cssi/SciSciGPT-SciSciNet huggingface dataset:
Fracture mechanics analysis for various fiber/matrix interface loadings

Fiber/matrix (F/M) cracking was analyzed to provide better understanding and guidance in developing F/M interface fracture toughness tests. Two configurations, corresponding to F/M cracking at a broken fiber and at the free edge, were investigated. The effects of mechanical loading, thermal cooldown, and friction were investigated. Each configuration was analyzed for two loadings: longitudinal and normal to the fiber. A nonlinear finite element analysis was performed to model friction and slip at the F/M interface. A new procedure for fitting a square-root singularity to calculated stresses was developed to determine stress intensity factors (K sub I and K sub II) for a bimaterial interface crack. For the case of F/M cracking at a broken fiber with longitudinal loading, crack tip conditions were strongly influenced by interface friction. As a result, an F/M interface toughness test based on this case was not recommended because nonlinear data analysis methods would be required. For the free edge crack configuration, both mechanical and thermal loading caused crack opening, theory avoiding fractional effects. A F/M interface toughness test based on this configuration would provide data for K(sub I/K(sub II) ratios of about 0.7 and 1.6 for fiber and radial normal loading, respectively. However, thermal effects must be accounted for in the data analysis.
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme

We present a novel approach for the problem of frequency estimation in data streams that is based on optimization and machine learning. Contrary to state-of-the-art streaming frequency estimation algorithms, which heavily rely on random hashing to maintain the frequency distribution of the data steam using limited storage, the proposed approach exploits an observed stream prefix to near-optimally hash elements and compress the target frequency distribution. We develop an exact mixed-integer linear optimization formulation, which enables us to compute optimal or near-optimal hashing schemes for elements seen in the observed stream prefix; then, we use machine learning to hash unseen elements. Further, we develop an efficient block coordinate descent algorithm, which, as we empirically show, produces high quality solutions, and, in a special case, we are able to solve the proposed formulation exactly in linear time using dynamic programming. We empirically evaluate the proposed approach both on synthetic datasets and on real-world search query data. We show that the proposed approach outperforms existing approaches by one to two orders of magnitude in terms of its average (per element) estimation error and by 45-90% in terms of its expected magnitude of estimation error.
High-speed multifocus phase imaging in thick tissue

Phase microscopy is widely used to image unstained biological samples. However, most phase imaging techniques require transmission geometries, making them unsuited for thick sample applications. Moreover, when applied to volumetric imaging, phase imaging generally requires large numbers of measurements, often making it too slow to capture live biological processes with fast 3D index-of-refraction variations. By combining oblique back-illumination microscopy and a z-splitter prism, we perform phase imaging that is both epi-mode and multifocus, enabling high-speed 3D phase imaging in thick, scattering tissues with a single camera. We demonstrate here 3D qualitative phase imaging of blood flow in chick embryos over a field of view of 546 × 546 × 137 µm3 at speeds up to 47 Hz.
Interrogation of the dynamic properties of higher-order heterochromatin using CRISPR-dCas9

Eukaryotic chromosomes feature large regions of compact, repressed heterochromatin hallmarked by Heterochromatin Protein 1 (HP1). HP1 proteins play multi-faceted roles in shaping heterochromatin, and in cells, HP1 tethering to individual gene promoters leads to epigenetic modifications and silencing. However, emergent properties of HP1 at supranucleosomal scales remain difficult to study in cells because of a lack of appropriate tools. Here, we develop CRISPR-engineered chromatin organization (EChO), combining live-cell CRISPR imaging with inducible large-scale recruitment of chromatin proteins to native genomic targets. We demonstrate that human HP1α tiled across kilobase-scale genomic DNA form novel contacts with natural heterochromatin, integrates two distantly targeted regions, and reversibly changes chromatin from a diffuse to compact state. The compact state exhibits delayed disassembly kinetics and represses transcription across over 600 kb. These findings support a polymer model of HP1α-mediated chromatin regulation and highlight the utility of CRISPR-EChO in studying supranucleosomal chromatin organization in living cells.
Equivariant Lagrangian Floer cohomology via semi-global Kuranishi structures

Using a simplified version of Kuranishi perturbation theory, which we call semi-global Kuranishi structures, we give a definition of the equivariant Lagrangian Floer cohomology of a pair of Lagrangian submanifolds that are fixed under a finite symplectic group action and satisfy certain simplifying assumptions.
The Role of Contracts in Venture Capital Returns

During contract negotiations with startups, venture capitalists (VCs) can receive preferred stock with additional cash flow rights to yield a higher return than the common stock return. The common share price is currently used to calculate payoffs to limited partners (LPs), but incorporating contract terms can considerably change the payoff distribution. Realized proceeds to LPs reveal that VCs exercise all available cash flow rights. Such choices are most financially significant when startups have relatively low acquisition prices, which is also the most frequent outcome. Consequently, the current post-money valuation method is an overvaluation of the true price of all outstanding securities. TOPICS:Real assets/alternative investments/private equity, security analysis and valuation, legal/regulatory/public policy Key Findings ▪ After constructing a novel dataset of realized proceeds to LPs, we found that VCs exercise all the preferred stock cash flow rights available to them in their contracts. ▪ VCs invest relatively the same amount of money into startups that become failures, small acquisitions, large acquisitions, or IPOs. Because they are not able to accurately predict a startup’s exit outcome, the cash flow rights accumulate into a significant amount for a fund. ▪ The post-money valuation calculation assumes common stock, and it is an overvaluation of the startup’s true value that considers all outstanding securities.
Six-point functions and collisions in the black hole interior

In the eternal AdS black hole geometry, we consider two signals sent from the boundaries into the black hole interior shared between the two asymptotic regions. We compute three different out-of-time-order six-point functions to quantify various properties of the collision of these signals behind the horizons: (i) We diagnose the strength of the collision by probing the two-signal state on a late time slice with boundary operators. (ii) We quantify two-sided operator growth, which provides a dual description of the signals meeting in the black hole interior, in terms of the quantum butterfly effect and quantum circuits. (iii) We consider an explicit coupling between the left and right CFTs to make the wormhole traversable and extract information about the collision product from behind the horizon. At a technical level, our results rely on the method of eikonal resummation to obtain the relevant gravitational contributions to Lorentzian six-point functions at all orders in the GN-expansion. We observe that such correlation functions display an intriguing factorization property. We corroborate these results with geodesic computations of six-point functions in two- and three-dimensional gravity.
A Deterministic Algorithm for Computing the Weight Distribution of Polar Codes

We present a deterministic algorithm for computing the entire weight distribution of polar codes. As the first step, we derive an efficient recursive procedure to compute the weight distributions that arise in successive cancellation decoding of polar codes along any decoding path. This solves the open problem recently posed by Polyanskaya, Davletshin, and Polyanskii. Using this recursive procedure, we can compute the entire weight distribution of certain polar cosets in time $O(n^{2})$ . Any polar code can be represented as a disjoint union of such cosets; moreover, this representation extends to polar codes with dynamically frozen bits. This implies that our methods can be also used to compute the weight distribution of polar codes with CRC precoding, of pol-arization-adjusted convolutional (PAC) codes and, in fact, general linear codes. However, the number of polar cosets in such representation scales exponentially with a parameter introduced herein, which we call the mixing factor. To reduce the exponential complexity of our algorithm, we make use of the fact that polar codes have a large automorphism group, which includes the lower-triangular affine group LTA $(m,2)$ . We prove that LTA $(m,2)$ acts transitively on certain subsets of polar codes, thereby drastically reducing the number of polar cosets we need to evaluate. This complexity reduction makes it possible to compute the weight distribution of any polar code of length up to $n=128$ .
Urinary cell mRNA profiling of kidney allograft recipients: A systematic investigation of a filtration based protocol for the simplification of urine processing.

Abstract Background Kidney transplantation is a life-restorative therapy, but immune rejection undermines allograft survival. Urinary cell mRNA profiles offer a noninvasive means of diagnosing kidney allograft rejection, but urine processing protocols have logistical constraints. We aimed to determine whether the centrifugation-based method for urinary cell mRNA profiling could be replaced with a simpler filtration-based method without undermining quality. Methods We isolated RNA from urine collected from kidney allograft recipients using the Cornell centrifugation-based protocol (CCBP) or the Zymo filter-based protocol (ZFBP) and compared RNA purity and yield using a spectrophotometer or a fluorometer and measured absolute copy number of transcripts using customized real-time quantitative PCR assays. We investigated the performance characteristics of RNA isolated using ZFBP and stored either at -80 °C or at ambient temperature for 2 to 4 days and also when shipped to our Gene Expression Monitoring (GEM) Core at ambient temperature. We examined the feasibility of initial processing of urine samples by kidney allograft recipients trained by the GEM Core staff and the diagnostic utility for acute rejection, of urine processed using the ZFBP. Results RNA purity (P = 0.0007, Wilcoxon matched paired signed-ranks test) and yield (P 0.05) in the filtrates containing RNA stored either at -80 °C or at ambient temperature for 2 to 4 days or shipped overnight at ambient temperature. RNA purity, yield, and absolute copy numbers of 18S rRNA and TGF-β1 mRNA were also not different (P > 0.05) between home processed and laboratory processed urine filtrates. Urinary cell levels of mRNA for granzyme B (P = 0.01) and perforin (P = 0.0002) in the filtrates were diagnostic of acute rejection in human kidney allografts. Conclusions Urinary cell mRNA profiling was simplified using the ZFBP without undermining RNA quality or diagnostic utility. Home processing by the kidney allograft recipients, the stability of RNA containing filtrates at ambient temperature, and the elimination of the need for centrifuges and freezers represent some of the advantages of ZFBP over the CCBP for urinary cell mRNA profiling.
Time integrator agnostic charge conserving finite element PIC

Developing particle-in-cell (PIC) methods using finite element basis sets, and without auxiliary divergence cleaning methods, was a long-standing problem until recently. It was shown that if consistent spatial basis functions are used, one can indeed create a methodology that was charge conserving, albeit using a leapfrog time stepping method. While this is a significant advance, leapfrog schemes are only conditionally stable and time step sizes are closely tied to the underlying mesh. Ideally, to take full advantage of advances in finite element methods (FEMs), one needs a charge conserving PIC methodology that is agnostic to the time stepping method. This is the principal contribution of this paper. In what follows, we shall develop this methodology, prove that both charge and Gauss' laws are discretely satisfied at every time step, provide the necessary details to implement this methodology for both the wave equation FEM and Maxwell solver FEM, and finally demonstrate its efficacy on a suite of test problems. The method will be demonstrated by single particle evolution, non-neutral beams with space-charge, and adiabatic expansion of a neutral plasma, where the Debye length has been resolved, and real mass ratios are used.
Experimental Study of Outdoor UAV Localization and Tracking using Passive RF Sensing

Extensive use of unmanned aerial vehicles (UAVs) is expected to raise privacy and security concerns among individuals and communities. In this context, detection and localization of UAVs will be critical for maintaining safe and secure airspace in the future. In this work, Keysight N6854A radio frequency (RF) sensors are used to detect and locate a UAV by passively monitoring the signals emitted from the UAV. First, the Keysight sensor detects the UAV by comparing the received RF signature with various other UAVs' RF signatures in the Keysight database using an envelope detection algorithm. Afterward, time difference of arrival (TDoA) based localization is performed by a central controller using the sensor data, and the drone is localized with some error. To mitigate the localization error, implementing an extended Kalman filter (EKF) is proposed in this study. The performance of the proposed approach is evaluated on a realistic experimental dataset. EKF requires basic assumptions on the type of motion throughout the trajectory, i.e., the movement of the object is assumed to fit some motion model (MM) such as constant velocity (CV), constant acceleration (CA), and constant turn (CT). In the experiments, an arbitrary trajectory is followed, therefore it is not feasible to fit the whole trajectory into a single MM. Consequently, the trajectory is segmented into sub-parts and a different MM is assumed in each segment while building the EKF model. Simulation results demonstrate an improvement in error statistics when EKF is used if the MM assumption aligns with the real motion.
Choquet random sup-measures with aggregations

A variation of Choquet random sup-measures is introduced. These random sup-measures are shown to arise as the scaling limits of empirical random sup-measures of a general aggregated model. Because of the aggregations, the finite-dimensional distributions of introduced random sup-measures do not necessarily have classical extreme-value distributions. Examples include the recently introduced stable-regenerative random sup-measures as a special case.
Bipartite 3-Regular Counting Problems with Mixed Signs

We prove a complexity dichotomy for a class of counting problems expressible as bipartite 3-regular Holant problems. For every problem of the form \({\text {Holant}}\left( f\mid =_3\right) \), where f is any integer-valued ternary symmetric constraint function on Boolean variables, we prove that it is either P-time computable or #P-hard, depending on an explicit criterion of f. The constraint function can take both positive and negative values, allowing for cancellations. In addition, we discover a new phenomenon: there is a set \(\mathcal {F}\) with the property that for every \(f \in \mathcal {F}\) the problem \({\text {Holant}}\left( f\mid =_3\right) \) is planar P-time computable but #P-hard in general, yet its planar tractability is by a combination of a holographic transformation by \(\left[ {\begin{matrix} 1 &{} 1 \\ 1 &{} -1 \end{matrix}}\right] \) to FKT together with an independent global argument.
Jobs for Sale: Corruption and Misallocation in Hiring

Corrupt government hiring is common in developing countries. This paper uses original data to document the operation and consequences of corrupt hiring in a health bureaucracy. Hires pay bribes averaging 17 months of salary, but contrary to conventional wisdom, their observable quality is comparable to counterfactual merit-based hires. Exploiting variation across jobs, I show that the consequences of corrupt allocations depend on the correlation between wealth and quality among applicants: service delivery outcomes are good for jobs where this was positive and poor when negative. In this setting, the correlation was typically positive, leading to relatively good performance of hires.
Bootstrap Your Own Correspondences

Geometric feature extraction is a crucial component of point cloud registration pipelines. Recent work has demonstrated how supervised learning can be leveraged to learn better and more compact 3D features. However, those approaches' reliance on ground-truth annotation limits their scalability. We propose BYOC: a self-supervised approach that learns visual and geometric features from RGB-D video without relying on ground-truth pose or correspondence. Our key observation is that randomly-initialized CNNs readily provide us with good correspondences; allowing us to bootstrap the learning of both visual and geometric features. Our approach combines classic ideas from point cloud registration with more recent representation learning approaches. We evaluate our approach on indoor scene datasets and find that our method outperforms traditional and learned descriptors, while being competitive with current state-of-the-art supervised approaches.
Object Permanence Through Audio-Visual Representations

As robots perform manipulation tasks and interact with objects, it is probable that they accidentally drop objects (e.g., due to an inadequate grasp of an unfamiliar object) that subsequently bounce out of their visual fields. To enable robots to recover from such errors, we draw upon the concept of object permanence —objects remain in existence even when they are not being sensed (e.g., seen) directly. In particular, we developed a multimodal neural network model—using a partial, observed bounce trajectory and the audio resulting from drop impact as its inputs—to predict the full bounce trajectory and the end location of a dropped object. We empirically show that: 1) our multimodal method predicted end locations close in proximity (i.e., within the visual field of the robot’s wrist camera) to the actual locations and 2) the robot was able to retrieve dropped objects by applying minimal vision-based pick-up adjustments. Additionally, we show that our method outperformed five comparison baselines in retrieving dropped objects. Our results contribute to enabling object permanence for robots and error recovery from object drops.
Metallic Hydrogen: A Liquid Superconductor?

Metallic hydrogen is expected to exhibit remarkable physics. Of particular interest in this work is the possibility of high-temperature superconductivity. Comparing calculations of the superconducting critical temperatures of the solid phase to melting temperatures over a range of pressures leads to an interesting question: Will the solid, in a superconducting state, melt to a liquid that remains a superconductor? In this work, the possibility of liquid superconductivity in metallic hydrogen is investigated. This is done by first-principles simulations, and using the results of these to solve the Eliashberg equations. These are carried out over the pressure (and temperature) conditions where molecular dissociation is expected to first occur in the solid phase. Over the pressure range $386.8(4)$--$783.7(4)$ GPa, $T_c$ increases from $308(6)$ to $372(2)$ K with a maximum uncertainty of $10$ K; it then decreases to $356(2)$ K at $883.7(3)$ GPa. Comparisons to the solid phase show that the critical temperature is not significantly changed between the two phases, though the physics behind their superconductivity is different. Careful comparisons of these values to recent results in the context of the hydrogen phase diagram show that they are higher than the melting temperatures and that the solid will melt to liquid atomic hydrogen. The results of this work (in this context) therefore suggest that liquid atomic hydrogen will indeed exist in a superconducting state. They also provide the pressure and temperature conditions over which to look for it.
Advanced Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

An advanced form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique, based on an eigenvalue decomposition of the background noise cross-spectral matrix, is robust against situations where isolated background auto-spectral levels are measured to be higher than levels of combined source and background signals. It also provides an alternate estimate of the cross-spectrum, which previously might have poor definition for low signal-to-noise ratio measurements. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels. Experimental results show limited success in recovering signal behavior for data where conventional background subtraction fails. They also demonstrate the new subtraction technique's ability to maintain a proper coherence relationship in the modified cross-spectral matrix. Beam-forming and de-convolution results indicate the method can successfully separate sources. Results also show a reduced need for the use of diagonal removal in phased array processing, at least for the limited data sets considered.
Distinct fastigial output channels and their impact on temporal lobe seizures.

Despite being canonically considered a motor control structure, the cerebellum is increasingly recognized for important roles in processes beyond this traditional framework, including seizure suppression. Excitatory fastigial neurons project to a large number of downstream targets, and it is unclear if this broad targeting underlies seizure suppression, or if a specific output may be sufficient. To address this question, we used the intrahippocampal kainic acid mouse model of temporal lobe epilepsy, male and female animals, and a dual-virus approach to selectively label and manipulate fastigial outputs. We examined fastigial neurons projecting to the superior colliculus, medullary reticular formation, and central lateral nucleus of the thalamus, and found that these comprise largely non-overlapping populations of neurons which send collaterals to unique sets of additional, somewhat overlapping, thalamic and brainstem regions. We found that neither optogenetic stimulation of superior colliculus nor reticular formation output channels attenuated hippocampal seizures. In contrast, on-demand stimulation of fastigial neurons targeting the central lateral nucleus robustly inhibited seizures. Our results indicate that fastigial control of hippocampal seizures does not require simultaneous modulation of many fastigial output channels. Rather, selective modulation of the fastigial output channel to the central lateral thalamus, specifically, is sufficient for seizure control. More broadly, our data highlight the concept of specific cerebellar output channels, whereby discrete cerebellar nucleus neurons project to specific aggregates of downstream targets, with important consequences for therapeutic interventions. Significance statement The cerebellum has an emerging relationship with non-motor systems and may represent a powerful target for therapeutic intervention in temporal lobe epilepsy. We find, as previously reported, that fastigial neurons project to numerous brain regions via largely segregated output channels, and that projection targets cannot be predicted simply by somatic locations within the nucleus. We further find that on-demand optogenetic excitation of fastigial neurons projecting to the central lateral nucleus of the thalamus – but not fastigial neurons projecting to the reticular formation, superior colliculus or ventral lateral thalamus – is sufficient to attenuate hippocampal seizures.
Gds1 interacts with NuA4 to promote H4 acetylation at ribosomal protein genes.

In our previously published studies, RNA polymerase II transcription initiation complexes were assembled from yeast nuclear extracts onto immobilized transcription templates and analyzed by quantitative mass spectrometry. In addition to the expected basal factors and coactivators, we discovered that the uncharacterized protein Gds1/YOR355W showed activator-stimulated association with promoter DNA. Gds1 co-precipitated with the histone H4 acetyltransferase NuA4, and its levels often tracked with NuA4 in immobilized template experiments. GDS1 deletion led to reduction in H4 acetylation in vivo, and caused other phenotypes consistent with partial loss of NuA4 activity. Genome-wide chromatin immunoprecipitation revealed that the reduction in H4 acetylation was strongest at ribosomal protein gene promoters and other genes with high NuA4 occupancy. Therefore, while Gds1 is not a stoichiometric subunit of NuA4, we propose that it interacts with and modulates NuA4 in specific promoter contexts. Gds1 has no obvious metazoan homolog, but the Alphafold2 algorithm predicts that a section of Gds1 resembles the winged-helix/forkhead domain found in DNA-binding proteins such as the FOX transcription factors and histone H1.
Connecting Complex Electronic Pattern Formation to Critical Exponents

Scanning probes reveal complex, inhomogeneous patterns on the surface of many condensed matter systems. In some cases, the patterns form self-similar, fractal geometric clusters. In this paper, we advance the theory of criticality as it pertains to those geometric clusters (defined as connected sets of nearest-neighbor aligned spins) in the context of Ising models. We show how data from surface probes can be used to distinguish whether electronic patterns observed at the surface of a material are confined to the surface, or whether the patterns originate in the bulk. Whereas thermodynamic critical exponents are derived from the behavior of Fortuin–Kasteleyn (FK) clusters, critical exponents can be similarly defined for geometric clusters. We find that these geometric critical exponents are not only distinct numerically from the thermodynamic and uncorrelated percolation exponents, but that they separately satisfy scaling relations at the critical fixed points discussed in the text. We furthermore find that the two-dimensional (2D) cross-sections of geometric clusters in the three-dimensional (3D) Ising model display critical scaling behavior at the bulk phase transition temperature. In particular, we show that when considered on a 2D slice of a 3D system, the pair connectivity function familiar from percolation theory displays more robust critical behavior than the spin-spin correlation function, and we calculate the corresponding critical exponent. We discuss the implications of these two distinct length scales in Ising models. We also calculate the pair connectivity exponent in the clean 2D case. These results extend the theory of geometric criticality in the clean Ising universality classes, and facilitate the broad application of geometric cluster analysis techniques to maximize the information that can be extracted from scanning image probe data in condensed matter systems.
Geodesic networks in Liouville quantum gravity surfaces

Recent work has shown that for $\gamma \in (0,2)$, a Liouville quantum gravity (LQG) surface can be endowed with a canonical metric. We prove several results concerning geodesics for this metric. In particular, we completely classify the possible networks of geodesics from a typical point on the surface to an arbitrary point on the surface, as well as the types of networks of geodesics joining two points which occur for a dense set of pairs of points on the surface. This latter result is the $\gamma$-LQG analog of the classification of geodesic networks in the Brownian map due to Angel, Kolesnik, and Miermont (2017). We also show that there is a deterministic $m\in\mathbb N$ such that almost surely any two points are joined by at most $m$ distinct LQG geodesics.
SARS-CoV-2 Beta Variant Substitutions Alter Spike Glycoprotein Receptor Binding Domain Structure and Stability.

The emergence of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) and the subsequent COVID-19 pandemic have visited a terrible cost on the world in the forms of disease, death, and economic turmoil. The rapid development and deployment of extremely effective vaccines against SARS-CoV-2 have seemingly brought within reach the end of the pandemic. However, the virus has acquired mutations. and emerging variants of concern are more infectious and reduce the efficacy of existing vaccines. Although promising efforts to combat these variants are underway, the evolutionary pressures leading to these variants are poorly understood. To that end, here we have studied the effects on the structure and function of the SARS-CoV-2 spike glycoprotein receptor-binding domain of three amino-acid substitutions found in several variants of concern, including alpha (B.1.1.7), beta (B.1.351), and gamma (P.1). We found that these substitutions alter the receptor-binding domain structure, stability, and ability to bind to angiotensin converting enzyme 2, in such a way as to possibly have opposing and compensatory effects. These findings provide new insights into how these variants of concern may have been selected for infectivity while maintaining the structure and stability of the receptor binding domain.
Two-sidedness, Relativity and CPT Symmetry

The property of two-sidedness that also makes a unified whole is developed, and showed consistent with unified field theory, general relativity, thermodynamics and cosmological theories that describe a mirror universe. Two-sidedness is described as a principle of relativity that defines the visible universe by recognizing constraints that are carried by reflection. Two-sidedness is consistent with the process philosophy of A.N. Whitehead and the phenomenology of E.G.A. Husserl. Moreover, the property of two-sidedness is an observed fact of nature, coming with abundant evidential support. Speculation about a hypothetical aether that joins the sides of the two-sided is more theoretical, and open to debate. Otherwise, this paper makes a strong case for the reality of two-sidedness, if not Whiteheadian panpsychism.
Safe Optimal Design with Applications in Policy Learning.

Motivated by practical needs in online experimentation and off-policy learning, we study the problem of safe optimal design, where we develop a data logging policy that efficiently explores while achieving competitive rewards with a baseline production policy. We first show, perhaps surprisingly, that a common practice of mixing the production policy with uniform exploration, despite being safe, is sub-optimal in maximizing information gain. Then we propose a safe optimal logging policy for the case when no side information about the actions' expected rewards is available. We improve upon this design by considering side information and also extend both approaches to a large number of actions with a linear reward model. We analyze how our data logging policies impact errors in off-policy learning. Finally, we empirically validate the benefit of our designs by conducting extensive experiments.
Altered synaptic connectivity and brain function in mice lacking microglial adapter protein Iba1.

Growing evidence indicates that microglia impact brain function by regulating synaptic pruning and formation as well as synaptic transmission and plasticity. Iba1 (ionized Ca+2-binding adapter protein 1), encoded by the Allograft inflammatory factor 1 (Aif1) gene, is an actin-interacting protein in microglia. Although Iba1 has long been used as a cellular marker for microglia, its functional role remains unknown. Here, we used global, Iba1-deficient (Aif1 -/-) mice to characterize microglial activity, synaptic function, and behavior. Microglial imaging in acute hippocampal slices and fixed tissues from juvenile mice revealed that Aif1 -/- microglia display reductions in ATP-induced motility and ramification, respectively. Biochemical assays further demonstrated that Aif1 -/- brain tissues exhibit an altered expression of microglial-enriched proteins associated with synaptic pruning. Consistent with these changes, juvenile Aif1 -/- mice displayed deficits in the excitatory synapse number and synaptic drive assessed by neuronal labeling and whole-cell patch-clamp recording in acute hippocampal slices. Unexpectedly, microglial synaptic engulfment capacity was diminished in juvenile Aif1 -/- mice. During early postnatal development, when synapse formation is a predominant event in the hippocampus, the excitatory synapse number was still reduced in Aif1 -/- mice. Together, these findings support an overall role of Iba1 in excitatory synaptic growth in juvenile mice. Lastly, postnatal synaptic deficits persisted in adulthood and correlated with significant behavioral changes in adult Aif1 -/- mice, which exhibited impairments in object recognition memory and social interaction. These results suggest that Iba1 critically contributes to microglial activity underlying essential neuroglia developmental processes that may deeply influence behavior.
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition

Author(s): Liu, Jiaming; Asif, M Salman; Wohlberg, Brendt; Kamilov, Ulugbek S | Abstract: The plug-and-play priors (PnP) and regularization by denoising (RED) methods have become widely used for solving inverse problems by leveraging pre-trained deep denoisers as image priors. While the empirical imaging performance and the theoretical convergence properties of these algorithms have been widely investigated, their recovery properties have not previously been theoretically analyzed. We address this gap by showing how to establish theoretical recovery guarantees for PnP/RED by assuming that the solution of these methods lies near the fixed-points of a deep neural network. We also present numerical results comparing the recovery performance of PnP/RED in compressive sensing against that of recent compressive sensing algorithms based on generative models. Our numerical results suggest that PnP with a pre-trained artifact removal network provides significantly better results compared to the existing state-of-the-art methods.
Measuring and Characterizing Generalization in Deep Reinforcement Learning

Deep reinforcement-learning methods have achieved remarkable performance on challenging control tasks. Observations of the resulting behavior give the impression that the agent has constructed a generalized representation that supports insightful action decisions. We re-examine what is meant by generalization in RL, and propose several definitions based on an agent's performance in on-policy, off-policy, and unreachable states. We propose a set of practical methods for evaluating agents with these definitions of generalization. We demonstrate these techniques on a common benchmark task for deep RL, and we show that the learned networks make poor decisions for states that differ only slightly from on-policy states, even though those states are not selected adversarially. Taken together, these results call into question the extent to which deep Q-networks learn generalized representations, and suggest that more experimentation and analysis is necessary before claims of representation learning can be supported.
The Great Divide: Regional Inequality and Fiscal Policy

Growing regional inequality within countries has raised the perception that 'someplaces and people' are left behind. This has prompted a shift toward inward-looking policies andaway from pro-growth reforms. This paper presents novel stylized facts on regional inequality forOECD countries. It shows that regional disparity in per-capita GDP is large (even after adjustingfor regional price differences), persistent, and widening over time. The paper also finds thatrising nationwide income inequality is associated with both rising within-region incomeinequality and widening average income across regions. The rise in inequality is related todeclining incentives for interregional labor mobility, especially for poor households in laggingregions, which are estimated to reduce by as much as one-third in the United States. Againstthese facts, the paper proposes a framework to identify whether, how and by whom fiscal policiescan be used to tackle regional inequality. It outlines conditions under which those policies shouldbe spatially-targeted and illustrates how they can be complementary to conventional means-testingmethods in mitigating income inequality.
Dietary Fat and Cholesterol Modulate the Plasma Lipoprotein Distribution and Production of Pigment or Cholesterol Gallstones in Hamsters

To evaluate the impact of key dietary factors on plasma lipoproteins and gallstone induction, male Syrian hamsters were fed either cholesterol and fat-supplemented purified diets containing glucose or lactose, or cholesterol and fat-free diets with or without fiber, for 13 wk. Fat-supplemented hamsters were hyperlipidemic in comparison to those fed fat-free diets. The former group revealed a greatly expanded VLDL fraction, whereas a normal HDL2 pool predominated in the latter group. Plasma fatty acids indicated that hamsters fed the fat-free diet were essential fatty acid deficient whilst the hamsters fed the fat-supplemented diet were subnormal in essential fatty acids. Ninety-three percent of the hamsters fed the fat-supplemented diet had gallstones (mostly cholesterol), whereas 62% of hamsters fed the fat-free diet had gallstones (almost all pigmented). Lactose increased cecal weight and prevented pigment stone formation in the fat-supplemented hamsters, whereas adding fiber to the fat-free diet contributed essential fatty acids, eliminated cholesterol stones and enhanced pigment stone formation. Thus, diets containing casein, rice flour, glucose and fiber with minimal essential fatty acids but no cholesterol promoted pigment stones (associated with a normal lipoprotein profile); a low fat diet limited in essential fatty acids but containing cholesterol and lactose, promoted cholesterol gallstones (associated with an expanded VLDL pool).
Crystallization of Escherichia coli catabolite gene activator protein with its DNA binding site. The use of modular DNA.

To obtain crystals of the Escherichia coli catabolite gene activator protein (CAP) complexed with its DNA-binding site, we have searched for crystallization conditions with 26 different DNA segments ≥28 base-pairs in length that explore a variety of nucleotide sequences, lengths, and extended 5′ or 3′ termini. In addition to utilizing uninterrupted asymmetric lac site sequences, we devised a novel approach of synthesizing half-sites that allowed us to efficiently generate symmetric DNA segments with a wide variety of extended termini and lengths in the large size range (≥28 bp) required by this protein. We report three crystal forms that are suitable for X-ray analysis, one of which (crystal form III) gives measurable diffraction amplitudes to 3 A resolution. Additives such as calcium, n-octyl-β- d -glucopyranoside and spermine produce modest improvements in the quality of diffraction from crystal form III. Adequate stabilization of crystal form III is unexpectedly complex, requiring a greater than tenfold reduction in the salt concentration followed by addition of 2-methyl-2,4-pentanediol and then an increase in the concentration of polyethylene glycol.
Getting Familiar with Code Composer Studio

This chapter explores the basic features of code composer studio (CCS). It also discusses debugging and benchmarking issues. It is important to understand the basic features of CCS in order to build and debug a program running on a digital signal processing (DSP) processor. The chapter also demonstrates compilation and linking of a DSP program by using CCS. The algorithm used consists of a sine wave generator using a difference equation. The CCS code development process begins with the creation of a project that integrates and manages all the required files in order to generate and run an executable file. After opening CCS by double-clicking the CCS icon on the desktop, the project view panel is seen on the left hand side of the CCS window. This panel provides an easy mechanism for building a project. In this panel, a project file can be created or opened to contain not only the source and library files but also the compiler, assembler, and linker options for generating an executable file.
An LSP based speech quality measure

An objective measure is introduced for predicting the subjective quality of a distorted speech signal. The unique feature of the measure is that it explicitly uses a parametric model of speech perception (rather than a signal fidelity measure) in the design of an objective measure for speech quality. Specifically, the known sensitivity of human auditory perception to perturbations in the speech formants is combined with a simple (statistical) relationship between the line spectrum pair (LSP) coefficients and the vocal tract formants to form a simple objective speech quality measure that performs better than any other known simple measure. A detailed description is given of the LSP measure, the performance results are presented, and its associated implementational advantages are discussed. >
Playing disjunctive sums is polynomial space complete

A position in a disjunctive sum of games is simply a collection of positions, one from each game: to move in a sum is to move in any one of its constituents. Sums have been studied extensively by Conway and others, and play an important rOle in Go.
The Relationship between Cultural Values and Political Ideology, and the Role of Political Knowledge

Cultural theory maintains that four worldviews—egalitarianism, individualism, hierarchicalism, and fatalism—can be used to describe people and societies. We examine survey measures of two of those worldviews—egalitarianism and individualism—to understand their relationship with belief systems. Contrary to what one might expect based on the cultural theory literature, we find that people with low levels of political knowledge seem not to have coherent worldviews regarding these issues. In contrast, people with high levels of political knowledge respond to egalitarianism and individualism questions as if they were opposite ends of a single, liberal-conservative continuum, rather than two of four distinct worldviews. We conclude that cultural theory researchers should take account of the influence of political knowledge whenever they investigate worldviews.
p53-independent apoptosis mediated by tachpyridine, an anti-cancer iron chelator

Iron is involved in essential biochemical reactions ranging from respiration to DNA synthesis. Consequently, iron deprivation has been proposed as a strategy for inhibition of tumor cell growth. We recently described a novel iron chelator, tachypyridine [N,N',N"-tris(2-pyridylmethyl)-cis,cis-1,3,5-triaminocyclohexane], and demonstrated that it not only inhibited growth of cultured tumor cells, but was actively cytotoxic. Here we explore the mechanisms underlying tachpyridine cytotoxicity. Using several criteria, including time-lapse video microscopy, DNA staining and TUNEL assays, tachpyridine was shown to specifically induce apoptotic cell death. Further, unlike numerous cytotoxic chemotherapeutic drugs which induce apoptosis by activating p53-dependent pathways, tachpyridine-mediated cell death did not require p53 activation. Although immunoblotting revealed rapid accumulation of p53 following treatment with tachpyridine, p21(WAF1) was not induced. Further, neither cytotoxicity nor apoptosis required p53. p53 null human lung cancer H1299 cells transfected with an ecdysone-inducible p53 exhibited equivalent sensitivity to tachpyridine in the presence and absence of p53, demonstrating the lack of requirement for p53 in an isogenic cell system. Further, time-lapse video microscopy and TUNEL assays demonstrated that both p53 null and p53 wild-type cells underwent apoptotic cell death in response to tachpyridine. In addition, in 55 human cancer cell lines the mean GI(50) of tachpyridine in cells with mutant p53 was virtually identical to the GI(50) in cells with wild-type p53. These results demonstrate that tachpyridine initiates an apoptotic mode of cell death that does not require functional p53. Since over 50% of human tumors contain a functionally defective p53 that reduces sensitivity to commonly used chemotherapeutic agents, such as etoposide and cisplatin, the ability of tachpyridine to induce apoptosis independently of p53 may offer an advantage in anti-tumor therapy.
Nanofabrication at Biologically Important Length Scale: Etching of Dislocation Array in Twist-bonded Bicrystals

A process to fabricate a periodic surface structure at biologically important length scale is developed and nanostructured silicon surface with a periodicity of 38 nm has been obtained. The technique relies on controlled etching of a dislocation array in the twist boundaries formed by silicon bicrystals. The deviation from a perfect periodic structure and the method to improve the perfection have been investigated.
Controllability of differential inclusions

We consider autonomous differential inclusions on compact Riemannian manifolds and characterize regions of complete controllability, the so-called control sets. Therefore we introduce appropriate dynamical systems and relate control sets to minimal sets. we get robustness and continuity results for control sets under perturbation of the attainable set semiflow. The results are applied to nonlinear singularly perturbed control systems.
Spatial structure in the viscous sublayer

An experimental investigation was performed to study the spatial coherence of structures in the sublayer of a turbulent boundary layer observed previously by flow visualization. The present work verifies these observations in an Eulerian reference frame and develops a statistical description of the phenomenon. The technique involves simultaneous digital sampling of an array of constant temperature hot-wire anemometers arranged to extract information about a spanwise variation in flow quantities. The quantitative description agrees with dimensionless measures of the structure scales previously published.
Bilingualism and socioemotional well-being

Abstract Using the Early Childhood Longitudinal Study — Kindergarten Cohort (ECLS-K), this paper examines Latino children's socioemotional trajectories from kindergarten to fifth grade, paying particular attention to children's language proficiency. Results from the growth-curve analysis indicate that most Latino children who spoke a non-English language were doing as well as, if not better than, their White English Monolingual peers on socioemotional well-being. By fifth grade, Fluent Bilingual and Non-English-Dominant Bilingual children were surpassing every other group with the highest levels of approaches-to-learning, self-control, and interpersonal skills and the lowest levels of internalizing and externalizing behavior problems. English-Dominant Bilingual children had similar levels and trajectories of socioemotional well-being as those of White English Monolingual children. Non-English Monolingual children, however, had the lowest self-control and interpersonal skills and the highest level of internalizing problems by fifth grade, as rated by their teachers.