cssi/SciSciGPT-SciSciNet huggingface dataset:
Achieving utility-delay-reliability tradeoff in stochastic network optimization with finite buffers

One practical open problem is the development of a distributed algorithm that achieves near-optimal utility using only a finite (and small) buffer size for queues in a stochastic network. This paper studies utility maximization (or cost minimization) in a finite-buffer regime and considers the corresponding delay and reliability (or rate of packet drops) tradeoff. A floating-queue algorithm allows the stochastic network optimization framework to be implemented with finite buffers at the cost of packet drops. Further, the buffer size requirement is significantly smaller than previous works in this area. With a finite buffer size of B packets, the proposed algorithm achieves within O(e−B) of the optimal utility while maintaining average per-hop delay of O(B) and an average per-hop drop rate of O(e−B) in steady state. From an implementation perspective, the floating-queue algorithm requires little modification of the well-known DriftPlus-Penalty policy (including MaxWeight and Backpressure policies). As a result, the floating-queue algorithm inherits the distributed and low complexity nature of these policies.
On Coloring Resilient Graphs

We introduce a new notion of resilience for constraint satisfaction problems, with the goal of more precisely determining the boundary between NP-hardness and the existence of efficient algorithms for resilient instances. In particular, we study r-resiliently k-colorable graphs, which are those k-colorable graphs that remain k-colorable even after the addition of any r new edges. We prove lower bounds on the NP-hardness of coloring resiliently colorable graphs, and provide an algorithm that colors sufficiently resilient graphs. We also analyze the corresponding notion of resilience for k-SAT. This notion of resilience suggests an array of open questions for graph coloring and other combinatorial problems.
A new registration approach for dynamic analysis of calcium signals in organs

Wing disc pouches of fruit flies are a powerful genetic model for studying physiological intercellular calcium (Ca2+) signals for dynamic analysis of cell signaling in organ development and disease studies. A key to analyzing spatial-temporal patterns of Ca2+ signal waves is to accurately align the pouches across image sequences. However, pouches in different image frames may exhibit extensive intensity oscillations due to Ca2+ signaling dynamics, and commonly used multimodal non-rigid registration methods may fail to achieve satisfactory results. In this paper, we develop a new two-phase non-rigid registration approach to register pouches in image sequences. First, we conduct segmentation of the region of interest. (i.e., pouches) using a deep neural network model. Second, we use a B-spline based registration to obtain an optimal transformation and align pouches across the image sequences. Evaluated using both synthetic data and real pouch data, our method considerably outperforms the state-of-the-art non-rigid registration methods.
Arithmetic Structure in Sparse Difference Sets

Abstract Using a slight modification of an argument of Croot, Ruzsa and Schoen we establish a quantitative result on the existence of a dilated copy of any given configuration of integer points in sparse difference sets. More precisely, given any configuration { v 1 , … , v l } of vectors in Z d , we show that if A ⊂ [ 1 , N ] d with | A | / N d ⩾ C N − 1 / l , then there necessarily exists r ≠ 0 such that { r v 1 , … , r v l } ⊆ A − A .
Nonuniqueness of weak solutions to the Navier-Stokes equation

For initial datum of finite kinetic energy, Leray has proven in 1934 that there exists at least one global in time finite energy weak solution of the 3D Navier-Stokes equations. In this paper we prove that weak solutions of the 3D Navier-Stokes equations are not unique in the class of weak solutions with finite kinetic energy. Moreover, we prove that Holder continuous dissipative weak solutions of the 3D Euler equations may be obtained as a strong vanishing viscosity limit of a sequence of finite energy weak solutions of the 3D Navier-Stokes equations.
Topological twistons in crystalline polyethylene

Abstract We introduce an alternate model to describe twistons in crystalline polyethylene. The model couples torsional and longitudinal degrees of freedom and appears as an extension of a model that describes only the torsional motion. We find exact solutions that describe stable topological twistons, in good agreement with the torsional and longitudinal interactions in polyethylene.
Leafwise Coisotropic Intersections

We establish the leafwise intersection property for closed, coisotropic submanifolds in an exact symplectic manifold satisfying natural additional assumptions.
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition

Inspired by "predictive coding" - a theory in neuroscience, we develop a bi-directional and dynamic neural network with local recurrent processing, namely predictive coding network (PCN). Unlike feedforward-only convolutional neural networks, PCN includes both feedback connections, which carry top-down predictions, and feedforward connections, which carry bottom-up errors of prediction. Feedback and feedforward connections enable adjacent layers to interact locally and recurrently to refine representations towards minimization of layer-wise prediction errors. When unfolded over time, the recurrent processing gives rise to an increasingly deeper hierarchy of non-linear transformation, allowing a shallow network to dynamically extend itself into an arbitrarily deep network. We train and test PCN for image classification with SVHN, CIFAR and ImageNet datasets. Despite notably fewer layers and parameters, PCN achieves competitive performance compared to classical and state-of-the-art models. Further analysis shows that the internal representations in PCN converge over time and yield increasingly better accuracy in object recognition. Errors of top-down prediction also reveal visual saliency or bottom-up attention.
What really happens in strongly correlated superconductors: insights from a quantum Monte-Carlo study of high temperature superconductivity in FeSe films

BCS theory and its extensions form the basis of a compelling and elegant understanding of the properties of conventional superconductors. However, it is a weak-coupling theory, organized around the infinitesimal "Cooper" instability of the Fermi liquid. This is not merely a theoretical abstraction: Schrieffer (among others) has emphasized that it is only because the normal state above \(T_\mathrm{c}\) is so accurately described by Fermi liquid theory that we can talk about collective pairing of well-defined quasiparticles. Moreover, the fact that the phonons involved are coherent collective modes permits the identification of a pairing glue, while the small ratio of the phonon frequencies to the Fermi energy allows the relatively weak retarded attraction they induce to overcome the strong Coulomb repulsion between electrons.
Strictly commutative complex orientation theory

For a multiplicative cohomology theory E, complex orientations are in bijective correspondence with multiplicative natural transformations to E from complex bordism cohomology MU. If E is represented by a spectrum with a highly structured multiplication, we give an iterative process for lifting an orientation $$MU \rightarrow E$$ to a map respecting this extra structure, based on work of Arone–Lesh. The space of strictly commutative orientations is the limit of an inverse tower of spaces parametrizing partial lifts; stage 1 corresponds to ordinary complex orientations, and lifting from stage $$(m-1)$$ to stage m is governed by the existence of an orientation for a family of E-modules over a fixed base space $$F_m$$ . When E is p-local, we can say more. We find that this tower only changes when m is a power of p, and if E is E(n)-local the tower is constant after stage $$p^n$$ . Moreover, if the coefficient ring $$E^*$$ is p-torsion free, the ability to lift from stage 1 to stage p is equivalent to a condition on the associated formal group law that was shown necessary by Ando.
There Exist Non-CM Hilbert Modular Forms of Partial Weight 1

In this note, we prove that there exists a classical Hilbert modular cusp form over Q(\sqrt{5}) of partial weight one which does not arise from the induction of a Grossencharacter from a CM extension of Q(\sqrt{5}).
Biophysics at the coffee shop: lessons learned working with George Oster

Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
Relatively spectral morphisms and applications to K-theory

Abstract Spectral morphisms between Banach algebras are useful for comparing their K-theory and their “noncommutative dimensions” as expressed by various notions of stable ranks. In practice, one often encounters situations where the spectral information is only known over a dense subalgebra. We investigate such relatively spectral morphisms. We prove a relative version of the Density Theorem regarding isomorphism in K-theory. We also solve Swan's problem for the connected stable rank, in fact for an entire hierarchy of higher connected stable ranks that we introduce.
Constructing the scattering matrix for optical microcavities as a nonlocal boundary value problem

We develop a numerical scheme to construct the scattering (S) matrix for optical microcavities, including the special cases with parity-time and other non-Hermitian symmetries. This scheme incorporates the explicit form of a nonlocal boundary condition, with the incident light represented by an inhomogeneous term. This approach resolves the artifact of a discontinuous normal derivative typically found in the R-matrix method. In addition, we show that, by excluding the aforementioned inhomogeneous term, the non-Hermitian Hamiltonian in our approach also determines the Periels–Kapur states, and it constitutes an alternative approach to derive the standard R-matrix result in this basis. Therefore, our scheme provides a convenient framework to explore the benefits of both approaches. We illustrate this boundary value problem using 1D and 2D scalar Helmholtz equations. The eigenvalues and poles of the S matrix calculated using our approach show good agreement with results obtained by other means.
Scattering from Colloid-Polymer Conjugates with Excluded Volume Effect

This work presents scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain as a model for protein–polymer conjugates and nanoparticle–polymer conjugates in solution. The model is directly derived from the two-point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shape of the colloid and polymer stiffness is investigated. The model is able to describe the experimental scattering signature of the solutions of suspending hard particle–polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugate and the microstructure of its constituent components.
NetREX: Network Rewiring using EXpression - Towards Context Specific Regulatory Networks

Understanding gene regulation is a fundamental step towards understanding of how cells function and respond to environmental cues and perturbations. An important step in this direction is to infer the transcription factor-gene regulatory network (GRN). However gene regulatory networks are typically constructed disregarding the fact that regulatory programs are conditioned on tissue type, developmental stage, sex, and other factors. Collecting multitude of features required for a reliable construction of GRNs such as physical features and functional features for every context of interest is costly. Therefore we need methods that is able to use the knowledge of a context-agnostic network for construction of a context specific regulatory network. To address this challenge we developed a computational approach that uses context specific expression data and a GRN constructed in a different but related context to construct a context specific GRN. Our method, NetREX, is inspired by network component analysis that estimates TF activities and their influences on target genes given predetermined topology of a TF-gene network. To predict a network under a different condition, NetREX removes the restriction that the topology of the TF-gene network is fixed and allows for adding and removing edges to that network. To solve the corresponding optimization problem, we provide a general mathematical framework allowing use of the recently proposed PALM technique and develop a convergent algorithm. We tested our NetREX on simulated data and subsequently applied it to gene expression data in adult females from Drosophila deletion (DrosDel) panel. The networks predicted by NetREX showed higher biological consistency than alternative approaches. In addition, we used the list of recently identified targets of the Doublesex (DSX) transcription factor to demonstrate the predictive power of our method.
Takagi lectures on Donaldson-Thomas theory

These are introductory notes on Donaldson–Thomas counts of curves in threefolds and their connections with other branches of mathematics and mathematical physics. They are based on my 2018 Takagi Lectures at The University of Tokyo.
A Fast Distributed Stateless Algorithm for $\alpha$-Fair Packing Problems

We study weighted alpha-fair packing problems, that is, the problems of maximizing the objective functions (i) sum_j w_j*x_j^{1-alpha}/(1-alpha) when alpha > 0, alpha != 1 and (ii) sum_j w_j*ln(x_j) when alpha = 1, over linear constraints A*x = 0, where wj are positive weights and A and b are non-negative. We consider the distributed computation model that was used for packing linear programs and network utility maximization problems. Under this model, we provide a distributed algorithm for general alpha that converges to an epsilon-approximate solution in time (number of distributed iterations) that has an inverse polynomial dependence on the approximation parameter epsilon and poly-logarithmic dependence on the problem size. This is the first distributed algorithm for weighted alpha-fair packing with poly-logarithmic convergence in the input size. The algorithm uses simple local update rules and is stateless (namely, it allows asynchronous updates, is self-stabilizing, and allows incremental and local adjustments). We also obtain a number of structural results that characterize alpha-fair allocations as the value of alpha is varied. These results deepen our understanding of fairness guarantees in alpha-fair packing allocations, and also provide insight into the behavior of alpha-fair allocations in the asymptotic cases alpha -> 0, alpha -> 1, and alpha -> infinity.
Benchmarking the Privacy-Preserving People Search.

People search is an important topic in information retrieval. Many previous studies on this topic employed social networks to boost search performance by incorporating either local network features (e.g. the common connections between the querying user and candidates in social networks), or global network features (e.g. the PageRank), or both. However, the available social network information can be restricted because of the privacy settings of involved users, which in turn would affect the performance of people search. Therefore, in this paper, we focus on the privacy issues in people search. We propose simulating different privacy settings with a public social network due to the unavailability of privacy-concerned networks. Our study examines the influences of privacy concerns on the local and global network features, and their impacts on the performance of people search. Our results show that: 1) the privacy concerns of different people in the networks have different influences. People with higher association (i.e. higher degree in a network) have much greater impacts on the performance of people search; 2) local network features are more sensitive to the privacy concerns, especially when such concerns come from high association peoples in the network who are also related to the querying user. As the first study on this topic, we hope to generate further discussions on these issues.
Stable solutions of symmetric systems on Riemannian manifolds

We examine stable solutions of the following symmetric system on a complete, connected, smooth Riemannian manifold $\mathbb{M}$ without boundary, \begin{equation*} -\Delta_g u_i = H_i(u_1,\cdots,u_m) \ \ \text{on} \ \ \mathbb{M}, \end{equation*} when $\Delta_g$ stands for the Laplace-Beltrami operator, $u_i:\mathbb{M}\to \mathbb R$ and $H_i\in C^1(\mathbb R^m) $ for $1\le i\le m$. This system is called symmetric if the matrix of partial derivatives of all components of $H$, that is $\mathbb H(u)=(\partial_j H_i(u))_{i,j=1}^m$, is symmetric. We prove a stability inequality and a Poincar\'{e} type inequality for stable solutions using the Bochner-Weitzenb\"{o}ck formula. Then, we apply these inequalities to establish Liouville theorems and flatness of level sets for stable solutions of the above symmetric system, under certain assumptions on the manifold and on solutions.
$N_6$ property for third Veronese embeddings

The rational homology groups of the matching complexes are closely related to the syzygies of the Veronese embeddings. In this paper we will prove the vanishing of certain rational homology groups of matching complexes, thus proving that the third Veronese embeddings satisfy the property $N_6$. This settles the Ottaviani-Paoletti conjecture for third Veronese embeddings. This result is optimal since $\nu_3(\PP^n)$ does not satisfy the property $N_7$ for $n\ge 2$ as shown by Ottaviani-Paoletti in \cite{OP}.
Optimizing the Quantity/Quality Trade-Off in Connectome Inference

We demonstrate a meaningful prospective power analysis for an (admittedly idealized) illustrative connectome inference task. Modeling neurons as vertices and synapses as edges in a simple random graph model, we optimize the trade-off between the number of (putative) edges identified and the accuracy of the edge identification procedure. We conclude that explicit analysis of the quantity/quality trade-off is imperative for optimal neuroscientific experimental design. In particular, identifying edges faster/more cheaply, but with more error, can yield superior inferential performance.
Higher Order Fermionic and Bosonic Operators on Cylinders and Hopf Manifolds

Higher order higher spin operators are generalizations of kth-powers of the Dirac operator. In this paper, we study higher order higher spin operators defined on some conformally flat manifolds, namely cylinders and Hopf manifolds. We will also construct the kernels of these operators on these manifolds.
Cultural selection shapes network structure

Cultural evolution relies on the social transmission of cultural traits along a population’s social network. Research indicates that network structure affects information spread and thus the capacity for cumulative culture. However, how network structure itself is driven by population-culture co-evolution remains largely unclear. We use a simple model to investigate how populations negotiate the trade-off between acquiring new skills and getting better at existing skills and how this trade-off shapes social networks. We find unexpected eco-evolutionary feedbacks from culture onto social networks and vice versa. We show that selecting for skill generalists results in sparse networks with diverse skill sets, whereas selecting for skill specialists results in dense networks and a population that specializes on the same few skills on which everyone is an expert. Our model advances our understanding of the complex feedbacks in cultural evolution and demonstrates how individual-level behavior can lead to the emergence of population-level structure.
Development of Real-Time ADAS Object Detector for Deployment on CPU

In this work, we outline the set of problems, which any neural network for object detection faces when its development comes to the deployment stage and propose methods to deal with such difficulties. We show that these practices allow one to get neural network for object detection, which can recognize two classes: vehicles and pedestrians and achieves more than 60 frames per second inference speed on Core\(^{\mathrm{TM}}\) i5-6500 CPU. The proposed model is built on top of the popular Single Shot MultiBox Object Detection framework but with substantial improvements, which were inspired by the discovered problems. The network has just 1.96 GMAC (GMAC – billions of multiply-accumulate operations) complexity and less than 7 MB model size. It is publicly available as a part of Intel® OpenVINO\(^{\mathrm{TM}}\) Toolkit.
Adversarial Reprogramming of Text Classification Neural Networks

Author(s): Neekhara, Paarth; Hussain, Shehzeen; Dubnov, Shlomo; Koushanfar, Farinaz | Abstract: Adversarial Reprogramming has demonstrated success in utilizing pre-trained neural network classifiers for alternative classification tasks without modification to the original network. An adversary in such an attack scenario trains an additive contribution to the inputs to repurpose the neural network for the new classification task. While this reprogramming approach works for neural networks with a continuous input space such as that of images, it is not directly applicable to neural networks trained for tasks such as text classification, where the input space is discrete. Repurposing such classification networks would require the attacker to learn an adversarial program that maps inputs from one discrete space to the other. In this work, we introduce a context-based vocabulary remapping model to reprogram neural networks trained on a specific sequence classification task, for a new sequence classification task desired by the adversary. We propose training procedures for this adversarial program in both white-box and black-box settings. We demonstrate the application of our model by adversarially repurposing various text-classification models including LSTM, bi-directional LSTM and CNN for alternate classification tasks.
Bridging the Gap Between Monaural Speech Enhancement and Recognition With Distortion-Independent Acoustic Modeling

Monaural speech enhancement has made dramatic advances since the introduction of deep learning a few years ago. Although enhanced speech has been demonstrated to have better intelligibility and quality for human listeners, feeding it directly to automatic speech recognition (ASR) systems trained with noisy speech has not produced expected improvements in ASR performance. The lack of an enhancement benefit on recognition, or the gap between monaural speech enhancement and recognition, is often attributed to speech distortions introduced in the enhancement process. In this article, we analyze the distortion problem, compare different acoustic models, and investigate a distortion-independent training scheme for monaural speech recognition. Experimental results suggest that distortion-independent acoustic modeling is able to overcome the distortion problem. Such an acoustic model can also work with speech enhancement models different from the one used during training. Moreover, the models investigated in this paper outperform the previous best system on the CHiME-2 corpus.
Axonal Conduction Velocity Impacts Neuronal Network Oscillations

Increasing experimental evidence suggests that axonal action potential conduction velocity is a highly adaptive parameter in the adult central nervous system. Yet, the effects of this newfound plasticity on global brain dynamics is poorly understood. In this work, we analyzed oscillations in biologically plausible neuronal networks with different conduction velocity distributions. Variation of 1–2 ms in average conduction velocity resulted in network oscillation frequency changes of 0–120 Hz. Our results suggest that changes in axonal conduction velocity may significantly affect both the frequency and synchrony of brain rhythms, which have well established connections to learning, memory, and other cognitive processes.
An Extended Expert System for Service Restoration of Distribution Feeders

Abstract The service restoration planning in distribution systems deals with the determination of necessary switching actions to restore the service of customers affected by an outage. In practice, it has been performed by system dispatchers based on experience. In this paper, an expert system which has the following capabilities is presented: two-phase service restoration considering zone priority and supervised switches, maintenance switching and user-specified zone priority ordering. The proposed expert system ERP (Enhanced Restoration Planner) is implemented in PROLOG and is able to come up with appropriate switching actions within a few seconds. The proposed expert system can be a powerful tool in aiding the distribution system dispatchers in emergency situations.
Japan's Public Sector Balance Sheet

This paper compiles and reviews the evolution of Japan’s Public Sector Balance Sheet (PSBS). In the past, large crossholdings of assets and liabilities within the public sector played a role in sustaining a high level of public debt and low interest rates. The Fiscal Investment and Loan Fund (FILF) channeled all postal deposits and pension savings to financing of public sector borrowing. After the FILF refrom in 2000, however, the Post Bank and pension funds shifted their assets to the portfolio investments and are seeking to maximize risk-adjusted returns. This has changed the implications of crossholdings for public debt management. In the future, population aging is expected to add more pressures on the PSBS, which already saw a considerable decrease of net worth over the last three decades.
Large Prandtl number asymptotics in randomly forced turbulent convection

We establish the convergence of statistically invariant states for the stochastic Boussinesq equations in the infinite Prandtl number limit and in particular demonstrate the convergence of the Nusselt number (a measure of heat transport in the fluid). This is a singular parameter limit significant in mantle convection and for gasses under high pressure. The equations are subject to a both temperature gradient on the boundary and internal heating in the bulk driven by a stochastic, white in time, gaussian forcing. Here, the stochastic source terms have a strong physical motivation for example as a model of radiogenic heating. Our approach uses mixing properties of the formal limit system to reduce the convergence of invariant states to an analysis of the finite time asymptotics of solutions and parameter-uniform moment bounds. Here, it is notable that there is a phase space mismatch between the finite Prandtl system and the limit equation, and we implement methods to lift both finite and infinite time convergence results to an extended phase space which includes velocity fields. For the infinite Prandtl stochastic Boussinesq equations, we show that the associated invariant measure is unique and that the dual Markovian dynamics are contractive in an appropriate Kantorovich–Wasserstein metric. We then address the convergence of solutions on finite time intervals, which is still a singular perturbation. In the process we derive well-posed equations which accurately approximate the dynamics up to the initial time when the Prandtl number is large.
A 2/3-approximation algorithm for vertex-weighted matching

Abstract We consider the maximum vertex-weighted matching problem (MVM) for non-bipartite graphs in which non-negative weights are assigned to the vertices of a graph and a matching that maximizes the sum of the weights of the matched vertices is desired. In earlier work we have described a 2 ∕ 3 -approximation algorithm for the MVM on bipartite graphs (Florin Dobrian et al., 2019). Here we show that a 2 ∕ 3 -approximation algorithm for MVM on non-bipartite graphs can be obtained by restricting the length of augmenting paths to at most three. The algorithm has time complexity O ( m log Δ + n log n ) , where n is the number of vertices, m is the number of edges, and Δ is the maximum degree of a vertex. The approximation ratio of the algorithm is obtained by considering failed vertices, i.e., vertices that the approximation algorithm fails to match but the exact algorithm does. We show that there are two distinct heavier matched vertices that we can charge each failed vertex to. Our proof techniques characterize the structure of augmenting paths in a novel way. We have implemented the 2 ∕ 3 -approximation algorithm and show that it runs in under a minute on graphs with tens of millions of vertices and hundreds of millions of edges. We compare its performance with five other algorithms: an exact algorithm for MVM, an exact algorithm for the maximum edge-weighted matching (MEM) problem, as well as three approximation algorithms. The approximation algorithms include a 1 ∕ 2 -approximation algorithm for MVM, and ( 2 ∕ 3 − ϵ ) - and ( 1 − ϵ ) -approximation algorithms for the MEM. In our test set of nineteen problems, there are graphs on which the exact algorithms fail to terminate in 100 hours. In addition, the new 2 ∕ 3 -approximation algorithm for MVM outperforms the other approximation algorithms by either being faster (often by orders of magnitude) or obtaining better weights.
Mineral deposition and vascular invasion of hydroxyapatite reinforced collagen scaffolds seeded with human adipose-derived stem cells.

Collagen-based scaffolds reinforced with hydroxyapatite (HA) are an attractive choice for bone tissue engineering because their composition mimics that of bone. We previously reported the development of compression-molded collagen-HA scaffolds that exhibited high porosity, interconnected pores, and mechanical properties that were well-suited for surgical handling and fixation. The objective of this study was to investigate these novel collagen-HA scaffolds in combination with human adipose-derived stem cells (hASCs) as a template for bone formation in a subcutaneous athymic mouse model. Collagen-HA scaffolds and collagen-only scaffolds were fabricated as previously described, and a clinically approved bone void filler was used as a control for the material. Constructs were seeded with hASCs and were pre-treated with either control or osteogenic media. A cell-free group was also included. Scaffolds were implanted subcutaneously in the backs of athymic nude mice for 8 weeks. Mineral deposition was quantified via micro-computed tomography. Histological and immunofluorescence images of the explants were used to analyze their vascular invasion, remodeling and cellularity. Cell-free collagen-HA scaffolds and those that were pre-seeded with osteogenically differentiated hASCs supported mineral deposition and vascular invasion at comparable rates, while cell-seeded constructs treated with the control medium showed lower mineralization after implantation. HA-reinforcement allowed collagen constructs to maintain their shape, provided improved cell-tissue-scaffold integration, and resulted in a more organized tissue when pre-treated in an osteogenic medium. Scaffold type and pre-treatment also determined osteoclast activity and therefore potential remodeling of the constructs. The results of this study cumulatively indicate that treatment medium and scaffold composition direct mineralization and angiogenic tissue formation in an ectopic model. The data suggest that it may be necessary to match the scaffold with a particular cell type and cell-specific pre-treatment to achieve optimal bone formation.
PilT and PilU are homohexameric ATPases that coordinate to retract type IVa pili

Bacterial type IV pili are critical for diverse biological processes including horizontal gene transfer, surface sensing, biofilm formation, adherence, motility, and virulence. These dynamic appendages extend and retract from the cell surface. In many type IVa pilus systems, extension occurs through the action of an extension ATPase, often called PilB, while optimal retraction requires the action of a retraction ATPase, PilT. Many type IVa systems also encode a homolog of PilT called PilU. However, the function of this protein has remained unclear because pilU mutants exhibit inconsistent phenotypes among type IV pilus systems and because it is relatively understudied compared to PilT. Here, we study the type IVa competence pilus of Vibrio cholerae as a model system to define the role of PilU. We show that the ATPase activity of PilU is critical for pilus retraction in PilT Walker A and/or Walker B mutants. PilU does not, however, contribute to pilus retraction in ΔpilT strains. Thus, these data suggest that PilU is a bona fide retraction ATPase that supports pilus retraction in a PilT-dependent manner. We also found that a ΔpilU mutant exhibited a reduction in the force of retraction suggesting that PilU is important for generating maximal retraction forces. Additional in vitro and in vivo data show that PilT and PilU act as independent homo-hexamers that may form a complex to facilitate pilus retraction. Finally, we demonstrate that the role of PilU as a PilT-dependent retraction ATPase is conserved in Acinetobacter baylyi, suggesting that the role of PilU described here may be broadly applicable to other type IVa pilus systems.
Lower Bounds and Fixed Points for the Centered Hardy–Littlewood Maximal Operator

For all $$p>1$$ and all centrally symmetric convex bodies, $$K\subset {\mathbb {R}}^d$$ defined Mf as the centered maximal function associated to K. We show that when $$d=1$$ or $$d=2$$ , we have $$||Mf||_p\ge (1+\epsilon (p,K))||f||_p$$ . For $$d\ge 3$$ , let $$q_0(K)$$ be the infimum value of p for which M has a fixed point. We show that for generic shapes K, we have $$q_0(K)>q_0(B(0,1))$$ .
Slow-wave structures-based method of measurements

A novel electromagnetic measurement method is described from the physical point of view. Based on the application of slow-wave structures, this method combines the advantages of relatively high and relatively low frequency bands. Concentration of an electromagnetic field, caused by wave deceleration, leads to a significant increase in sensitivity. The main parameters and characteristics of the sensitive elements, built as sections of slow-wave structures, are considered in this paper. It is shown that the electric and magnetic fields split in the transverse direction in sensors based on coupled slow-wave structures. This leads to an additional increase in sensitivity. Some examples of practical slow-wave structure-based measurement methods are also presented.
Nof kdumim: Remaking the ancient landscape in East Jerusalem’s national parks:

This article explores two national parks in East Jerusalem and their legal administration as the focus of contradictory and complementary attempts at preservation, colonization, and normalization. ...
Gaia Assorted Mass Binaries Long Excluded from SLoWPoKES (GAMBLES): Identifying Ultra-wide Binary Pairs with Components of Diverse Mass

The formation and evolution of binary star systems still remain key questions in modern astronomy. Wide binary pairs (separations $>10^3$ AU) are particularly intriguing because their low binding energies make it difficult for the stars to stay gravitationally bound over extended timescales,and thus probe the dynamics of binary formation and dissolution. Our previous SLoWPoKES I \& II catalogs provided the largest and most complete sample of wide binary pairs of low masses. Here we present an extension of these catalogs to a broad range of stellar masses: the Gaia Assorted Mass Binaries Long Excluded from SloWPoKES (GAMBLES), comprising 8,660 statistically significant wide pairs that we make available in a living online database. Within this catalog we identify a subset of 543 long-lived (dissipation timescale $>$1.5 Gyr) candidate binary pairs, of assorted mass, with typical separations between $10^3-10^{5.5}$ AU ($0.002-1.5$ pc), using the published distances and proper motions from the Tycho-Gaia Astrometric Solution and Sloan Digital Sky Survey photometry. Each pair has at most a false positive probability of 0.05; the total expectation is 2.44 false binaries in our sample. Among these, we find 22 systems with 3 components, 1 system with 4 components, and 15 pairs consisting of at least 1 possible red giant. We find the largest long-lived binary separation to be nearly 3.2 pc; even so, $>76\%$ of GAMBLES long-lived binaries have large binding energies and dissipation lifetimes longer than 1.5 Gyr. Finally, we find the distribution of binary separations is clearly bimodal, corroborating the finding from SloWPoKES and suggesting multiple pathways for the formation and dissipation of the widest binaries in the Galaxy.
The Ricci flow on the sphere with marked points

The Ricci flow on the $2$-sphere with marked points is shown to converge in all three stable, semi-stable, and unstable cases. In the stable case, the flow was known to converge without any reparametrization, and a new proof of this fact is given. The semistable and unstable cases are new, and it is shown that the flow converges in the Gromov–Hausdorff topology to a limiting metric space which is also a $2$-sphere, but with different marked points and, hence, a different complex structure. The limiting metric is the unique conical constant curvature metric in the semi-stable case, and the unique conical shrinking gradient Ricci soliton metric in the unstable case.
Real world hybrid closed-loop discontinuation: Predictors and perceptions of youth discontinuing the 670G system in the first 6 months.

OBJECTIVE To describe predictors of hybrid closed loop (HCL) discontinuation and perceived barriers to use in youth with type 1 diabetes. SUBJECTS Youth with type 1 diabetes (eligible age 2-25 y; recruited age 8-25 y) who initiated the Minimed 670G HCL system were followed prospectively for 6 mo in an observational study. RESEARCH DESIGN AND METHODS Demographic, glycemic (time-in-range, HbA1c), and psychosocial variables [Hypoglycemia Fear Survey (HFS); Problem Areas in Diabetes (PAID)] were collected for all participants. Participants who discontinued HCL (<10% HCL use at clinical visit) completed a questionnaire on perceived barriers to HCL use. RESULTS Ninety-two youth (15.7 ± 3.6 y, HbA1c 8.8 ± 1.3%, 50% female) initiated HCL, and 28 (30%) discontinued HCL, with the majority (64%) discontinuing between 3 and 6 mo after HCL start. Baseline HbA1c predicted discontinuation (P = .026) with the odds of discontinuing 2.7 times higher (95% CI: 1.123, 6.283) for each 1% increase in baseline HbA1c. Youth who discontinued HCL rated difficulty with calibrations, number of alarms, and too much time needed to make the system work as the most problematic aspects of HCL. Qualitatively derived themes included technological difficulties (error alerts, not working correctly), too much work (calibrations, fingersticks), alarms, disappointment in glycemic control, and expense (cited by parents). CONCLUSIONS Youth with higher HbA1c are at greater risk for discontinuing HCL than youth with lower HbA1c, and should be the target of new interventions to support device use. The primary reasons for discontinuing HCL relate to the workload required to use HCL.
Sawtooth-wave adiabatic passage in a magneto-optical trap

We investigate theoretically the application of sawtooth-wave adiabatic passage (SWAP) in a one-dimensional (1D) magneto-optical trap (MOT). As opposed to related methods that have been previously discussed, our approach utilizes repeated cycles of stimulated absorption and emission processes to achieve both trapping and cooling, thereby reducing the adverse effects that arise from photon scattering. Specifically, we demonstrate this method's ability to cool, slow, and trap particles with fewer spontaneously emitted photons, with higher forces, and in less time when compared to a traditional MOT scheme that utilizes the same narrow linewidth transition. We calculate the phase-space compression that is achievable and characterize the resulting system equilibrium cloud size and temperature.
Simultaneous Identification and Control Using Active Signal Injection for Series Hybrid Electric Vehicles Based on Dynamic Programming

Hybrid electric vehicles (HEVs) are overactuated systems in that they include two power sources: a battery pack and an internal combustion engine. This feature of HEVs is exploited in this article to achieve accurate identification of battery parameters/states. By actively injecting currents, the state of charge, state of health, and other battery parameters can be estimated in a specific sequence to improve identification performance when compared to the case where all parameters and states are estimated concurrently using baseline currents. A dynamic programming strategy is developed to provide the benchmark results regarding how to balance the conflicting objectives corresponding to the identification and system efficiency. The tradeoff between different objectives is presented to optimize the current profile so that the richness of the signal can be ensured and the good fuel economy can be achieved. In addition, simulation results show that the root-mean-square error of the estimation can be decreased by up to 100% at a cost of less than a 2% increase in fuel consumption. With the proposed simultaneous identification and control algorithm, the parameters/states of the battery can be monitored to ensure safe and efficient operation of the battery for HEVs.
Formation of Hypervalent Ammoniated Radicals by Neutralized Ion Beam Techniques

Generation d'une serie de racicaux hypervalents par neutralisation d'un faisceau rapide des ions NH 4 (NH 3 ) n + ou CH 3 NH 3 (NH 3 ) 2 + dans des reactions de transfert d'electrons. Effets de l'excitation interne sur les diagrammes de decomposition des radicaux
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

As machine learning black boxes are increasingly being deployed in domains such as healthcare and criminal justice, there is growing emphasis on building tools and techniques for explaining these black boxes in an interpretable manner. Such explanations are being leveraged by domain experts to diagnose systematic errors and underlying biases of black boxes. In this paper, we demonstrate that post hoc explanations techniques that rely on input perturbations, such as LIME and SHAP, are not reliable. Specifically, we propose a novel scaffolding technique that effectively hides the biases of any given classifier by allowing an adversarial entity to craft an arbitrary desired explanation. Our approach can be used to scaffold any biased classifier in such a way that its predictions on the input data distribution still remain biased, but the post hoc explanations of the scaffolded classifier look innocuous. Using extensive evaluation with multiple real world datasets (including COMPAS), we demonstrate how extremely biased (racist) classifiers crafted by our framework can easily fool popular explanation techniques such as LIME and SHAP into generating innocuous explanations which do not reflect the underlying biases.
Existence of traveling wave solutions of a deterministic vector-host epidemic model with direct transmission

Abstract We consider an epidemic model with direct transmission given by a system of nonlinear partial differential equations and study the existence of traveling wave solutions. When the basic reproductive number of the considered model is less than one, we show that there is no nontrivial traveling wave solution. On the other hand, when the basic reproductive number is greater than one, we prove that there is a minimum wave speed c ⁎ such that the system has a traveling wave solution with speed c connecting both equilibrium points for any c ≥ c ⁎ . Moreover, under suitable assumption on the diffusion rates, we show that there is no traveling wave solution with speed less than c ⁎ . We conclude with numerical simulations to illustrate our findings. The numerical experiments support the validity of our theoretical results.
The balance of interaction types determines the assembly and stability of ecological communities.

What determines the assembly and stability of complex communities is a central question in ecology. Past work has suggested that mutualistic interactions are inherently destabilizing. However, this conclusion relies on the assumption that benefits from mutualisms never stop increasing. Furthermore, almost all theoretical work focuses on the internal (asymptotic) stability of communities assembled all at once. Here, we present a model with saturating benefits from mutualisms and sequentially assembled communities. We show that such communities are internally stable for any level of diversity and any combination of species interaction types. External stability, or resistance to invasion, is thus an important but overlooked measure of stability. We demonstrate that the balance of different interaction types governs community dynamics. A higher fraction of mutualistic interactions can increase the external stability and diversity of communities as well as species persistence, if mutualistic interactions tend to provide unique benefits. Ecological selection increases the prevalence of mutualisms, and limits on biodiversity emerge from species interactions. Our results help resolve long-standing debates on the stability, saturation and diversity of communities. A model of community assembly that is sequential and has saturating benefits of mutualism produces communities with internal stability for any level of diversity, and for which external stability depends on the balance of interaction types.
Pharmacological target-focused transcriptomic analysis of native vs cultured human and mouse dorsal root ganglia

Dorsal root ganglion (DRG) neurons detect sensory inputs and are crucial for pain processing. They are often studied in vitro as dissociated cell cultures with the assumption that this reasonably represents in vivo conditions. However, to the best of our knowledge, no study has directly compared genome-wide transcriptomes of DRG tissue in vivo versus in vitro or between laboratories and culturing protocols. Comparing RNA sequencing-based transcriptomes of native to cultured (4 days in vitro) human or mouse DRG, we found that the overall expression levels of many ion channels and G-protein-coupled receptors specifically expressed in neurons are markedly lower although still expressed in culture. This suggests that most pharmacological targets expressed in vivo are present under the condition of dissociated cell culture, but with changes in expression levels. The reduced relative expression for neuronal genes in human DRG cultures is likely accounted for by increased expression of genes in fibroblast-like and other proliferating cells, consistent with their mitotic status in these cultures. We found that the expression of a subset of genes typically expressed in neurons increased in human and mouse DRG cultures relative to the intact ganglion, including genes associated with nerve injury or inflammation in preclinical models such as BDNF, MMP9, GAL, and ATF3. We also found a striking upregulation of a number of inflammation-associated genes in DRG cultures, although many were different between mouse and human. Our findings suggest an injury-like phenotype in DRG cultures that has important implications for the use of this model system for pain drug discovery.