cssi/SciSciGPT-SciSciNet huggingface dataset:
Effect of Armed Conflict on Intimate Partner Violence : Evidence from the Boko Haram Insurgency in Nigeria

Intimate partner violence is the most common form of violence against women in conflict and non-conflict settings, but in conflict settings it often receives less attention than other forms of gender-based violence, such as conflict-related sexual violence. Using data from the 2008 and 2013 Domestic Violence module of the Nigerian Demographic and Health Survey spatially linked to the Boko Haram actor file of the Armed Conflict Location and Events Database, this paper employs a kernel-based difference-in-difference model to examine the effect of the Boko Haram insurgency on women's experience of physical and sexual intimate partner violence. It also examines the effect of the Boko Haram insurgency on women's experience of controlling behavior from a husband or partner, women's autonomy in household decision making, and their control over their own earnings. The paper finds that the Boko Haram insurgency is associated with slower progress toward preventing and eliminating women's experiences of physical and sexual intimate partner violence. Controlling behaviors from husbands/partners and reductions in women's autonomy in household decision making are heightened in locations that are impacted by the Boko Haram insurgency, indicating that the Boko Haram insurgency adversely affects women's agency and exacerbates behaviors that are often precursors to intimate partner violence.
Peering Into the Anneal Process of a Quantum Annealer

Commercial adiabatic quantum annealers have the potential to solve important NP-hard optimization problems efficiently. The newest generation of those machines additionally allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the annealing. In this work we use the aforementioned feature of the D-Wave 2000Q to attempt to monitor how the anneal solution evolves during the anneal process. This process we call slicing: at each time slice during the anneal, we are able to obtain an approximate distribution of anneal solutions. We use our technique to obtain a variety of insights into the D-Wave 2000Q. For example, we observe when individual bits flip during the anneal process and when they stabilize, which allows us to determine the freeze-out point for each qubit individually. We highlight our results using both random QUBO (quadratic unconstrained binary optimization) instances and, for better visualization, instances which we specifically optimize (using our own genetic algorithm) to exhibit a pronounced evolution of its solution during the anneal.
Single cell RNA-seq analysis reveals compartment-specific heterogeneity and plasticity of microglia

Microglia are heterogeneous and ubiquitous CNS-resident macrophages that maintain homeostasis of neural tissues and protect them from pathogen attacks. Yet, their differentiation in different compartments remains elusive. We performed single cell RNA-seq (scRNA-seq) analysis to compare the transcriptomes of microglia in adult mouse (C57/Bl) brains and spinal cords to identify microglial subtypes in these CNS compartments. Cortical microglia from 2-month mice consisted of a predominant population of the homeostatic subtype (HOM-M) and a small population (4%) of the inflammatory subtype (IFLAM-M), while spinal microglia consisted of 55% HOM-M and 45% IFLAM-M subtype. Comparison of cortical and spinal microglia at 2, 4 and 8 months revealed consistently a higher composition of the IFLAM-M subtype in the spinal cord. At 8-month, cortical microglia differentiated a small new subtype with interferon response phenotypes (INF-M), while spinal microglia polarized toward a proinflammatory phenotype, as indicated by the increase of microglia expressing IL-1β. To further characterize the differential plasticity of cortical and spinal microglial heterogeneity, we determined the microglial transcriptomes from HIV-1 gp120 transgenic (Tg) mice, a model of HIV-associated neurological disorders. Compared with wilt-type (Wt) cortical microglia, the gp120Tg cortical microglia had three new subtypes, with signatures of interferon I response (INF-M), cell proliferation (PLF-M), and myelination or demyelination (MYE-M) respectively; while INF-M and PLF-M subtypes presented at all ages, the MYE-M only at 4-month. In contrast, only the INF-M subtype was observed in the spinal microglia from 2- and 4-month gp120tg mice. Bioinformatic analysis of regulated molecular pathways of individual microglial subtypes indicated that gp120 more severely impaired the biological function of microglia in cortices than in the spinal cord. The results collectively reveal differential heterogeneity and plasticity of cortical and spinal microglia, and suggest functional differentiation of microglia in different CNS compartments.
Optically tunable microresonator using an azobenzene monolayer

Photoswitchable organic molecules can undergo reversible structural changes with an external light stimulus. These optically controlled molecules have been used in the development of “smart” polymers, optical writing of grating films, and even controllable in vivo drug release. Being the simplest class of photoswitches in terms of structure, azobenzenes have become the most ubiquitous, well-characterized, and implemented organic molecular switches. Given their predictable response, they are ideally suited to create an all-optically controlled switch. However, fabricating a monolithic optical device comprised solely of azobenzene while maintaining the photoswitching functionality is challenging. In this work, we combine integrated photonics with optically switchable organic molecules to create an optically controlled integrated device. A silica toroidal resonant cavity is functionalized with a monolayer of an azobenzene derivative. After functionalization, the loaded cavity Q is above 105. When 450 nm light is coupled into cavity resonance, the azobenzene isomerizes from trans isomer to cis isomer, inducing a refractive index change. Because the resonant wavelength of the cavity is governed by the index, the resonant wavelength changes in parallel. At a probe wavelength of 1300 nm, the wavelength shift is determined by the duration and intensity of the 450 nm light and the density of azobenzene functional groups on the device surface, providing multiple control mechanisms. Using this photoswitchable device, resonance frequency tuning as far as 60% of the cavity’s free spectral range in the near-IR is demonstrated. The kinetics of the tuning are in agreement with spectroscopic and ellipsometry measurements coupled with finite element method calculations.
On the Construction of Closed Nonconvex Nonsoliton Ancient Mean Curvature Flows

We construct closed, embedded, ancient mean curvature flows in each dimension $n\ge 2$ with the topology of $S^1 \times S^{n-1}$. These examples are not mean convex and not solitons. They are constructed by analyzing perturbations of the self-shrinking doughnuts constructed by Drugan and Nguyen (or, alternatively, Angenent's self shrinking torus when $n =2$)
Regional UK house price co-movement

Cyclical synchronization of home prices has important implications for monetary (and other) policies. Regional house price divergence, even over a business cycle, can inhibit labour mobility and pr...
Rapid Simulation of Photonic Integrated Circuits Using Verilog-A Compact Models

Silicon-based electronic-photonic integration offers several opportunities for integrated circuits (IC) designers to innovate systems architectures that leverage the advantages of optical-domain signal processing and low-loss transmission in optical fibers. However, photonic integrated circuit (PIC) design tools have evolved from the numerical Maxwell field solvers and are completely disjointed from the electronic circuit simulation tools such as SPICE and Cadence Spectre. Thus there is a gap that needs to be filled by the IC community where they can instantiate photonic building blocks to form PICs and perform co-simulation with interfacing (Bi)CMOS electronic circuits. In recent work, Verilog-A compact models have been developed for photonic device building blocks that enable transient simulations of hybrid electronic-photonic components such as lasers, modulators and detectors. However, frequency sweeps of radio-frequency (RF) photonic filters remain unwieldy due to the long simulation times of stepped frequency transient simulations. In this work, we present complex frequency chirp based methods for rapid frequency-domain simulation of PICs. The trade-offs involved in selecting the simulation parameters for a given frequency response accuracy and simulation time are studied along with the impact of windowing and frequency chirp profile. The presented method can result in over $1000\times $ improvement in simulation time of frequency sweeps of higher-order RF photonic filter topologies.
CHAPTER 2 – Measures

Publisher Summary This chapter discusses the measure-theoretic foundation and presents the definition of Hausdorff measure and covering theory. There is a unique Borel regular, translation invariant measure on Rn such that the measure of the unit cube [0, l]n is 1. This measure is called Lebesgue measure. In 1918, F. Hausdorff introduced an m-dimensional measure in Rn that gives the same area for submanifolds but is defined on all subsets of Rn. When m = n, it turns out to be equal Lebesgue measure. In 1932, J. Favard defined another m-dimensional measure on Rn (m = 0, 1, … , n), which is called integral-geometric measure. It turns out that integral-geometric measure agrees with Hausdorff measure on all smooth m-dimensional submanifolds and other nice sets but disagrees and often is zero on Cantor-like sets.
The future of telecommuting

Abstract Interest in telecommuting is growing among workers, employers, transportation planners, communities, the telecommunications industry, and others. But actual levels of telecommuting appear to be increasing slowly, although there is little reliable data on trends. The future of telecommuting depends on whether employers provide the opportunity to telecommute and whether workers take advantage of this opportunity; government policies can encourage both. This article addresses that future by outlining and evaluating important trends in a variety of factors and explores the need for further research on telecommuting trends and impacts. For the most part the future of telecommuting looks promising, but many questions remain about how telecommuting will evolve over time.
Moderate Amounts of Epistasis are Not Evolutionarily Stable in Small Populations

High mutation rates select for the evolution of mutational robustness where populations inhabit flat fitness peaks with little epistasis, protecting them from lethal mutagenesis. Recent evidence suggests that a different effect protects small populations from extinction via the accumulation of deleterious mutations. In drift robustness, populations tend to occupy peaks with steep flanks and positive epistasis between mutations. However, it is not known what happens when mutation rates are high and population sizes are small at the same time. Using a simple fitness model with variable epistasis, we show that the equilibrium fitness has a minimum as a function of the parameter that tunes epistasis, implying that this critical point is an unstable fixed point for evolutionary trajectories. In agent-based simulations of evolution at finite mutation rate, we demonstrate that when mutations can change epistasis, trajectories with a subcritical value of epistasis evolve to decrease epistasis, while those with supercritical initial points evolve towards higher epistasis. These two fixed points can be identified with mutational and drift robustness, respectively.
Reducing Product Expiration by Aligning Salesforce Incentives: A Data‐driven Approach

Product expirations at retail stores erode profits and burden the environment. We investigate whether manufacturers can leverage salesforce compensation design as a waste‐reduction tool. We propose a data‐driven framework that uses structural econometric modeling and agency theory. Our analysis starts with a game theoretic model in which a salesperson interacts with a manufacturer that reimburses retailers and penalizes its own salesforce for expired products. We then use our model’s equilibrium outcome to estimate factors that determine the effort exerted by the sales representatives of a consumer‐packaged‐goods manufacturer. We first show theoretically that a manufacturer can simultaneously increase profits and reduce waste by increasing its sales representatives’ penalty for product expiration that occurs at the retailer. Based on this, we formulate a manufacturer’s profit maximization problem to compute optimum expiration penalties. Solving this problem for the manufacturer, we find the potential to simultaneously reduce waste and improve profits for 14% of the product–market combinations in our dataset. For these cases, we find that charging the salesperson 2.1 times the commission (on average) for each expired unit can increase the manufacturer’s profits by 0.58% and reduce waste by 23.3%. This study determines that a profit‐seeking manufacturer can reduce waste at retailers by optimizing its salesforce incentive structure. Our work bridges the salesforce compensation and sustainable operations literatures. Furthermore, our framework allows consumer‐packaged‐goods manufacturers to identify win‐win opportunities for the environment and their bottom line.
Intertemporal substitution, risk aversion, and economic performance in a stochastically growing open economy

Abstract The constant elasticity utility function implies that the intertemporal elasticity of substitution is the inverse of the coefficient of relative risk aversion. With empirical evidence suggesting that this relationship may or may not hold, studies of risk and growth should decouple these two parameters. This paper provides an analytical characterization and numerical simulations of the equilibrium of a stochastically growing small open economy under general recursive preferences. We show that errors committed by using the constant elasticity utility function, even for small violations of the compatibility condition, can be substantial. Our results suggest that the constant elasticity utility function should be employed with caution.
Single-molecule orientation localization microscopy for resolving structural heterogeneities between amyloid fibrils

Simultaneous measurements of single-molecule positions and orientations provide critical insight into a variety of biological and chemical processes. Various engineered point spread functions (PSFs) have been introduced for measuring the orientation and rotational diffusion of dipole-like emitters, but the widely used Cramer-Rao bound (CRB) only evaluates performance for one specific orientation at a time. Here, we report a performance metric, termed variance upper bound (VUB), that yields a global maximum CRB for all possible molecular orientations, thereby enabling the measurement performance of any PSF to be computed efficiently (~1000× faster than calculating average CRB). Our VUB reveals that the simple polarized standard PSF provides robust and precise orientation measurements if emitters are near a refractive index interface. Using this PSF, we measure the orientations and positions of Nile red (NR) molecules transiently bound to amyloid aggregates. Our super-resolved images reveal the main binding mode of NR on amyloid fiber surfaces, as well as structural heterogeneities along amyloid fibrillar networks, that cannot be resolved by single-molecule localization alone.
Career Concerns of Mutual Fund Managers

We examine the labor market for mutual fund managers. Using data from 1992–1994, we find that "termination" is more performance-sensitive for younger managers. We identify possible implicit incentives created by the termination-performance relationship. The shape of the termination-performance relationship may give younger managers an incentive to avoid unsystematic risk. Direct effects of portfolio composition may also give younger managers an incentive to "herd" into popular sectors. Consistent with these incentives, we find that younger managers hold less unsystematic risk and have more conventional portfolios. Promotion incentives and market responses to managerial turnover are also studied.
Nonlinear Mixed Effects Models

Nonlinear mixed-effects (NLME) models are a generalization of LME and nonlinear regression models and are used when data have a hierarchical growth-curve structure where an LME model might be used but a nonlinear model is required to fit the data. Both LME and NLME models require some care in estimating and testing model parameters. NLME models have additional difficulties due to the lack of a closed form for the marginal distribution of the data (see following sections). Keywords: linear mixed-effects models; hierarchical models; nonlinear regression; repeated measures data; longitudinal data; growth-curve data
STABILITY OF NON-COMPACT SETS

Publisher Summary This chapter discusses the stability of noncompact sets in semidynamical systems (SDSs.). These systems are continuous flows defined for all future time (non-negative t). The chapter presents the natural examples of SDSs by functional differential equations for which existence and uniqueness conditions hold. SDSs offer new and interesting notions which are not possible in dynamical systems. The chapter discusses limit sets and prolongations and their limit sets. For a rim-compact space, t each of positive limit set and prolongational limit is weakly negatively invariant and contains no start points; moreover if the prolongational limit set is nonempty and compact, so is the positive limit set. The chapter also describes stability and asymptotic stability.
Are there civic returns to education

Abstract The hypothesized effects of educational attainment on adult civic engagement and attitudes provide some of the most important justifications for government intervention in the market for education. In this study, I present evidence on whether these externalities exist. I assess and implement two strategies for identifying the effects of educational attainment. One is based on the availability of junior and community colleges; the other, on changes in teen exposure to child labor laws. The results suggest that educational attainment has large and statistically significant effects on subsequent voter participation and support for free speech. I also find that additional schooling appears to increase the quality of civic knowledge as measured by the frequency of newspaper readership.
Investigating the dynamics of microbial consortia in spatially structured environments

The spatial organization of microbial communities arises from a complex interplay of biotic and abiotic interactions, and is a major determinant of ecosystem functions. Here we design a microfluidic platform to investigate how the spatial arrangement of microbes impacts gene expression and growth. We elucidate key biochemical parameters that dictate the mapping between spatial positioning and gene expression patterns. We show that distance can establish a low-pass filter to periodic inputs and can enhance the fidelity of information processing. Positive and negative feedback can play disparate roles in the synchronization and robustness of a genetic oscillator distributed between two strains to spatial separation. Quantification of growth and metabolite release in an amino-acid auxotroph community demonstrates that the interaction network and stability of the community are highly sensitive to temporal perturbations and spatial arrangements. In sum, our microfluidic platform can quantify spatiotemporal parameters influencing diffusion-mediated interactions in microbial consortia.
Projective-umbilic points of circular real hypersurfaces in $\mathbb {C}^2$

We show that the boundary of any bounded strongly pseudoconvex complete circular domain in $\mathbb C^2$ must contain points that are exceptionally tangent to a projective image of the unit sphere.
Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics

Mendelian randomization (MR) is a valuable tool for detecting causal effects by using genetic variant associations. Opportunities to apply MR are growing rapidly with the increasing number of genome-wide association studies (GWAS). However, existing MR methods rely on strong assumptions that are often violated, leading to false positives. Correlated horizontal pleiotropy, which arises when variants affect both traits through a heritable shared factor, remains a particularly challenging problem. We propose a new MR method, Causal Analysis Using Summary Effect estimates (CAUSE), that accounts for correlated and uncorrelated horizontal pleiotropic effects. We demonstrate, in simulations, that CAUSE avoids more false positives induced by correlated horizontal pleiotropy than other methods. Applied to traits studied in recent GWAS studies, we find that CAUSE detects causal relationships that have strong literature support and avoids identifying most unlikely relationships. Our results suggest that shared heritable factors are common and may lead to many false positives using alternative methods.
DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection

Pulmonary nodule detection plays an important role in lung cancer screening with low-dose computed tomography (CT) scans. It remains challenging to build nodule detection deep learning models with good generalization performance due to unbalanced positive and negative samples. In order to overcome this problem and further improve state-of-the-art nodule detection methods, we develop a novel deep 3D convolutional neural network with an Encoder-Decoder structure in conjunction with a region proposal network. Particularly, we utilize a dynamically scaled cross entropy loss to reduce the false positive rate and combat the sample imbalance problem associated with nodule detection. We adopt the squeeze-and-excitation structure to learn effective image features and utilize inter-dependency information of different feature maps. We have validated our method based on publicly available CT scans with manually labelled ground-truth obtained from LIDC/IDRI dataset and its subset LUNA16 with thinner slices. Ablation studies and experimental results have demonstrated that our method could outperform state-of-the-art nodule detection methods by a large margin.
Understanding Spatial Relations through Multiple Modalities

Recognizing spatial relations and reasoning about them is essential in multiple applications including navigation, direction giving and human-computer interaction in general. Spatial relations between objects can either be explicit – expressed as spatial prepositions, or implicit – expressed by spatial verbs such as moving, walking, shifting, etc. Both these, but implicit relations in particular, require significant common sense understanding. In this paper, we introduce the task of inferring implicit and explicit spatial relations between two entities in an image. We design a model that uses both textual and visual information to predict the spatial relations, making use of both positional and size information of objects and image embeddings. We contrast our spatial model with powerful language models and show how our modeling complements the power of these, improving prediction accuracy and coverage and facilitates dealing with unseen subjects, objects and relations.
Power to the outsiders: External hiring and decision authority allocation within organizations

Research Summary This study examines the relationship between external hiring and the allocation of decision authority within organizations, and how they interact to affect organizational change and innovation. We test our hypotheses using panel data for a nationally representative sample of businesses in Canada. We find that the practice of external hiring of managers and high‐skilled nonmanagerial employees predicts greater decision authority allocated to each respective level of the hierarchy. Reallocation of authority is positively moderated by the strategic priority of (a) workplace reorganization for managerial hiring, and (b) new product development for nonmanagerial hiring. We also find evidence of related associations with workplace reorganization and product innovation. The findings suggest that decision authority allocation is essential to effectively utilize externally acquired human capital. Managerial Summary This study examines how the effectiveness of hiring managers and high‐skilled nonmanagerial employees from outside the firm is related to how much decision authority they are granted. We show that for both types of employees, external hiring predicts greater decision authority allocated to each respective level of the organization. For managers, external hiring predicts a greater likelihood of organizational change when more decision authority is granted. Similarly, for high‐skilled nonmanagerial employees, external hiring predicts the development of more novel innovations when more decision authority is given. Overall, the results suggest that hiring talent from outside the firm by itself is not sufficient to expect benefits to the organization—instead, firms must also empower outside hires with the authority needed to translate their knowledge into performance.
Fast, Convexified Stochastic Optimal Open-Loop Control for Linear Systems Using Empirical Characteristic Functions

We consider the problem of stochastic optimal control in the presence of an unknown disturbance. We characterize the disturbance via empirical characteristic functions, and employ a chance constrained approach. By exploiting properties of characteristic functions and underapproximating cumulative distribution functions, we can reformulate a nonconvex problem by a conic, convex under-approximation. This results in extremely fast solutions that are assured to maintain probabilistic constraints. We construct algorithms to solve an optimal open-loop control problem and demonstrate our approach on two examples.
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

We consider nonconvex-concave minimax problems, $\min_{\mathbf{x}} \max_{\mathbf{y} \in \mathcal{Y}} f(\mathbf{x}, \mathbf{y})$, where $f$ is nonconvex in $\mathbf{x}$ but concave in $\mathbf{y}$ and $\mathcal{Y}$ is a convex and bounded set. One of the most popular algorithms for solving this problem is the celebrated gradient descent ascent (GDA) algorithm, which has been widely used in machine learning, control theory and economics. Despite the extensive convergence results for the convex-concave setting, GDA with equal stepsize can converge to limit cycles or even diverge in a general setting. In this paper, we present the complexity results on two-time-scale GDA for solving nonconvex-concave minimax problems, showing that the algorithm can find a stationary point of the function $\Phi(\cdot) := \max_{\mathbf{y} \in \mathcal{Y}} f(\cdot, \mathbf{y})$ efficiently. To the best our knowledge, this is the first nonasymptotic analysis for two-time-scale GDA in this setting, shedding light on its superior practical performance in training generative adversarial networks (GANs) and other real applications.
DeltaGrad: Rapid retraining of machine learning models

Machine learning models are not static and may need to be retrained on slightly changed datasets, for instance, with the addition or deletion of a set of data points. This has many applications, including privacy, robustness, bias reduction, and uncertainty quantifcation. However, it is expensive to retrain models from scratch. To address this problem, we propose the DeltaGrad algorithm for rapid retraining machine learning models based on information cached during the training phase. We provide both theoretical and empirical support for the effectiveness of DeltaGrad, and show that it compares favorably to the state of the art.
Novel Object Viewpoint Estimation Through Reconstruction Alignment

The goal of this paper is to estimate the viewpoint for a novel object. Standard viewpoint estimation approaches generally fail on this task due to their reliance on a 3D model for alignment or large amounts of class-specific training data and their corresponding canonical pose. We overcome those limitations by learning a reconstruct and align approach. Our key insight is that although we do not have an explicit 3D model or a predefined canonical pose, we can still learn to estimate the object’s shape in the viewer’s frame and then use an image to provide our reference model or canonical pose. In particular, we propose learning two networks: the first maps images to a 3D geometry-aware feature bottleneck and is trained via an image-to-image translation loss; the second learns whether two instances of features are aligned. At test time, our model finds the relative transformation that best aligns the bottleneck features of our test image to a reference image. We evaluate our method on novel object viewpoint estimation by generalizing across different datasets, analyzing the impact of our different modules, and providing a qualitative analysis of the learned features to identify what representation is being learnt for alignment.
Early Outcomes of Preoperative 5-Fraction Radiation Therapy for Soft Tissue Sarcoma Followed by Immediate Surgical Resection

Abstract Purpose There are limited data regarding the use of hypofractionated radiation therapy (RT) for soft tissue sarcoma. We report early oncologic outcomes and wound complications of patients undergoing preoperative hypofractionated (5 fraction) RT followed by immediate surgical resection. Methods and Materials An institutional review board–approved database of patients treated with preoperative RT for soft tissue sarcoma was queried. Patients treated with a hypofractionated dosing regimen followed by immediate (within 7 days) planned wide surgical resection were identified. Results Between 2016 and 2019, 16 patients met eligibility criteria. The median patient age was 64 years old (range, 33-88). Ten of the sarcomas were located in the lower extremity, 4 in the upper extremity, and 2 were located in the trunk. Four patients had metastatic disease at diagnosis. The majority of the patients received a total radiation dose of 30 Gy in 5 fractions (range, 27.5-40 Gy) on consecutive days. All patients were planned with intensity modulated radiation therapy or volumetric arc therapy. The median time to surgical resection after the completion of RT was 1 day (range, 0-7 days). The median time from initial biopsy results to completion of primary oncologic therapy was 20 days (range, 16-35). Ten patients achieved R0 resection, whereas the remaining 6 patients achieved R1 resection. Of the 13 patients assessed for local control, no patients developed local failure. Within the median follow-up time of 10.7 months (range, 1.7-33.2), 5 patients developed wound healing complications (31%), of which only 3 patients (19%) required return to the operating room. Conclusions Treatment of soft tissue sarcoma with preoperative hypofractionated RT followed by immediate resection resulted in a median of 20 days from biopsy results to completion of oncologic therapy. Early outcomes demonstrate favorable wound healing. Further prospective data with long-term follow-up is required to determine the oncologic outcomes and toxicity of hypofractionated preoperative RT.
Size-Regulated Symmetry Breaking in Reaction-Diffusion Models of Developmental Transitions

The development of multicellular organisms proceeds through a series of morphogenetic and cell-state transitions, transforming homogeneous zygotes into complex adults by a process of self-organisation. Many of these transitions are achieved by spontaneous symmetry breaking mechanisms, allowing cells and tissues to acquire pattern and polarity by virtue of local interactions without an upstream supply of information. The combined work of theory and experiment has elucidated how these systems break symmetry during developmental transitions. Given that such transitions are multiple and their temporal ordering is crucial, an equally important question is how these developmental transitions are coordinated in time. Using a minimal mass-conserved substrate-depletion model for symmetry breaking as our case study, we elucidate mechanisms by which cells and tissues can couple reaction–diffusion-driven symmetry breaking to the timing of developmental transitions, arguing that the dependence of patterning mode on system size may be a generic principle by which developing organisms measure time. By analysing different regimes of our model, simulated on growing domains, we elaborate three distinct behaviours, allowing for clock-, timer- or switch-like dynamics. Relating these behaviours to experimentally documented case studies of developmental timing, we provide a minimal conceptual framework to interrogate how developing organisms coordinate developmental transitions.
Packet chasing: spying on network packets over a cache side-channel

This paper presents Packet Chasing, an attack on the network that does not require access to the network, and works regardless of the privilege level of the process receiving the packets. A spy process can easily probe and discover the exact cache location of each buffer used by the network driver. Even more useful, it can discover the exact sequence in which those buffers are used to receive packets. This then enables packet frequency and packet sizes to be monitored through cache side channels. This allows both covert channels between a sender and a remote spy with no access to the network, as well as direct attacks that can identify, among other things, the web page access patterns of a victim on the network. In addition to identifying the potential attack, this work proposes a software-based short-term mitigation as well as a light-weight, adaptive, cache partitioning mitigation that blocks the interference of I/O and CPU requests in the last-level cache.
Convection-induced singularity suppression in the Keller-Segel and other non-linear PDEs

In this paper we study the effect of the addition of a convective term, and of the resulting increased dissipation rate, on the growth of solutions to a general class of non-linear parabolic PDEs. In particular, we show that blow-up in these models can always be prevented if the added drift has a small enough dissipation time. We also prove a general result relating the dissipation time and the effective diffusivity of stationary cellular flows, which allows us to obtain examples of simple incompressible flows with arbitrarily small dissipation times. As an application, we show that blow-up in the Keller-Segel model of chemotaxis can always be prevented if the velocity field of the ambient fluid has a sufficiently small dissipation time. We also study reaction-diffusion equations with ignition-type nonlinearities, and show that the reaction can always be quenched by the addition of a convective term with a small enough dissipation time, provided the average initial temperature is initially below the ignition threshold.
Balancing security and liberty

This is an excellent time to make security fundamental to any real next-generation network, and for the technical community to get involved in continuing efforts to preserve liberty as well as safety.
Improving Sustainability of Cryptocurrency Payment Networks for IoT Applications

Blockchain-based cryptocurrencies received a lot of attention recently for their applications in many domains. IoT domain is one of such applications, which can utilize cryptocur-rencies for micro payments without compromising their payment privacy. However, long confirmation times of transactions and relatively high fees hinder the adoption of cryptoccurency based micro-payments. The payment channel networks is one of the proposed solutions to address these issue where nodes establish payment channels among themselves without writing on blockchain. IoT devices can benefit from such payment networks as long as they are capable of sustaining their overhead. Payment channel networks pose unique characteristics as far as the routing problem is concerned. Specifically, they should stay balanced to have a sustainable network for maintaining payments for longer times, which is crucial for IoT devices once they are this http URL this paper, we present a payment channel network design that aims to keep the channels balanced by using a common weight policy across the network. We additionally propose using multi-point connections to nodes for each IoT device for unbalanced payment scenarios. The experiment results show that we can keep the channels in the network more equally balanced compared to the minimal fee approach. In addition, multiple connections from IoT devices to nodes increase the success ratio significantly.
Sex-Dependent Macromolecule and Nanoparticle Delivery in Experimental Brain Injury

The development of effective therapeutics for brain disorders is challenging, in particular, the blood-brain barrier (BBB) severely limits access of the therapeutics into the brain parenchyma. Traumatic brain injury (TBI) may lead to transient BBB permeability that affords a unique opportunity for therapeutic delivery via intravenous administration ranging from macromolecules to nanoparticles (NPs) for developing precision therapeutics. In this regard, we address critical gaps in understanding the range/size of therapeutics, delivery window(s), and moreover, the potential impact of biological factors for optimal delivery parameters. Here we show, for the first time, to the best of our knowledge, that 24-h postfocal TBI female mice exhibit a heightened macromolecular tracer and NP accumulation compared with male mice, indicating sex-dependent differences in BBB permeability. Furthermore, we report for the first time the potential to deliver NP-based therapeutics within 3 days after focal injury in both female and male mice. The delineation of injury-induced BBB permeability with respect to sex and temporal profile is essential to more accurately tailor time-dependent precision and personalized nanotherapeutics. Impact statement In this study, we identified a sex-dependent temporal profile of blood/brain barrier disruption in a preclinical mouse model of traumatic brain injury (TBI) that contributes to starkly different macromolecule and nanoparticle delivery profiles post-TBI. The implications and potential impact of this work are profound and far reaching as it indicates that a demand of true personalized medicine for TBI is necessary to deliver the right therapeutic at the right time for the right patient.
Partial regularity of weak solutions and life-span of smooth solutions to a biological network formulation model

In this paper we study partial regularity of weak solutions to the initial boundary value problem for the system $$-\text {div}\left[ (I+\mathbf{m}\otimes \mathbf{m})\nabla p\right] =S(x),\ \ \partial _t\mathbf{m}-D^2\Delta \mathbf{m}-E^2(\mathbf{m}\cdot \nabla p)\nabla p+|\mathbf{m}|^{2(\gamma -1)}{} \mathbf{m}=0$$ , where S(x) is a given function and $$D, E, \gamma$$ are given numbers. This problem has been proposed as a PDE model for biological transportation networks. The mathematical difficulty is due to the fact that the system in the model features both a quadratic nonlinearity and a cubic nonlinearity. The regularity issue seems to have a connection to a conjecture by De Giorgi (Congetture sulla continuita delle soluzioni di equazioni lineari ellittiche autoaggiunte a coefficienti illimitati, Unpublished, 1995). We also investigate the life-span of classical solutions. Our results show that local existence of a classical solution can always be obtained and the life-span of such a solution can be extended as far away as one wishes as long as the term $$\Vert \mathbf{m}(x,0)\Vert _{\infty , \Omega }+\Vert S(x)\Vert _{\frac{2N}{3}, \Omega }$$ is made suitably small, where N is the space dimension and $$\Vert \cdot \Vert _{q,\Omega }$$ denotes the norm in $$L^q(\Omega )$$ .
Understanding the Value of Delayed Discounts in Retail Rewards Programs

In practice it is not uncommon for a retailer to incentivize consumers to purchase its products by instituting a standing ``rewards program'' across its product line. These rewards often take the form of earned credit, calculated based on current spending, applicable towards a future purchase. In this paper we show that despite their euphemistic `rewards' label, the future-credit promotion structure is often advantageous for the retailer, even given customers who behave rationally. By analyzing a retailer that sells distinct products to heterogeneous consumers with stochastic demands, we find that a time-lagged discount increases the number of resulting net-price states, thus expanding the set of rational shopping behaviors and segmentation. We also prove that even while delayed rewards generally yield higher discount levels (relative to immediate discounts), they can generate higher expected profits. We also consider the impact of imposing a spending-level threshold for customers to earn rewards, and analyze the impact of the distinct shopping behaviors which then emerge. By proving the efficacy of such delayed-reward promotion structures, relative to the alternative of immediate discounts, we establish a theoretical basis for explaining why rewards programs are common in retail practice.
User-Space Emulation Framework for Domain-Specific SoC Design.

In this work, we propose a portable, Linux-based emulation framework to provide an ecosystem for hardware-software co-design of Domain-specific SoCs (DSSoCs) and enable their rapid evaluation during the pre-silicon design phase. This framework holistically targets three key challenges of DSSoC design: accelerator integration, resource management, and application development. We address these challenges via a flexible and lightweight user-space runtime environment that enables easy integration of new accelerators, scheduling heuristics, and user applications, and we illustrate the utility of each through various case studies. With signal processing (WiFi and RADAR) as the target domain, we use our framework to evaluate the performance of various dynamic workloads on hypothetical DSSoC hardware configurations composed of mixtures of CPU cores and FFT accelerators using a Zynq UltraScale+ TM MPSoC. We show the portability of this framework by conducting a similar study on an Odroid platform composed of big.LITTLE ARM clusters. Finally, we introduce a prototype compilation toolchain that enables automatic mapping of unlabeled C code to DSSoC platforms. Taken together, this environment offers a unique ecosystem to rapidly perform functional verification and obtain performance and utilization estimates that help accelerate convergence towards a final DSSoC design.
A hybrid achromatic metalens

Metalenses, ultra-thin optical elements that focus light using subwavelength structures, have been the subject of a number of recent investigations. Compared to their refractive counterparts, metalenses offer reduced size and weight, and new functionality such as polarization control. However, metalenses that correct chromatic aberration also suffer from markedly reduced focusing efficiency. Here we introduce a Hybrid Achromatic Metalens (HAML) that overcomes this trade-off and offers improved focusing efficiency over a broad wavelength range from 1000–1800 nm. HAMLs can be designed by combining recursive ray-tracing and simulated phase libraries rather than computationally intensive global search algorithms. Moreover, HAMLs can be fabricated in low-refractive index materials using multi-photon lithography for customization or using molding for mass production. HAMLs demonstrated diffraction limited performance for numerical apertures of 0.27, 0.11, and 0.06, with average focusing efficiencies greater than 60% and maximum efficiencies up to 80%. A more complex design, the air-spaced HAML, introduces a gap between elements to enable even larger diameters and numerical apertures. Metalenses that correct chromatic aberration also suffer from reduced focusing efficiency. Here, the authors introduce a Hybrid Achromatic Metalens which merges a metalens and phase plate to offer improved focusing efficiency over a broad wavelength range and diffraction limited imaging performance.
Drivers of COVID-19 Stay at Home Orders: Epidemiologic, Economic, or Political Concerns?

What factors affected whether or not a U.S. state governor issued a state-wide stay-at-home order in response to the COVID-19 pandemic of early 2020? Once issued, what factors affected the length of this stay-at-home order? Using duration analysis, we test a number of epidemiological, economic, and political factors for their impact on a state governor's decision to ultimately issue, and then terminate, blanket stay-at-home orders across the 50 U.S. states. Results indicate that while epidemiologic and economic variables had some impact on the delay to initiation and length of the stay-at-home orders, political factors dominated both the initiation and ultimate duration of stay-at-home orders across the United States.
Electron energy loss of ultraviolet plasmonic modes in aluminum nanodisks

We theoretically investigated electron energy loss spectroscopy (EELS) of ultraviolet surface plasmon modes in aluminum nanodisks. Using full-wave Maxell electromagnetic simulations, we studied the impact of the diameter on the resonant modes of the nanodisks. We found that the mode behavior can be separately classified for two distinct cases: (1) flat nanodisks where the diameter is much larger than the thickness and (2) thick nanodisks where the diameter is comparable to the thickness. While the multipolar edge modes and breathing modes of flat nanostructures have previously been interpreted using intuitive, analytical models based on surface plasmon polariton (SPP) modes of a thin-film stack, it has been found that the true dispersion relation of the multipolar edge modes deviates significantly from the SPP dispersion relation. Here, we developed a modified intuitive model that uses effective wavelength theory to accurately model this dispersion relation with significantly less computational overhead compared to full-wave Maxwell electromagnetic simulations. However, for the case of thick nanodisks, this effective wavelength theory breaks down, and such intuitive models are no longer viable. We found that this is because some modes of the thick nanodisks carry a polar (i.e., out of the substrate plane or along the electron beam direction) dependence and cannot be simply categorized as radial breathing modes or angular (azimuthal) multipolar edge modes. This polar dependence leads to radiative losses, motivating the use of simultaneous EELS and cathodoluminescence measurements when experimentally investigating the complex mode behavior of thick nanostructures.
Tackling the Federal Debt Problem Fairly.

Rising federal debt threatens to reduce the growth of the economy, people’s living standards, wages, and the standard of living. A policy solution needs to respect many constraints, most importantl...