cssi/SciSciGPT-SciSciNet huggingface dataset:
New Insights into the Lactate Shuttle: Role of MCT4 in the Modulation of the Exercise Capacity.

Summary Lactate produced by muscle during high-intensity activity is an important end product of glycolysis that supports whole body metabolism. The lactate shuttle model suggested that lactate produced by glycolytic muscle fibers is utilized by oxidative fibers. MCT4 is a proton coupled monocarboxylate transporter preferentially expressed in glycolytic muscle fibers and facilitates the lactate efflux. Here we investigated the exercise capacity of mice with disrupted lactate shuttle due to global deletion of MCT4 (MCT4−/−) or muscle-specific deletion of the accessory protein Basigin (iMSBsg−/−). Although MCT4−/− and iMSBsg−/− mice have normal muscle morphology and contractility, only MCT4−/− mice exhibit an exercise intolerant phenotype. In vivo measurements of compound muscle action potentials showed a decrement in the evoked response in the MCT4−/− mice. This was accompanied by a significant structural degeneration of the neuromuscular junctions (NMJs). We propose that disruption of the lactate shuttle impacts motor function and destabilizes the motor unit.
Operating Characteristics for Binary Hypothesis Testing in Quantum Systems

Receiver operating characteristics (ROCs) are a well-established representation of the tradeoff between detection and false alarm probabilities in classical binary hypothesis testing. We use classical ROCs as motivation for two types of operating characteristics for binary hypothesis testing in quantum systems – decision operating characteristics (QDOCs) and measurement operating characteristics (QMOCs). Both are described in the context of a framework we propose that encompasses the typical formulations of binary hypothesis testing in both the classical and quantum scenarios. We interpret Helstrom’s well-known result [1] regarding discrimination between two quantum density operators with minimum probability of error in this framework. We also present a generalization of previous results [2], [3] regarding the correspondence between classical Parseval frames and quantum measurements. The derivation naturally leads to a constructive procedure for generating many different measurements besides Helstrom’s optimal measurement, some standard and others non-standard, that achieve minimum probability of error.
How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories.

Reconstruction of population histories is a central problem in population genetics. Existing coalescent-based methods, like the seminal work of Li and Durbin (Nature, 2011), attempt to solve this problem using sequence data but have no rigorous guarantees. Determining the amount of data needed to correctly reconstruct population histories is a major challenge. Using a variety of tools from information theory, the theory of extremal polynomials, and approximation theory, we prove new sharp information-theoretic lower bounds on the problem of reconstructing population structure—the history of multiple subpopulations that merge, split and change sizes over time. Our lower bounds are exponential in the number of subpopulations, even when reconstructing recent histories. We demonstrate the sharpness of our lower bounds by providing algorithms for distinguishing and learning population histories with matching dependence on the number of subpopulations.
High Transcriptional Error Rates Vary as a Function of Gene Expression Level

Errors in gene transcription can be costly, and organisms have evolved to prevent their occurrence or mitigate their costs. The simplest interpretation of the drift barrier hypothesis suggests that species with larger population sizes would have lower transcriptional error rates. However, Escherichia coli seems to have a higher transcriptional error rate than species with lower effective population sizes, for example Saccharomyces cerevisiae. This could be explained if selection in E. coli were strong enough to maintain adaptations that mitigate the consequences of transcriptional errors through robustness, on a gene by gene basis, obviating the need for low transcriptional error rates and associated costs of global proofreading. Here, we note that if selection is powerful enough to evolve local robustness, selection should also be powerful enough to locally reduce error rates. We therefore predict that transcriptional error rates will be lower in highly abundant proteins on which selection is strongest. However, we only expect this result when error rates are high enough to significantly impact fitness. As expected, we find such a relationship between expression and transcriptional error rate for non-C→U errors in E. coli (especially G→A), but not in S. cerevisiae. We do not find this pattern for C→U changes in E. coli, presumably because most deamination events occurred during sample preparation, but do for C→U changes in S. cerevisiae, supporting the interpretation that C→U error rates estimated with an improved protocol, and which occur at rates comparable with E. coli non-C→U errors, are biological.
An enterprise control methodology for the techno-economic assessment of the energy water nexus

Abstract This paper investigates the techno-economic impact of flexible operation of energy-water resources on power systems performance. More specifically, it presents a methodology that combines the lessons learnt from the renewable energy integration literature and the energy-water nexus literature into a single coherent framework that finds synergies between these two fields. From the renewable energy literature, the enterprise control methodology is employed to quantify the energy market production costs, dispatched energy mixes, required operating reserves, levels of curtailment, and grid imbalances for a system with high penetrations of solar and wind energy. This methodology is extended to allow for flexible energy-water resources within the grid’s energy resource portfolio and to quantify the amounts of water withdrawn and consumed by thermal power plants, as well as carbon dioxide ( CO 2 ) emissions. The study considers two cases: (1.) a control case where the system lacks flexible energy-water resources and (2.) an experimental case where hydroelectric power plants, water and wastewater treatment systems serve as flexible energy-water resources for demand response and reserve acquisition. The simulation methodology is demonstrated on the Reliability Test System Grid Modernization Lab Consortium (RTS-GMLC) test case. The experimental case results indicate up to 24.93% and 15.12% improvements in load-following and ramping reserves respectively. Flexible operation also reduces water withdrawals by 5.47% and CO 2 emissions by 1.14%. Finally, the experimental case results in lower day-ahead and real-time market production costs by 2.518 M$ and 2.892 M$ respectively.
Morbidity and mortality after general surgery in heart and lung transplant patients.

Abstract Background Heart and lung transplant patients can develop conditions necessitating general surgery procedures. Their postoperative morbidity and mortality remain poorly characterized and limited to case series from select centers. Methods The National Inpatient Sample (1998–2015) was used to identify 6433 heart and 3015 lung transplant patient admissions for general surgery procedures. For a comparator group, we identified 23,764,164 nontransplant patient admissions for the same procedures. Patient morbidity and mortality after general surgery were compared between transplant patients and nontransplant patients. Data were analyzed with frequency tables, χ2 analysis, and a mixed-effects multivariate regression. Results Overall mortality was higher and length of stay longer in the transplant group compared to the nontransplant group. Analysis revealed that hospital size and comorbidities were predictors of mortality for patients undergoing certain general surgery procedures. Transplant status alone did not predict mortality. Conclusion Our findings demonstrate that heart and lung transplant patients, compared to nontransplant patients, have more complications and a higher length of stay after certain general surgery procedures.
Designing an Intervention in Reading and Self-Regulation for Students With Significant Reading Difficulties, Including Dyslexia:

The purpose of this feasibility study was to inform the development of an intervention to support reading and self-regulation for students with significant reading difficulties and disabilities (RD...
Near-optimal bounds for online caching with machine learned advice

In the model of online caching with machine learned advice, introduced by Lykouris and Vassilvitskii, the goal is to solve the caching problem with an online algorithm that has access to next-arrival predictions: when each input element arrives, the algorithm is given a prediction of the next time when the element will reappear. The traditional model for online caching suffers from an Ω(log k) competitive ratio lower bound (on a cache of size k). In contrast, the augmented model admits algorithms which beat this lower bound when the predictions have low error, and asymptotically match the lower bound when the predictions have high error, even if the algorithms are oblivious to the prediction error. In particular, Lykouris and Vassilvitskii showed that there is a prediction-augmented caching algorithm with a competitive ratio of O(1 + min([MATH HERE], log k)) when the overall e1 prediction error is bounded by η, and opt is the cost of the optimal offline algorithm. The dependence on k in the competitive ratio is optimal, but the dependence on η/opt may be far from optimal. In this work, we make progress towards closing this gap. Our contributions are twofold. First, we provide an improved algorithm with a competitive ratio of O(1 + min((η/opt)/k, 1) log k). Second, we provide a lower bound of Ω(log min((η/opt)/(k log k), k)).
From Pixels to Buildings: End-to-end Probabilistic Deep Networks for Large-scale Semantic Mapping

We introduce TopoNets, end-to-end probabilistic deep networks for modeling semantic maps with structure reflecting the topology of large-scale environments. TopoNets build a unified deep network spanning multiple levels of abstraction and spatial scales, from pixels representing geometry of local places to high-level descriptions of semantics of buildings. To this end, TopoNets leverage complex spatial relations expressed in terms of arbitrary, dynamic graphs. We demonstrate how TopoNets can be used to perform end-to-end semantic mapping from partial sensory observations and noisy topological relations discovered by a robot exploring large-scale office spaces. Thanks to their probabilistic nature and generative properties, TopoNets extend the problem of semantic mapping beyond classification. We show that TopoNets successfully perform uncertain reasoning about yet unexplored space and detect novel and incongruent environment configurations unknown to the robot. Our implementation of TopoNets achieves real-time, tractable and exact inference, which makes these new deep models a promising, practical solution to mobile robot spatial understanding at scale.
Distributed flexibility in inertial swimmers

We study a linear inviscid model of a passively flexible swimmer with distributed flexibility, calculating its propulsive performance and optimal distributions of flexibility. The frequencies of actuation and mean stiffness ratios we consider span a large range, while the mass ratio is fixed to a low value representative of swimmers. We present results showing how the trailing edge deflection, thrust coefficient, power coefficient and efficiency vary with frequency, mean stiffness and stiffness distribution. Swimmers with distributed flexibility have the same qualitative features as those with uniform flexibility. Significant gains in thrust can be made, however, by tuning the stiffness such that a resonant response is triggered, or by concentrating stiffness towards the leading edge if resonance cannot be triggered. To minimize power, the opposite is true. Meaningful gains in efficiency can be made at low frequencies by concentrating stiffness away from the leading edge, since doing so induces efficient travelling wave kinematics. We also speculate on the effects of a finite Reynolds number in the form of streamwise drag. The drag adds an offset to the net thrust produced by the swimmer, causing efficiency-maximizing distributions of flexibility to tend towards thrust-maximizing ones, representative of what is found in nature.
Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs.

The rapid increase in antibiotic resistant pathogenic bacteria has become a global threat, which besides the development of new drugs, requires rapid, cheap, scalable, and accurate diagnostics. Label free biosensors relying on electrochemical, mechanical, and mass based detection of whole bacterial cells have attempted to meet these requirements. However, the trade-off between selectivity and sensitivity of such sensors remains a key challenge. In particular, point-of-care diagnostics that are able to reduce and/or prevent unneeded antibiotic prescriptions require highly specific probes with sensitive and accurate transducers that can be miniaturized and multiplexed, and that are easy to operate and cheap. Towards achieving this goal, we present a number of advances in the use of graphene field effect transistors (G-FET) including the first use of peptide probes to electrically detect antibiotic resistant bacteria in a highly specific manner. In addition, we dramatically reduce the needed concentration for detection by employing dielectrophoresis for the first time in a G-FET, allowing us to monitor changes in the Dirac point due to individual bacterial cells. Specifically, we realized rapid binding of bacterial cells to a G-FET by electrical field guiding to the device to realize an overall 3 orders of magnitude decrease in cell-concentration enabling a single-cell detection limit, and 9-fold reduction in needed time to 5 min. Utilizing our new biosensor and procedures, we demonstrate the first selective, electrical detection of the pathogenic bacterial species Staphylococcus aureus and antibiotic resistant Acinetobacter baumannii on a single platform.
Scattering of Dirac electrons from a skyrmion: Emergence of robust skew scattering

This paper studies the experimentally feasible setting where the surface electrons of a three dimensional topological insulator are scattered from an embedded, two-dimensional magnetic structure whose effective mass sign can be engineered to being negative, generating a skyrmion structure. The authors find that the skyrmion can lead to strong skew scattering, on which classical chaos produced by geometric deformation has little effect.
Graph Temporal Logic Inference for Classification and Identification

Inferring spatial-temporal properties from data is important for many complex systems, such as additive manufacturing systems, swarm robotic systems and biological networks. Such systems can often be modeled as a labeled graph where labels on the nodes and edges represent relevant measurements such as temperatures and distances. We introduce graph temporal logic (GTL) which can express properties such as "whenever a node’s label is above 10, for the next 3 time units there are always at least two neighboring nodes with an edge label of at most 2 where the node labels are above 5". This paper is a first attempt to infer spatial (graph) temporal logic formulas from data for classification and identification. For classification, we infer a GTL formula that classifies two sets of graph temporal trajectories with minimal misclassification rate. For identification, we infer a GTL formula that is informative and is satisfied by the graph temporal trajectories in the dataset with high probability. The informativeness of a GTL formula is measured by the information gain with respect to given prior knowledge represented by a prior probability distribution. We implement the proposed approach to classify the graph patterns of tensile specimens built from selective laser sintering (SLS) process with varying strengths, and to identify informative spatial-temporal patterns from experimental data of the SLS cooldown process and simulation data of a swarm of robots.
Energy-Aware Multi-Server Mobile Edge Computing: A Deep Reinforcement Learning Approach

We investigate the problem of computation offloading in a mobile edge computing architecture, where multiple energy-constrained users compete to offload their computational tasks to multiple servers through a shared wireless medium. We propose a multi-agent deep reinforcement learning algorithm, where each server is equipped with an agent, observing the status of its associated users and selecting the best user for offloading at each step. We consider computation time (i.e., task completion time) and system lifetime as two key performance indicators, and we numerically demonstrate that our approach outperforms baseline algorithms in terms of the trade-off between computation time and system lifetime.
Integrating International Graduate Students on Campus: The Perspectives of Student Affairs Professionals

Higher education institutions in the United States (U.S.) recruit international students as part of their internationalization strategies. The overall number of international students enrolled in American universities and colleges between 2017 and 2018 increased by 1.5% compared to the previous year, totaling over 1 million international students (Institute of International Education 2018). Of this total, 382,983 are international graduate students. International graduate students are good resources for the internationalization and economy of higher education institutions in the U.S. (Urban and Palmer, 2014) and, despite the reduction in the number of visas approved and job prospects, their numbers continue to grow (Almurideef 2016; Killick 2015). These students come from different countries, have different cultural backgrounds and needs, and face different challenges that student affairs professionals at host institutions must address to integrate them into campus (Harper and Hurtado, 2007; Lee and Rice 2007). Moreover, the needs and challenges of international students differ depending on their level of studies, undergraduate vs. graduate (Rai 2002). While student affairs professionals are often the first contacts for all international students, and they play a key role in the integration and development of international graduate students on campus (Brandenburg 2016), most higher education institutions and their student affairs units today are not yet prepared to serve international graduate students (Arokiasamy 2011; Burdzinski 2014; Castellanos et al., 2007; Di Maria 2012; Moswela and Mukhopadhyay 2011; Yakaboski and Perozzi 2018). The purpose of this study is to understand the perspectives of student affairs professional about their role in integrating international graduate students into campus and the policies, services, programs, and other elements they consider most helpful in integrating these students.
A Robotic Excavator for Autonomous Truck Loading

Excavators are used for the rapid removal of soil and other materials in mines, quarries, and construction sites. The automation of these machines offers promise for increasing productivity and improving safety. To date, most research in this area has focussed on selected parts of the problem. In this paper, we present a system that completely automates the truck loading task. The excavator uses two scanning laser rangefinders to recognize and localize the truck, measure the soil face, and detect obstacles. The excavator‘s software decides where to dig in the soil, where to dump in the truck, and how to quickly move between these points while detecting and stopping for obstacles. The system was fully implemented and was demonstrated to load trucks as fast as human operators.
Rapid adaptation to elevated extracellular potassium in the pyloric circuit of the crab, Cancer borealis

Elevated potassium concentration ([K+]) is often used to alter excitability in neurons and networks by shifting the potassium equilibrium potential (EK) and, consequently, the resting membrane potential. We studied the effects of increased extracellular [K+] on the well-described pyloric circuit of the crab Cancer borealis. A 2.5-fold increase in extracellular [K+] (2.5×[K+]) depolarized pyloric dilator (PD) neurons and resulted in short-term loss of their normal bursting activity. This period of silence was followed within 5-10 min by the recovery of spiking and/or bursting activity during continued superfusion of 2.5×[K+] saline. In contrast, when PD neurons were pharmacologically isolated from pyloric presynaptic inputs, they exhibited no transient loss of spiking activity in 2.5×[K+], suggesting the presence of an acute inhibitory effect mediated by circuit interactions. Action potential threshold in PD neurons hyperpolarized during an hour-long exposure to 2.5×[K+] concurrent with the recovery of spiking and/or bursting activity. Thus the initial loss of activity appears to be mediated by synaptic interactions within the network, but the secondary adaptation depends on changes in the intrinsic excitability of the pacemaker neurons. The complex sequence of events in the responses of pyloric neurons to elevated [K+] demonstrates that electrophysiological recordings are necessary to determine both the transient and longer term effects of even modest alterations of K+ concentrations on neuronal activity.NEW & NOTEWORTHY Solutions with elevated extracellular potassium are commonly used as a depolarizing stimulus. We studied the effects of high potassium concentration ([K+]) on the pyloric circuit of the crab stomatogastric ganglion. A 2.5-fold increase in extracellular [K+] caused a transient loss of activity that was not due to depolarization block, followed by a rapid increase in excitability and recovery of spiking within minutes. This suggests that changing extracellular potassium can have complex and nonstationary effects on neuronal circuits.
Hopf algebras for matroids over hyperfields

Abstract Recently, M. Baker and N. Bowler introduced the notion of matroids over hyperfields as a unifying theory of various generalizations of matroids. In this paper we generalize the notion of minors and direct sums from ordinary matroids to matroids over hyperfields. Using this we generalize the classical construction of matroid-minor Hopf algebras to the case of matroids over hyperfields.
The Impact of Genistein Supplementation on Tendon Functional Properties and Gene Expression in Estrogen-Deficient Rats

Tendinopathy risk increases with menopause. The phytoestrogen genistein prevents collagen loss during estrogen deficiency (ovariectomy [OVX]). The influence of genistein on tendon function and extracellular matrix (ECM) regulation is not well known. We determined the impact of genistein on tendon function and the expression of several genes important for the regulation of tendon ECM. Eight-week-old rats (n = 42) were divided into three groups: intact, OVX, or OVX-genistein (6 mg/kg/day) for 6 weeks. Tail fascicles were assessed with a Deben tensile stage. Achilles tendon mRNA expression was determined with digital droplet polymerase chain reaction. Compared to intact, fascicle stress tended to be lower in untreated OVX rats (P = .022). Furthermore, fascicle modulus and energy density were greater in genistein-treated rats (P .05). Compared to intact, Tnmd and Esr1 expression were greater and Pcna and Timp1 expression were lower in OVX rats (P .05). Several β-catenin/Wnt signaling-related molecules were not altered by OVX or genistein (P > .05). Our findings demonstrate that genistein improves tendon function in estrogen-deficient rats. The effect of genistein in vivo was predominately on genes related to cell proliferation rather than collagen remodeling.
Multidimensional coherent spectroscopy of a semiconductor microcavity

ABSTRACT Multidimensional coherent spectroscopy maps the detuning dependence of the upper (UP) and lower (LP) exciton-polariton branches 1 in a wedged microcavity with a single InGaAs quantum well at 5 K. Features on the diagonal correspond to intra- action coherences of the UP and LP branches. Off- diagonal peaks are interaction coherences between the UP and LP branches. With increasing detuning (' , all peaks move to higher energy, the exciton-like (E EX ) and cavity-like (E J ) modes swap position and have maximum intensity near the anti-crossing at ' =0. An isolated biexciton (B) is only seen at ' 0, the spectral weight of the off-diagonal features swap, as the LP and B come into resonance. This indicates that the off-diagonal features are sensitive to the interactions including two-quantum contributions and that a situation similar to a Feshbach resonance exists. 2 Polarization of two-quantum contributions show spin sensi tive two-polariton and new biexciton correlations. The latter likely influence the Feshbach resonance between biexcitons and two-polariton states. The two-quantum signatures also demonstate that biexcitons perturb the light-matter coupling in the microcavity to reduce the mixed two-polariton contributions. Detuning dependence of zero-quantum contributions show Raman-like coherences that are enhanced near zero detuning. Asymmetry of the Raman coherences are indicative of many-body interactions, which also grow stronger as the light-matter interactions are enhanced near zero deuning. Keywords: Polaritons, Excitons, Microc avities, Coherent Spectroscopy
Richard Morton, 1637-1698, limner of anorexia nervosa: his life and times. A tercentenary essay.

IN 1689, Richard Morton, a fellow of the College of Physicians, published his magnum opus, “Phthisiologia, seu Exercitationes de Phthisi”. In this seminal volume, translated into English five years later, and subtitled, “A Treatise of Consumption.?', he outlined in painstaking detail, the many disease processes that cause wasting of body tissues. All of the material was based on his own clinical observations, with little reference to books. The text, which is richly descriptive, is best known for his comments on tuberculosis. A specialist in the treatment of this disease (OSLER, 1904; TRAIL, 1970), he was the first physician to state that tubercles are always present in the pulmonary form. Morton is best known today (BLISS and BRANCH, 1960) as the author of the first medical account of anorexia nervosa, a condition that he referred to as “a Nervous Consumption”, caused by, “Sadness, and anxious Cares”. The clinical description, printed in its entirety, is as follows: “Mr. Duke’s daughter in St. Mary Axe, in the year 1684, and the Eighteenth Year of her Age, in the month of July fell into a total suppression of her Monthly Courses from a multitude of Cares and Passions of her Mind, but without any Symptom of the Green-Sickness following upon it. From which time her Appetite began to abate, and her Digestion to be bad; her Flesh also began to be flaccid and loose, and her looks pale, with other Symptoms usual in an Universal Consumption of the Habit of the Body, and by the extream and memorable cold Weather which happened the Winter following, this Consumption did seem to be not a little improved; for that she was wont by her studying at Night, and continual poring upon Books, to expose her self both Day and Night to the injuries of the Air, which was at that time extreamly cold, not without some manifest Prejudice to the System of her Nerves. The Spring following by the Prescription of some Emperick, she took a Vomit, and after that I know not what Steel Medicines, but without any Advantage. So from that time loathing all sorts of Medlcaments, she wholly neglected the care of her self for two full Years, till at last king brought to the last degree of a Marasmus, or Consumption, and thereupon subject to frequent Fainting Fits, she apply’d her self to me for Advice. I do not remember that I did ever in all my Practice see one, that was conversant with the Living so much wasted with the greatest degree of a Consumption, (like a Skeleton only clad with skin) yet there was no Fever, but on the contrary a coldness of the whole Body; no Cough, or difficulty of Breathing,
Molecular biology of nickel carcinogenesis.

A review of the molecular mechanisms of nickel carcinogenesis has been compiled. This work is based upon approximately 20 years of research conducted in my laboratory. Molecular mechanisms of nickel carcinogenesis are considered from the point‐of‐view of the uptake of nickel, both soluble and insoluble particles in cells, its dissolution and its effects on heterochromatin. Molecular mechanisms by which nickel induces gene silencing in cells by DNA hypermethylation in mammalian cells and by inhibiting histone acetylation in yeast cells are also discussed.
Chapter 13 – Static Electricity

Publisher Summary The basic concept of static electricity is the generation of an electrical charge after two bodies are brought into close physical contact and then separated, for instance, a belt running over a pulley. When two bodies, particularly when they are of different materials, are brought into close physical contact a redistribution of electrons in the bodies occurs, causing the bodies to produce an attractive force. When the bodies are separated, a counter force is created and appears as energy between the bodies causing them to be charged. The charges appear as a potential difference or a voltage between the two bodies. The voltage so obtained is the result of numerous physical contacts and separations. One body will become positively charged because it is left with an excess of protons and another will become negatively charged because of an excess of electrons. If the body has sufficient energy a spark may occur and if the spark occurs in the presence of a flammable vapor-air mixture, ignition may result. The ability of a spark to produce ignition is mainly a function of its energy. The possibility of a spark is reduced when the loading product consists of crude oil or Class II and Class III flammable liquids. However, for a rapid reduction of such accumulated charges, all equipments used in a hazardous area should be adequately bonded and grounded.
The need for specialized training for adults with congenital urologic conditions: differences in opinion among specialties.

Introduction The aim of this study was to survey pediatric urology fellowship directors (PFD) and adult reconstruction fellowship directors (AFD) to assess who they believe has sufficient training to care for adults with congenital urologic conditions (ACUC). Material and methods An online survey was created to assess attitudes towards specific training to care for ACUC. The survey was administered to 27 PFD and 26 AFD [16 from genitourinary reconstructive surgery (GURS) and 10 from female pelvic medicine and reconstructive surgery (FPMRS)]. Both groups were asked if specific training is warranted, and if general urologists, pediatric urologists or adult reconstructive urologists were sufficiently trained to care for ACUC. Results A total of 26 (96%) PFD and 10 (39%) AFD completed the survey. All PFD were fellowship trained in pediatrics. Of the AFD, 5 were GURS trained, 4 were FPMRS trained and 1 was not fellowship trained. The majority (65% PFD, 90% AFD) believed specific training is warranted. Few believed general urologists have sufficient training (8% PFD, 20% AFD). Most PFD believed pediatric urologists have sufficient training (85%), but a minority believed those with adult reconstructive training do (40%). Conversely, a minority of AFD believed that pediatric urologists have sufficient training (40%), while those with adult reconstructive training do (FPMRS: 67%, GURS: 60%). Conclusions Both pediatric and adult reconstructive urologists believe specific training to care for adults with congenital urologic conditions is warranted. Neither group considers the other to be ideally suited to care for this complex patient group. This suggests both groups may have something to learn from each other.
Design of a multivariable flutter control/gust load alleviation system

This paper discusses the use of eigenspace techniques for the design of an active flutter control/gust load alleviation system for a hypothetical research drone. One leading edge and two trailing edge aerodynamic surfaces are available for control. Full state control laws are designed for two combinations of control surfaces by selecting feedback gains which place closed loop eigenvalues and shape closed loop eigenvectors so as to stabilize wing flutter and reduce gust loads at the wing root while yielding acceptable robustness and satisfying constraints on rms control surface activity. These controllers are realized by state estimators designed using an eigenvalue placement/eigenvector shaping technique which results in recovery of the loop transfer characteristics of the full state feedback systems. The resulting feedback compensators are shown to perform almost as well as the full state designs. They also exhibit acceptable performance in situations in which the failure of an actuator is simulated.
Markovian Social Security in Unequal Societies

In this paper, we develop a dynamic political-economic theory of social security. We analytically characterize a Markov perfect equilibrium and find that the interaction between Markovian tax policy and tax distortion on private investment in human capital shapes an intertemporal policy rule, linking taxes positively over time. By allowing current taxpayers to influence their own future social security benefits, the positive intertemporal tax linkage provides political support for social security. Moreover, this positive tax linkage leads to a negative correlation between wage inequality and the size of a nation's social security system, consistent with the empirical pattern observed across OECD countries.
Measurements of linear polarization of satellite transitions from Li- and Be-like Ar ions

Non-thermal electron distributions, such as beams of electrons, are found in many laboratory and astrophysical plasma sources and can produce anisotropic and polarized emission. Theories used to model the emission require sublevel specific analysis, which can be difficult to verify experimentally. Using two polarization-sensitive Johann-type crystal spectrometers at the National Institute of Standards and Technology (NIST) electron beam ion trap facility, we measured the linear polarization of well-known dielectronic recombination satellite transitions from Li-like Ar ions and two blended features from Be-like ions. The spectrometers observed the plasma at 90$\degree$ relative to the electron beam propagation direction, and the crystal dispersion planes were oriented perpendicular relative to each other to allow for differing polarization sensitivities. Measurements were taken near the resonance energies of each line and compared with theoretical predictions based on relativistic magnetic sublevel atomic kinetics using the density-matrix theory. Most of the predictions are in excellent agreement with measured values.
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS

Cloud Infrastructure as a Service (IaaS) is vulnerable to malware due to its exposure to external adversaries, making it a lucrative attack vector for malicious actors. A datacenter infected with malware can cause data loss and/or major disruptions to service for its users. This paper analyzes and compares various Convolutional Neural Networks (CNNs) for online detection of malware in cloud IaaS. The detection is performed based on behavioural data using process level performance metrics including cpu usage, memory usage, disk usage etc. We have used the state of the art DenseNets and ResNets in effectively detecting malware in online cloud system. These CNNs are designed to extract features from data gathered from live malware running on a real cloud environment. Experiments are performed on OpenStack (a cloud IaaS software) testbed designed to replicate a typical 3-tier web architecture. Comparative analysis is performed for different CNN models.
Multi-omic signatures identify pan-cancer classes of tumors beyond tissue of origin

Despite recent advances in treatment, cancer continues to be one of the most lethal human maladies. One of the challenges of cancer treatment is the diversity among similar tumors that exhibit different clinical outcomes. Most of this variability comes from wide-spread molecular alterations that can be summarized by omic integration. Here, we have identified eight novel tumor groups (C1-8) via omic integration, characterized by unique cancer signatures and clinical characteristics. C3 had the best clinical outcomes, while C2 and C5 had poorest. C1, C7, and C8 were upregulated for cellular and mitochondrial translation, and relatively low proliferation. C6 and C4 were also downregulated for cellular and mitochondrial translation, and had high proliferation rates. C4 was represented by copy losses on chromosome 6, and had the highest number of metastatic samples. C8 was characterized by copy losses on chromosome 11, having also the lowest lymphocytic infiltration rate. C6 had the lowest natural killer infiltration rate and was represented by copy gains of genes in chromosome 11. C7 was represented by copy gains on chromosome 6, and had the highest upregulation in mitochondrial translation. We believe that, since molecularly alike tumors could respond similarly to treatment, our results could inform therapeutic action.
Structured randomness: jamming of soft discs and pins

Simulations are used to find the zero temperature jamming threshold, φj, for soft, bidisperse disks in the presence of small fixed particles, or "pins", arranged in a lattice. The presence of pins leads, as one expects, to a decrease in φj. Structural properties of the system near the jamming threshold are calculated as a function of the pin density. While the correlation length exponent remains ν = 1/2 at low pin densities, the system is mechanically stable with more bonds, yet fewer contacts than the Maxwell criterion implies in the absence of pins. In addition, as pin density increases, novel bond orientational order and long-range spatial order appear, which are correlated with the square symmetry of the pin lattice.
Fast Erasure Coding for Data Storage: A Comprehensive Study of the Acceleration Techniques

Various techniques have been proposed in the literature to improve erasure code computation efficiency, including optimizing bitmatrix design and computation schedule, common XOR (exclusive-OR) operation reduction, caching management techniques, and vectorization techniques. These techniques were largely proposed individually, and, in this work, we seek to use them jointly. To accomplish this task, these techniques need to be thoroughly evaluated individually and their relation better understood. Building on extensive testing, we develop methods to systematically optimize the computation chain together with the underlying bitmatrix. This led to a simple design approach of optimizing the bitmatrix by minimizing a weighted computation cost function, and also a straightforward coding procedure—follow a computation schedule produced from the optimized bitmatrix to apply XOR-level vectorization. This procedure provides better performances than most existing techniques (e.g., those used in ISA-L and Jerasure libraries), and sometimes can even compete against well-known but less general codes such as EVENODD, RDP, and STAR codes. One particularly important observation is that vectorizing the XOR operations is a better choice than directly vectorizing finite field operations, not only because of the flexibility in choosing finite field size and the better encoding throughput, but also its minimal migration efforts onto newer CPUs.
Acarbose protects from central and peripheral metabolic imbalance induced by benzene exposure

Benzene is a well-known human carcinogen that is one of the major components of air pollution. Sources of benzene in ambient air include cigarette smoke, e-cigarettes vaping, and evaporation of benzene containing petrol processes. While the carcinogenic effects of benzene exposure have been well studied, less is known about the metabolic effects of benzene exposure. We show that chronic exposure to benzene at low levels induces a severe metabolic imbalance in a sex-specific manner, and is associated with hypothalamic inflammation and endoplasmic reticulum (ER) stress. Benzene exposure rapidly activates hypothalamic ER stress and neuroinflammatory responses in male mice, while pharmacological inhibition of ER stress response by inhibiting IRE1α-XBP1 pathway significantly alleviates benzene-induced glial inflammatory responses. Additionally, feeding mice with Acarbose, a clinically available anti-diabetes drug, protected against benzene induced central and peripheral metabolic imbalance. Acarbose imitates the slowing of dietary carbohydrate digestion, suggesting that choosing a diet with a low glycemic index might be a potential strategy for reducing the negative metabolic effect of chronic exposure to benzene for smokers or people living/working in urban environments with high concentrations of exposure to automobile exhausts.
MUXConv: Information Multiplexing in Convolutional Neural Networks

Convolutional neural networks have witnessed remarkable improvements in computational efficiency in recent years. A key driving force has been the idea of trading-off model expressivity and efficiency through a combination of 1x1 and depth-wise separable convolutions in lieu of a standard convolutional layer. The price of the efficiency, however, is the sub-optimal flow of information across space and channels in the network. To overcome this limitation, we present MUXConv, a layer that is designed to increase the flow of information by progressively multiplexing channel and spatial information in the network, while mitigating computational complexity. Furthermore, to demonstrate the effectiveness of MUXConv, we integrate it within an efficient multi-objective evolutionary algorithm to search for the optimal model hyper-parameters while simultaneously optimizing accuracy, compactness, and computational efficiency. On ImageNet, the resulting models, dubbed MUXNets, match the performance (75.3% top-1 accuracy) and multiply-add operations (218M) of MobileNetV3 while being 1.6x more compact, and outperform other mobile models in all the three criteria. MUXNet also performs well under transfer learning and when adapted to object detection. On the ChestX-Ray 14 benchmark, its accuracy is comparable to the state-of-the-art while being 3.3x more compact and 14x more efficient. Similarly, detection on PASCAL VOC 2007 is 1.2% more accurate, 28% faster and 6% more compact compared to MobileNetV2.
Green-Lazarsfeld condition for toric edge ideals of bipartite graphs

Abstract Previously, Ohsugi and Hibi gave a combinatorial description of bipartite graphs G whose toric edge ideal I G is generated by quadrics, showing that every cycle of G of length at least 6 must have a chord. This corresponds to the Green-Lazarsfeld condition N 1 . In this paper, we investigate the higher syzygies of I G and give combinatorial descriptions of the Green-Lazarsfeld conditions N p of toric edge ideals of bipartite graphs for all p ≥ 1 . In particular, we show that I G is linearly presented (i.e. satisfies condition N 2 ) if and only if the bipartite complement of G is a tree of diameter at most 3. We also investigate the regularity of linearly presented toric edge ideals and give criteria for polyomino ideals to satisfy the Green-Lazarsfeld conditions.
Niche-Selective Inhibition of Pathogenic Th17 Cells by Targeting Metabolic Redundancy

Summary Targeting glycolysis has been considered therapeutically intractable owing to its essential housekeeping role. However, the context-dependent requirement for individual glycolytic steps has not been fully explored. We show that CRISPR-mediated targeting of glycolysis in T cells in mice results in global loss of Th17 cells, whereas deficiency of the glycolytic enzyme glucose phosphate isomerase (Gpi1) selectively eliminates inflammatory encephalitogenic and colitogenic Th17 cells, without substantially affecting homeostatic microbiota-specific Th17 cells. In homeostatic Th17 cells, partial blockade of glycolysis upon Gpi1 inactivation was compensated by pentose phosphate pathway flux and increased mitochondrial respiration. In contrast, inflammatory Th17 cells experience a hypoxic microenvironment known to limit mitochondrial respiration, which is incompatible with loss of Gpi1. Our study suggests that inhibiting glycolysis by targeting Gpi1 could be an effective therapeutic strategy with minimum toxicity for Th17-mediated autoimmune diseases, and, more generally, that metabolic redundancies can be exploited for selective targeting of disease processes.
Joint Multi-Dimensional Model for Global and Time-Series Annotations

Crowdsourcing is a popular approach to collect annotations for unlabeled data instances. It involves collecting a large number of annotations from several, often naive untrained annotators for each data instance which are then combined to estimate the ground truth. Further, annotations for constructs such as affect are often multi-dimensional with annotators rating multiple dimensions, such as valence and arousal, for each instance. Most annotation fusion schemes however ignore this aspect and model each dimension separately. In this work we address this by proposing a generative model for multi-dimensional annotation fusion, which models the dimensions jointly leading to more accurate ground truth estimates. The model we propose is applicable to both global and time series annotation fusion problems and treats the ground truth as a latent variable distorted by the annotators. The model parameters are estimated using the Expectation-Maximization algorithm and we evaluate its performance using synthetic data and real emotion corpora as well as on an artificial task with human annotations.
How do external conditions affect the design of local governments' sustainability strategies?

Local governments nationwide have been adopting a variety of sustainability practices in the absence of strong federal guidance. The collection of these practices, which differ in design, forms the local government’s sustainability strategy. Some local governments may develop a more focused sustainability strategy to achieve more predictable environmental benefits around a narrower array of environmental issues. By contrast, other local governments are developing a more comprehensive sustainability strategy that is more broadly focused to address complex, interconnected environmental issues. However, the external conditions that give rise to these different strategies is not well understood. Drawing on data for more than 950 U.S. municipal governments, this study provides important evidence that local governments’ comprehensive sustainability strategies are influenced more by their community constituents and external environmental settings, with greater pressures in particular from constituents in new economy industries and environmental NGOs. These strategies are also more strongly related to higher disaster risk in the external environmental setting than more focused sustainability strategies. These findings broaden our understanding about why local governments’ sustainability strategies differ in their design, which may provide a starting point for understanding how different sustainability strategies relate to actual environmental performance outcomes.