cssi/SciSciGPT-SciSciNet huggingface dataset:
Securing Legacy Mobile Medical Devices

Millions of people use mobile medical devices—more every day. But our understanding of device security and privacy for such devices is incomplete. Man-in-the-middle attacks can be performed on typical Bluetooth-enabled mobile medical devices, compromising the privacy and safety of patients. In response, we developed the Personal Security Device, a portable device to improve security for mobile medical systems. This device requires no changes to either the medical device or its monitoring software, and offers protection for millions of existing devices. We evaluate our defense mechanism to show that it adds insignificant overhead and analyze its robustness against various attacks.
Condensation of fermion pairs in a domain

We consider a gas of fermions at zero temperature and low density, interacting via a microscopic two-body potential which admits a bound state. The particles are confined to a domain with Dirichlet boundary conditions. Starting from the microscopic BCS theory, we derive an effective macroscopic Gross–Pitaevskii (GP) theory describing the condensate of fermion pairs. The GP theory also has Dirichlet boundary conditions. Along the way, we prove that the GP energy, defined with Dirichlet boundary conditions on a bounded Lipschitz domain, is continuous under interior and exterior approximations of that domain.
Performance and cost characteristics of multi-electron transfer, common ion exchange non-aqueous redox flow batteries

Abstract Non-aqueous redox flow batteries (NAqRFBs) have recently received considerable attention as promising high energy density, low cost grid-level energy storage technologies. Despite these attractive features, NAqRFBs are still at an early stage of development and innovative design techniques are necessary to improve performance and decrease costs. In this work, we investigate multi-electron transfer, common ion exchange NAqRFBs. Common ion systems decrease the supporting electrolyte requirement, which subsequently improves active material solubility and decreases electrolyte cost. Voltammetric and electrolytic techniques are used to study the electrochemical performance and chemical compatibility of model redox active materials, iron (II) tris(2,2′-bipyridine) tetrafluoroborate (Fe(bpy) 3 (BF 4 ) 2 ) and ferrocenylmethyl dimethyl ethyl ammonium tetrafluoroborate (Fc1N112-BF 4 ). These results help disentangle complex cycling behavior observed in flow cell experiments. Further, a simple techno-economic model demonstrates the cost benefits of employing common ion exchange NAqRFBs, afforded by decreasing the salt and solvent contributions to total chemical cost. This study highlights two new concepts, common ion exchange and multi-electron transfer, for NAqRFBs through a demonstration flow cell employing model active species. In addition, the compatibility analysis developed for asymmetric chemistries can apply to other promising species, including organics, metal coordination complexes (MCCs) and mixed MCC/organic systems, enabling the design of low cost NAqRFBs.
Keeping Signals Straight: How Cells Process Information and Make Decisions

As we become increasingly dependent on electronic information-processing systems at home and work, it's easy to lose sight of the fact that our very survival depends on highly complex biological information-processing systems. Each of the trillions of cells that form the human body has the ability to detect and respond to a wide range of stimuli and inputs, using an extraordinary set of signaling proteins to process this information and make decisions accordingly. Indeed, cells in all organisms rely on these signaling proteins to survive and proliferate in unpredictable and sometimes rapidly changing environments. But how exactly do these proteins relay information within cells, and how do they keep a multitude of incoming signals straight? Here, I describe recent efforts to understand the fidelity of information flow inside cells. This work is providing fundamental insight into how cells function. Additionally, it may lead to the design of novel antibiotics that disrupt the signaling of pathogenic bacteria or it could help to guide the treatment of cancer, which often involves information-processing gone awry inside human cells.
Photochemical Reactions of Carbohydrate Triflates

AbstractThe photochemical reactions of eight carbohydrate trifluoromethanesulfonates (triflates) have been investigated in methanol in the presence of potassium iodide. For those compounds which do not contain an aromatic chromophore, photolysis results in two types of reaction. One type produces deoxy sugars by replacement of the trifluoromethylsulfonyloxy (triflyloxy) group with a hydrogen atom. The second type of reaction generates partially protected sugars by replacement of the trifluoromethylsulfonyl (triflyl) group with a hydrogen atom. When the triflate being irradiated also has a protecting group containing an aromatic ring (i.e., benzyl, benzoyl, or p-tolylsulfonyl group), removal of the protecting group is the exclusive reaction pathway.
Interest rate spreads and banking system efficiency: General considerations with an application to the transition economies of Central and Eastern Europe

Abstract Low spreads between loan rates and deposit rates are indicative of a more efficient financial system. We argue that spreads are better cross country measures of banking system efficiency than the net interest margins used in previous studies. We present theoretical and empirical evidence that the spread may be a particularly good measure of efficiency, both for the transition economies and other countries. The spread is a financial intermediation measure and is highly negatively correlated with conventional measures of intermediation. Consistent with theory, the spread is negatively related to economic growth. We also find that the spread has determinants similar to other FI measures. International agencies should report spreads and put more emphasis on this measure of efficiency.
Connection tree based micro-mobility management for IP-centric mobile networks

There is on-going convergence of IP and traditional telecommunication networks (both wired and wireless). To facilitate fast handoff and real-time location tracking, and reduce the location update overhead in IP based mobile networks, hierarchical IP mobility management schemes, i.e., Mobile IP for macro-mobility (inter mobile domains) and cellular-network-optimized schemes for micro-mobility within mobile domains, are needed. In this paper, we apply the connection tree concept that was originally proposed for wireless ATM networks to IP micro-mobility management for mobile users with QoS requirements by using such new concepts as virtual multicast, virtual sender/receiver, null filter spec and dormant reservation. Our scheme enables fast and smooth handoff by localizing most of the location update related operation and pre-establishing connections to/from multiple base stations. It integrates seamlessly with such IP QoS mechanisms as RSVP, enables quick reservation restoration during handoff, and naturally supports soft handoff.
DeepQA: improving the estimation of single protein model quality with deep belief networks.

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .
International Differences in the Cost of Equity Capital: Do Legal Institutions and Securities Regulation Matter?

This paper examines international differences in firms' cost of equity capital across 40 countries. We analyze whether the effectiveness of a country's legal institutions and securities regulation is systematically related to cross-country differences in the cost of equity capital. We employ several models to estimate firms' implied or ex ante cost of capital. Our results support the conclusion that firms from countries with more extensive disclosure requirements, stronger securities regulation, and stricter enforcement mechanisms have a significantly lower cost of capital. We perform extensive sensitivity analyses to assess the potentially confounding influence of countries' long-run growth differences on our results. We also show that, consistent with theory, the cost of capital effects of strong legal institutions become substantially smaller and, in many cases, statistically insignificant as capital markets become globally more integrated.
Design of the second-generation ARIANNA ultra-high-energy neutrino detector systems

We report on the development of the seven station ARIANNA Hexagonal Radio Array neutrino detector systems in Antarctica. The primary goal of the ARIANNA project is to observe ultra-high energy (>100 PeV) cosmogenic neutrino signatures using a large array of autonomous stations each dispersed 1 km apart on the surface of the Ross Ice Shelf. Sensing radio emissions of 100 MHz to 1 GHz, each station in the array contains RF antennas, amplifiers, a 2 G-sample/s signal acquisition and trigger circuit I.C. (the “SST”), an embedded CPU, 32 GB of solid-state data storage, a 20 Ah LiFePO 4 battery with associated battery management unit, Iridium short-burst messaging satellite and long-distance WiFi communications. The new SST chip is completely synchronous, contains 4 channels of 256 samples per channel, obtains 6 orders of magnitude sample rate range up to 2 GHz acquisition speeds. It achieves 1.5 GHz bandwidth, 12 bits RMS of dynamic range, ∼1 mV RMS trigger sensitivity at >600 MHz trigger bandwidth and ps-level timing accuracy. Power is provided by the sun and LiFePO4 storage batteries, and the second-generation stations consume an average of 4W of power. The station's trigger capabilities reduce the trigger rates to a few milli-Hertz with ≤4-sigma thresholds while retaining high efficiency for neutrino signals.
In vivo delivery of transcription factors with chemically modified oligonucleotides

T based on transcription factors have the potential to revolutionize medicine, but have had limited medical impact because of delivery problems. In this presentation, we demonstrate that a delivery vehicle, termed DARTs (DNA Assembled Recombinant Transcription factors), can for the first time deliver recombinant transcription factors in vivo, and rescue mice from acute liver failure. DARTs are composed of a double stranded oligonucleotide that contain a transcription factor binding sequence, and have hydrophobic C25 alkyl chains located at their 3’ ends, which are “masked” by acid cleavable galactose residues. DARTs have a unique molecular architecture, which allows them to complex transcription factors, target hepatocytes, disrupt endosomes, and release transcription factors into hepatocytes. We show here that DARTs can deliver the transcription factor Nrf2, to the liver, enhance the transcription of Nrf2 downstream genes, and protect mice from acetaminophen induced liver injury. The DART delivery strategy has tremendous therapeutic potential given the central role of transcription factors in biology and medicine.
A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation

Branching events in phylogenetic trees reflect bifurcating and/or multifurcating speciation and splitting events. In the presence of gene flow, a phylogeny cannot be described by a tree but is instead a directed acyclic graph known as a phylogenetic network. Both phylogenetic trees and networks are typically reconstructed using computational analysis of multi-locus sequence data. The advent of high-throughput sequencing technologies has brought about two main scalability challenges: (1) dataset size in terms of the number of taxa and (2) the evolutionary divergence of the taxa in a study. The impact of both dimensions of scale on phylogenetic tree inference has been well characterized by recent studies; in contrast, the scalability limits of phylogenetic network inference methods are largely unknown. In this study, we quantify the performance of state-of-the-art phylogenetic network inference methods on large-scale datasets using empirical data sampled from natural mouse populations and a range of simulations using model phylogenies with a single reticulation. We find that, as in the case of phylogenetic tree inference, the performance of leading network inference methods is negatively impacted by both dimensions of dataset scale. In general, we found that topological accuracy degrades as the number of taxa increases; a similar effect was observed with increased sequence mutation rate. The most accurate methods were probabilistic inference methods which maximize either likelihood under coalescent-based models or pseudo-likelihood approximations to the model likelihood. The improved accuracy obtained with probabilistic inference methods comes at a computational cost in terms of runtime and main memory usage, which become prohibitive as dataset size grows past twenty-five taxa. None of the probabilistic methods completed analyses of datasets with 30 taxa or more after many weeks of CPU runtime. We conclude that the state of the art of phylogenetic network inference lags well behind the scope of current phylogenomic studies. New algorithmic development is critically needed to address this methodological gap.
Bounded topological speedups

ABSTRACTThis paper explores the range of bounded speedups in the topological category. Bounded speedups represent both a strengthening of topological speedups as first defined by the second author. and a generalization of powers of a transformation. Here we show that bounded speedups preserve the structure of two classical minimal Cantor systems. Specifically, a minimal bounded speedup of an odometer is a conjugate odometer, and a minimal bounded speedup of a primitive substitution is again a primitive substitution, though it is never conjugate to the original substitution system. Further, we give bounds on the topological entropy of bounded speedups, and in special cases, we compute the topological entropy of bounded speedups.
PROXIMAL HUMERAL FRACTURES: WHEN NOT TO PERFORM A REVERSE ARTHROPLASTY

A reverse shoulder arthroplasty has become increasingly common for the treatment of proximal humerus fractures. A reverse shoulder arthroplasty is indicated especially in older and osteopenic individuals in whom the osteopenia, fracture type or comminution precludes fixation. However, there are many other ways to treat proximal humerus fractures and many of these are appropriate for different indications. Percutaneous pinning remains an option in certain surgical neck or valgus impacted proximal humerus fractures with minimal or no comminution at the medial calcar. In general, a fracture that is amenable to open reduction and fixation should be fixed. Open reduction and internal fixation should be the gold standard treatment for three-part fractures in younger and middle-aged patients. Four-part fractures should also be fixed in younger patients. Hemiarthroplasty results are less predictable as they are very dependent on tuberosity healing. While a reverse shoulder replacement may be considered in patients with severe comorbidities, patients always have better outcomes in the setting of an appropriately reduced and stably fixed proximal humerus fracture.
NOT ALL CEMENTLESS STEMS ARE CREATED EQUAL: A SELECTION ALGORITHM

Cementless femoral components have an excellent track record that includes efficient implantation and long-term survival, thus are the predominant stem utilised in North America. Femoral component stability and resistance to subsidence are critical for osseointegration and clinical success. Implant design, surgical technique, anatomic fit, and patient characteristics, such as bone quality, can all effect initial implant stability and resistance to subsidence. Variability in stem shape and in the anatomy of the proximal femoral metaphysis has been implicated in the failure of some stem designs. Biologic fixation obtained with osseointegration of cementless implants may improve implant longevity in young, active, and obese patients. Lack of intimate fit can lead to clinical complications such as subsidence, aseptic loosening, and peri-prosthetic fracture. Currently, there are several stem designs, all of which aim to achieve maximal femoral stability and minimal subsidence and include: Fit and Fill / Double Taper Proximally Porous Coated Stems; Parallel Sided Taper Wedge or “Blade” Stems; Wagner Style Conical Shape Splined Titanium Stems; Tapered Rectangular Cross-Section Zweymuller Stem; Fully-Porous Coated Stems; Modular Proximal Sleeve Fluted Stem; Anatomic Proximally Porous Coated Stems. The majority of patients with relatively straightforward anatomy can be treated with any of the aforementioned femoral implant types. However, more complicated femoral anatomy frequently requires a particular implant type to maximise stability and promote osseointegration. Stems with femoral deformity in the meta-diaphyseal region may require a shorter stem in order to avoid an osteotomy. Distorted femoral anatomy typically seen in childhood diseases, such as dysplasia, may require a modular proximal sleeve tapered fluted stem or Wagner style cone stem to impart optimal stem anteversion separate from the native femoral neck version. The most severe forms of dysplasia may require a shortening osteotomy and subsequent distal fixation and neck version flexibility, which can be addressed with a modular proximal sleeve fluted or fully porous coated stem. A stovepipe or osteoporotic femur may require a stem that engages more distally such as a conical splined tapered stem, a fully porous coated stem or even a cemented stem to achieve adequate stability. Finally, obese patients are a particular challenge and emerging data suggests that a morphologically based parallel-sided taper wedge stems may confer greater stability and resistance to subsidence in these patients. Ultimately, an appropriate selection algorithm will facilitate an appropriate match of the patient morphology with femoral implant geometry that facilitates stable fixation and osseointegration.
Eigensystem multiscale analysis for Anderson localization in energy intervals

We present an eigensystem multiscale analysis for proving localization (pure point spectrum with exponentially decaying eigenfunctions, dynamical localization) for the Anderson model in an energy interval. In particular, it yields localization for the Anderson model in a nonempty interval at the bottom of the spectrum. This eigensystem multiscale analysis in an energy interval treats all energies of the finite volume operator at the same time, establishing level spacing and localization of eigenfunctions with eigenvalues in the energy interval in a fixed box with high probability. In contrast to the usual strategy, we do not study finite volume Green's functions. Instead, we perform a multiscale analysis based on finite volume eigensystems (eigenvalues and eigenfunctions). In any given scale we only have decay for eigenfunctions with eigenvalues in the energy interval, and no information about the other eigenfunctions. For this reason, going to a larger scale requires new arguments that were not necessary in our previous eigensystem multiscale analysis for the Anderson model at high disorder, where in a given scale we have decay for all eigenfunctions.
Using the Control Balance Theory to Explain Social Media Deviance

Online Social Media Deviance (OSMD) is one the rise; however, research in this area traditionally has lacked a strong theoretical foundation. Following calls to reveal the theoretical underpinnings of this complex phenomenon, our study examines the causes of OSMD from several novel angles not used in the literature before, including: (1) the influence of control imbalances (CIs) on deviant behavior, (2) the role of perceived accountability and deindividuation in engendering CI, (3) and the role of IT in influencing accountability and deindividuation. Using an innovative factorial survey method that enabled us to manipulate the IT artifacts for a nuanced view, we tested our model with 507 adults and found strong support for our model. The results should thus have a strong impetus not only on future SM research but also for social media (SM) designers who can use these ideas to further develop SM networks that are safe, supportive, responsible, and constructive.
Mathematical foundations for social computing

Social computing benefits from mathematical foundations, but research has barely scratched the surface.
A Rhizobiales-Specific Unipolar Polysaccharide Adhesin Contributes to Rhodopseudomonas palustris Biofilm Formation across Diverse Photoheterotrophic Conditions

Bacteria predominantly exist as members of surfaced-attached communities known as biofilms. Many bacterial species initiate biofilms and adhere to each other using cell surface adhesins. This is the case for numerous ecologically diverse Alphaprotebacteria, which use polar exopolysaccharide adhesins for cell-cell adhesion and surface attachment. Here, we show that Rhodopseudomonas palustris, a metabolically versatile member of the alphaproteobacterial order Rhizobiales, contains a functional unipolar polysaccharide (UPP) biosynthesis gene cluster. Deletion of genes predicted to be critical for UPP biosynthesis and export abolished UPP production. We also found that R. palustris uses UPP to mediate biofilm formation across diverse photoheterotrophic growth conditions, wherein light and organic substrates are used to support growth. However, UPP was less important for biofilm formation during photoautotrophy, where light and CO2 support growth, and during aerobic respiration with organic compounds. Expanding our analysis beyond R. palustris, we examined the phylogenetic distribution and genomic organization of UPP gene clusters among Rhizobiales species that inhabit diverse niches. Our analysis suggests that UPP is a conserved ancestral trait of the Rhizobiales but that it has been independently lost multiple times during the evolution of this clade, twice coinciding with adaptation to intracellular lifestyles within animal hosts. Importance Bacteria are ubiquitously found as surface-attached communities and cellular aggregates in nature. Here, we address how bacterial adhesion is coordinated in response to diverse environments using two complementary approaches. First, we examined how Rhodopseudomonas palustris, one of the most metabolically versatile organisms ever described, varies its adhesion to surfaces in response to different environmental conditions. We identified critical genes for the production of a unipolar polysaccharide (UPP) and showed that UPP is important for adhesion when light and organic substrates are used for growth. Looking beyond R. palustris, we performed the most comprehensive survey to date on the conservation of UPP biosynthesis genes among a group of closely related bacteria that occupy diverse niches. Our findings suggest that UPP is important for free-living and plant-associated lifestyles but dispensable for animal pathogens. Additionally, we propose guidelines for classifying the adhesins produced by various Alphaprotebacteria, facilitating future functional and comparative studies.
Rotor Noise Measurement Using a Directional Microphone Array

A directional array of microphones was used to measure the noise from a 40 percent scale model rotor in a large aeroacoustic wind tunnel. The development and design of this directional array is described. A design goal was that the array focus on a constant sensing area over a broad frequency range. The implementation of the array design is presented, followed by sample results for several different rotor test conditions. The directional array spectral results are compared with predictions of broadband self noise, and with total rotor noise measurements obtained from individual microphones of the array. The directional array is demonstrated to be a useful tool in examining noise source distributions.
Vacancies, unemployment, and the Phillips curve

Abstract The canonical new Keynesian Phillips curve has become a standard component of models designed for monetary policy analysis. However, in the basic new Keynesian model, there is no unemployment, all variation in labor input occurs along the intensive hours margin, and the driving variable for inflation depends on workers’ marginal rates of substitution between leisure and consumption. In this paper, we incorporate a theory of unemployment into the new Keynesian theory of inflation and empirically test its implications for inflation dynamics. We show how a traditional Phillips curve linking inflation and unemployment can be derived and how the elasticity of inflation with respect to unemployment depends on structural characteristics of the labor market such as the matching technology that pairs vacancies with unemployed workers. We estimate on US data the Phillips curve generated by the model. While we can reject the baseline new Keynesian Phillips curve in favor of the search-frictions specification, we show it is still too stylized to fully describe the dynamics of firms’ marginal costs.
A defect in holographic interpretations of tensor networks

We initiate the study of how tensor networks reproduce properties of static holographic space-times, which are not locally pure anti-de Sitter. We consider geometries that are holographically dual to ground states of defect, interface and boundary CFTs and compare them to the structure of the requisite MERA networks predicted by the theory of minimal updates. When the CFT is deformed, certain tensors require updating. On the other hand, even identical tensors can contribute differently to estimates of entanglement entropies. We interpret these facts holographically by associating tensor updates to turning on non-normalizable modes in the bulk. In passing, we also clarify and complement existing arguments in support of the theory of minimal updates, propose a novel ansatz called rayed MERA that applies to a class of generalized interface CFTs, and analyze the kinematic spaces of the thin wall and AdS3-Janus geometries.
Design and Analysis of Stability-Guaranteed PUFs

The lack of stability is one of the limitations that constrain physical unclonable function (PUF) from being put in widespread practical use. In this paper, we propose a weak PUF and a strong PUF that are both completely stable. These PUFs are called locally enhanced defectivity physical unclonable function (LEDPUF). An LEDPUF is a pure functional PUF that does not require any kinds of correction schemes as conventional parametric PUFs do. The source of randomness of an LEDPUF is extracted from locally enhance defectivity without affecting other parts of the chip. In this paper, we construct a weak LEDPUF by forming arrays of directed self-assembly random connections, and the strong LEDPUF is implemented by using the weak LEDPUF as the key of a keyed-hash message authentication code. Our simulation and statistical results show that the entropy of the weak LEDPUF bits is close to ideal, and the inter-chip Hamming distances of both weak and strong LEDPUFs are about 50%, which means that these LEDPUFs are not only stable but also unique. We develop a new unified framework for evaluating the security of PUFs, based on password security, by using information theoretic tools of guesswork. The guesswork model allows us to quantitatively compare, with a single unified metric, PUFs with varying levels of stability, bias, and available side information. In addition, it generalizes other measures to evaluate the security level, such as min-entropy and mutual information. We evaluate the guesswork-based security of some measured static random access memory and ring oscillator PUFs as an example and compare them with an LEDPUF to show that the stability has a more severe impact on the PUF security than biased responses. Furthermore, we find the guesswork of two new problems: guesswork under the probability of attack failure and the guesswork of strong PUFs that are used for authentication.
BILIARY EXCRETION OF XENOBIOTICS

Publisher Summary This chapter discusses experimental studies on biliary excretion of xenobiotics. The position of the liver is particularly advantageous for removing toxicants from the blood after its absorption by the gastrointestinal tract. Because the blood from the gastrointestinal tract passes through the liver before it reaches the general systematic circulation, theoretically, the liver can remove toxicants from the blood and prevent their distribution to other parts of the body. Differences in the rates of biliary excretion of ouabain are also observed when administered systemically and intraportally. Alterations in biliary excretion can have marked effects on the toxicity of chemicals. Many factors such as age and environment can affect the biliary excretion of xenobiotics. The use of isolated hepatocytes can be useful in delineating the cellular mechanism by which compounds enter the liver as well as aiding in deleneating the site at which alterations in hepatic excretory function occurs.
Equidistribution of Neumann data mass on triangles

In this paper we study the behaviour of the Neumann data of Dirichlet eigenfunctions on triangles. We prove that the $L^2$ norm of the (semi-classical) Neumann data on each side is equal to the length of the side divided by the area of the triangle. The novel feature of this result is that it is {\it not} an asymptotic, but an exact formula. The proof is by simple integrations by parts.
Exponential and double exponential tails for maximum of two-dimensional discrete Gaussian free field

We study the tail behavior for the maximum of discrete Gaussian free field on a 2D box with Dirichlet boundary condition after centering by its expectation. We show that it exhibits an exponential decay for the right tail and a double exponential decay for the left tail. In particular, our result implies that the variance of the maximum is of order 1, improving an \(o(\log n)\) bound by Chatterjee (Chaos, concentration, and multiple valleys, 2008) and confirming a folklore conjecture. An important ingredient for our proof is a result of Bramson and Zeitouni (Commun. Pure Appl. Math, 2010), who proved the tightness of the centered maximum together with an evaluation of the expectation up to an additive constant.
Multi-scale spectrum sensing in small-cell mm-wave cognitive wireless networks

In this paper, a multi-scale approach to spectrum sensing in cognitive cellular networks is proposed. In order to overcome the huge cost incurred in the acquisition of full network state information, a hierarchical scheme is proposed, based on which local state estimates are aggregated up the hierarchy to obtain aggregate state information at multiple scales, which are then sent back to each cell for local decision making. Thus, each cell obtains fine-grained estimates of the channel occupancies of nearby cells, but coarse-grained estimates of those of distant cells. The performance of the aggregation scheme is studied in terms of the trade-off between the throughput achievable by secondary users and the interference generated by the activity of these secondary users to primary users. In order to account for the irregular structure of interference patterns arising from path loss, shadowing, and blockages, which are especially relevant in millimeter wave networks, a greedy algorithm is proposed to find a multi-scale aggregation tree to optimize the performance. It is shown numerically that this tailored hierarchy outperforms a regular tree construction by 60%.
Experimental determination of phonon thermal conductivity and Lorenz ratio of single crystal metals: Al, Cu, and Zn

We use a magnetothermal resistance method to measure lattice thermal conductivity of pure single crystal metals over the intermediate temperature range of 5–60 K. Large transverse magnetic fields are applied to suppress electronic thermal conduction. The total thermal conductivity and the electrical conductivity are measured as functions of applied magnetic field. The lattice thermal conductivity is then extracted by extrapolating the thermal conductivity versus electrical conductivity curve at zero electrical conductivity. We used this method to experimentally measure the lattice thermal conductivity and Lorenz number in single crystal Al (100), Cu (100), and Zn (001) in the intermediate temperature range. Our results show that the measured phonon thermal conductivity versus temperature plot has a peak around ΘD/10, and the Lorenz number is found to deviate from the Sommerfeld value in the intermediate temperature range.
DECREASED RATE OF EARLY REVISION IN SENSOR-ASSISTED TKA

Total knee arthroplasty (TKA) is currently one of the most common elective surgical procedures in the United States. The increase in the proportion of younger patients in receipt of surgery, in concert with a dramatic rise in the incidence of obesity, has contributed to the on-going, exponential increase in the number of arthroplasties performed annually. Despite materials advances for implants, the U.S. revision burden has remained static for the last decade. According to the 2013 CMS MEDPAR file the typical CMS reimbursement falls far short of costs incurred by the hospital, resulting in an average net loss of revenue of $9,539; and over 90% of hospitals lose money for every revision case performed. Today, approximately 5% of all primaries performed will result in an early revision (< 3 years). In order to understand ways with which to mitigate the incidence of early revision due to mechanical complications, a multicentric group of sensor-assisted patients was follow-up out to 3 years. In this study, 278 sensor-assisted patients were followed out to 3 years. The intraoperative devices used in this study contain microsensors and a processing unit. Kinetic and center of load location data are projected, in real-time, to a screen. Because of the wireless nature of the intraoperative sensors, the patella can be reduced, and kinematic data can be evaluated through the range of motion. For each patient, the soft-tissue envelope was balanced to within a mediolateral differential of 15 lbf., through the ROM, as per the suggestion of previously reported literature. The average patient profile indicates: age = 69.7 years, BMI = 30.4, gender distribution = 36% male/64% female. Any adverse event within the 3-year follow-up interval was captured. By 3 years, 1 patient in this population has required revision surgeon due to mechanical complicatons. Overall adverse events included: pain in hip (3), pain in contralateral knee (2), wound drainage (3), DVT (1), death (1), stiffness in operative knee (2), infection (3), global pain (2), back pain (2). Based on the average reported number of early revisions that occur in the U.S. (5% of primaries), it was anticipated for this patient group to require approximately 13 revisions by the 3-year follow-up interval. Using 2013 CMS MEDPAR data, these 13 revisions would have resulted in $124,007 cost-to-hospital. However, only 1 revision (0.4%) was observered, therefore $114,468 in additional costs were spared for the aggregate of participating hospitals. This data suggests that the incorporation of kinetic sensors in TKA may assist the surgeon in achieving soft-tissue balance and thereby avoiding adverse mechanical complications that require surgical intervention.
A class of Markov chains with no spectral gap

This is the publisher’s final pdf. The published article is copyrighted by American Mathematical Society and can be found at: http://www.ams.org/publications/journals/journalsframework/proc.
Axiomatic attribution for deep networks

We study the problem of attributing the prediction of a deep network to its input features, a problem previously studied by several other works. We identify two fundamental axioms— Sensitivity and Implementation Invariance that attribution methods ought to satisfy. We show that they are not satisfied by most known attribution methods, which we consider to be a fundamental weakness of those methods. We use the axioms to guide the design of a new attribution method called Integrated Gradients. Our method requires no modification to the original network and is extremely simple to implement; it just needs a few calls to the standard gradient operator. We apply this method to a couple of image models, a couple of text models and a chemistry model, demonstrating its ability to debug networks, to extract rules from a network, and to enable users to engage with models better.
New Discretization Schemes for Time-Harmonic Maxwell Equations by Weak Galerkin Finite Element Methods

Abstract This paper introduces new discretization schemes for time-harmonic Maxwell equations in a connected domain by using the weak Galerkin (WG) finite element method. The corresponding WG algorithms are analyzed for their stability and convergence. Error estimates of optimal order in various discrete Sobolev norms are established for the resulting finite element approximations.
Currency Matters: Analyzing International Bond Portfolios

Abstract Bonds denominated in the investor's currency are special. We show this indirectly in a global dataset of bilateral bond holdings—indirectly because the global holdings dataset does not differentiate by currency denomination—and then more directly in datasets of US holdings of foreign bonds that do differentiate by currency. We find that the share of a country's bonds denominated in investors' currencies is an important determinant of the amount of cross-border investment it receives; factors associated with greater (or less) cross-border investment in bonds differ by currency denomination; and one phenomenon of international portfolios—the ever-present home bias—in some cases actually disappears when bonds are denominated in the investor's currency, suggesting that the home bias is to some extent a home currency bias.
Rising Food Prices in South Asia: A Policy Framework to Mitigate Adverse Effects

The recent commodity boom has seriously affected South Asia, particularly due to higher food prices and their impact on the welfare of poor and vulnerable populations. This paper describes the food crisis and its effect on the region and then goes on to outline policies that countries in the region need to put in place in order to mitigate the risks associated with the adverse effects of the commodity boom. National policies, as well as regional and global level cooperation efforts are needed to improve agricultural productivity and reduce speculative activities that threaten food price stability in South Asia.
Numerical analysis of the Leray reduced order model

Abstract Standard ROMs generally yield spurious numerical oscillations in the simulation of convection-dominated flows. Regularized ROMs use explicit ROM spatial filtering to decrease these spurious numerical oscillations. The Leray ROM is a recently introduced regularized ROM that utilizes explicit ROM spatial filtering of the convective term in the Navier–Stokes equations. This paper presents the numerical analysis of the finite element discretization of the Leray ROM. Error estimates for the ROM differential filter, which is the explicit ROM spatial filter used in the Leray ROM, are proved. These ROM filtering error estimates are then used to prove error estimates for the Leray ROM. Finally, both the ROM filtering error estimates and the Leray ROM error estimates are numerically investigated in the simulation of the two-dimensional Navier–Stokes equations with an analytic solution.
Repeat vasectomy reversal yields high success rates

We retrospectively reviewed our experiences with repeat vasectomy reversal and report the patency and natural pregnancy rates. Our data demonstrate that repeat vasectomy reversal is a valid option in patients with a failed initial reversal, although the suitability of repeat reversal should be based on the obstructive interval, the original reversal, the experience of the reversal surgeon, and any female factors, as well as the couple's wishes.
The Effect of Labor Market Information on Community College Students’ Major Choice

Abstract An important goal of community colleges is to prepare students for the labor market. But are students aware of the labor market outcomes in different majors? And how much do students weigh labor market outcomes when choosing a major? In this study we find that less than 15% of a sample of community college students in California rank broad categories of majors accurately in terms of labor market outcomes. Students believe that salaries are 13% higher than they actually are, on average, and students underestimate the probability of being employed by almost 25%. We find that the main determinants of major choice are beliefs about course enjoyment and grades, but expected labor market outcomes also matter. Experimental estimates of the impact of expected labor market outcomes are larger than OLS estimates and show that a 10% increase in salary is associated with a 14 to 18% increase in the probability of choosing a specific category of majors.
BREP-INDEX: A MULTIDIMENSIONAL SPACE PARTITIONING TREE

In this paper we present the Brep-index, a multidimensional space partitioning data structure that provides quick spatial access to the vertices, edges and faces of a boundary representation (Brep), thus yielding a single unified representation for polyhedral solids. We give an algorithm for the construction of the Brep-index and prove its correctness. We show that its size is Ω(v+e+f), where v, e, and f are the number of vertices, edges, and faces of the Brep. The lower bound can be achieved for some Breps by compressing the structure using simple rewrite rules. We then demonstrate robust point and line/Brep classification methods given an implementation that uses finite-precision arithmetic.
Generation of forerunner electron beam during interaction of ion beam pulse with plasma

The long-time evolution of the two-stream instability of a cold tenuous ion beam pulse propagating through the background plasma with density much higher than the ion beam density is investigated using a large-scale one-dimensional electrostatic kinetic simulation. The three stages of the instability are investigated in detail. After the initial linear growth and saturation by the electron trapping, a portion of the initially trapped electrons becomes detrapped and moves ahead of the ion beam pulse forming a forerunner electron beam, which causes a secondary two-stream instability that preheats the upstream plasma electrons. Consequently, the self-consistent nonlinear-driven turbulent state is set up at the head of the ion beam pulse with the saturated plasma wave sustained by the influx of the cold electrons from upstream of the beam that lasts until the final stage when the beam ions become trapped by the plasma wave. The beam ion trapping leads to the nonlinear heating of the beam ions that eventually ...
Research on fragile X syndrome and autism: Implications for the study of genes, environments, and developmental language disorders

Contents: M.L. Rice, S.F. Warren, Preface. M.L. Rice, S.F. Warren, Introduction. Part I:Phenotypes of Language Impairments Within Clinical Diagnoses. C. Lord, S. Risi, A. Pickles, Trajectory of Language Development in Autistic Spectrum Disorders. H. Tager-Flusberg, Do Autism and Specific Language Impairment Represent Overlapping Language Disorders? J.B. Tomblin, X. Zhang, A. Weiss, H. Catts, S.E. Weismer, Dimensions of Individual Differences in Communication Skills Among Primary Grade Children. L. Abbeduto, M.M. Murphy, Language, Social Cognition, Maladaptive Behavior, and Communication in Down Syndrome and Fragile X Syndrome. A. Zukowski, Investigating Knowledge of Complex Syntax: Insights From Experimental Studies of Williams Syndrome. D.B. Bailey, Jr., J.E. Roberts, S.R. Hooper, D.D. Hatton, P.L. Mirrett, J.E. Roberts, J.M. Schaaf, Research on Fragile X Syndrome and Autism: Implications for the Study of Genes, Environments, and Developmental Language Disorders. Part II:Investigating Language Impairments Across Diagnostic Categories. C.B. Mervis, Cross-Etiology Comparisons of Cognitive and Language Development. S.F. Warren, Intervention as Experiment. M.L. Rice, Growth Models of Developmental Language Disorders. C. Phillips, Linguistics and Linking Problems. Part III:Neural, Genetic, and Behavioral Elements of Inherited Factors. R-A. Muller, Genes, Language Disorders, and Developmental Archaeology: What Role Can Neuroimaging Play? S.D. Smith, Localization and Identification of Genes Affecting Language and Learning. C.A. Morris, Genotype-Phenotype Correlations: Lessons From Williams Syndrome Research. Part IV:Research Action Steps for the Short and Long Term. P. McCardle, J. Cooper, Next Steps in the Study of Genetics and Language Disorders.
Oil prices implied volatility or direction: Which matters more to financial markets?

We examine the impact of oil price uncertainty on US stock returns by industry using the US Oil Fund options implied volatility OVX index and a GJR-GARCH model. We test the effect of the implied volatility of oil on a wide array of domestic industries’ returns using daily data from 2007 to 2016, controlling for a variety of variables such as aggregate market returns, market volatility, exchange rates, interest rates, and inflation expectations. Our main finding is that the implied volatility of oil prices has a consistent and statistically significant negative impact on nine out of the ten industries defined in the Fama and French (J Financ Econ 43:153–193, 1997) 10-industry classification. Oil prices, on the other hand, yield mixed results, with only three industries showing a positive and significant effect, and two industries exhibiting a negative and significant effect. These findings are an indication that the volatility of oil has now surpassed oil prices themselves in terms of influence on financial markets. Furthermore, we show that both oil prices and their volatility have a positive and significant effect on corporate bond credit spreads. Overall, our results indicate that oil price uncertainty increases the risk of future cash flows for goods and services, resulting in negative stock market returns and higher corporate bond credit spreads.
Learnable programming: blocks and beyond

New blocks frameworks open doors to greater experimentation for novices and professionals alike.