cssi/SciSciGPT-SciSciNet huggingface dataset:
Modeling and Control of a Low-Speed Flywheel Driving System for Pulsed-Load Mitigation in DC Distribution Networks

This paper details the modeling and development of an improved controller design for a dc flywheel energy storage system (FESS) driving circuit. The driving system is based on a bidirectional buck–boost converter. The modeling of this converter including the parasitic resistances for all the components was carried out. In this model, the equivalent circuit of the machine was integrated in the converter state-space model for improved accuracy and controllability. The system has two operating modes; when the FESS is charging, the converter operates in the buck mode. A controller was designed to regulate the charging rate through controlling the machine’s terminal voltage. In the discharging mode, the converter operates in the boost mode. A current controller takes over to control the injected current from the machine to the dc bus. The detailed design of both control loops was identified. Simulation results show the accuracy of the derived model and the enhanced performance of the FESS. Further, it is shown that the reversal of power-flow direction was performed seamlessly. A hardware prototype of the converter was implemented and the effectiveness of the developed system was experimentally verified. The experimental results are in excellent agreement with the simulation.
One-Pot Synthesis of Highly Substituted N-Fused Heteroaromatic Bicycles from Azole Aldehydes

An efficient route to substituted N-fused aromatic heterocycles, including indolizines, imidazo[1,2-a]pyridines, and imidazo[1,5-a]pyridines from azole aldehydes, is reported. Wittig olefination of the aldehydes with fumaronitrile and triethylphosphine affords predominantly E-alkenes that undergo rapid cyclization upon treatment with a mild base. Substituent control of the 1-, 2-, and 3-positions of the resulting heteroaromatic bicycles is shown. Alternatively, the isolable E-alkene undergoes selective alkylation with electrophiles, followed by in situ annulation to indolizines additionally substituted at the 6-position.
Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi

Living cells grow and divide with remarkable precision to ensure that their genetic material is faithfully duplicated and distributed equally to the newly formed daughter cells. This precision is achieved through a series of steps known as the cell cycle. The cell cycle is ancient and conserved across all Eukaryotes, including plants, animals and fungi. However, some of the core proteins present in animals and fungi are unrelated. This raises the question as to how a drastic change could have occurred and been tolerated over evolution. In animals and plants, a protein called E2F controls the expression of genes that are needed to begin the cell cycle. In most fungi, an equivalent protein called SBF performs the same role as E2F, but the two proteins are very different and do not appear to share a common ancestor. This is unexpected given that fungi and animals are more closely related to one another than either is to plants. Medina et al. searched the genomes of many animals, fungi, plants, algae, and their closest relatives for genes that encoded proteins like E2F and SBF. SBF-like proteins were only found in fungi, yet some fungal groups had cell cycle regulators like those found in animals. Zoosporic fungi, which diverged early from the fungal ancestor, had both SBF- and E2F-like proteins, while many fungi later lost E2F during evolution. So how did fungi acquire SBF? Medina et al. observed that part of the SBF protein is similar to proteins found in many viruses. The broad distribution of these viral SBF-like proteins suggests that they arose first in viruses, and a fungal ancestor acquired one such protein during a viral infection. As SBF and E2F bind similar DNA sequences, Medina et al. hypothesized that this viral SBF hijacked control of the cell cycle in the fungal ancestor by controlling expression of genes that were originally controlled only by E2F. In support of this idea, experiments showed that many E2F binding sites in modern genes are also SBF binding sites, and that E2F sites can substitute for SBF sites in SBF-controlled genes. Future experiments in zoosporic fungi, which have animal-like and fungal-like features, would provide a glimpse of how a fungal ancestor may have used both SBF and E2F. These experiments may also reveal why most fungi have retained the newer SBF but lost the ancestral and widely conserved E2F protein.
Homogenization of nanowire-based composites with anisotropic unit-cell and layered substructure

We analyze the optical properties of composite materials that combine nanowire and nanolayer platforms. We revisit effective-medium theory (EMT) description of wire materials with high filling fraction positioned in anisotropic unit cells and present a simple numerical technique to extend Maxwell-Garnett formalism in this limit. We also demonstrate that the resulting EMT can be combined with transfer-matrix technique to adequately describe photonic band gap behavior, previously observed in epitaxially grown semiconductor multilayer nanowires.
Reverse Coarse-Graining for Equation-Free Modeling: Application to Multiscale Molecular Dynamics.

Constructing atom-resolved states from low-resolution data is of practical importance in many areas of science and engineering. This problem is addressed in this article in the context of multiscale factorization methods for molecular dynamics. These methods capture the crosstalk between atomic and coarse-grained scales arising in macromolecular systems. This crosstalk is accounted for by Trotter factorization, which is used to separate the all-atom from the coarse-grained phases of the computation. In this approach, short molecular dynamics runs are used to advance in time the coarse-grained variables, which in turn guide the all-atom state. To achieve this coevolution, an all-atom microstate consistent with the updated coarse-grained variables must be recovered. This recovery is cast here as a nonlinear optimization problem that is solved with a quasi-Newton method. The approach yields a Boltzmann-relevant microstate whose coarse-grained representation and some of its fine-scale features are preserved. ...
DUAL MOBILITY IMPLANTS ARE COST-SAVING FOR PRIMARY THA: A COST-UTILITY ANALYSIS USING DIRECT AND INDIRECT COSTS

Introduction Postoperative dislocation remains a vexing problem for patients and surgeons following total hip arthroplasty (THA). It is the commonest reason for revision THA in the US. Dual mobility (DM) THA implants markedly decrease the risk of THA instability. However, DM implants are more expensive than those used for conventional THA. The purpose of this study was to perform a cost-effectiveness analysis of DM implants compared to conventional bearing couples for unilateral primary THA using a computer model-based evaluation. Methods A state-transition Markov computer simulation model was developed to compare the cost-utility of dual mobility versus conventional THA for hip osteoarthritis from a societal perspective (Figure 1). The model was populated with health outcomes and probabilities from registry and published data. Health outcomes were expressed as quality-adjusted life years (QALYs). Direct costs were derived from the literature and from administrative claims data, and indirect costs reflected estimated lost wages. All costs were expressed in 2013 US dollars. Health and cost outcomes were discounted by 3% annually. The base case modeled a 65-year-old patient undergoing THA for unilateral hip osteoarthritis. A lifetime time horizon was analyzed. The primary outcome was the incremental cost-effectiveness ratio (ICER). The willingness-to-pay threshold was set at $100,000/QALY. Threshold, one-way, two-way, and probabilistic sensitivity analyses were performed to assess model uncertainty. Results DM THA exhibited absolute dominance over conventional THA with lower accrued costs (US$45,960 versus $47,103) and higher accrued utility (12.08 QALY versus 11.84 QALY). The ICER was -$4,771/QALY, suggesting that DM THA is cost-saving compared to conventional THA. The cost threshold at which dual mobility implants were cost-ineffective was $25,000 (Figure 2), and the threshold at which DM implants ceased being cost-saving was $12,845. Sensitivity analyses demonstrated that the probability of intraprosthetic dislocation, primary THA utility, and age at index THA most influenced model results. In the probabilistic sensitivity analysis, 90% of model iterations resulted in cost savings for DM THA (Figure 3). Discussion Dual mobility components showed clear cost-utility advantages over conventional THA components, and DM implants are cost-saving for primary unilateral THA from a societal perspecitve. Model results suggest that DM THA need not be limited to only high-risk patients, although patient age and risk of dislocation are important determinants of its cost-utility.
Efficient Design and Analysis for a Selective Choice Process

AbstractVariable selection is a decision heuristic that describes a selective choice process in which choices are made on the basis of only a subset of product attributes while the presence of other (“inactive”) attributes plays no active role in the decision. Within this context, the authors address two integrated topics that have received scant attention: the efficient design of choice experiments and the analysis of data that arises from a selective choice process. The authors propose a new dual-objective compound design criterion that incorporates prior information for the joint purpose of efficiently estimating the effects of the active attributes and detecting the effects of attributes labeled as inactive that may turn out to be active. The approach leverages self-stated auxiliary data as prior information both for individual-level customized design construction and in a heterogeneous variable selection model. The authors demonstrate the efficiency advantages of the approach relative to design bench...
The Mit Deliberatorium - Enabling Large-scale Deliberation about Complex Systemic Problems.

Humanity now finds itself faced with a range of highly complex problems - such as climate change, the spread of disease, international security, scientific collaborations, product development, and so on - that call upon us to bring together large numbers of experts and stakeholders to deliberate collectively on a global scale. Collocated meetings can however be impractically expensive, severely limit the concurrency and thus breadth of interaction, and are prone to serious dysfunctions such as polarization and hidden profiles. Social media such as email, blogs, wikis, chat rooms, and web forums provide unprecedented opportunities for interacting on a massive scale, but have yet to realize their potential for helping people deliberate effectively, typically generating poorly-organized, unsystematic and highly redundant contributions of widely varying quality. Large-scale argumentation systems represent a promising approach for addressing these challenges, by virtue of providing a simple systematic structure that radically reduces redundancy and encourages clarity. This paper will address this important question, discussing (1) the strengths and limitations of current deliberation technologies, and (2) how large-scale argumentation can help address these limitations.
Differentiable McCormick relaxations

McCormick's classical relaxation technique constructs closed-form convex and concave relaxations of compositions of simple intrinsic functions. These relaxations have several properties which make them useful for lower bounding problems in global optimization: they can be evaluated automatically, accurately, and computationally inexpensively, and they converge rapidly to the relaxed function as the underlying domain is reduced in size. They may also be adapted to yield relaxations of certain implicit functions and differential equation solutions. However, McCormick's relaxations may be nonsmooth, and this nonsmoothness can create theoretical and computational obstacles when relaxations are to be deployed. This article presents a continuously differentiable variant of McCormick's original relaxations in the multivariate McCormick framework of Tsoukalas and Mitsos. Gradients of the new differentiable relaxations may be computed efficiently using the standard forward or reverse modes of automatic differentiation. Extensions to differentiable relaxations of implicit functions and solutions of parametric ordinary differential equations are discussed. A C++ implementation based on the library MC++ is described and applied to a case study in nonsmooth nonconvex optimization.
Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks

Influence Maximization (IM), that seeks a small set of key users who spread the influence widely into the network, is a core problem in multiple domains. It finds applications in viral marketing, epidemic control, and assessing cascading failures within complex systems. Despite the huge amount of effort, IM in billion-scale networks such as Facebook, Twitter, and World Wide Web has not been satisfactorily solved. Even the state-of-the-art methods such as TIM+ and IMM may take days on those networks. In this paper, we propose SSA and D-SSA, two novel sampling frameworks for IM-based viral marketing problems. SSA and D-SSA are up to 1200 times faster than the SIGMOD'15 best method, IMM, while providing the same (1-1/e-e) approximation guarantee. Underlying our frameworks is an innovative Stop-and-Stare strategy in which they stop at exponential check points to verify (stare) if there is adequate statistical evidence on the solution quality. Theoretically, we prove that SSA and D-SSA are the first approximation algorithms that use (asymptotically) minimum numbers of samples, meeting strict theoretical thresholds characterized for IM. The absolute superiority of SSA and D-SSA are confirmed through extensive experiments on real network data for IM and another topic-aware viral marketing problem, named TVM.
A Complete Calculus of Monotone and Antitone Higher-Order Functions

rst argument, monotone in its second. Though soundness of the main two proof rules (our (Mono) and (Anti) below in Def. 9) can be demonstrated [5, 6, 4], much of this work is informal, and so much is implicit. In particular, there are no completeness results, and even some of the delicate formal details of the type system, the language, and its interpretation are less developed. Work on this topic has been revived by computational linguists; see [2, 3] for example. Although our ultimate aim is the application to NL semantics and to computational linguistics, we hold that the issues of monotonicty and antitonicity are of mathematical interest to the TACL community. In this paper, we provide mathematical underpinnings of the Monotonicty Calculus. We devise a type system that includes marked types at any level of the functional hierarchy, and dene languages of typed terms made up of constants by function applications (thus, no variables). Our main interest is a proof calculus for deriving inequality statements between typed terms. We prove soundness and completeness of the calculus with respect to the natural class of models, hierarchies of monotone and antitone functions over base preorders.
GENERAL PERSPECTIVES, PATHOGENESIS, PATHOPHYSIOLOGY AND SKELETAL DYSFUNCTION

A better understanding of the pathogenesis and pathophysiology of the metastatic process is leading to improvements in diagnosis and treatment. Evaluation of specific areas of disorder of skeletal function, including hematopoiesis, mineral metabolism, and structural support, is important. Continued developments are necessary to minimize or prevent effects on the skeleton related to the metastatic process.
Enterprise Systems Education: New Directions & Challenges for the Future.

Enterprise systems design, implementation, and integration are focal points for business and information technology (IT). Businesses of all sizes are looking to information technology to better integrate with business partners, reduce costs, and provide strategic advantage. These challenges require a new type of technical professional, one with the training and perspective of an enterprise architect with general technical expertise as well as business strategy and planning skills. This paper investigates the need for this new type of IT professional and the implications for higher education.
Directed width parameters and circumference of digraphs

We prove that the directed treewidth, DAG-width and Kelly-width of a digraph are bounded above by its circumference plus one.
Global biogeography of microbial nitrogen-cycling traits in soil

Microorganisms drive much of the Earth’s nitrogen (N) cycle, but we still lack a global overview of the abundance and composition of the microorganisms carrying out soil N processes. To address this gap, we characterized the biogeography of microbial N traits, defined as eight N-cycling pathways, using publically available soil metagenomes. The relative frequency of N pathways varied consistently across soils, such that the frequencies of the individual N pathways were positively correlated across the soil samples. Habitat type, soil carbon, and soil N largely explained the total N pathway frequency in a sample. In contrast, we could not identify major drivers of the taxonomic composition of the N functional groups. Further, the dominant genera encoding a pathway were generally similar among habitat types. The soil samples also revealed an unexpectedly high frequency of bacteria carrying the pathways required for dissimilatory nitrate reduction to ammonium, a little-studied N process in soil. Finally, phylogenetic analysis showed that some microbial groups seem to be N-cycling specialists or generalists. For instance, taxa within the Deltaproteobacteria encoded all eight N pathways, whereas those within the Cyanobacteria primarily encoded three pathways. Overall, this trait-based approach provides a baseline for investigating the relationship between microbial diversity and N cycling across global soils.
Characteristics of social media stories

An emerging trend in social media is for users to create and publish "stories", or curated lists of? Web resources, with the purpose of creating a particular narrative of interest to the user. While some stories on the Web are automatically generated, such as Facebook's "Year in Review", one of the most popular storytelling services is "Storify", which provides users with curation tools to select, arrange, and annotate stories with content from social media and the Web at large. We would like to use tools, such as Storify, to present (semi-)automatically created summaries of archival collections. To support automatic story creation, we need to better understand as a baseline the structural characteristics of popular (i.e., receiving the most views) human-generated stories. We investigated 14,568 stories from Storify, comprising 1,251,160 individual resources, and found that popular stories (i.e., top 25?% of views normalized by time available on the Web) have the following characteristics: 2/28/1950 elements (min/median/max), a median of 12 multimedia resources (e.g., images, video), 38?% receive continuing edits, and 11?% of their elements are missing from the live Web. We also checked the population of Archive-It collections (3109 collections comprising 305,522 seed URIs) for better understanding the characteristics of the collections that we intend to summarize. We found that the resources in human-generated stories are different from the resources in Archive-It collections. In summarizing a collection, we can only choose from what is archived (e.g., twitter.com is popular in Storify, but rare in Archive-It). However, some other characteristics of human-generated stories will be applicable, such as the number of resources.
NEUROLOGICAL COMPROMISE IN NASOPHARYNGEAL CARCINOMA WITH SPINAL METASTASIS

Summary Neurological deficits resulting from spinal cord compression occur infrequently. When presented with neurological compromise, the most common management was radiotherapy, with surgery only being offered to patients who developed neurological deficit or pathological fracture resulting in unresolved severe pain post radiotherapy. Introduction Nasopharyngeal carcinoma has been reported to have a higher incidence of distant metastases to the spine. This study was conducted to evaluate the incidence, presentation and management of neurological involvement related to spinal metastasis from nasopharyngeal carcinoma. Patients and Methods 814 patients with the diagnosis of NPC who presented to the National University Hospital (NUH), Singapore, over a 5-year period (2007–2011) were recruited for this study. Case records from clinics, wards, operating theatres at NUH and nationwide electronic records of polyclinics and Emergency Medical Department (EMD) were obtained and reviewed. The data collected included demographics, medical history, radiologic and histopathology reports. Results Of 814 patients with NPC, 99 had spinal metastasis. 26 were treated with radiotherapy, 25 with chemotherapy, 5 with both chemo and radiotherapy and 6 with surgery. Out of 6 patients requiring spinal surgical procedure, 3 had neurological deficits in the form of focal sensory or motor deficits and 4 had symptoms of pathologic fracture. One patient had both neurological deficit and pathological fracture. All these 6 patients were treated with a spinal surgical procedure of stabilization and/or decompression. Discussion/Conclusion Spinal metastasis is common in patients with NPC and back pain is the usual presentation. Neurological deficits resulting from nerve root or spinal cord compression occur infrequently. When presented with neurological compromise, the most common management was radiotherapy, with surgery only being offered to patients who developed neurological deficit or pathological fracture resulting in unresolved severe pain post radiotherapy.
Reproducibility of T1 and T2 Relaxation Times Calculated from Routine MR Imaging Sequences: Phantom Study

Measurement of T1 and T2 relaxation times has been sought as one fundamental way to characterize tissue. Relaxation times can be calculated from routine spin-echo (SE) imaging sequences using two distinct repetition times (TRs), each with two SE samplings of signal intensity. Previous reports have quantified relaxation times without discussing the variation in their measurements. By imaging a phantom containing different samples with known T1 and T2 relaxation times on three separate occasions, the variation in relaxation time measurements inherent in different routine imaging sequences was studied. For the present study a more complete and accurate equation was used to calculate T1 values. The variation in T1 and T2 relaxation times for samples with relaxation times similar to solid tissue was 2%–4%. The amount of variability in calculated relaxation times was found to be dependent on the magnitude of the relaxation times themselves. However, the mean values were independent of the imaging sequences used to calculate the relaxation times. No significant differences were seen between left-to-right or section-to-section position within the same study or between studies performed on different occasions. The variability in the calculated T1 was dependent on the pair of TR sequences used to calculate T1. Samples with long T1 and T2 relaxation times, similar to many body fluids, had much larger variability. A computer simulation of measurement error was created to explain these results. This study indicates that properly performed routine imaging studies do yield reproducible T1 and T2 measurements.
The tubulin repertoire of C. elegans sensory neurons and its context-dependent role in process outgrowth

Microtubules contribute to many cellular processes, including transport, signaling, and chromosome separation during cell division (Kapitein and Hoogenraad, 2015). They are comprised of αβ‐tubulin heterodimers arranged into linear protofilaments and assembled into tubes. Eukaryotes express multiple tubulin isoforms (Gogonea et al., 1999), and there has been a longstanding debate as to whether the isoforms are redundant or perform specialized roles as part of a tubulin code (Fulton and Simpson, 1976). Here, we use the well‐characterized touch receptor neurons (TRNs) of Caenorhabditis elegans to investigate this question, through genetic dissection of process outgrowth both in vivo and in vitro. With single‐cell RNA-seq, we compare transcription profiles for TRNs with those of two other sensory neurons, and present evidence that each sensory neuron expresses a distinct palette of tubulin genes. In the TRNs, we analyze process outgrowth and show that four tubulins (tba‐1, tba‐2, tbb‐1, and tbb‐2) function partially or fully redundantly, while two others (mec‐7 and mec‐12) perform specialized, context‐dependent roles. Our findings support a model in which sensory neurons express overlapping subsets of tubulin genes whose functional redundancy varies between cell types and in vivo and in vitro contexts.
Prize and incentives in double-elimination tournaments

Abstract I examine a game-theoretical model of two variants of double-elimination tournaments, and derive the equilibrium behavior of symmetric players and the optimal prize allocation assuming a designer aims to maximize total effort. I compare these theoretical properties to the well-known single-elimination tournament.
Characterization of white matter abnormalities in early-stage schizophrenia.

Aim White matter abnormalities have been reported in schizophrenia and may indicate altered cortical network integrity and structural connectivity, which have been hypothesized as key pathophysiological components of this illness. In this study, we aimed to further characterize the nature and progression of white matter alterations during the early stages of the disorder. Methods We employed diffusion tensor imaging (DTI) approaches to investigate fractional anisotropy (FA), radial diffusivity (RD) and axial diffusivity (AD) in 40 patients with schizophrenia and related psychotic disorders (aged 18–30 years) who were within 5 years of illness, along with an age-, sex- and race-matched sample of 21 healthy controls. Relationships with illness duration, lifetime antipsychotic medication exposure and symptom levels were examined. Results Patients had lower FA and higher RD than controls in numerous white matter tracts, including the corpus callosum (CC) and the superior longitudinal fasciculus. Illness duration was associated with lower FA and higher RD, most prominently in the CC. No group differences or relationships to illness duration were detected with AD, and no relationships between any DTI measurements and lifetime antipsychotic medication use were found. Conclusions This investigation provides evidence of widespread disruptions to structural connectivity in the early stages of schizophrenia. The relationship to illness duration, coupled with an absence of relationships to AD or antipsychotic drug exposure, provides evidence of a progressive disease process, although prospective assessments with repeated DTI measurements are needed to fully characterize the trajectory of white matter abnormalities in this illness.
The modular organization of human anatomical brain networks: Accounting for the cost of wiring

Brain networks are expected to be modular. However, existing techniques for estimating a network's modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.
Inferring Brain Signals Synchronicity from a Sample of EEG Readings.

Inferring patterns of synchronous brain activity from a heterogeneous sample of electroencephalograms is scientifically and methodologically challenging. While it is intuitively and statistically a...
Cornering Natural SUSY at LHC Run II and Beyond

We derive the latest constraints on various simplified models of natural SUSY with light higgsinos, stops and gluinos, using a detailed and comprehensive reinterpretation of the most recent 13 TeV ATLAS and CMS searches with ∼ 15 fb−1 of data. We discuss the implications of these constraints for fine-tuning of the electroweak scale. While the most “vanilla” version of SUSY (the MSSM with R-parity and flavor-degenerate sfermions) with 10% fine-tuning is ruled out by the current constraints, models with decoupled valence squarks or reduced missing energy can still be fully natural. However, in all of these models, the mediation scale must be extremely low (<100 TeV). We conclude by considering the prospects for the high-luminosity LHC era, where we expect the current limits on particle masses to improve by up to ∼ 1 TeV, and discuss further model-building directions for natural SUSY that are motivated by this work.
Sensitivity analysis for an unobserved moderator in RCT-to-target-population generalization of treatment effects

In the presence of treatment effect heterogeneity, the average treatment effect (ATE) in a randomized controlled trial (RCT) may differ from the average effect of the same treatment if applied to a target population of interest. If all treatment effect moderators are observed in the RCT and in a dataset representing the target population, then we can obtain an estimate for the target population ATE by adjusting for the difference in the distribution of the moderators between the two samples. This paper considers sensitivity analyses for two situations: (1) where we cannot adjust for a specific moderator $V$ observed in the RCT because we do not observe it in the target population; and (2) where we are concerned that the treatment effect may be moderated by factors not observed even in the RCT, which we represent as a composite moderator $U$. In both situations, the outcome is not observed in the target population. For situation (1), we offer three sensitivity analysis methods based on (i) an outcome model, (ii) full weighting adjustment and (iii) partial weighting combined with an outcome model. For situation (2), we offer two sensitivity analyses based on (iv) a bias formula and (v) partial weighting combined with a bias formula. We apply methods (i) and (iii) to an example where the interest is to generalize from a smoking cessation RCT conducted with participants of alcohol/illicit drug use treatment programs to the target population of people who seek treatment for alcohol/illicit drug use in the US who are also cigarette smokers. In this case a treatment effect moderator is observed in the RCT but not in the target population dataset.
Inferring Individual Attributes from Search Engine Queries and Auxiliary Information

Internet data has surfaced as a primary source for investigation of different aspects of human behavior. A crucial step in such studies is finding a suitable cohort (i.e., a set of users) that shares a common trait of interest to researchers. However, direct identification of users sharing this trait is often impossible, as the data available to researchers is usually anonymized to preserve user privacy. To facilitate research on specific topics of interest, especially in medicine, we introduce an algorithm for identifying a trait of interest in anonymous users. We illustrate how a small set of labeled examples, together with statistical information about the entire population, can be aggregated to obtain labels on unseen examples. We validate our approach using labeled data from the political domain. We provide two applications of the proposed algorithm to the medical domain. In the first, we demonstrate how to identify users whose search patterns indicate they might be suffering from certain types of cancer. This shows, for the first time, that search queries can be used as a screening device for diseases that are currently often discovered too late, because no early screening tests exists. In the second, we detail an algorithm to predict the distribution of diseases given their incidence in a subset of the population at study, making it possible to predict disease spread from partial epidemiological data.
INTRA- AND EXTRA-ARTICULAR DEFORMITY: CORRECTIVE STRATEGIES

Extra-articular deformity may be present in patients requiring TKA. Underlying causes include trauma, metabolic bone disease, congenital deformity, or prior osteotomy. Patients with intra-articular deformity can have a combination of intra-articular bone loss and concomitant ligament contraction which can be managed in the standard fashion. In these cases establishing appropriate limb alignment and management of bone loss coincide well with the standard ligament balancing employed to provide a stable knee. However, if extra-articular deformity is not corrected extra-articularly, it must be corrected by a compensatory distal femoral or proximal tibial resection to reproduce appropriate limb alignment. Complex instabilities may result from this type of wedge resection because it occurs between the proximal and distal attachments of the collateral ligaments and so produces asymmetrical ligament length alterations. Femoral compensatory wedge resection for extra-articular deformity produces extension instability without affecting the flexion gap and so femoral deformities are POTENTIALLY more difficult to correct than tibial deformities where the compensatory tibial cut influences flexion AND extension equally. Lack of access to the intramedullary canal (as well as increased complexity of producing appropriately placed bone cuts) may be managed with computer guidance or patient specific instruments. The closer a deformity is to the knee, the greater its importance and the effect on the surgical correction. This is a directly proportional relationship, so that as the apex of the deformity moves from juxta-articular to more distant, the amount of corrective wedge needed to re-align the limb decreases proportionally. Rotatory deformities are complex and most commonly effect extensor mechanism tracking. In general the effect is similar to any other deformity in that proximity to the knee increases the likelihood that it will have a significant local effect. In general, these deformities are clinically, and radiographically more subtle and so must be searched for. They should be managed by an attempt to restore normal rotational parameters of the bone itself or appropriate compensation of component rotation in relation to the bone. As prosthetic constraint increases one may need to use intramedullary stems. Their use may be compromised by the deformity. Finally, the younger the patient and the more severe the deformity the more likely I am to treat the deformity by correction at the site of the deformity rather than compensating with abnormal bone resections. The older the patient and the milder the deformity (or the amount of wedge correction required) the more likely I am to manage the deformity with intra-articular correction and increased TKA constraint.
From Physical to Cyber: Escalating Protection for Personalized Auto Insurance

Nowadays, auto insurance companies set personalized insurance rate based on data gathered directly from their customers' cars. In this paper, we show such a personalized insurance mechanism -- wildly adopted by many auto insurance companies -- is vulnerable to exploit. In particular, we demonstrate that an adversary can leverage off-the-shelf hardware to manipulate the data to the device that collects drivers' habits for insurance rate customization and obtain a fraudulent insurance discount. In response to this type of attack, we also propose a defense mechanism that escalates the protection for insurers' data collection. The main idea of this mechanism is to augment the insurer's data collection device with the ability to gather unforgeable data acquired from the physical world, and then leverage these data to identify manipulated data points. Our defense mechanism leveraged a statistical model built on unmanipulated data and is robust to manipulation methods that are not foreseen previously. We have implemented this defense mechanism as a proof-of-concept prototype and tested its effectiveness in the real world. Our evaluation shows that our defense mechanism exhibits a false positive rate of 0.032 and a false negative rate of 0.013.
Development of a novel magnetic resonance imaging acquisition and analysis workflow for the quantification of shock wave lithotripsy-induced renal hemorrhagic injury.

The current accepted standard for quantifying shock wave lithotripsy (SWL)-induced tissue damage is based on morphometric detection of renal hemorrhage in serial tissue sections from fixed kidneys. This methodology is time and labor intensive and is tissue destructive. We have developed a non-destructive magnetic resonance imaging (MRI) method that permits rapid assessment of SWL-induced hemorrhagic lesion volumes in post-mortem kidneys using native tissue contrast to reduce cycle time. Kidneys of anesthetized pigs were targeted with shock waves using the Dornier Compact S lithotripter. Harvested kidneys were then prepared for tissue injury quantification. T1 weighted (T1W) and T2 weighted (T2W) images were acquired on a Siemens 3T Tim Trio MRI scanner. Images were co-registered, normalized, difference (T1W − T2W) images generated, and volumes classified and segmented using a Multi-Spectral Neural Network (MSNN) classifier. Kidneys were then subjected to standard morphometric analysis for the measurement of lesion volumes. Classifications of T1W, T2W and difference image volumes were correlated with morphometric measurements of whole kidney and parenchymal lesion volumes. From these relationships, a mathematical model was developed that allowed predictions of the morphological parenchymal lesion volume from MRI whole kidney lesion volumes. Predictions and morphology were highly correlated (R = 0.9691, n = 20) and described by the relationship y = 0.84x + 0.09, and highly accurate with a sum of squares difference error of 0.79%. MRI and the MSNN classifier provide a semi-automated segmentation approach, which provide a rapid and reliable means to quantify renal injury lesion volumes due to SWL.
Critical comments on the Conservative Power Theory (CPT)

Main features of the Conservative Power Theory (CPT) are examined in the paper. It was concluded that the “reactive energy” as defined in CPT cannot be regarded as a physical quantity. It was demonstrated that separation of the void reactive current can lead to wrong conclusions at a reactive compensator design. It was shown that distortion power defined in the CPT has no relation to mutual distortion of the load voltage and current. The meaning of the term “conservative” as used in the CPT, is discussed as well. It is emphasized that the conservative property of the “reactive energy” is only mathematical, but not physical property of that “energy”.
Noise near the carrier in microwave oscillators

This experimental study aimed at observing and whenever possible verifying the sources of noise near the carrier in microwave oscillators. The noise was detected as equivalent amplitude and frequency modulations; these and other signals of interest were analyzed by a spectrum analyzer resolving 25 bands of about \frac{1}{2} octave each, covering 14 cps to 34 Kc. The frequency domain across spectra (correlations) were also measured. The correlation measurements greatly facilitated the control of power supplies and environment. The tubes tested were two reflex klystrons and 3 B.W.O.'s, all operated cw at 9 Gc. It was found in all cases that the amplitude noise was negligible, being orders of magnitude lower in sideband energy than the frequency noise. The correlation between beam current and frequency was so small that it could be safely concluded that internally generated beam current fluctuations were a negligible source of frequency noise in the tubes tested. From the shape of the frequency noise spectra, it appeared that a major source of frequency noise was the perturbation of the beam in the interaction region by ions. It is hoped to directly verify this by controlled experiments.
Macroscopic directional analysis of pedestrian flow

Incidents at mass gatherings all over the world continue to raise concern about pedestrian safety. This rising concern calls for researchers to understand the underlying dynamics behind pedestrian and mass movements. The literature offers several approaches that reproduce reality to varying degrees, simulate it, and model it under different circumstances. Across these approaches, limited effort has been invested in looking at the projection of flow measures along different directions of travel (e.g., longitudinal versus lateral movement in omnidirectional environments) at the macroscopic level. To address this gap, this paper looks at directional flows and speeds and how they relate to each other at the macroscopic level. The results from analysis of experimental three-dimensional trajectory data show that a macroscopic analysis of directional travel, particularly of lateral travel, helps explain when and to what extent sidestepping occurs in the corridor. An increase in areawide density results in a decr...
JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open source, available under an MIT license, and can be installed using the Julia package manager from the JuPOETs GitHub repository
Electromagnetic perturbations of a de Sitter black hole in massive gravity

The main purpose of this paper is to study quasinormal modes (QNM) of a black hole in massive gravity with a positive cosmological constant due to electromagnetic perturbations. A detailed study of...
A microRNA signature in circulating exosomes is superior to exosomal glypican-1 levels for diagnosing pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a deadly malignancy that often presents clinically at an advanced stage and that may be confused with chronic pancreatitis (CP). Conversely, CP may be misdiagnosed as PDAC leading to unwarranted pancreas resection. Therefore, early PDAC diagnosis and clear differentiation between PDAC and CP are crucial for improved care. Exosomes are circulating microvesicles whose components can serve as cancer biomarkers. We compared exosomal glypican-1 (GPC1) and microRNA levels in normal control subjects and in patients with PDAC and CP. We report that exosomal GPC1 is not diagnostic for PDAC, whereas high exosomal levels of microRNA-10b, (miR-10b), miR-21, miR-30c, and miR-181a and low miR-let7a readily differentiate PDAC from normal control and CP samples. By contrast with GPC1, elevated exosomal miR levels decreased to normal values within 24 h following PDAC resection. All 29 PDAC cases exhibited significantly elevated exosomal miR-10b and miR-30c levels, whereas 8 cases had normal or slightly increased CA 19-9 levels. Thus, our exosomal miR signature is superior to exosomal GPC1 or plasma CA 19-9 levels in establishing a diagnosis of PDAC and differentiating between PDAC and CP.
The Power of Slightly More than One Sample in Randomized Load Balancing

In many computing and networking applications, arriving tasks have to be routed to one of many servers, with the goal of minimizing queueing delays. When the number of processors is very large, a popular routing algorithm works as follows: select two servers at random and route an arriving task to the least loaded of the two. It is well known that this algorithm dramatically reduces queueing delays compared to an algorithm, which routes to a single randomly selected server. In recent cloud computing applications, it has been observed that even sampling two queues per arriving task can be expensive and can even increase delays due to messaging overhead. So there is an interest in reducing the number of sampled queues per arriving task. In this paper, we show that the number of sampled queues can be dramatically reduced by using the fact that tasks arrive in batches (called jobs). In particular, we sample a subset of the queues such that the size of the subset is slightly larger than the batch size (thus, o...