidated due to its rarity.
Hubble Ultraviolet Spectroscopy of Jupiter Trojans

We present the first ultraviolet spectra of Jupiter Trojans. These observations were carried out using the Space Telescope Imaging Spectrograph on the Hubble Space Telescope and cover the wavelength range 200–550 nm at low resolution. The targets include objects from both of the Trojan color subpopulations (less-red and red). We do not observe any discernible absorption features in these spectra. Comparisons of the averaged UV spectra of less-red and red targets show that the subpopulations are spectrally distinct in the UV. Less-red objects display a steep UV slope and a rollover at around 450 nm to a shallower visible slope, whereas red objects show the opposite trend. Laboratory spectra of irradiated ices with and without H_2S exhibit distinct UV absorption features; consequently, the featureless spectra observed here suggest H_2S alone is not responsible for the observed color bimodality of Trojans, as has been previously hypothesized. We propose some possible explanations for the observed UV-visible spectra, including complex organics, space weathering of iron-bearing silicates, and masked features due to previous cometary activity.
Nonlinear System Identification via Tensor Completion

Function approximation from input and output data pairs constitutes a fundamental problem in supervised learning. Deep neural networks are currently the most popular method for learning to mimic the input-output relationship of a general nonlinear system, as they have proven to be very effective in approximating complex highly nonlinear functions. In this work, we show that identifying a general nonlinear function y = ƒ(x1,…,xN) from input-output examples can be formulated as a tensor completion problem and under certain conditions provably correct nonlinear system identification is possible. Specifically, we model the interactions between the N input variables and the scalar output of a system by a single N-way tensor, and setup a weighted low-rank tensor completion problem with smoothness regularization which we tackle using a block coordinate descent algorithm. We extend our method to the multi-output setting and the case of partially observed data, which cannot be readily handled by neural networks. Finally, we demonstrate the effectiveness of the approach using several regression tasks including some standard benchmarks and a challenging student grade prediction task.
Ensemble Learning of Partition Functions for the Prediction of Thermodynamic Properties of Adsorption in Metal–Organic and Covalent Organic Frameworks

We develop several ensemble learning models to predict the partition function of fluids adsorbed in nanoporous materials. The partition functions so obtained allow rapid access to all thermodynamic...
Tractable Unordered 3-CNF Games

The classic TQBF problem can be viewed as a game in which two players alternate turns assigning truth values to a CNF formula’s variables in a prescribed order, and the winner is determined by whether the CNF gets satisfied. The complexity of deciding which player has a winning strategy in this game is well-understood: it is \(\textsf {NL}\)-complete for 2-CNFs and \(\textsf {PSPACE}\)-complete for 3-CNFs.
The past and future of global river ice

More than one-third of Earth’s landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic1,2, ecologic3,4, climatic5 and socio-economic6–8 functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world1, the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures9,10, were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-°C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 ± 0.08 days per 1-°C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984–2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080–2100: compared with 2009–2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century. An analysis based on Landsat imagery shows that the extent of river ice has declined extensively over past decades and that this trend will continue under future global warming.
A Queueing Model and Analysis for Autonomous Vehicles on Highways

We investigate the effects of autonomous vehicles (AVs) on highway congestion. AVs have the potential to significantly reduce highway congestion because they can maintain smaller intervehicle gaps ...
Ellipticity of Bartnik Boundary Data for Stationary Vacuum Spacetimes

We establish a moduli space $${\mathbb {E}}$$ of stationary vacuum metrics in a spacetime, and set up a well-defined boundary map $$\Pi $$ in $${\mathbb {E}}$$, assigning a metric class with its Bartnik boundary data. Furthermore, we prove the boundary map $$\Pi $$ is Fredholm by showing that the stationary vacuum equations (combined with proper gauge terms) and the Bartnik boundary conditions form an elliptic boundary value problem. As an application, we show that the Bartnik boundary data near the standard flat Bartnik data admits a unique (up to diffeomorphisms) stationary vacuum extension locally.
A Demonstration of Quantum Key Distribution with Entangled Photons for the Undergraduate Laboratory

Now that fundamental quantum principles of indeterminacy and measurement have become the basis of new technologies that provide secrecy between two communicating parties, there is a need to provide teaching laboratories that illustrate how these technologies work. In this article, we describe a laboratory exercise in which students perform quantum key distribution with single photons, and see how the secrecy of the communication is ensured by the principles of quantum superposition and state projection. We used a table-top apparatus, similar to those used in correlated-photon undergraduate laboratories, to implement the Bennett-Brassard-84 protocol with polarization-entangled photons. Our experiment shows how the communication between two parties is disrupted by an eavesdropper. We use a simple quartz plate to mimic how an eavesdropper intercepts, measures, and resends the photons used in the communication, and we analyze the state of the light to show how the eavesdropper changes it.
Gapsplit: efficient random sampling for non-convex constraint-based models.

SUMMARY Gapsplit generates random samples from convex and non-convex constraint-based models by targeting under-sampled regions of the solution space. Gapsplit provides uniform coverage of linear, mixed-integer and general non-linear models. AVAILABILITY AND IMPLEMENTATION Python and Matlab source code are freely available at http://jensenlab.net/tools. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Combinatorial Constructions of Weight Bases: The Gelfand-Tsetlin Basis

This work is part of a project on weight bases for the irreducible representations of semisimple Lie algebras with respect to which the representation matrices of the Chevalley generators are given by explicit formulas. In the case of $\mathfrak{ sl}$$_n$, the celebrated Gelfand-Tsetlin basis is the only such basis known. Using the setup of supporting graphs developed by Donnelly, we present a new interpretation and a simple combinatorial proof of the Gelfand-Tsetlin formulas based on a rational function identity (all the known proofs use more sophisticated algebraic tools). A constructive approach to the Gelfand-Tsetlin formulas is then given, based on a simple algorithm for solving certain equations on the lattice of semistandard Young tableaux. This algorithm also implies certain extremal properties of the Gelfand-Tsetlin basis.
Ethical and Legal Aspects of Ambient Intelligence in Hospitals.

Ambient intelligence in hospitals is an emerging form of technology characterized by a constant awareness of activity in designated physical spaces and of the use of that awareness to assist health care workers such as physicians and nurses in delivering quality care. Recently, advances in artificial intelligence (AI) and, in particular, computer vision, the domain of AI focused on machine interpretation of visual data, have propelled broad classes of ambient intelligence applications based on continuous video capture. One important goal is for computer vision-driven ambient intelligence to serve as a constant and fatigue-free observer at the patient bedside, monitoring for deviations from intended bedside practices, such as reliable hand hygiene and central line insertions. While early studies took place in single patient rooms, more recent work has demonstrated ambient intelligence systems that can detect patient mobilization activities across 7 rooms in an ICU ward and detect hand hygiene activity across 2 wards in 2 hospitals. As computer vision–driven ambient intelligence accelerates toward a future when its capabilities will most likely be widely adopted in hospitals, it also raises new ethical and legal questions. Although some of these concerns are familiar from other health surveillance technologies, what is distinct about ambient intelligence is that the technology not only captures video data as many surveillance systems do but does so by targeting the physical spaces where sensitive patient care activities take place, and furthermore interprets the video such that the behaviors of patients, health care workers, and visitors may be constantly analyzed. This Viewpoint focuses on 3 specific concerns: (1) privacy and reidentification risk, (2) consent, and (3) liability.
Concurrent Flow-Based Localization and Mapping in Time-Invariant Flow Fields

We present the concept of concurrent flow-based localization and mapping (FLAM) for autonomous field robots navigating within background flows. Different from the classical simultaneous localization and mapping (SLAM) problem, where the robot interacts with discrete features, FLAM utilizes the continuous flow fields as navigation references for mobile robots and provides flow field mapping capability with in-situ flow velocity observations. This approach is of importance to underwater vehicles in mid-depth oceans or aerial vehicles in GPS-denied atmospheric circulations. This article introduces the formulation of FLAM as a full SLAM solution motivated by the feature-based GraphSLAM framework. The performance of FLAM was demonstrated through simulation within artificial flow fields that represent typical geophysical circulation phenomena: a steady single-gyre flow field and a double-gyre flow field with unsteady turbulent perturbations. The results indicate that FLAM provides significant improvements in the robots’ localization accuracy and a consistent approximation of the background flow field. It is also shown that FLAM leads to smooth robot trajectory estimates.
Self-Reported Omega-3 Supplement Use Moderates the Association between Age and Exercising Cerebral Blood Flow Velocity in Older Adults

Cerebral blood flow (CBF) decreases across the lifespan, and chronic conditions such as dementia and stroke accelerate this decline. Impaired CBF results in reduced delivery of oxygen and nutrients, which can damage the brain over time. Thus, there is a need to identify lifestyle interventions, including diet and exercise, to maintain CBF with aging and in the presence of chronic disease. In the present study, we used transcranial Doppler ultrasound to record middle cerebral artery velocity (MCAv), a surrogate measure of CBF, during moderate-intensity exercise in sedentary, cognitively normal older adults (n = 90). A multiple linear regression model (F(4, 85) = 3.21, p = 0.02) showed that self-reported omega-3 supplement use significantly moderated the association between age and mean exercising MCAv in these individuals (p = 0.01). Older age was associated with lower exercising MCAv in the group not taking omega-3 supplements, while exercising MCAv showed no decline with increasing age in the group who reported omega-3 supplement use. These findings suggest omega-3 supplementation may have an important role in the preservation of CBF with aging.
Study of Eggers’ Method for the Determination of Wavemaking Resistance

Abstract : One of the assumptions in Eggers' method for the determination of the wave resistance of a ship form from transverse surface-profile measurements is that a 'near-field' term in the expression for the surface disturbance may be neglected. Application to a family of vertical struts, with drafts varying from shiplike dimensions to infinity, indicates that, by measuring the transverse profiles at many sections at least one model length downstream, the error due to this assumption can be reduced to less than one percent for forms of shiplike draft, but may be as large as 5 percent for drafts of the order of magnitude of the model length. A procedure for reducing these errors further is suggested. (Author)
Beaconism and the Trumpian Metamorphosis of Chinese Liberal Intellectuals

This article examines the puzzling phenomenon that many Chinese liberal intellectuals fervently idolize Donald Trump and embrace the alt-right ideologies he epitomizes. Rejecting ‘pure tactic’ and ...
Safe Policy Synthesis in Multi-Agent POMDPs via Discrete-Time Barrier Functions

A multi-agent partially observable Markov decision process (MPOMDP) is a modeling paradigm used for high-level planning of heterogeneous autonomous agents subject to uncertainty and partial observation. Despite their modeling efficiency, MPOMDPs have not received significant attention in safety-critical settings. In this paper, we use barrier functions to design policies for MPOMDPs that ensure safety. Notably, our method does not rely on discretizations of the belief space, or finite memory. To this end, we formulate sufficient and necessary conditions for the safety of a given set based on discrete-time barrier functions (DTBFs) and we demonstrate that our formulation also allows for Boolean compositions of DTBFs for representing more complicated safe sets. We show that the proposed method can be implemented online by a sequence of one-step greedy algorithms as a standalone safe controller or as a safety-filter given a nominal planning policy. We illustrate the efficiency of the proposed methodology based on DTBFs using a high-fidelity simulation of heterogeneous robots.
Rotation and outbursts of comet P/Schwassmann-Wachmann 1

The paper examines rotation and outbursts of comet P/Schwassmann-Wachmann 1. The observations of the P/Schwassmann-Wachmann 1 show this comet to flare above its quiescent level from before perihelion q=5.5 AU, to after aphelion Q of about 7AU. Cometary 'afternoon' activity suggests counterclockwise rotation of aphelion pole as seen near lambda=100 deg; outburst dates were derived from observed coma diameters, and the rotation was found to be direct with pole near lambda=280 deg. Usually one large area of the comet is active during one opposition, although two were observed concurrently in four very active oppositions; old active areas persist near the East limb of the comet and new areas resist development toward the West limb.
Stacked Garbling for Disjunctive Zero-Knowledge Proofs

Zero-knowledge (ZK) proofs (ZKP) have received wide attention, focusing on non-interactivity, short proof size, and fast verification time. We focus on the fastest total proof time, in particular for large Boolean circuits. Under this metric, Garbled Circuit (GC)-based ZKP (Jawurek et al., [JKO], CCS 2013) remained the state-of-the-art technique due to the low-constant linear scaling of computing the garbling.
Sparse domination of singular Radon transform

Abstract The purpose of this paper is to study the sparse bound of the operator of the form f ↦ ψ ( x ) ∫ f ( γ t ( x ) ) K ( t ) d t , where γ t ( x ) is a C ∞ function defined on a neighborhood of the origin in ( x , t ) ∈ R n × R k , satisfying γ 0 ( x ) ≡ x , ψ is a C ∞ cut-off function supported on a small neighborhood of 0 ∈ R n and K is a Calderon-Zygmund kernel supported on a small neighborhood of 0 ∈ R k . Christ, Nagel, Stein and Wainger gave conditions on γ under which T : L p ↦ L p ( 1 p ∞ ) is bounded. Under the these same conditions, we prove sparse bounds for T, which strengthens their result. As a corollary, we derive weighted norm estimates for such operators.
Structural color in Junonia butterflies evolves by tuning scale lamina thickness

From iridescent blues to vibrant purples, many butterflies display dazzling ‘structural colors’ created not by pigments but by microscopic structures that interfere with light. For instance, the scales that coat their wings can contain thin films of chitin, the substance that normally makes the external skeleton of insects. In slim layers, however, chitin can also scatter light to produce color, the way that oil can create iridescence at the surface of water. The thickness of the film, which is encoded by the genes of the butterfly, determines what color will be produced. Yet, little is known about how common thin films are in butterflies, exactly how genetic information codes for them, and how their thickness and the colors they produce can evolve. To investigate, Thayer et al. used a technique called Helium Ion Microscopy and examined the wings of ten related species of butterflies, showing that thin film structures were present across this sample. However, the different species have evolved many different structural colors over the past millions of years by changing the thickness of the films. Next, Thayer et al. showed that this evolution could be reproduced at a faster pace in the laboratory using common buckeye butterflies. These insects mostly have brown wings, but they can have specks of blue created by thin film structures. Individuals with more blue on their wings were mated and over the course of a year, the thickness of the film structures increased by 74%, leading to shiny blue butterflies. Deleting a gene called optix from the insects also led to blue wings. Optix was already known to control the patterns of pigments in butterflies, but it now appears that it controls structural colors as well. From solar panels to new fabrics, microscopic structures that can scatter light are useful in a variety of industries. Understanding how these elements exist and evolve in organisms may help to better design them for human purposes.
Advances in Bayesian Probabilistic Modeling for Industrial Applications

Industrial applications frequently pose a notorious challenge for state-of-the-art methods in the contexts of optimization, designing experiments and modeling unknown physical response. This proble...
Joint Optimization of Sampling Patterns and Deep Priors for Improved Parallel MRI

Multichannel imaging techniques are widely used in MRI to reduce the scan time. These schemes typically perform un-dersampled acquisition and utilize compressed-sensing based regularized reconstruction algorithms. Model-based deep learning (MoDL) frameworks are now emerging as powerful alternatives to compressed sensing, with significantly improved image quality. In this work, we investigate the impact of sampling patterns on the quality of the image recovered using the MoDL algorithm. We introduce a scheme to jointly optimize the sampling pattern and the reconstruction network parameters in MoDL for parallel MRI. The improved decoupling of the network parameters from the sampling patterns offered by the MoDL scheme translates to improved optimization and thus improved performance. Preliminary experimental results demonstrate that the proposed joint opti-mization framework significantly improves the image quality.
Crumples as a Generic Stress-Focusing Instability in Confined Sheets

Thin elastic solids are easily deformed into a myriad of three-dimensional shapes, which may contain sharp localized structures as in a crumpled candy wrapper, or have smooth and diffuse features like the undulating edge of a flower. Anticipating and controlling these morphologies is crucial to a variety of applications involving textiles, synthetic skins, and inflatable structures. Here we show that a "wrinkle-to-crumple" transition, previously observed in specific settings, is a ubiquitous response for confined sheets. This unified picture is borne out of a suite of model experiments on polymer films confined to liquid interfaces with spherical, hyperbolic, and cylindrical geometries, which are complemented by experiments on macroscopic membranes inflated with gas. We use measurements across this wide range of geometries, boundary conditions, and lengthscales to quantify several robust morphological features of the crumpled phase, and we build an empirical phase diagram for crumple formation that disentangles the competing effects of curvature and compression. Our results suggest that crumples are a generic microstructure that emerge at large curvatures due to a competition of elastic and substrate energies.
Clock Feedthrough in CMOS Analog Transmission Gate Switches

An analysis of clock feedthrough in CMOS analog transmission gate (TG) switches is presented in this paper. The mechanism for clock feedthrough and a related model of a transmission gate switch are established in the current-voltage domain. A region map is developed for the TG switch during the period when both devices are turned off. The region map is further divided into zones. From these region and zone maps, the sign and relative magnitude of the clock feedthrough noise can be efficiently estimated for different signal levels. Placing the input voltage near half of the power supply voltage is a useful technique for minimizing clock feedthrough noise. A model of clock feedthrough noise as compared with SPICE simulations exhibits less than 3% error.
Attention Variation and Welfare: Theory and Evidence from a Tax Salience Experiment

This article shows that accounting for variation in mistakes can be crucial for welfare analysis. Focusing on consumer under-reaction to not-fully-salient sales taxes, we show theoretically that the efficiency costs of taxation are amplified by differences in under-reaction across individuals and across tax rates. To empirically assess the importance of these issues, we implement an online shopping experiment in which 2,998 consumers purchase common household products, facing tax rates that vary in size and salience. We replicate prior findings that, on average, consumers under-react to non-salient sales taxes—consumers in our study react to existing sales taxes as if they were only 25% of their size. However, we find significant individual differences in this under-reaction, and accounting for this heterogeneity increases the efficiency cost of taxation estimates by at least 200%. Tripling existing sales tax rates nearly doubles consumers’ attention to taxes, and accounting for this endogeneity increases efficiency cost estimates by 336%. Our results provide new insights into the mechanisms and determinants of boundedly rational processing of not-fully-salient incentives, and our general approach provides a framework for robust behavioural welfare analysis.
AReN: assured ReLU NN architecture for model predictive control of LTI systems

In this paper, we consider the problem of automatically designing a Rectified Linear Unit (ReLU) Neural Network (NN) architecture that is sufficient to implement the optimal Model Predictive Control (MPC) strategy for an LTI system with quadratic cost. Specifically, we propose AReN, an algorithm to generate Assured ReLU Architectures. AReN takes as input an LTI system with quadratic cost specification, and outputs a ReLU NN architecture with the assurance that there exist network weights that exactly implement the associated MPC controller. AReN thus offers new insight into the design of ReLU NN architectures for the control of LTI systems: instead of training a heuristically chosen NN architecture on data - or iterating over many architectures until a suitable one is found - AReN can suggest an adequate NN architecture before training begins. While several previous works were inspired by the fact that ReLU NN controllers and optimal MPC controllers are both Continuous, Piecewise-Linear (CPWL) functions, exploiting this similarity to design NN architectures with correctness guarantees has remained elusive. AReN achieves this using two novel features. First, we reinterpret a recent result about the implementation of CPWL functions via ReLU NNs to show that a CPWL function may be implemented by a ReLU architecture that is determined by the number of distinct affine regions in the function. Second, we show that we can efficiently over-approximate the number of affine regions in the optimal MPC controller without solving the MPC problem exactly. Together, these results connect the MPC problem to a ReLU NN implementation without explicitly solving the MPC: the result is a NN architecture that has the assurance that it can implement the MPC controller. We show through numerical results the effectiveness of AReN in designing an NN architecture.
Human Settlements as Sociotechnical-Economic Processes

In recent times, increasing numbers of people in the world have migrated to the cities. There they have become a part of a sociotechnical-economic system from which they must obtain goods and services with which to live, and to which they should contribute their skills and efforts. Many of the goods and services require much money and time to be made available and require joint funding and public approval to be initiated.
Firms' Voluntary Recognition of Stock‐Based Compensation Expense

We investigate factors associated with firms' decisions in 2002 and early 2003 to recognize stock-based compensation expense under Statement of Financial Accounting Standards (SFAS) No. 123. We find that the likelihood of SFAS 123 expense recognition is significantly related to the extent of the firm's participation in capital markets, the private incentives of top management and members of the board of directors, the level of information asymmetry, and political costs. Although recognizing firms have significantly smaller SFAS 123 expense, we find no significant incremental relation between recognition likelihood and SFAS 123 expense magnitude after controlling for other factors that we expect explain the recognition decision. We also find positive and significant announcement returns for earlier announcing firms, particularly those stating that increased earnings transparency motivates their decision.
Chapter 7 – Drug Metabolism

Publisher Summary This chapter discusses the analytical methods in drug metabolism and pathways for drug deactivation and elimination. Drug metabolism studies are essential for evaluating the potential safety and efficacy of drugs. The chapter illustrates the various reactions involved in the biotransformation of drugs. Only small quantities of drugs are required to elicit the appropriate response. The four principal steps in drug metabolism studies are isolation (extraction), separation (chromatography), identification (spectrometry), and quantification of the metabolites. Detection systems are sensitive enough to allow the isolation and identification of submicrogram quantities of metabolites. The function of drug metabolism is to convert a molecule that can cross biological membranes into one that is cleared in the urine. Each progressive metabolic step usually reduces the lipophilicity of the compound. Drug metabolism principally causes pharmacological deactivation of a drug by altering its structure so that it no longer interacts appropriately with the target receptor and becomes more susceptible to excretion. Drug metabolism can have a variety of profound effects on drugs.
Edgeworth Price Cycles: Evidence from the Toronto Retail Gasoline Market

In this article, I exploit a new station-level, twelve-hourly price dataset to examine the strong retail price cycles in the Toronto gasoline market. The cycles are visually similar to the theoretical Edgeworth Cycles of Maskin & Tirole [1988]: strongly asymmetric, tall, rapid, and highly synchronous across stations. I test a series of predictions made by the theory about how firm behaviors would differentially evolve over the path of a cycle. The evidence is consistent with the existence of Edgeworth Cycles and inconsistent with competing hypotheses. One finding is that smaller firms are more likely than larger firms to initiate rounds of price undercutting but the reverse is true for rounds of price increases. While the cycles are an interesting phenomenon for study in their own right, the evidence has important implications for understanding market power in both cycling and non-cycling gasoline markets.
Depletion of the AD Risk Gene SORL1 Selectively Impairs Neuronal Endosomal Traffic Independent of Amyloidogenic APP Processing

SORL1/SORLA is a sorting receptor involved in retromer-related endosomal traffic and an Alzheimer's disease (AD) risk gene. Using CRISPR-Cas9, we deplete SORL1 in hiPSCs to ask if loss of SORL1 contributes to AD pathogenesis by endosome dysfunction. SORL1-deficient hiPSC neurons show early endosome enlargement, a hallmark cytopathology of AD. There is no effect of SORL1 depletion on endosome size in hiPSC microglia, suggesting a selective effect on neuronal endosomal trafficking. We validate defects in neuronal endosomal traffic by showing altered localization of amyloid precursor protein (APP) in early endosomes, a site of APP cleavage by the β-secretase (BACE). Inhibition of BACE does not rescue endosome enlargement in SORL1-deficient neurons, suggesting that this phenotype is independent of amyloidogenic APP processing. Our data, together with recent findings, underscore how sporadic AD pathways regulating endosomal trafficking and autosomal-dominant AD pathways regulating APP cleavage independently converge on the defining cytopathology of AD.