cssi/SciSciGPT-SciSciNet huggingface dataset:
The Cellular NMD Pathway Restricts Zika Virus Infection and Is Targeted by the Viral Capsid Protein.

Zika virus (ZIKV) infection of neural progenitor cells (NPCs) in utero is associated with neurological disorders, such as microcephaly, but a detailed molecular understanding of ZIKV-induced pathogenesis is lacking. Here we show that in vitro ZIKV infection of human cells, including NPCs, causes disruption of the nonsense-mediated mRNA decay (NMD) pathway. NMD is a cellular mRNA surveillance mechanism that is required for normal brain size in mice. Using affinity purification-mass spectrometry, we identified multiple cellular NMD factors that bind to the viral capsid protein, including the central NMD regulator up-frameshift protein 1 (UPF1). Endogenous UPF1 interacted with the ZIKV capsid protein in coimmunoprecipitation experiments, and capsid expression posttranscriptionally downregulated UPF1 protein levels, a process that we confirmed occurs during ZIKV infection. Cellular fractionation studies show that the ZIKV capsid protein specifically targets nuclear UPF1 for degradation via the proteasome. A further decrease in UPF1 levels by RNAi significantly enhanced ZIKV infection in NPC cultures, consistent with a model in which NMD restricts ZIKV infection in the fetal brain. We propose that ZIKV, via the capsid protein, has evolved a strategy to lower UPF1 levels and dampen antiviral activities of NMD, which in turn contributes to neuropathology in vivo IMPORTANCE Zika virus (ZIKV) is a significant global health threat, as infection has been linked to serious neurological complications, including microcephaly. Using a human stem cell-derived neural progenitor model system, we find that a critical cellular quality control process called the nonsense-mediated mRNA decay (NMD) pathway is disrupted during ZIKV infection. Importantly, disruption of the NMD pathway is a known cause of microcephaly and other neurological disorders. We further identify an interaction between the capsid protein of ZIKV and up-frameshift protein 1 (UPF1), the master regulator of NMD, and show that ZIKV capsid targets UPF1 for degradation. Together, these results offer a new mechanism for how ZIKV infection can cause neuropathology in the developing brain.
Total synthesis of antofine using the net [5+5]-cycloaddition of γ,δ-unsaturated carbene complexes and 2-alkynylphenyl ketones as a key step

A compound containing all of the carbons of the anticancer agent antofine was produced in a single step from the coupling of a γ,δ-unsaturated carbene complex with a 2-alkynylphenyl ketone derivati...
Convenient syntheses of 6-methylpurine and related nucleosides.

Abstract Efficient methods for the synthesis of 6-methylpurine (3), 9-(2-deoxy-β-D-erythro-pentofuranosyl)-6-methylpurine (8), and 6-methyl-9-β-D-ribofuranosylpurine (5) are described. Methodology involving the (Ph3P)4Pd catalyzed cross-coupling reaction of CH3ZnBr with several different 6-chloropurine derivatives is described in high yield. This methodology now provides a facile and high-yielding synthesis of 8, which is needed in significant amounts for studies in cancer gene therapy.
Engineering species-like barriers to sexual reproduction.

Controlling the exchange of genetic information between sexually reproducing populations has applications in agriculture, eradication of disease vectors, control of invasive species, and the safe study of emerging biotechnology applications. Here we introduce an approach to engineer a genetic barrier to sexual reproduction between otherwise compatible populations. Programmable transcription factors drive lethal gene expression in hybrid offspring following undesired mating events. As a proof of concept, we target the ACT1 promoter of the model organism Saccharomyces cerevisiae using a dCas9-based transcriptional activator. Lethal overexpression of actin results from mating this engineered strain with a strain containing the wild-type ACT1 promoter. Genetic isolation of a genetically modified organism represents a useful strategy for biocontainment. Here the authors use dCas9-VP64-driven gene expression to construct a ‘species-like’ barrier to reproduction between two otherwise compatible populations.
Consistent Histories and Quantum Delayed Choice

John Wheeler devised a gedanken experiment in which a piece of apparatus can be altered just before the arrival of particle, and this “delayed choice” can, seemingly, alter the quantum state of the particle at a much earlier time, long before the choice is made. A slightly different gedanken experiment, which exhibits the same conceptual difficulty, is analyzed using the techniques of consistent history quantum theory. The idea that the future influences the past disappears when proper account is taken of the diversity of possible quantum descriptions of the world, and their mutual compatibility
Asymmetric syntheses, opioid receptor affinities, and antinociceptive effects of 8-amino-5,9-methanobenzocyclooctenes, a new class of structural analogues of the morphine alkaloids.

Several 8-amino-5,9-methanobenzocyclooctenes have been prepared by asymmetric organic synthesis techniques. Opioid receptor affinity studies have revealed the virtual absence of enantioselectivity for receptor binding, particularly at the μ-receptor, for the (+)-3a−f and the (−)-3a−f series. It is noteworthy that inversion of configuration at the nitrogen-bearing carbon atom [(5S,8S,9S)-8-amino-3-hydroxy-5,9-methano-9-(methoxymethyl)-5-methylbenzocyclooctene, (+)-3a vs (5S,8S,9R)-8-amino-3-hydroxy-5,9-methano-9-(methoxymethyl)-5-methylbenzocyclooctene, (dl)-22] resulted in a >10-fold increase in κ-receptor affinity. Antinociceptive studies demonstrated that (dl)-22 was a full κ-agonist while (+)-3a and (−)-3a did not possess κ-activity. Although both (dl)-22 and (+)-3a/(−)-3a had high affinity for the μ-receptor, these compounds did not act as high-affinity agonists or antagonists at this receptor.
Solution-phase parallel Wittig olefination : Synthesis of substituted 1,2-diarylethanes

An efficient strategy for solution-phase parallel synthesis of substituted 1,2-diarylethanes is described. A stilbene library was initially generated by Wittig olefination utilizing amino-labeled phosphines. The stilbene analogues were obtained in high yields and excellent purities after solid-phase extraction. Subsequent reduction of the stilbene libraries simultaneously unmasked functional groups by deprotection, facilitating orthogonal synthesis and further diversification into sublibraries. The libraries from libraries were obtained in good yields and purities using parallel solution-phase alkylation and acylation methodologies. Screening of the sublibraries revealed selective 5-HT2A inverse agonists with IC-50 values between 10 and 100 nM.
Synthesis, structure, and bonding of hypoelectronic SrIn4: Direct example of a dominant size effect in structure selection

The structure of the new title compound, the same type as EuIn4, was refined in the monoclinic space group C2/m, with Z = 4. The compound exhibits a complex three-dimensional network built of four- and five-bonded indium atoms in fused and interbonded pentagons that sandwich the strontium atoms. Both electronic band-structure calculations and property measurements show that the compound is metallic. A detailed band-structure analysis indicates that the compound is hypoelectronic with a one-electron deficiency, but the In−In bonding is effectively optimized in the structure. The important role of cation size in the structure choice is noted in a comparative study of BaIn4, which has the closely related BaAl4-type structure in which barium atoms are sandwiched by six-membered rings.
Cross-species complementation reveals conserved functions for EARLY FLOWERING 3 between monocots and dicots.

Plant responses to the environment are shaped by external stimuli and internal signaling pathways. In both the model plant Arabidopsis thaliana (Arabidopsis) and crop species, circadian clock factors are critical for growth, flowering, and circadian rhythms. Outside of Arabidopsis, however, little is known about the molecular function of clock gene products. Therefore, we sought to compare the function of Brachypodium distachyon (Brachypodium) and Setaria viridis (Setaria) orthologs of EARLY FLOWERING 3, a key clock gene in Arabidopsis. To identify both cycling genes and putative ELF3 functional orthologs in Setaria, a circadian RNA-seq dataset and online query tool (Diel Explorer) were generated to explore expression profiles of Setaria genes under circadian conditions. The function of ELF3 orthologs from Arabidopsis, Brachypodium, and Setaria was tested for complementation of an elf3 mutation in Arabidopsis. We find that both monocot orthologs were capable of rescuing hypocotyl elongation, flowering time, and arrhythmic clock phenotypes. Using affinity purification and mass spectrometry, our data indicate that BdELF3 and SvELF3 could be integrated into similar complexes in vivo as AtELF3. Thus, we find that, despite 180 million years of separation, BdELF3 and SvELF3 can functionally complement loss of ELF3 at the molecular and physiological level.
Transoid, Ortho, and Gauche Conformers of n-Si4Cl10: Raman and Mid-IR Matrix-Isolation Spectra†

Calculations at the HF/6-31G*, MP2(FC)/6-31G*, and B3LYP/6-31G* levels of theory predict the existence of three pairs of enantiomeric conformers on the potential energy surface of n-Si4Cl10: trans...
Structure, Magnetism, and Magnetoresistance of the Compounds Eu14MnAs11 and Eu14MnP11

The new compounds Eu14MnAs11 and Eu14MnP11 were synthesized from stoichiometric amounts of the elements. The compounds are isotypic to Ca14AlSb11 and crystallize in the tetragonal space group I41/acd (Z = 8). Lattice parameters obtained from single-crystal X-ray diffraction at 130 K are a = 16.318 (2) A, c = 21.684 (4) A and a = 15.930 (4) A, c = 21.213 (5) A for Eu14MnAs11 and Eu14MnP11, respectively. In the refinement of each structure, the central Pn(4) site of a Pn37- linear unit (Pn = As, P) shows positional disorder; this is in contrast to the ordered structures formed when Pn = Sb and Bi. Eu14MnAs11 and Eu14MnP11 are ferromagnetic with transitions at 74 and 52 K, respectively. Eu14MnAs11 also has a low-temperature transition at ∼25 K. Resistivity measurements indicate an insulator-to-metal transition near the magnetic transition, and plots of ln ρ vs 1/T are linear above TC, providing activation energies of 0.03 eV (As; 240−300 K) and 0.31 eV (P). The resistivity is suppressed in the presence of a ...
ChIPWig: a random access-enabling lossless and lossy compression method for ChIP-seq data.

Motivation Chromatin immunoprecipitation sequencing (ChIP-seq) experiments are inexpensive and time-efficient, and result in massive datasets that introduce significant storage and maintenance challenges. To address the resulting Big Data problems, we propose a lossless and lossy compression framework specifically designed for ChIP-seq Wig data, termed ChIPWig. ChIPWig enables random access, summary statistics lookups and it is based on the asymptotic theory of optimal point density design for nonuniform quantizers. Results We tested the ChIPWig compressor on 10 ChIP-seq datasets generated by the ENCODE consortium. On average, lossless ChIPWig reduced the file sizes to merely 6% of the original, and offered 6-fold compression rate improvement compared to bigWig. The lossy feature further reduced file sizes 2-fold compared to the lossless mode, with little or no effects on peak calling and motif discovery using specialized NarrowPeaks methods. The compression and decompression speed rates are of the order of 0.2 sec/MB using general purpose computers. Availability and implementation The source code and binaries are freely available for download at https://github.com/vidarmehr/ChIPWig-v2, implemented in C ++. Contact milenkov@illinois.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Consistency and linearity in quantum theory

Abstract Quantum theory is formulated as the unique way to manipulate amplitudes consistently. The consistency requirement that if an amplitude is calculable in two different ways then the two answers must agree leads to the usual sum and product rules for amplitudes. This implies that the Schrodinger equation must be linear.
Integrative deep models for alternative splicing.

Motivation Advancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work, we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors. Results We perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction in exon skipping events and show it significantly improves model accuracy. Next, we develop a modeling framework that leverages transfer learning to incorporate CLIP-Seq, knockdown and over expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available. Availability and implementation Code and data available at: majiq.biociphers.org/jha_et_al_2017/. Contact yosephb@upenn.edu. Supplementary information Supplementary data are available at Bioinformatics online.
CHARM MIXING IN THE STANDARD MODEL AND BEYOND

The motivation most often cited in searches for $D^0-\overline{D^0}$ mixing and CP-violation in charm system lies with the possibility of observing a signal from New Physics which dominates that from the Standard Model. We review recent theoretical predictions and experimental constraints on $D^0-\overline{D^0}$ mixing parameters, concentrating on possible effects of New Physics.
Asymmetric synthesis of ω-bromo-2(S)-azido acids as precursors for the synthesis of novel amino acids

Abstract A series of ω-bromo-2(S)-azido acids with side-chain lengths ranging from 3–5 methylene units has been synthesized. These intermediates enable the facile synthesis of chiral non-natural amino acids containing virtually any nucleophile capable of substituting the ω-bromo group.
Thermal transport due to liquid jet impingement on superhydrophobic surfaces with isotropic slip: Isoflux wall

Abstract Thermal transport due to a liquid water jet impinging an isoflux superhydrophobic surface with isotropic slip was modeled analytically. An integral analysis of the transport equations resulting in a system of ordinary differential equations was solved numerically. Impingement on superhydrophobic surfaces greatly reduces the heat transfer that occurs relative to a smooth surface due to gas trapped in cavities on the surface. This results in an apparent slip velocity and temperature jump at the surface. Local and average Nusselt numbers are presented as a function of radial position (0 to 45 jet radii), jet Reynolds number ( 3 × 10 3 to 1.5 × 10 4 ), liquid Prandtl number (2 to 11), normalized slip length (0 to 0.2), and normalized temperature jump length (0 to 0.2). All results are compared to classical (no-slip, no temperature jump) behavior on a smooth surface. Although local Nusselt numbers for the isoflux scenario are greater than the corresponding isothermal case, the difference in Nusselt number between these two heating conditions becomes negligible as the temperature jump length increases to quantities realizable on superhydrophobic surfaces. These results may be utilized to explore heat transfer degradation in applications where smooth surfaces are replaced by superhydrophobic surfaces to avoid fouling.
Advances in catalytic, enantioselective aldol addition reactions with novel Ti(IV) complexes

Global competition demands that new pharmaceuticals be prepared using cost-efficient and environmentally benign processes. The discovery and study of chemical reactions for applications in the synthesis of bioactive molecules is, therefore, of paramount importance. Advances in asymmetric catalysis should have an unquestionable impact on the development of chemotherapeutic agents. Here, the authors describe some recent developments from their laboratories in the general area of catalytic, enantioselective C C bond-forming reactions.
Prins cyclization of 4-allyl-1,3-dioxanes prepared from 1,3-diol synthons. A rapid entry into functionalized tetrahydropyrans

Abstract A variety of 4-allyl-1,3-dioxanes were prepared and cyclized to give 4-chloro or 4-acetoxy tetrahydropyrans in good yields and with high stereoselectivity.
Syntheses and binding studies of oligonucleotides containing N-hydroxycarbamate linkages: potential DNA cleaving antisense oligomers

Abstract An efficient synthesis of N-hydroxycarbamate containing thymidine dimer 9 was accomplished and it was incorporated into automatic DNA syntheses to make thymidine 16mers T*-1, T*-2 and T*-3. Binding abilities of T*-1, T*-2 and T*-3 with poly (dA)-16mer were assayed by melting denaturation (Tm) studies of the corresponding duplexes. Iron binding ability of a thymidine oligomer with N-hydroxycarbamate linkages was studied by MALDI-MS. Nuclease stability assays showed that the modified oligonucleotides have enhanced resistance toward nuclease S1 (endonuclease) compared to natural oligonucleotides.
Exfoliated-Restacked Phase of WS2

A modified method for obtaining large quantities of exfoliated single layers of WS2 is reported. The restacked WS2 obtained from the precipitation of the single layers is metastable with respect to...
Applications of Community Detection Techniques to Brain Graphs: Algorithmic Considerations and Implications for Neural Function

The human brain can be represented as a graph in which neural units such as cells or small volumes of tissue are heterogeneously connected to one another through structural or functional links. Brain graphs are parsimonious representations of neural systems that have begun to offer fundamental insights into healthy human cognition, as well as its alteration in disease. A critical open question in network neuroscience lies in how neural units cluster into densely interconnected groups that can provide the coordinated activity that is characteristic of perception, action, and adaptive behaviors. Tools that have proven particularly useful for addressing this question are community detection approaches, which can identify communities or modules: groups of neural units that are densely interconnected with other units in their own group but sparsely interconnected with units in other groups. In this paper, we describe a common community detection algorithm known as modularity maximization, and we detail its application to brain graphs constructed from neuroimaging data. We pay particular attention to important algorithmic considerations, especially in recent extensions of these techniques to graphs that evolve in time. After recounting a few fundamental insights that these techniques have provided into brain function, we highlight potential avenues of methodological advancements for future studies seeking to better characterize the patterns of coordinated activity in the brain that accompany human behavior. This tutorial provides a reader with an introduction to theoretical considerations pertinent to the generation of brain graphs, an understanding of modularity maximization for community detection, a resource of statistical measures that can be used to characterize community structure, and an appreciation of the usefulness of these approaches in uncovering behaviorally relevant network dynamics in neuroimaging data.
Indolyl participation in the Mitsunobu reaction : retention of stereochemistry

Abstract The Mitsunobu reaction of trans -3-(2-hydroxycyclohexyl)indole with phthalimide results in the formation of trans -3-(2-N-phthalimidocyclohexyl)indole, presumably via indolyl participation in the displacement reaction. Involvement of symmetrical intermediate 7 is evidenced by deuterium label scrambling.
Amine-Catalyzed Coupling of Aldehydes and Ketenes Derived from Fischer Carbene Complexes: Formation of β-Lactones and Enol Ethers

Aldehydes react with ketenes generated from photolysis of Fischer chromium carbene complexes to generate either β-lactones or enol ethers resulting from decarboxylation of β-lactones. The reaction is catalyzed by tertiary amines and can occur with diastereoselectivity greater than 20:1 with DMAP as the catalyst.
Technology transfer and adoption for smallholder climate change adaptation: opportunities and challenges

Technologies help build farmer resilience to climate change, but the relationships among technology transfer, adoption, vulnerability, and resilience are not well-understood. This paper empirically...
Blurred Molecular Epidemiological Lines Between the Two Dominant Methicillin-Resistant Staphylococcus aureus Clones.

Background. Methicillin-resistant Staphylococcus aureus (MRSA) causes life-threatening infections in both community and hospital settings and is a leading cause of health care–associated infections (HAIs). We sought to describe the molecular epidemiological landscape of patients with MRSA bloodstream infections (BSIs) at an urban medical center by evaluating the clinical characteristics associated with the two dominant endemic clones. Methods. Comprehensive clinical data from the electronic health records of 227 hospitalized patients ≥18 years old with MRSA BSI over a 33-month period in New York City were collected. The descriptive epidemiology and mortality associated with the two dominant clones were compared using logistic regression. Results. Molecular analysis revealed that 91% of all single-patient MRSA BSIs were due to two equally represented genotypes, clonal complex (CC) 5 (n = 117) and CC8 (n = 110). MRSA BSIs were associated with a 90-day mortality rate of 27%. CC8 caused disease more frequently in younger age groups (56 ± 17 vs 67 ± 17 years old; P < .001) and in those of nonwhite race (odds ratio [OR], 3.45; 95% confidence interval [CI], 1.51–7.87; P = .003), with few other major distinguishing features. Morbidity and mortality also did not differ significantly between the two clones. CC8 caused BSIs more frequently in the setting of peripheral intravenous catheters (OR, 5.96; 95% CI, 1.51–23.50; P = .01). Conclusions. The clinical features distinguishing dominant MRSA clones continue to converge. The association of CC8 with peripheral intravenous catheter infections underscores the importance of classical community clones causing hospital-onset infections. Ongoing monitoring and analysis of the dynamic epidemiology of this endemic pathogen are crucial to inform management and prevent disease.
Power domination throttling

Abstract A power dominating set of a graph G = ( V , E ) is a set S ⊂ V that colors every vertex of G according to the following rules: in the first timestep, every vertex in N [ S ] becomes colored; in each subsequent timestep, every vertex which is the only non-colored neighbor of some colored vertex becomes colored. The power domination throttling number of G is the minimum sum of the size of a power dominating set S and the number of timesteps it takes S to color the graph. In this paper, we determine the complexity of power domination throttling and give some tools for computing and bounding the power domination throttling number. Some of our results apply to very general variants of throttling and to other aspects of power domination.
Exact Lagrangian caps of Legendrian knots

We prove that any Legendrian knot in $(S^3,\xi_{std})$ bounds an exact Lagrangian surface in $\mathbb{R}^4\setminus B^4$ after a sufficient number of stabilizations. In order to show this, we construct a family combinatorial moves on knot projections with some additional data that correspond to Lagrangian cobordisms between knots.
Discretized configurations and partial partitions

We show that the discretized configuration space of $k$ points in the $n$-simplex is homotopy equivalent to a wedge of spheres of dimension $n-k+1$. This space is homeomorphic to the order complex of the poset of ordered partial partitions of $\{1,...,n+1\}$ with exactly $k$ parts. We compute the exponential generating function for the Euler characteristic of this space in two different ways, thereby obtaining a topological proof of a combinatorial recurrence satisfied by the Stirling numbers of the second kind.
Financial Analysis of a Grid-connected Photovoltaic System in South Florida

In this paper the performance and financial analysis of a grid-connected photovoltaic system installed at Florida Atlantic University (FAU) is evaluated. The power plant has the capacity of 14.8 kW and has been under operation since August 2014. This solar PV system is composed of two 7.4 kW sub-arrays, one fixed and one with single axis tracking. First, an overview of the system followed by local weather characteristics in Boca Raton, Florida is presented. In addition, monthly averaged daily solar radiation in Boca Raton as well as system AC are calculated utilizing the PVwatts simulation calculator. Inputs such as module and inverter specifications are applied to the System Advisor Model (SAM) to design and optimize the system. Finally, the estimated local load demand as well as simulation results are extracted and analyzed.
An Exposition of the Connection between Limit-Periodic Potentials and Profinite Groups

We classify the hulls of different limit-periodic potentials and show that the hull of a limit-periodic potential is a procyclic group. We describe how limit-periodic potentials can be generated from a procyclic group and answer arising questions. As an expository paper, we discuss the connection between limit-periodic potentials and profinite groups as completely as possible and review some recent results on Schr¨ odinger operators obtained in this context.
A restriction estimate using polynomial partitioning

If $S$ is a smooth compact surface in $\mathbb{R}^3$ with strictly positive second fundamental form, and $E_S$ is the corresponding extension operator, then we prove that for all $p > 3.25$, $\| E_S f\|_{L^p(\mathbb{R}^3)} \le C(p,S) \| f \|_{L^\infty(S)}$. The proof uses polynomial partitioning arguments from incidence geometry.
Crystallization-Arrested Viscoelastic Phase Separation in Semiconducting Polymer Gels

Through a combination of rheological characterization and temperature-variable imaging methods, a novel gelation pathway in dilute solutions of a semiconducting polymer to achieve interconnected, c...
Bridging The GAP: Simultaneous Fine Tuning for Data Re-Balancing

There are many real-world classification problems wherein the issue of data imbalance (the case when a data set contains substantially more samples for one/many classes than the rest) is unavoidable. While under-sampling the problematic classes is a common solution, this is not a compelling option when the large data class is itself diverse and/or the limited data class is especially small. We suggest a strategy based on recent work concerning limited data problems which utilizes a supplemental set of images with similar properties to the limited data class to aid in the training of a neural network. We show results for our model against other typical methods on a real-world synthetic aperture sonar data set. Code can be found at github.com/JohnMcKay/dataImbalance.
Finite-Height Effect on Electron Energy Structure of Lead Salts Nanorods

The effect of the finite height of a cylindrical lead salt nanorod on its electronic structure is studied within the effective mass formalism. It is demonstrated that, for most practical purposes, it can be accounted for by sampling the sub-band dispersion dependencies of the infinite cylindrical quantum wire of the same radius at wave numbers kz = πnz/H, where H is the nanorod height and nz is an integer. However, under certain conditions, the otherwise degenerate electron energy levels will repel. A detailed account of these conditions is provided.
A Feature Selection Method Based on Shapley Value to False Alarm Reduction in ICUs A Genetic-Algorithm Approach

High false alarm rate in intensive care units (ICUs) has been identified as one of the most critical medical challenges in recent years. This often results in overwhelming the clinical staff by numerous false or unurgent alarms and decreasing the quality of care through enhancing the probability of missing true alarms as well as causing delirium, stress, sleep deprivation and depressed immune systems for patients. One major cause of false alarms in clinical practice is that the collected signals from different devices are processed individually to trigger an alarm, while there exists a considerable chance that the signal collected from one device is corrupted by noise or motion artifacts. In this paper, we propose a low-computational complexity yet accurate game-theoretic feature selection method which is based on a genetic algorithm that identifies the most informative biomarkers across the signals collected from various monitoring devices and can considerably reduce the rate of false alarms 1.
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo

We provide convergence guarantees in Wasserstein distance for a variety of variance-reduction methods: SAGA Langevin diffusion, SVRG Langevin diffusion and control-variate underdamped Langevin diffusion. We analyze these methods under a uniform set of assumptions on the log-posterior distribution, assuming it to be smooth, strongly convex and Hessian Lipschitz. This is achieved by a new proof technique combining ideas from finite-sum optimization and the analysis of sampling methods. Our sharp theoretical bounds allow us to identify regimes of interest where each method performs better than the others. Our theory is verified with experiments on real-world and synthetic datasets.
DiffuserCam: lensless single-exposure 3D imaging

We demonstrate a compact, easy-to-build computational camera for single-shot three-dimensional (3D) imaging. Our lensless system consists solely of a diffuser placed in front of an image sensor. Every point within the volumetric field-of-view projects a unique pseudorandom pattern of caustics on the sensor. By using a physical approximation and simple calibration scheme, we solve the large-scale inverse problem in a computationally efficient way. The caustic patterns enable compressed sensing, which exploits sparsity in the sample to solve for more 3D voxels than pixels on the 2D sensor. Our 3D reconstruction grid is chosen to match the experimentally measured two-point optical resolution, resulting in 100 million voxels being reconstructed from a single 1.3 megapixel image. However, the effective resolution varies significantly with scene content. Because this effect is common to a wide range of computational cameras, we provide a new theory for analyzing resolution in such systems.
Simulation Factory: Taming application configuration and workflow on high-end resources

Computational Science on large high performance computing resources is hampered by the complexity of these systems. Much of this complexity is due to low-level details on these resources that are exposed to the application and the end user. This includes (but is not limited to) mechanisms for remote access, configuring and building applications from source code, and managing simulations and their output files via batch queue systems.
Filters in the partition lattice

Given a filter $$\Delta $$Δ in the poset of compositions of n, we form the filter $$\Pi ^{*}_{\Delta }$$źΔź in the partition lattice. We determine all the reduced homology groups of the order complex of $$\Pi ^{*}_{\Delta }$$źΔź as $${\mathfrak S}_{n-1}$$Sn-1-modules in terms of the reduced homology groups of the simplicial complex $$\Delta $$Δ and in terms of Specht modules of border shapes. We also obtain the homotopy type of this order complex. These results generalize work of Calderbank---Hanlon---Robinson and Wachs on the d-divisible partition lattice. Our main theorem applies to a plethora of examples, including filters associated with integer knapsack partitions and filters generated by all partitions having block sizes a or b. We also obtain the reduced homology groups of the filter generated by all partitions having block sizes belonging to the arithmetic progression $$a, a + d, \ldots , a + (a-1) \cdot d$$a,a+d,ź,a+(a-1)·d, extending work of Browdy.
Intersections of three quadrics in $\mathbb{P}^7$

We study rationality properties of smooth complete intersections of three quadrics in $\mathbb{P}^7$. We exhibit a smooth family of such intersections with both rational and non-rational fibers.
The structure of sobolev extension operators

Let $L^{m,p}(\R^n)$ denote the Sobolev space of functions whose $m$-th derivatives lie in $L^p(\R^n)$, and assume that $p>n$. For $E \subset \R^n$, denote by $L^{m,p}(E)$ the space of restrictions to $E$ of functions $F \in L^{m,p}(\R^n)$. It is known that there exist bounded linear maps $T : L^{m,p}(E) \rightarrow L^{m,p}(\R^n)$ such that $Tf = f$ on $E$ for any $f \in L^{m,p}(E)$. We show that $T$ cannot have a simple form called "bounded depth."
The Influence of Behavioral Relevance on the Processing of Global Scene Properties: An ERP Study

Abstract Recent work studying the temporal dynamics of visual scene processing (Harel et al., 2016) has found that global scene properties (GSPs) modulate the amplitude of early Event-Related Potentials (ERPs). It is still not clear, however, to what extent the processing of these GSPs is influenced by their behavioral relevance, determined by the goals of the observer. To address this question, we investigated how behavioral relevance, operationalized by the task context impacts the electrophysiological responses to GSPs. In a set of two experiments we recorded ERPs while participants viewed images of real-world scenes, varying along two GSPs, naturalness (manmade/natural) and spatial expanse (open/closed). In Experiment 1, very little attention to scene content was required as participants viewed the scenes while performing an orthogonal fixation-cross task. In Experiment 2 participants saw the same scenes but now had to actively categorize them, based either on their naturalness or spatial expense. We found that task context had very little impact on the early ERP responses to the naturalness and spatial expanse of the scenes: P1, N1, and P2 could distinguish between open and closed scenes and between manmade and natural scenes across both experiments. Further, the specific effects of naturalness and spatial expanse on the ERP components were largely unaffected by their relevance for the task. A task effect was found at the N1 and P2 level, but this effect was manifest across all scene dimensions, indicating a general effect rather than an interaction between task context and GSPs. Together, these findings suggest that the extraction of global scene information reflected in the early ERP components is rapid and very little influenced by top-down observer-based goals.
On estimates for the Fu–Yau generalization of a Strominger system

We study an equation proposed by Fu and Yau as a natural n-dimensional generalization of a Strominger system that they solved in dimension 2. It is a complex Hessian equation with right hand side depending on gradients. Building on the methods of Fu and Yau, we obtain C0, C2, and C2,α a priori estimates. We also identify difficulties in extending the Fu-Yau arguments for non-degeneracy from dimension 2 to higher dimensions.
A simple optimal binary representation of mosaic floorplans and Baxter permutations

Mosaic floorplans are rectangular structures subdivided into smaller rectangular sections and are widely used in VLSI circuit design. Baxter permutations are a set of permutations that have been shown to have a one-to-one correspondence to objects in the Baxter combinatorial family, which includes mosaic floorplans. An important problem in this area is to find short binary string representations of the set of n-block mosaic floorplans and Baxter permutations of length n. The best known representation is the Quarter-State Sequence which uses 4n bits. This paper introduces a simple binary representation of n-block mosaic floorplan using 3n−3 bits. It has been shown that any binary representation of n-block mosaic floorplans must use at least (3n−o(n)) bits. Therefore, the representation presented in this paper is optimal (up to an additive lower order term).
Deep Learning for Joint Source-Channel Coding of Text

We consider the problem of joint source and channel coding of structured data such as natural language over a noisy channel. The typical approach to this problem in both theory and practice involves performing source coding to first compress the text and then channel coding to add robustness for the transmission across the channel. This approach is optimal in terms of minimizing end-to-end distortion with arbitrarily large block lengths of both the source and channel codes when transmission is over discrete memoryless channels. However, the optimality of this approach is no longer ensured for documents of finite length and limitations on the length of the encoding. We will show in this scenario that we can achieve lower word error rates by developing a deep learning based encoder and decoder. While the approach of separate source and channel coding would minimize bit error rates, our approach preserves semantic information of sentences by first embedding sentences in a semantic space where sentences closer in meaning are located closer together, and then performing joint source and channel coding on these em-beddings.
Modeling Customer Engagement from Partial Observations

It is of high interest for a company to identify customers expected to bring the largest profit in the upcoming period. Knowing as much as possible about each customer is crucial for such predictions. However, their demographic data, preferences, and other information that might be useful for building loyalty programs is often missing. Additionally, modeling relations among different customers as a network can be beneficial for predictions at an individual level, as similar customers tend to have similar purchasing patterns. We address this problem by proposing a robust framework for structured regression on deficient data in evolving networks with a supervised representation learning based on neural features embedding. The new method is compared to several unstructured and structured alternatives for predicting customer behavior (e.g. purchasing frequency and customer ticket) on user networks generated from customer databases of two companies from different industries. The obtained results show 4% to 130% improvement in accuracy over alternatives when all customer information is known. Additionally, the robustness of our method is demonstrated when up to 80% of demographic information was missing where it was up to several folds more accurate as compared to alternatives that are either ignoring cases with missing values or learn their feature representation in an unsupervised manner.
Growth of Turaev–Viro invariants and cabling

The Chen–Yang volume conjecture [Q. Chen and T. Yang, Volume conjectures for the Reshetikhin–Turaev and the Turaev–Viro invariants, preprint (2015), arXiv:1503.02547] states that the growth rate of...
Coherence conditions in flat regular pullbacks

Abstract We investigate the behavior of four coherent-like conditions in regular conductor squares. In particular, we find necessary and sufficient conditions in order that a pullback ring be a finite conductor ring, a coherent ring, a generalized GCD ring, or quasi-coherent ring. As an application of these results, we are able to determine exactly when the ring of integer-valued polynomials determined by a finite subset possesses one of the four coherent-like properties.
Deep Cross Residual Learning for Multitask Visual Recognition

Residual learning has recently surfaced as an effective means of constructing very deep neural networks for object recognition. However, current incarnations of residual networks do not allow for the modeling and integration of complex relations between closely coupled recognition tasks or across domains. Such problems are often encountered in multimedia applications involving large-scale content recognition. We propose a novel extension of residual learning for deep networks that enables intuitive learning across multiple related tasks using cross-connections called cross-residuals. These cross-residuals connections can be viewed as a form of in-network regularization and enables greater network generalization. We show how cross-residual learning (CRL) can be integrated in multitask networks to jointly train and detect visual concepts across several tasks. We present a single multitask cross-residual network with >40% less parameters that is able to achieve competitive, or even better, detection performance on a visual sentiment concept detection problem normally requiring multiple specialized single-task networks. The resulting multitask cross-residual network also achieves better detection performance by about 10.4% over a standard multitask residual network without cross-residuals with even a small amount of cross-task weighting.
"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

Automatic fake news detection is a challenging problem in deception detection, and it has tremendous real-world political and social impacts. However, statistical approaches to combating fake news has been dramatically limited by the lack of labeled benchmark datasets. In this paper, we present LIAR: a new, publicly available dataset for fake news detection. We collected a decade-long, 12.8K manually labeled short statements in various contexts from PolitiFact.com, which provides detailed analysis report and links to source documents for each case. This dataset can be used for fact-checking research as well. Notably, this new dataset is an order of magnitude larger than previously largest public fake news datasets of similar type. Empirically, we investigate automatic fake news detection based on surface-level linguistic patterns. We have designed a novel, hybrid convolutional neural network to integrate meta-data with text. We show that this hybrid approach can improve a text-only deep learning model.
Small amplitude traveling waves in the full-dispersion Whitham equation

In this article, we provide an alternative way to construct small amplitude traveling waves for general Whitham type equations, in both periodic and whole line contexts. More specifically, Fourier analysis techniques allow us to reformulate the problem to the study of waves that are small and regular perturbations of well-understood ODE’s. In addition, rigorous spectral stability of these waves is established.
Voltage multi-stability in distribution grids with power flow reversal

In future distribution grids with high penetration of distributed generators more stable solutions may appear because of active or reactive power reversal. The systems can operate at very different states, and additional control measures may be required to ensure that it remains at the appropriate point. Under typical scenarios such as subjected to disturbances or load shedding, the system may be trapped at another stable equilibrium without violating any voltage constraints. In other words, the stable equilibrium is viable. This paper aims to analyze how the distribution system converge to the second stable and viable equilibrium. The dynamic simulations are carried out using Wolfram System Modeler. The results are then analyzed and explained from various viewpoints giving better understanding of the system dynamics. In order to prevent undesired situations, new policies such as regulating reactive power compensations have been proposed. Moreover, a generic dynamic load modeling is developed to capture the essential dynamic characteristics of most of popular loads in power systems.
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection

Automated analysis methods are crucial aids for monitoring and defending a network to protect the sensitive or confidential data it hosts. This work introduces a flexible, powerful, and unsupervised approach to detecting anomalous behavior in computer and network logs; one that largely eliminates domain-dependent feature engineering employed by existing methods. By treating system logs as threads of interleaved ``sentences'' (event log lines) to train online unsupervised neural network language models, our approach provides an adaptive model of normal network behavior. We compare the effectiveness of both standard and bidirectional recurrent neural network language models at detecting malicious activity within network log data. Extending these models, we introduce a tiered recurrent architecture, which provides context by modeling sequences of users' actions over time. Compared to Isolation Forest and Principal Components Analysis, two popular anomaly detection algorithms, we observe superior performance on the Los Alamos National Laboratory Cyber Security dataset. For log-line-level red team detection, our best performing character-based model provides test set area under the receiver operator characteristic curve of 0.98, demonstrating the strong fine-grained anomaly detection performance of this approach on open vocabulary logging sources.
On logarithmic improvements of critical geodesic restriction bounds in the presence of nonpositive curvature

We consider upper bounds on the growth of L p norms of restrictions of eigenfunctions and spectral clusters to geodesic segments in a nonpositively curved manifold in the high frequency limit. This sharpens results of Chen and Sogge as well as Xi and Zhang, which showed that the crux of the problem is to establish bounds on the mixed partials of the distance function on the covering manifold restricted to geodesic segments. The innovation in this work is the development of a formula for the third variation of arc length on the covering manifold, which allows for a coordinate free expressions of these mixed partials.
Strong Successive Refinability and Rate-Distortion-Complexity Tradeoff

We investigate the second order asymptotics (source dispersion) of the successive refinement problem. Similar to the classical definition of a successively refinable source, we say that a source is strongly successively refinable if successive refinement coding can achieve the second order optimum rate (including the dispersion terms) at both decoders. We establish a sufficient condition for strong successive refinability. We show that any discrete source under Hamming distortion and the Gaussian source under quadratic distortion are strongly successively refinable. We also demonstrate how successive refinement ideas can be used in point-to-point lossy compression problems in order to reduce complexity. We give two examples, the binary-Hamming and Gaussian-quadratic cases, in which a layered code construction results in a low complexity scheme that attains optimal performance. For example, when the number of layers grows with the block length $n$ , we show how to design an $O(n^{\log (n)})$ algorithm that asymptotically achieves the rate-distortion bound.
Invariant trilinear forms for spherical degenerate principal series of complex symplectic groups

We compute generalized Bernstein–Reznikov integrals associated with standard complex symplectic forms by studying Knapp–Stein intertwining operators between spherical degenerate principal series of Sp(n, ℂ).