cssi/SciSciGPT-SciSciNet huggingface dataset:
A mechanistic first–passage time framework for bacterial cell-division timing

How exponentially growing cells maintain size homeostasis is an important fundamental problem. Recent single-cell studies in prokaryotes have uncovered the adder principle, where cells on average, add a fixed size (volume) from birth to division. Interestingly, this added volume differs considerably among genetically-identical newborn cells with similar sizes suggesting a stochastic component in the timing of cell-division. To mechanistically explain the adder principle, we consider a time-keeper protein that begins to get stochastically expressed after cell birth at a rate proportional to the volume. Cell-division time is formulated as the first-passage time for protein copy numbers to hit a fixed threshold. Consistent with data, the model predicts that while the mean cell-division time decreases with increasing size of newborns, the noise in timing increases with size at birth. Intriguingly, our results show that the distribution of the volume added between successive cell-division events is independent of the newborn cell size. This was dramatically seen in experimental studies, where histograms of the added volume corresponding to different newborn sizes collapsed on top of each other. The model provides further insights consistent with experimental observations: the distributions of the added volume and the cell-division time when scaled by their respective means become invariant of the growth rate. Finally, we discuss various modifications to the proposed model that lead to deviations from the adder principle. In summary, our simple yet elegant model explains key experimental findings and suggests a mechanism for regulating both the mean and fluctuations in cell-division timing for size control.
Intramolecular cyclization of aryl substituted iodonium ylides with copper(I) chloride

Abstract Cu(I)Cl decomposition of the phenyliodonium ylides derived from o-, m- and p-methoxyphenyl-3-ketopentanoic acid methyl esters affords the corresponding 5-, 6- and 7-methoxy-1-carbomethoxy-2-tetralones in preparative yields. The lower homologous phenyliodonium ylides derived from o-, m- and p-methoxyphenyl-3-ketobutyric acid methyl esters yield the analogous 1-carbomethoxy-2-indanone only in the meta-methoxyphenyl case, and the ortho- and para-methoxyphenyl substituted iodonium ylides yield dimeric products.
Improved synthesis of (4-ethenylphenyl)diphenyl methanol and its application in the preparation of trityl functionalized polystyrene resin containing tetrahydrofuran derived cross-linker

Abstract An improved and straightforward synthesis of (4-ethenylphenyl)diphenyl methanol is described. This monomer was used in the preparation of trityl functionalized polystyrene containing a flexible tetrahydrofuran cross-linker, giving rise to a suitable support for solid-phase organic synthesis.
A Non-Dicer RNase III and Four Other Novel Factors Required for RNAi-Mediated Transposon Suppression in the Human Pathogenic Yeast Cryptococcus neoformans

The human pathogenic yeast Cryptococcus neoformans silences transposable elements using endo-siRNAs and an Argonaute, Ago1. Endo-siRNAs production requires the RNA-dependent RNA polymerase, Rdp1, and two partially redundant Dicer enzymes, Dcr1 and Dcr2, but is independent of histone H3 lysine 9 methylation. We describe here an insertional mutagenesis screen for factors required to suppress the mobilization of the C. neoformans HARBINGER family DNA transposon HAR1 Validation experiments uncovered five novel genes (RDE1-5) required for HAR1 suppression and global production of suppressive endo-siRNAs. The RDE genes do not impact transcript levels, suggesting the endo-siRNAs do not act by impacting target transcript synthesis or turnover. RDE3 encodes a non-Dicer RNase III related to S. cerevisiae Rnt1, RDE4 encodes a predicted terminal nucleotidyltransferase, while RDE5 has no strongly predicted encoded domains. Affinity purification-mass spectrometry studies suggest that Rde3 and Rde5 are physically associated. RDE1 encodes a G-patch protein homologous to the S. cerevisiae Sqs1/Pfa1, a nucleolar protein that directly activates the essential helicase Prp43 during rRNA biogenesis. Rde1 copurifies Rde2, another novel protein obtained in the screen, as well as Ago1, a homolog of Prp43, and numerous predicted nucleolar proteins. We also describe the isolation of conditional alleles of PRP43, which are defective in RNAi. This work reveals unanticipated requirements for a non-Dicer RNase III and presumptive nucleolar factors for endo-siRNA biogenesis and transposon mobilization suppression in C. neoformans.
Synthesis of (+)-1-deoxygalactonojirimycin and a related indolizidine

Abstract Amido-alcohol 1 is transformed via aminal 2 into 1-deoxygalactonojirimycin ( 3 ) and the structurally related indolizidine 4 .
An application of electronic asymmetry to highly enantioselective catalytic Diels-Alder reactions.

The compounds (RRu)-[CyRuCl(S)-BINPO]SbF6 and [CyRuCl(S)-TolBINPO]SbF6 (Cy = η6-cymene), were synthesized from (CyRuCl2)2 and the appropriate non-C2-symmetric bisphosphine monoxide ligands (S)-BINPO and (S)-TolBINPO (BINPO = 2,2‘-bis(diphenylphosphino)-1,1‘-binaphthyl) in the presence of NaSbF6. When these complexes were mixed with AgSbF6 the resulting Lewis acids catalyzed the Diels−Alder cycloaddition of cyclopentadiene and methacrolein. The product (2S)-methylbicyclo[2.2.1]hept-5-ene-2-carboxaldehyde was obtained with excellent diastereoselectivity (up to 99%) and enantioselectivity (up to 99%) in several cases. When the complexes containing the analogous C2-symmetric bisphosphine ligands (S)-BINAP and (S)-TolBINAP were employed as catalysts, the Diels−Alder cycloadducts were obtained with much lower enantioselectivity (19 to 50%) for the opposite antipode. Although some of the effect may arise from chelate ring size change, much of the enhanced stereoselectivity of (RRu)-[CyRuCl(S)-BINPO]SbF6 and [CyR...
Relief of the Dma1-mediated checkpoint requires Dma1 autoubiquitination and dynamic localization.

Spindle pole body (SPB) localization of the ubiquitin ligase Dma1 is required for its function in a mitotic checkpoint that stalls cytokinesis during a mitotic stress. We found that Dma1 autoubiqui...
Preparative-scale synthesis of 3,3,3-trifluoropropene oxide

Bromination of 3,3,3-trifluoropropene in 20% oleum, followed by treatment with acetic acid furnishes 2-bromo-3,3,3-trifluoropropyl acetate in quantitative yield, which upon acid hydrolysis and cyclization with alkali affords 3,3,3-trifluoropropene oxide (TFPO) in 63% overall yield.
Hydrogen in Polar Intermetallics. Binary Pnictides of Divalent Metals with Mn5Si3-type Structures and Their Isotypic Ternary Hydride Solutions

Studies of the hydrogen-free binary A5Pn3 systems for A = Ca, Sr, Ba, Sm, Eu, Yb and Pn (pnictogen) = As, Sb, Bi, reveal four new examples, (Ca,Yb)5Bi3 and Eu5(Sb,Bi)3, among the 16 that form with a hexagonal (P63/mcm) Mn5Si3-type structure. Most of the previous literature on unit cell dimensions for these correspond to those of smaller ternary hydrides (or other materials). Previously reported Ba5As3 and cubic SmAs could not be reproduced. New cubic anti-Th3P4 phases are also found in the Sm−As and Ba−Sb−F systems. Crystal structures have been refined from single-crystal X-ray data for hexagonal Sr5As3H∼1, Ca5Sb3, Ba5Sb3H∼0.7, Sm5Sb3H∼1, Eu5Sb3, Yb5Sb3, and Eu5Bi3. The widths of H solubility regions in the hexagonal parent structures in terms of cell constant changes have been determined for 12 examples, eight of which with more hydrogen further convert into known orthorhombic Ca5Sb3F-type phases. The Sm5Sb3 and Sm5Bi3 members contain trivalent cations according to several criteria. Magnetic susceptibili...
Significant distinct branches of hierarchical trees: a framework for statistical analysis and applications to biological data.

One of the most common goals of hierarchical clustering is finding those branches of a tree that form quantifiably distinct data subtypes. Achieving this goal in a statistically meaningful way requires (a) a measure of distinctness of a branch and (b) a test to determine the significance of the observed measure, applicable to all branches and across multiple scales of dissimilarity. We formulate a method termed Tree Branches Evaluated Statistically for Tightness (TBEST) for identifying significantly distinct tree branches in hierarchical clusters. For each branch of the tree a measure of distinctness, or tightness, is defined as a rational function of heights, both of the branch and of its parent. A statistical procedure is then developed to determine the significance of the observed values of tightness. We test TBEST as a tool for tree-based data partitioning by applying it to five benchmark datasets, one of them synthetic and the other four each from a different area of biology. For each dataset there is a well-defined partition of the data into classes. In all test cases TBEST performs on par with or better than the existing techniques. Based on our benchmark analysis, TBEST is a tool of choice for detection of significantly distinct branches in hierarchical trees grown from biological data. An R language implementation of the method is available from the Comprehensive R Archive Network: http://www.cran.r-project.org/web/packages/TBEST/index.html .
Cycloadditions of Ketene Diethyl Acetal and 2-Methylene-1,3-dioxepane to Electrophilic Alkenes†

Reactions of strong electron-rich donor alkenes with strong electron-poor acceptor alkenes give a variety of products, including cyclobutanes, cyclohexanes composed of two alkenes of one kind and one of the other, open chain adducts, and homopolymers of the alkenes. We examined cycloadditions of ketene diethyl acetal and 2-methylene-1,3-dioxepane to alkenes containing from one to four acceptor groups. The products and rates, in particular the structure of the cyclohexane adducts produced, are correlated with the ionic homopolymerizability of the alkenes, zwitterion stabilization, and gem-dialkyl cyclization effects. These concepts are extended to enamines and enolate anions as other electron-rich alkenes. 2-Methylene-1,3-dioxepane is the ketene acetal of choice for the preparation of many cyclobutanes, presumably due to the instability of the cationic end of the initial zwitterion from this cyclic ketene acetal relative to those from acyclic ketene acetals.
Biology and Bias in Cell Type-Specific RNAseq of Nucleus Accumbens Medium Spiny Neurons

Subcellular RNAseq promises to dissect transcriptional dynamics but is not well characterized. Furthermore, FACS may introduce bias but has not been benchmarked genome-wide. Finally, D1 and D2 dopamine receptor-expressing medium spiny neurons (MSNs) of the nucleus accumbens (NAc) are fundamental to neuropsychiatric traits but have only a short list of canonical surface markers. We address these gaps by systematically comparing nuclear-FACS, whole cell-FACS, and RiboTag affinity purification from D1- and D2-MSNs. Using differential expression, variance partitioning, and co-expression, we identify the following trade-offs for each method. RiboTag-seq best distinguishes D1- and D2-MSNs but has the lowest transcriptome coverage. Nuclear-FACS-seq generates the most differentially expressed genes and overlaps significantly with neuropsychiatric genetic risk loci, but un-annotated genes hamper interpretation. Whole cell-FACS is more similar to nuclear-FACS than RiboTag, but captures aspects of both. Using pan-method approaches, we discover that transcriptional regulation is predominant in D1-MSNs, while D2-MSNs tend towards cytosolic regulation. We are also the first to find evidence for moderate sexual dimorphism in these cell types at baseline. As these results are from 49 mice (nmale = 39, nfemale = 10), they represent generalizable ground-truths. Together, these results guide RNAseq methods selection, define MSN transcriptomes, highlight neuronal sex differences, and provide a baseline for D1- and D2-MSNs.
O-Alkylation of 3-hydroxy-1-phenyl-2-pyrazolin-5-one

3-Hydroxy-1-phenyl-2-pyrazolin-5-one 1 reacts with primary, secondary and allylic alcohols under catalytic acidic conditions and in the presence of 3 A molecular sieves, to afford 3-alkoxy-1-phenyl-2-pyrazolin-5-ones 3.
trans-Pd(OAc)2(Cy2NH)2 catalyzed Suzuki coupling reactions and its temperature-dependent activities toward aryl bromides

Abstract A new catalytic system based on Pd-simple amines for Suzuki coupling reactions of aryl bromides is described. A well-defined air-stable complex, trans-Pd(OAc)2(Cy2NH)2 effectively promotes Suzuki couplings of aryl bromides with a range of aryl boronic acids to give diaryl products in high yields. It also exhibits temperature-dependent activity toward aryl bromides bearing different electronic substituents under reaction conditions.
Online Algorithms for POMDPs with Continuous State, Action, and Observation Spaces.

Online solvers for partially observable Markov decision processes have been applied to problems with large discrete state spaces, but continuous state, action, and observation spaces remain a challenge. This paper begins by investigating double progressive widening (DPW) as a solution to this challenge. However, we prove that this modification alone is not sufficient because the belief representations in the search tree collapse to a single particle causing the algorithm to converge to a policy that is suboptimal regardless of the computation time. This paper proposes and evaluates two new algorithms, POMCPOW and PFT-DPW, that overcome this deficiency by using weighted particle filtering. Simulation results show that these modifications allow the algorithms to be successful where previous approaches fail.
Novel epimerization of aromatic C-nucleosides with electron-withdrawing substituents with trifluoroacetic acid-benzenesulfonic acid using mild conditions

Abstract Trifluoroacetic acid and benzenesulfonic acid in dichloromethane at ambient temperature have been found to be efficient co-catalysts for the epimerization of C -nucleosides with electron-withdrawing substituents. This approach provides a convenient route to the β anomer of the nucleosides with high yields in the range 54–78%. Synthesis of the 3′-phosphoramidite of 2,4-difluorophenyl C -nucleoside suitable for solid-phase DNA synthesis is described.
Structures of Cribochalines A and B, Branched-Chain Methoxylaminoalkyl Pyridines from the Micronesian Sponge, Cribochalina sp. Absolute Configuration and Enantiomeric Purity of Related O-Methyl Oximes

Two new 3-alkyl pyridines, cribochalines A (2) and B (3), were isolated from the North Pacific sponge Cribochalina sp. The known related oxime, ikimine A, was shown to be a 2.8:1 mixture of the (S)- and (R)-enantiomers. Cribochaline A exhibited antifungal activity against Candida albicans ATCC and Fluconazole-resistant strains C. albicans 96–489, C. krusei and C. glabrata.
Reactive dienes: intramolecular aromatic oxidation of 3-(2-hydroxyphenyl)-propionic acids.

Treatment of 3-(2-hydroxyphenyl)-propionic acids with a hypervalent iodine reagent in the presence of a dienophile initiates a tandem intramolecular aromatic oxidation/Diels−Alder reaction. Herein we report (1) investigations on the scope and limitations of this novel reaction combination and (2) preliminary diastereoselectivity studies using α- and β-substituted acids.
Omnivory does not preclude strong trophic cascades

Author(s): Fahimipour, AK; Levin, DA; Anderson, KE | Abstract: Omnivory has been cited as an explanation for why trophic cascades are weak in many ecosystems, but empirical support for this prediction is equivocal. Compared to predators that feed only on herbivores, top omnivores-species that feed on both herbivores and primary producers-have been observed generating cascades ranging from strong to moderate, null, and negative. To gain intuition about the sensitivity of cascades to omnivory, we analyzed models describing systems with top omnivores that display either fixed or flexible diets, two foraging strategies that are supported by empirical observations. We identified regions of parameter space, wherein omnivores following a fixed foraging strategy, with herbivores and producers comprising a constant proportion of the diet, non-intuitively generate stronger cascades than predators that are otherwise demographically identical: (1) high productivity relative to herbivore mortality and (2) small discrepancies in producer vs. herbivore reward create conditions in which cascades are stronger with moderate omnivory. In contrast, flexible omnivores that attempt to optimize per capita growth rates during search never induce cascades that are stronger than the case of predators. Although we focus on simple models, the consistency of these general patterns together with prior empirical evidence suggests that omnivores should not be uniformly ruled out as agents of strong trophic cascades.
Timing in chemical reaction networks

Chemical reaction networks (CRNs) formally model chemistry in a well-mixed solution. CRNs are widely used to describe information processing occurring in natural cellular regulatory networks, and with upcoming advances in synthetic biology, CRNs are a promising programming language for the design of artificial molecular control circuitry. Due to a formal equivalence between CRNs and a model of distributed computing known as population protocols, results transfer readily between the two models.We show that if a CRN respects finite density (at most O(n) additional molecules can be produced from n initial molecules), then starting from any dense initial configuration (all molecular species initially present have initial count Ω(n), where n is the initial molecular count and volume), every producible species is produced in constant time with high probability.This implies that no CRN obeying the stated constraints can function as a timer, able to produce a molecule, but doing so only after a time that is an unbounded function of the input size. This has consequences regarding an open question of Angluin, Aspnes, and Eisenstat concerning the ability of population protocols to perform fast, reliable leader election and to simulate arbitrary algorithms from a uniform initial state.
Gap eigenvalues and asymptotic dynamics of geometric wave equations on hyperbolic space

In this paper we study k -equivariant wave maps from the hyperbolic plane into the 2-sphere as well as the energy critical equivariant SU(2) S U ( 2 ) Yang–Mills problem on 4-dimensional hyperbolic space. The latter problem bears many similarities to a 2-equivariant wave map into a surface of revolution. As in the case of 1-equivariant wave maps considered in [9] , both problems admit a family of stationary solutions indexed by a parameter that determines how far the image of the map wraps around the target manifold. Here we show that if the image of a stationary solution is contained in a geodesically convex subset of the target, then it is asymptotically stable in the energy space. However, for a stationary solution that covers a large enough portion of the target, we prove that the Schrodinger operator obtained by linearizing about such a harmonic map admits a simple positive eigenvalue in the spectral gap. As there is no a priori nonlinear obstruction to asymptotic stability, this gives evidence for the existence of metastable states (i.e., solutions with anomalously slow decay rates) in these simple geometric models.
Hasse principle for hermitian spaces over semi-global fields

Abstract In a recent paper, Colliot-Thelene, Parimala and Suresh conjectured that a local–global principle holds for projective homogeneous spaces under connected linear algebraic groups over function fields of p-adic curves. In this paper, we show that the conjecture is true for any linear algebraic group whose almost simple factors of its semisimple part are isogenous to unitary groups or special unitary groups of hermitian or skew-hermitian spaces over central simple algebras with involutions. The proof implements patching techniques of Harbater, Hartmann and Krashen. As an application, we obtain a Springer-type theorem for isotropy of hermitian spaces over odd degree extensions of function fields of p-adic curves.
Successive Refinement of Abstract Sources

In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain the target distortions at each decoding stage. In this paper, we derive a parametric characterization of the rate-distortion region for successive refinement of abstract sources. Our characterization extends Csiszar’s result to successive refinement, and generalizes a result by Tuncel and Rose, applicable for finite alphabet sources, to abstract sources. This characterization spawns a family of outer bounds to the rate-distortion region. It also enables an iterative algorithm for computing the rate-distortion region, which generalizes Blahut’s algorithm to successive refinement. Finally, it leads a new nonasymptotic converse bound. In all the scenarios where the dispersion is known, this bound is second-order optimal. In our proof technique, we avoid Karush–Kuhn–Tucker conditions of optimality, and we use basic tools of probability theory. We leverage the Donsker–Varadhan lemma for the minimization of relative entropy on abstract probability spaces.
Moduli spaces of semitoric systems

Abstract Recently Pelayo–Vũ Ngọc classified simple semitoric integrable systems in terms of five symplectic invariants. Using this classification we define a family of metrics on the space of semitoric integrable systems. The resulting metric space is incomplete and we construct the completion.
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large number of samples to achieve good performance. Model-based algorithms, in principle, can provide for much more efficient learning, but have proven difficult to extend to expressive, high-capacity models such as deep neural networks. In this work, we demonstrate that neural network dynamics models can in fact be combined with model predictive control (MPC) to achieve excellent sample complexity in a model-based reinforcement learning algorithm, producing stable and plausible gaits that accomplish various complex locomotion tasks. We further propose using deep neural network dynamics models to initialize a model-free learner, in order to combine the sample efficiency of model-based approaches with the high task-specific performance of model-free methods. We empirically demonstrate on MuJoCo locomotion tasks that our pure model-based approach trained on just random action data can follow arbitrary trajectories with excellent sample efficiency, and that our hybrid algorithm can accelerate model-free learning on high-speed benchmark tasks, achieving sample efficiency gains of $3-5\times$ on swimmer, cheetah, hopper, and ant agents. Videos can be found at https://sites.google.com/view/mbmf
Graded-irreducible modules are irreducible

ABSTRACTWe show that if a graded submodule of a Noetherian module cannot be written as a proper intersection of graded submodules, then it cannot be written as a proper intersection of submodules at all. More generally, we show that a natural extension of the index of reducibility to the graded setting coincides with the ordinary index of reducibility. We also investigate the question of uniqueness of the components in a graded-irreducible decomposition, as well as the relation between the index of reducibility of a non-graded ideal and that of its largest graded subideal.
Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM)

Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis, a need that can potentially be met by novel microscopy methods. We present a quantitative method for label-free breast tissue evaluation using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective, label-free and potentially automatable method for breast histopathology. We demonstrated our method by imaging a tissue microarray consisting of 68 different subjects −34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. Our disease signatures represent intrinsic physical attributes of the sample, independent of staining quality, facilitating classification through machine learning packages since our images do not vary from scan to scan or instrument to instrument.
Convex fused lasso denoising with non-convex regularization and its use for pulse detection

We propose a convex formulation of the fused lasso signal approximation problem consisting of non-convex penalty functions. The fused lasso signal model aims to estimate a sparse piecewise constant signal from a noisy observation. Originally, the l1 norm was used as a sparsity-inducing convex penalty function for the fused lasso signal approximation problem. However, the l1 norm underestimates signal values. Non-convex sparsity-inducing penalty functions better estimate signal values. In this paper, we show how to ensure the convexity of the fused lasso signal approximation problem with non-convex penalty functions. We further derive a computationally efficient algorithm using the majorization-minimization technique. We apply the proposed fused lasso method for the detection of pulses.
Atoms of multistationarity in chemical reaction networks

Chemical reaction systems are dynamical systems that arise in chemical engineering and systems biology. In this work, we consider the question of whether the minimal (in a precise sense) multistationary chemical reaction networks, which we propose to call ‘atoms of multistationarity,’ characterize the entire set of multistationary networks. Our main result states that the answer to this question is ‘yes’ in the context of fully open continuous-flow stirred-tank reactors (CFSTRs), which are networks in which all chemical species take part in the inflow and outflow. In order to prove this result, we show that if a subnetwork admits multiple steady states, then these steady states can be lifted to a larger network, provided that the two networks share the same stoichiometric subspace. We also prove an analogous result when a smaller network is obtained from a larger network by ‘removing species.’ Our results provide the mathematical foundation for a technique used by Siegal- Gaskins et al. of establishing bistability by way of ‘network ancestry.’ Additionally, our work provides sufficient conditions for establishing multistationarity by way of atoms and moreover reduces the problem of classifying multistationary CFSTRs to that of cataloging atoms of multistationarity. As an application, we enumerate and classify all 386 bimolecular and reversible two-reaction networks. Of these, exactly 35 admit multiple positive steady states. Moreover, each admits a unique minimal multistationary subnetwork, and these subnetworks form a poset (with respect to the relation of ‘removing species’) which has 11 minimal elements (the atoms of multistationarity).
Dynamic communicability and epidemic spread: a case study on an empirical dynamic contact network

We analyse a recently proposed temporal centrality measure applied to an empirical network based on person-to-person contacts in an emergency department of a busy urban hospital. We show that temporal centrality identifies a distinct set of top-spreaders than centrality based on the time-aggregated binarized contact matrix, so that taken together, the accuracy of capturing top-spreaders improves significantly. However, with respect to predicting epidemic outcome, the temporal measure does not necessarily outperform less complex measures. Our results also show that other temporal markers such as duration observed and the time of first appearance in the network can be used in a simple predictive model to generate predictions that capture the trend of the observed data remarkably well.
Effective field theory of dissipative fluids

We develop an effective field theory for dissipative fluids which governs the dynamics of long-lived gapless modes associated with conserved quantities. The resulting theory gives a path integral formulation of fluctuating hydrodynamics which systematically incorporates nonlinear interactions of noises. The dynamical variables are mappings between a “fluid spacetime” and the physical spacetime and an essential aspect of our formulation is to identify the appropriate symmetries in the fluid spacetime. The theory applies to nonlinear disturbances around a general density matrix. For a thermal density matrix, we require an additional Z 2 symmetry, to which we refer as the local KMS condition. This leads to the standard constraints of hydrodynamics, as well as a nonlinear generalization of the Onsager relations. It also leads to an emergent supersymmetry in the classical statistical regime, and a higher derivative deformation of supersymmetry in the full quantum regime.
Bloch waves in crystals and periodic high contrast media

Analytic representation formulas and power series are developed describing the band structure inside periodic photonic and acoustic crystals made from high contrast inclusions. Central to this approach is the identification and utilization of a resonance spectrum for quasi-periodic source free modes. These modes are used to represent solution operators associated with electromagnetic and acoustic waves inside periodic high contrast media. Convergent power series for the Bloch wave spectrum is recovered from the representation formulas. Explicit conditions on the contrast are found that provide lower bounds on the convergence radius. These conditions are sufficient for the separation of spectral branches of the dispersion relation.
Utilization of Water Supply Networks for Harvesting Renewable Energy

Renewable surplus power is increasing due to the increasing penetration of these intermittent resources. In practice, electric grid operators either curtail the surplus energy resulting from renewable-based generations or utilize energy storage resources to absorb it. In this paper, we propose a framework for utilizing water pumps and tanks in water supply networks to absorb the surplus electrical energy resulting from renewable-based electricity generation resources in the electrical grid. We model water supply networks analytically, and propose a two-step procedure that utilizes the water tanks in the water supply network to harvest the surplus energy from an electrical grid. In each step, the water network operator needs to solve an optimization problem that is nonconvex. To compute optimal pump schedules and water flows, we develop a second-order cone relaxation and an approximation technique that enable us to transform the proposed problems into mixed-integer second-order cone programs. We then provide the conditions under which the proposed relaxation is exact, and present an algorithm for constructing an exact solution to the original problem from a solution to the relaxed problem. We demonstrate the effectiveness of the proposed framework via numerical simulations.
Linear network coding for two-unicast-Z networks: A commutative algebraic perspective and fundamental limits

We consider a two-unicast-Z network over a directed acyclic graph of unit capacitated edges; the two-unicast-Z network is a special case of two-unicast networks where one of the destinations has apriori side information of the unwanted (interfering) message. In this paper, we settle open questions on the limits of network coding for two-unicast-Z networks by showing that the generalized network sharing bound is not tight, vector linear codes outperform scalar linear codes, and nonlinear codes outperform linear codes in general. We also develop a commutative algebraic approach to deriving linear network coding achievability results, and demonstrate our approach by providing an alternate proof to the previous result of Wang et. al. regarding feasibility of rate (1,1) in the network.
Automorphisms of p-local compact groups

Abstract Self equivalences of classifying spaces of p-local compact groups are well understood by means of the algebraic structure that gives rise to them, but explicit descriptions are lacking. In this paper we use Robinson's construction of an amalgam G, realising a given fusion system, to produce a split epimorphism from the outer automorphism group of G to the group of homotopy classes of self homotopy equivalences of the classifying space of the corresponding p-local compact group.
The quantum effects of the spin and the Bohm potential in the oblique propagation of magnetosonic waves

Abstract We study the quantum corrections to the oblique propagation of the magnetosonic waves in a warm quantum magnetoplasma composed by mobile ions and electrons. We use a fluid formalism to include quantum corrections due to the Bohm potential and to the spin magnetization energy of electrons. The effects of both quantum corrections are shown in the dispersion relation for perpendicular, parallel and oblique propagation. We find that the quantum contributions to the low frequency depend on the type in the oblique propagation with respect to the background magnetic field. The relevance in astrophysical scenarios is exemplified.
Multi-centrality graph spectral decompositions and their application to cyber intrusion detection

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the Fiedler vector of centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles of graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.
F-jumping and F-Jacobian ideals for hypersurfaces

Abstract We introduce two families of ideals, F-jumping ideals and F-Jacobian ideals, in order to study the singularities of hypersurfaces in positive characteristic. Both families are defined using the D-modules M α that were introduced by Blickle, Mustaţa and Smith. Using strong connections between F-jumping ideals and generalized test ideals, we give a characterization of F-jumping numbers for hypersurfaces via D-modules and F-modules. In addition, we use F-Jacobian ideals to study intrinsic properties of the singularities of hypersurfaces. In particular, we give conditions for F-regularity. Moreover, we prove several properties of F-Jacobian ideals that resemble those of Jacobian ideals of polynomials.
Universal Theorems for Total Energy of the Dynamics of Linearly Elastic Heterogeneous Solids

In this paper we consider a sample of a linearly elastic heterogeneous composite in elastodynamic equilibrium and present universal theorems which provide lower bounds for the total elastic strain energy plus the kinetic energy, and the total complementary elastic energy plus the kinetic energy. For a general heterogeneous sample which undergoes harmonic motion at a single frequency, we show that, among all consistent boundary data which produce the same average strain, the uniform-stress boundary data render the total elastic strain energy plus the kinetic energy an absolute minimum. We also show that, among all consistent boundary data which produce the same average momentum in the sample, the uniform velocity boundary data render the total complementary elastic energy plus the kinetic energy an absolute minimum. We do not assume statistical homogeneity or material isotropy in our treatment, although they are not excluded. These universal theorems are the dynamic equivalent of the universal theorems already known for the static case Nemat-Nasser and Hori (1993, 1995). It is envisaged that the bounds on the total energy presented in this paper will be used to formulate computable bounds on the overall dynamic properties of linearly elastic heterogeneous composites with arbitrary microstructures.
Learning from clinical judgments: semi-Markov-modulated marked Hawkes processes for risk prognosis

Critically ill patients in regular wards are vulnerable to unanticipated adverse events which require prompt transfer to the intensive care unit (ICU). To allow for accurate prognosis of deteriorating patients, we develop a novel continuous-time probabilistic model for a monitored patient's temporal sequence of physiological data. Our model captures "informatively sampled" patient episodes: the clinicians' decisions on when to observe a hospitalized patient's vital signs and lab tests over time are represented by a marked Hawkes process, with intensity parameters that are modulated by the patient's latent clinical states, and with observable physiological data (mark process) modeled as a switching multi-task Gaussian process. In addition, our model captures "informatively censored" patient episodes by representing the patient's latent clinical states as an absorbing semi-Markov jump process. The model parameters are learned from offline patient episodes in the electronic health records via an EM-based algorithm. Experiments conducted on a cohort of patients admitted to a major medical center over a 3-year period show that risk prognosis based on our model significantly outperforms the currently deployed medical risk scores and other baseline machine learning algorithms.
Algorithms for Metric Learning via Contrastive Embeddings.

We study the problem of supervised learning a metric space under discriminative constraints. Given a universe $X$ and sets ${\cal S}, {\cal D}\subset {X \choose 2}$ of similar and dissimilar pairs, we seek to find a mapping $f:X\to Y$, into some target metric space $M=(Y,\rho)$, such that similar objects are mapped to points at distance at most $u$, and dissimilar objects are mapped to points at distance at least $\ell$. More generally, the goal is to find a mapping of maximum accuracy (that is, fraction of correctly classified pairs). We propose approximation algorithms for various versions of this problem, for the cases of Euclidean and tree metric spaces. For both of these target spaces, we obtain fully polynomial-time approximation schemes (FPTAS) for the case of perfect information. In the presence of imperfect information we present approximation algorithms that run in quasipolynomial time (QPTAS). Our algorithms use a combination of tools from metric embeddings and graph partitioning, that could be of independent interest.
Dynamical intricacy and average sample complexity

We propose a new way to measure the balance between freedom and coherence in a dynamical system and a new measure of its internal variability. Based on the concept of entropy and ideas from neurosc...
Counter-Example Guided Synthesis of control Lyapunov functions for switched systems

We investigate the problem of synthesizing switching controllers for stabilizing continuous-time plants. First, we introduce a class of control Lyapunov functions (CLFs) for switched systems along with a switching strategy that yields a closed loop system with a guaranteed minimum dwell time in each switching mode. However, the challenge lies in automatically synthesizing appropriate CLFs. Assuming a given fixed form for the CLF with unknown coefficients, we derive quantified nonlinear constraints whose feasible solutions (if any) correspond to CLFs for the original system. However, solving quantified nonlinear constraints pose a challenge to most LMI/BMI-based relaxations. Therefore, we investigate a general approach called Counter-Example Guided Inductive Synthesis (CEGIS), that has been widely used in the emerging area of automatic program synthesis. We show how a LMI-based relaxation can be formulated within the CEGIS framework for synthesizing CLFs. We also evaluate our approach on a number of interesting benchmarks, and compare the performance of the new approach with our previous work that uses off-the-shelf nonlinear constraint solvers instead of the LMI relaxation. The results shows synthesizing CLFs by using LMI solvers inside a CEGIS framework can be a computational feasible approach to synthesizing CLFs.
Value added or misattributed? A multi-institution study on the educational benefit of labs for reinforcing physics content

Instructional labs are widely seen as a unique, albeit expensive, way to teach scientific content. We measured the effectiveness of introductory lab courses at achieving this educational goal across nine different lab courses at three very different institutions. These institutions and courses encompassed a broad range of student populations and instructional styles. The nine courses studied had two key things in common: the labs aimed to reinforce the content presented in lectures, and the labs were optional. By comparing the performance of students who did and did not take the labs (with careful normalization for selection effects), we found universally and precisely no added value to learning from taking the labs as measured by course exam performance. This work should motivate institutions and departments to reexamine the goals and conduct of their lab courses, given their resource-intensive nature. We show why these results make sense when looking at the comparative mental processes of students involved in research and instructional labs, and offer alternative goals and instructional approaches that would make lab courses more educationally valuable.
Monopoles, Dipoles, and Harmonic Functions on Bratteli Diagrams

In our study of electrical networks we develop two themes: finding explicit formulas for special classes of functions defined on the vertices of a transient network, namely monopoles, dipoles, and harmonic functions. Secondly, our interest is focused on the properties of electrical networks supported on Bratteli diagrams. We show that the structure of Bratteli diagrams allows one to describe algorithmically harmonic functions as well as monopoles and dipoles. We also discuss some special classes of Bratteli diagrams (stationary, Pascal, trees), and we give conditions under which the harmonic functions defined on these diagrams have finite energy.
Vassiliev Invariants from Parity Mappings

Parity mappings (weights) from the chords of a Gauss diagram to the integers are defined. The parity of the chords is used to construct families of invariants of Gauss diagrams and consequently, virtual knots. Each family forms a set of degree n Vassiliev invariants for n ≥ 1.
MILNOR FILLABLE CONTACT STRUCTURES ARE UNIVERSALLY TIGHT

We show that the canonical contact structure on the link of a normal complex singularity is universally tight. As a corollary we show the existence of closed, oriented, atoroidal 3-manifolds with infinite fundamental groups which carry universally tig ht contact structures that are not deforma- tions of taut (or Reebless) foliations. This answers two questions of Etnyre in (12). Let (X, x) be a normal complex surface singularity. Fix a local embedding of (X, x) in (C N , 0). Then a small sphere S 2N−1 e ⊂ C N centered at the origin intersects X transversely, and the complex hyperplane distribution ξcan on M = X ∩ S 2N−1 e induced by the complex structure on X is called the canonical contact structure. For sufficiently small radius e, the contact manifold is independent of e and the embedding, up to isomorphism. The 3-manifold M is called the link of the singularity, and (M, ξcan) is called the contact boundaryof (X, x). A contact manifold (Y, ξ) is said to be Milnor fillable if it is isomorphic to the contact bound- ary (M, ξcan) of some isolated complex surface singularity (X, x). In addition, we say that a closed and oriented 3-manifold Y is Milnor fillable if it carries a contact structure ξ so that (Y, ξ) is Milnor fillable. It is known that a closed and oriented 3-ma nifold is Milnor fillable if and only if it can be obtained by plumbing according to a weighted graph with negative definite intersection matrix (cf. (25) and (18)). Moreover a ny 3-manifold has at most one Milnor fillable contact structure up to isomorphism(cf. (5)). Note that Milnor fillable contact structures are Stein fillable (see (4)) and hence tight (10). Here we prove that every Milnor fillable contact structure is in fact universally tight, i.e ., the pullback to the universal cover is tight. We would like to point out that universal tightness of a contact structure is not implied by any other type of fillability. In (12), Etnyre settled a question of Eliashberg and Thurston (11) by proving that every contact structure on a closed oriented 3-manifold is obtained by a deformation of a foliation and raised two other related questions:
Graphs and metric 2-step nilpotent Lie algebras

Dani and Mainkar introduced a method for constructing a 2-step nilpotent Lie algebra $\mathfrak{n}_G$ from a simple directed graph $G$ in 2005. There is a natural inner product on $\mathfrak{n}_G$ arising from the construction. We study geometric properties of the associated simply connected 2-step nilpotent Lie group $N$ with Lie algebra $\mathfrak{n}_G$. We classify singularity properties of the Lie algebra $\mathfrak{n}_G$ in terms of the graph $G$. A comprehensive description is given of graphs $G$ which give rise to Heisenberg-like Lie algebras. Conditions are given on the graph $G$ and on a lattice $\Gamma \subseteq N$ for which the quotient $\Gamma \backslash N$, a compact nilmanifold, has a dense set of smoothly closed geodesics.
Cyber-Physical Simulation Platform for Security Assessment of Transactive Energy Systems

Transactive energy systems (TES) are emerging as a transformative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources and rapid growth in scalability of managing active distribution system (ADS). On the one hand, these changes pose a decentralized power system control problem, requiring strategic control to maintain reliability and resiliency for the community and for the utility. On the other hand, they require robust financial markets while allowing participation from diverse prosumers. To support the computing and flexibility requirements of TES while preserving privacy and security, distributed software platforms are required. In this paper, we enable the study and analysis of security concerns by developing Transactive Energy Security Simulation Testbed (TESST), a TES testbed for simulating various cyber attacks. In this work, the testbed is used for TES simulation with centralized clearing market, highlighting weaknesses in a centralized system. Additionally, we present a blockchain enabled decentralized market solution supported by distributed computing for TES, which on one hand can alleviate some of the problems that we identify, but on the other hand, may introduce newer issues. Future study of these differing paradigms is necessary and will continue as we develop our security simulation testbed.