cssi/SciSciGPT-SciSciNet huggingface dataset:
Analysis of distance-based protein structure prediction by deep learning in CASP13

This paper reports the CASP13 results of distance-based contact prediction, threading, and folding methods implemented in three RaptorX servers, which are built upon the powerful deep convolutional residual neural network (ResNet) method initiated by us for contact prediction in CASP12. On the 32 CASP13 FM (free-modeling) targets with a median multiple sequence alignment (MSA) depth of 36, RaptorX yielded the best contact prediction among 46 groups and almost the best 3D structure modeling among all server groups without time-consuming conformation sampling. In particular, RaptorX achieved top L/5, L/2, and L long-range contact precision of 70%, 58%, and 45%, respectively, and predicted correct folds (TMscore > 0.5) for 18 of 32 targets. Further, RaptorX predicted correct folds for all FM targets with >300 residues (T0950-D1, T0969-D1, and T1000-D2) and generated the best 3D models for T0950-D1 and T0969-D1 among all groups. This CASP13 test confirms our previous findings: (a) predicted distance is more useful than contacts for both template-based and free modeling; and (b) structure modeling may be improved by integrating template and coevolutionary information via deep learning. This paper will discuss progress we have made since CASP12, the strength and weakness of our methods, and why deep learning performed much better in CASP13.
Weak-Unforgeable Tags for Secure Supply Chain Management

Given the value of imported counterfeit and pirated goods, the need for secure supply chain management is pertinent. Maleki et al. (HOST 2017) propose a new management scheme based on RFID tags (with 2–3K bits NVM) which, if compared to other schemes, is competitive on several performance and security metrics. Its main idea is to have each RFID tag stores its reader events in its own NVM while moving through the supply chain. In order to bind a tag’s identity to each event such that an adversary is not able to impersonate the tag’s identity on another duplicate tag, a function with a weak form of unforgeability is needed. In this paper, we formally define this security property, present three constructions (MULTIPLY-ADD, ADD-XOR, and S-Box-CBC) having this security property, and show how to bound the probability of successful impersonation in concrete parameter settings. Finally, we compare our constructions with the light-weight hash function PHOTON used by Maleki et al. in terms of security and circuit area needed. We conclude that our ADD-XOR and S-Box-CBC constructions have approximately \(1/4-1/3\) of PHOTON’s total circuit area (this also includes the control circuitry besides PHOTON) while maintaining an appropriate security level which takes care of economically motivated adversaries.
The Experimental Realization of an Artificial Low-Reynolds-Number Swimmer with Three-Dimensional Maneuverability

The motion of biological micro-robots – similar to that of swimming microorganisms such as bacteria or spermatozoa – is governed by different physical rules than what we experience in our daily life. This is particularly due to the low-Reynolds-number condition of swimmers in micron scales. The Quadroar swimmer, with three-dimensional maneuverability, has been introduced for moving in these extreme cases: either as a bio-medical micro-robot swimming in biological fluids or a mm-scale robot performing inspection missions in highly viscous fluid reservoirs. Our previous studies address the theoretical modeling of this type of swimmer system. In this work, we present the mechatronic design, fabrication, and experimental study of a mm-scale Quadroar swimmer. We describe the design methodology and component selection of the system based on the required performance. A supervisory control scheme is presented to achieve an accurate trajectory tracking for all the actuators used in the swimmer. Finally, we have conducted experiments in silicone oil (with 5000 cP viscosity) where two primary modes of swimming - forward translation and planar reorientation - have been tested and compared with the theoretical model.
Single-Server Multi-Message Individually-Private Information Retrieval with Side Information

We consider a multi-user variant of the private information retrieval problem described as follows. Suppose there are D users, each of which wants to privately retrieve a distinct message from a server with the help of a trusted agent. We assume that the agent has a subset of M messages whose indices are unknown to the server. The goal of the agent is to collectively retrieve the users’ requests from the server. For this problem, we introduce the notion of individual-privacy – the agent is required to protect the privacy only for each individual user (but may leak some correlations among user requests). We refer to this problem as Individually-Private Information Retrieval with Side Information (IPIR-SI).We first establish a lower bound on the capacity, which is defined as the maximum achievable download rate, of the IPIR-SI problem by presenting a novel achievability protocol. Next, we characterize the capacity of IPIR-SI problem for M = 1 and D = 2. In the process of characterizing the capacity for arbitrary M and D we present a novel combinatorial conjecture, that may be of independent interest.
Joint inference and alignment of genome structures enables characterization of compartment-independent reorganization across cell types.

Comparisons of Hi–C data sets between cell types and conditions have revealed differences in topologically associated domains (TADs) and A/B compartmentalization, which are correlated with differences in gene regulation. However, previous comparisons have focused on known forms of 3D organization while potentially neglecting other functionally relevant differences. We aimed to create a method to quantify all locus-specific differences between two Hi–C data sets. We developed MultiMDS to jointly infer and align 3D chromosomal structures from two Hi–C data sets, thereby enabling a new way to comprehensively quantify relocalization of genomic loci between cell types. We demonstrate this approach by comparing Hi–C data across a variety of cell types. We consistently find relocalization of loci with minimal difference in A/B compartment score. For example, we identify compartment-independent relocalizations between GM12878 and K562 cells that involve loci displaying enhancer-associated histone marks in one cell type and polycomb-associated histone marks in the other. MultiMDS is the first tool to identify all loci that relocalize between two Hi–C data sets. Our method can identify 3D localization differences that are correlated with cell-type-specific regulatory activities and which cannot be identified using other methods.
The Industry Supply Function and the Long-Run Competitive Equilibrium with Heterogeneous Firms

Abstract In developing the theory of long-run competitive equilibrium (LRCE), Marshall ( 1890 ) used the notion of a representative firm. The identity of this firm, however, remained unclear. Subsequent theory either focused on the case where all firms are identical or else incorporated heterogeneity but disregarded the notion of a representative firm. Using Hopenhayn's ( 1992 ) model of competitive industry dynamics, we extend the theory of LRCE to account for heterogeneous firms and show that the long-run supply function can indeed be characterized as the solution to the minimization of a representative average cost function.
SOS: symmetry-operational similarity

Symmetry often governs condensed matter physics. The act of breaking symmetry spontaneously leads to phase transitions, and various observables or observable physical phenomena can be directly associated with broken symmetries. Examples include ferroelectric polarization, ferromagnetic magnetization, optical activities (including Faraday and magneto-optic Kerr rotations), second harmonic generation, photogalvanic effects, nonreciprocity, various Hall-effect-type transport properties, and multiferroicity. Herein, we propose that observable physical phenomena can occur when specimen constituents (i.e., lattice distortions or spin arrangements, in external fields or other environments) and measuring probes/quantities (i.e., propagating light, electrons, or other particles in various polarization states, including vortex beams of light and electrons, bulk polarization, or magnetization) share symmetry-operational similarity (SOS) in relation to broken symmetries. In addition, quasi-equilibrium electronic transport processes such as diode-type transport effects, linear or circular photogalvanic effects, Hall-effect-type transport properties ((planar) Hall, Ettingshausen, Nernst, thermal Hall, spin Hall, and spin Nernst effects) can be understood in terms of symmetry-operational systematics. The power of the SOS approach lies in providing simple and physically transparent views of otherwise unintuitive phenomena in complex materials. In turn, this approach can be leveraged to identify new materials that exhibit potentially desired properties as well as new phenomena in known materials.
An economic analysis of international environmental rights

This article offers a descriptive and normative economic analysis of international environmental rights. States, sovereignty, international negotiations, and international law resemble legal persons, property, the market, and private law, respectively. Just as the initial entitlement of persons’ property rights is important to increasing welfare when transaction costs are significant, so too is that of states’ sovereignty rights, including those regarding the environment. What is the initial entitlement of these rights? Is this relatively efficient? How are these rights protected? The article considers three possible initial entitlements. First, states’ right to cause transboundary environmental harm and, second, their right to be free therefrom are each rejected due to weak theoretical support and insufficient state practice. These initial entitlements would also be less efficient. In contrast, an initial entitlement consisting of both the prevention of transboundary harm and the equitable use of shared natural resources is supported by theory and practice. This entitlement appears relatively efficient, and the relevant legal instruments reveal an implicit underlying economic logic. These international environmental rights are generally protected by mechanisms that resemble liability.
Assembly, annotation, and comparison of Macrophomina phaseolina isolates from strawberry and other hosts

Macrophomina phaseolina is a fungal plant pathogen with a broad host range, but one genotype was shown to exhibit host preference/specificity on strawberry. This pathogen lacked a high-quality genome assembly and annotation, and little was known about genomic differences among isolates from different hosts. We used PacBio sequencing and Hi-C scaffolding to provide nearly complete genome assemblies for M. phaseolina isolates representing the strawberry-specific genotype and another genotype recovered from alfalfa. The strawberry isolate had 59 contigs/scaffolds with an N50 of 4.3 Mb. The isolate from alfalfa had an N50 of 5.0 Mb and 14 nuclear contigs with half including telomeres. Both genomes were annotated with MAKER using transcript evidence generated in this study with over 13,000 protein-coding genes predicted. Unique groups of genes for each isolate were identified when compared to closely related fungal species. Structural comparisons between the isolates reveal large-scale rearrangements including chromosomal inversions and translocations. To include isolates representing a range of pathogen genotypes, an additional 30 isolates were sequenced with Illumina, assembled, and compared to the strawberry genotype assembly. Within the limits of comparing Illumina and PacBio assemblies, no conserved structural rearrangements were identified among the isolates from the strawberry genotype compared to those from other hosts, but some candidate genes were identified that were largely present in isolates of the strawberry genotype and absent in other genotypes. High-quality reference genomes of M. phaseolina have allowed for the identification of structural changes associated with a genotype that has a host preference toward strawberry and will enable future comparative genomics studies. Having more complete assemblies allows for structural rearrangements to be more fully assessed and ensures a greater representation of all the genes. Work with Illumina data from additional isolates suggests that some genes are predominately present in isolates of the strawberry genotype, but additional work is needed to confirm the role of these genes in pathogenesis. Additional work is also needed to complete the scaffolding of smaller contigs identified in the strawberry genotype assembly and to determine if unique genes in the strawberry genotype play a role in pathogenicity.
Driven by Capacity or Blockage? A Millimeter Wave Blockage Analysis.

Millimeter wave (mmWave) communication systems can provide high data rates, but the system performance may degrade significantly due to mobile blockers and the user's own body. A high frequency of interruptions and long duration of blockage may degrade the quality of experience. Macrodiversity of base stations (BSs) has been considered a promising solution where the user equipment (UE) can handover to other available BSs, if the current serving BS gets blocked. However, an analytical model to evaluate the system performance of dynamic blockage events in this setting is largely unknown. In this paper, we consider an open park-like scenario and obtain closed-form expressions for the blockage probability, the expected frequency and duration of blockage events using stochastic geometry. Our results indicate that the minimum density of BS that is required to satisfy the Quality of Service (QoS) requirements of AR/VR and other Ultra Reliable Low Latency Communication (URLLC) applications is largely driven by blockage events rather than capacity requirements. As an alternative to increasing BS density, placing the BS at a greater height reduces the likelihood of blockage. We present a closed-form expression for the BS density-height trade-off that can be used for network planning.
Multiplatform biomarker identification using a data-driven approach enables single-sample classification

High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify a set of reliable and reproducible biomarkers across various gene expression platforms and laboratories for single sample diagnosis and prognosis. We address this need with our Data-Driven Reference (DDR) approach, which employs stably expressed housekeeping genes as references to eliminate platform-specific biases and non-biological variabilities. Our method identifies biomarkers with “built-in” features, and these features can be interpreted consistently regardless of profiling technology, which enable classification of single-sample independent of platforms. Validation with RNA-seq data of blood platelets shows that DDR achieves the superior performance in classification of six different tumor types as well as molecular target statuses (such as MET or HER2-positive, and mutant KRAS, EGFR or PIK3CA) with smaller sets of biomarkers. We demonstrate on the three microarray datasets that our method is capable of identifying robust biomarkers for subgrouping medulloblastoma samples with data perturbation due to different microarray platforms. In addition to identifying the majority of subgroup-specific biomarkers in CodeSet of nanoString, some potential new biomarkers for subgrouping medulloblastoma were detected by our method. In this study, we present a simple, yet powerful data-driven method which contributes significantly to identification of robust cross-platform gene signature for disease classification of single-patient to facilitate precision medicine. In addition, our method provides a new strategy for transcriptome analysis.
What Is Antagonistic Pleiotropy

Antagonistic Pleiotropy (AP) is today the best-accepted theory for the evolutionary origin of aging. According to AP theory, aging is a side effect of genes that are selected for their contribution to fertility and other essential components of individual fitness. In this standard view, aging exists because the benefits of enhanced fertility early in life are linked logically or physically to the long-term deterioration of the body, and evolution has been compelled to accept the latter as a cost of the former. What is the evidence for this proposition? Indeed, biological aging has sometimes been observed to be genetically associated with enhancement of fertility or survivability early in life, but the association is not universal or consistent. There are known examples of mutations that lead to longer lifespan without apparent cost. This is a major problem for AP theory, because AP theory supposes that senescence could never have evolved on its own, and (according to AP theory) there should be a substantial fitness dividend for any individual that manages to extend its lifespan without curtailing its fertility. How can we understand the observed fact that genetic mechanisms of aging are sometimes pleiotropic and sometimes not? I propose herein an alternative interpretation, in which antagonistic pleiotropy is not a precondition imposed on evolution, but an evolved adaptation in its own right. My hypothesis is that aging is selected because of important long-term benefits for the community, but in the short term, individual selection is stronger than group selection. Therefore, the communal benefits are in danger of being lost. Antagonistic pleiotropy evolves as an evolvability adaptation that protects long term group-level benefits from being lost to short term individual selection. The mechanism of selection is indirect, the benefit long-term, and it accrues only to the group at the expense of the individual. By standard population genetic reasoning, selection for pleiotropy should be too weak to matter; but in our individual-based simulation, pleiotropy evolves consistently under a broad swath of parameter space. A key feature of the model contributing to the viability of group adaptations is the assumption of a predator species in a geographically structured population, such that any population that evolves a reproduction rate exceeding the local prey population is punished by high rates of starvation. The combination of high fertility and long lifespan is a temptation for individuals, but a danger for the stability of populations. Once a sustainable mix of fertility and longevity has been established by multilevel natural selection, pleiotropy can help to assure that it is not lost. The population is free to shift from (high fertility/short lifespan) to (lower fertility/longer lifespan) as varying environmental conditions demand, without risking population overshoot and collapse.
Modernizing Titan2D, a Parallel AMR Geophysical Flow Code to Support Multiple Rheologies and Extendability

In this work, we report on strategies and results of our initial approach for modernization of Titan2D code. Titan2D is a geophysical mass flow simulation code designed for modeling of volcanic flows, debris avalanches and landslides over a realistic terrain model. It solves an underlying hyperbolic system of partial differential equations using parallel adaptive mesh Godunov scheme. The following work was done during code refactoring and modernization. To facilitate user input two level python interface was developed. Such design permits large changes in C++ and Python low-level while maintaining stable high-level interface exposed to the end user. Multiple diverged forks implementing different material models were merged back together. Data storage layout was changed from a linked list of structures to a structure of arrays representation for better memory access and in preparation for further work on better utilization of vectorized instruction. Existing MPI parallelization was augmented with OpenMP parallelization. The performance of a hash table used to store mesh elements and nodes references was improved by switching from a linked list for overflow entries to dynamic arrays allowing the implementation of the binary search algorithm. The introduction of the new data layout made possible to reduce the number of hash table look-ups by replacing them with direct use of indexes from the storage class. The modifications lead to 8–9 times performance improvement for serial execution.
Elliptic variational problems with mixed nonlinearities

In this paper, we study the existence and multiplicity results of nontrivial positive solutions to a quasilinear elliptic equation in $\RN$, when $N\geq2$, as \begin{equation} \Lp u+u^{p-1}=\lambda\hspace{0.2mm}k(x)u^{r-1}-h(x)u^{q-1}.\nonumber \end{equation} Here, $h(x),k(x)>0$ are Lebesgue measurable functions, $1 0$ is a parameter.
Complete Intersection Hom Injective Dimension

We introduce and investigate a new injective version of the complete intersection dimension of Avramov, Gasharov, and Peeva. It is like the complete intersection injective dimension of Sahandi, Sharif, and Yassemi in that it is built using quasi-deformations. Ours is different, however, in that we use a Hom functor in place of a tensor product. We show that (a) this invariant characterizes the complete intersection property for local rings, (b) it fits between the classical injective dimension and the G-injective dimension of Enochs and Jenda, (c) it provides modules with Bass numbers that are bounded by polynomials, and (d) it improves a theorem of Peskine, Szpiro, and Roberts (Bass’ conjecture).
Isometric exercise facilitates attention to salient events in women via the noradrenergic system

The locus coeruleus (LC) regulates attention via the release of norepinephrine (NE), with levels of tonic LC activity constraining the intensity of phasic LC responses. In the current fMRI study, we used isometric handgrip to modulate tonic LC-NE activity in older women and in young women with different hormone statuses during the time period immediately after the handgrip. During this post-handgrip time, an oddball detection task was used to probe how changes in tonic arousal influenced functional coordination between the LC and a right frontoparietal network that supports attentional selectivity. As expected, the frontoparietal network responded more to infrequent target and novel sounds than to frequent sounds. Across participants, greater LC-frontoparietal functional connectivity, pupil dilation, and faster oddball detection were all positively associated with LC MRI structural contrast from a neuromelanin-sensitive scan. Thus, LC structure was related to LC functional dynamics and attentional performance during the oddball task. We also found that handgrip influenced pupil and attentional processing during a subsequent oddball task. Handgrip decreased subsequent tonic pupil size, increased phasic pupil responses to oddball sounds, speeded oddball detection speed, and increased frontoparietal network activation, suggesting that inducing strong LC activity benefits attentional performance in the next few minutes, potentially due to reduced tonic LC activity. In addition, older women showed a similar benefit of handgrip on frontoparietal network activation as younger women, despite showing lower frontoparietal network activation overall. Together these findings suggest that a simple exercise may improve selective attention in healthy aging, at least for several minutes afterwards.
A Toxic RNA Catalyzes the Cellular Synthesis of Its Own Inhibitor, Shunting It to Endogenous Decay Pathways.

Summary Myotonic dystrophy type 2 (DM2) is a genetically defined disease caused by a toxic expanded repeat of r(CCUG) [r(CCUG)exp], harbored in intron 1 of CCHC-type zinc-finger nucleic acid binding protein (CNBP) pre-mRNA. This r(CCUG)exp causes toxicity via a gain-of-function mechanism, resulting in three pathological hallmarks: aggregation into nuclear foci; sequestration of muscleblind-like-1 (MBNL1) protein, leading to splicing defects; and retention of CNBP intron 1. We studied two types of small molecules with different modes of action, ones that simply bind and ones that are templated by r(CCUG)exp in cells, i.e., the RNA synthesizes its own drug. Indeed, our studies completed in DM2 patient-derived fibroblasts showed that the compounds disrupt the r(CCUG)exp-MBNL1 complex, reduce intron retention, subjecting the liberated intronic r(CCUG)exp to native decay pathways, and rescue other DM2-associated cellular defects. Importantly, this study shows that small molecules can modulate RNA biology by shunting toxic transcripts toward native decay pathways.
Computing circle packing representations of planar graphs

The Circle Packing Theorem states that every planar graph can be represented as the tangency graph of a family of internally-disjoint circles. A well-known generalization is the Primal-Dual Circle Packing Theorem for 3-connected planar graphs. The existence of these representations has widespread applications in theoretical computer science and mathematics; however, the algorithmic aspect has received relatively little attention. In this work, we present an algorithm based on convex optimization for computing a primal-dual circle packing representation of maximal planar graphs, i.e. triangulations. This in turn gives an algorithm for computing a circle packing representation of any planar graph. Both take O(n log (R/e)) expected run-time to produce a solution that is e close to a true representation, where R is the ratio between the maximum and minimum circle radius in the true representation.
Harmonic symmetries for Hermitian manifolds

Complex manifolds with compatible metric have a naturally defined subspace of harmonic differential forms that satisfy Serre, Hodge, and conjugation duality, as well as hard Lefschetz duality. This last property follows from a representation of $sl(2,\mathbb{C})$, generalizing the well known structure on the harmonic forms of compact Kahler manifolds. Some topological implications are deduced.
Problems on track runners

Abstract Consider the circle C of length 1 and a circular arc A of length l ∈ ( 0 , 1 ) . It is shown that there exists k = k ( l ) ∈ N , and a schedule for k runners along the circle with k constant but distinct positive speeds so that at any time t ≥ 0 , at least one of the k runners is not in A. On the other hand, we show the following. Assume that k runners 1 , 2 , … , k , with constant rationally independent (thus distinct) speeds ξ 1 , ξ 2 , … , ξ k , run clockwise along a circle of length 1, starting from arbitrary points. For every circular arc A ⊂ C and for every T > 0 , there exists t > T such that all runners are in A at time t. Several other problems of a similar nature are investigated.
Class number divisibility for imaginary quadratic fields

In this note we revisit classic work of Soundararajan on class groups of imaginary quadratic fields. Let $$A,B,g \ge 3$$ be positive integers such that $$\gcd (A,B)$$ is square-free. We refine Soundararajan’s result to show that if $$4 \not \mid g$$ or if A and B satisfy certain conditions, then the number of negative square-free $$D \equiv A \pmod {B}$$ down to $$-X$$ such that the ideal class group of $${\mathbb {Q}} (\sqrt{D})$$ contains an element of order g is bounded below by $$X^{\frac{1}{2} + \epsilon (g) - \epsilon }$$, where the exponent is the same as in Soundararajan’s theorem. Combining this with a theorem of Frey, we give a lower bound for the number of quadratic twists of certain elliptic curves with p-Selmer group of rank at least 2, where $$p \in \{3,5,7\}$$.
Fingerprint Presentation Attack Detection: Generalization and Efficiency

We study the problem of fingerprint presentation attack detection (PAD) under unknown PA materials not seen during PAD training. A dataset of 5, 743 bonafide and 4, 912 PA images of 12 different materials is used to evaluate a state-of-the-art PAD, namely Fingerprint Spoof Buster. We utilize 3D t-SNE visualization and clustering of material characteristics to identify a representative set of PA materials that cover most of PA feature space. We observe that a set of six PA materials, namely Silicone, 2D Paper, Play Doh, Gelatin, Latex Body Paint and Monster Liquid Latex provide a good representative set that should be included in training to achieve generalization of PAD. We also implement an optimized Android app of Fingerprint Spoof Buster that can run on a commodity smartphone (Xiaomi Redmi Note 4) without a significant drop in PAD performance (from TDR = 95.7% to 95.3% @ FDR = 0.2%) which can make a PA prediction in less than 300ms.
Local Search for Group Closeness Maximization on Big Graphs

In network analysis and graph mining, closeness centrality is a popular measure to infer the importance of a vertex. Computing closeness efficiently for individual vertices received considerable attention. The NP-hard problem of group closeness maximization, in turn, is more challenging: the objective is to find a vertex group that is central as a whole and state-of the-art heuristics for it do not scale to very big graphs yet.In this paper, we present new local search heuristics for group closeness maximization. By using randomized approximation techniques and dynamic data structures, our algorithms are often able to perform locally optimal decisions efficiently. The final result is a group with high (but not optimal) closeness centrality. We compare our algorithms to the current state-of-the-art greedy heuristic both on weighted and on unweighted real-world graphs. For graphs with hundreds of millions of edges, our local search algorithms take only around ten minutes, while greedy requires more than ten hours. Overall, our new algorithms are between one and two orders of magnitude faster, depending on the desired group size and solution quality. For example, on weighted graphs and $k =10$, our algorithms yield solutions of 12.4% higher quality, while also being $793. 6 \times $ faster. For unweighted graphs and $k =10$, we achieve solutions within 99.4% of the state-of-the-art quality while being $127. 8 \times $ faster.
Deep Reinforcement Learning for Minimizing Age-of-Information in UAV-Assisted Networks

Unmanned aerial vehicles (UAVs) are expected to be a key component of the next-generation wireless systems. Due to their deployment flexibility, UAVs are being considered as an efficient solution for collecting information data from ground nodes and transmitting it wirelessly to the network. In this paper, a UAV-assisted wireless network is studied, in which energy-constrained ground nodes are deployed to observe different physical processes. In this network, a UAV that has a time constraint for its operation due to its limited battery, moves towards the ground nodes to receive status update packets about their observed processes. The flight trajectory of the UAV and scheduling of status update packets are jointly optimized with the objective of achieving the minimum weighted sum for the age- of-information (AoI) values of different processes at the UAV, referred to as weighted sum-AoI. The problem is modeled as a finite- horizon Markov decision process (MDP) with finite state and action spaces. Since the state space is extremely large, a deep reinforcement learning (RL) algorithm is proposed to obtain the optimal policy that minimizes the weighted sum-AoI, referred to as the age-optimal policy. Several simulation scenarios are considered to showcase the convergence of the proposed deep RL algorithm. Moreover, the results also demonstrate that the proposed deep RL approach can significantly improve the achievable sum- AoI per process compared to the baseline policies, such as the distance-based and random walk policies. The impact of various system design parameters on the optimal achievable sum-AoI per process is also shown through extensive simulations.
Parity nonconservation in atoms; past work and trapped atom future

Parity nonconservation has now been measured in atomic cesium with a fractional uncertainty of 2%. This was done by observing the 6S–7S laser excited transition rate in a “handed” apparatus. When combined with recent precise calculations of the cesium atomic structure, this provides an important test of the Standard Model. Efforts are under way to achieve a more sensitive test by measuring parity nonconservation in a series of radioactive cesium isotopes which have been trapped using laser light.
Generalized Degrees Freedom of Noncoherent MIMO Channels With Asymmetric Link Strengths

We study the generalized degrees of freedom (gDoF) of block-fading noncoherent multiple input multiple output (MIMO) channels with asymmetric distributions of link strengths and a coherence time of ${T}$ symbol durations. We derive the optimal signaling structure for communication for the asymmetric MIMO channel, which is distinct from that for the MIMO channel with independent and identically distributed (i.i.d.) links. We extend the existing results for the single input multiple output (SIMO) channel with i.i.d. links to the asymmetric case, proving that selecting the statistically best antenna is gDoF-optimal. Using the gDoF result for the SIMO channel, we prove that for ${T}=1$ , the gDoF is zero for MIMO channels with arbitrary link strengths. We show that selecting the statistically best antenna is gDoF-optimal for the multiple input single output (MISO) channel. We also derive the gDoF for the $2\times 2$ MIMO channel with different exponents in the direct and cross links. In this setting, we show that it is always necessary to use both the antennas to achieve the gDoF, in contrast to the results for the $2\times 2$ MIMO channel with i.i.d. links. We show that having weaker crosslinks, gives gDoF gain compared to the case with i.i.d. links. For the noncoherent MIMO channel with i.i.d. links, the traditional method of training each transmit antenna independently is degrees of freedom (DoF) optimal, whereas we observe that for the asymmetric $2\times 2$ MIMO channel, the traditional training is not gDoF-optimal. We extend this observation to a larger ${M}\times {M}$ MIMO channel by demonstrating a strategy that can achieve larger gDoF than a traditional training-based method.
Placement Optimization with Deep Reinforcement Learning

Placement Optimization is an important problem in systems and chip design, which consists of mapping the nodes of a graph onto a limited set of resources to optimize for an objective, subject to constraints. In this paper, we start by motivating reinforcement learning as a solution to the placement problem. We then give an overview of what deep reinforcement learning is. We next formulate the placement problem as a reinforcement learning problem, and show how this problem can be solved with policy gradient optimization. Finally, we describe lessons we have learned from training deep reinforcement learning policies across a variety of placement optimization problems.
Complementarities between early educational intervention and later educational quality? A systematic review of the sustaining environments hypothesis

Abstract The sustaining environments hypothesis refers to the popular idea, stemming from theories in developmental, cognitive, and educational psychology, that the long-term success of early educational interventions is contingent on the quality of the subsequent learning environment. Several studies have investigated whether specific kindergarten classroom and other elementary school factors account for patterns of persistence and fadeout of early educational interventions. These analyses focus on the statistical interaction between an early educational intervention – usually whether the child attended preschool – and several measures of the quality of the subsequent educational environment. The key prediction of the sustaining environments hypothesis is a positive interaction between these two variables. To quantify the strength of the evidence for such effects, we meta-analyze existing studies that have attempted to estimate interactions between preschool and later educational quality in the United States. We then attempt to establish the consistency of the direction and a plausible range of estimates of the interaction between preschool attendance and subsequent educational quality by using a specification curve analysis in a large, nationally representative dataset that has been used in several recent studies of the sustaining environments hypothesis. The meta-analysis yields small positive interaction estimates ranging from approximately 0.00 to 0.04, depending on the specification. The specification curve analyses yield interaction estimates of approximately 0. Results suggest that the current mix of methods used to test the sustaining environments hypothesis cannot reliably detect realistically sized effects. Our recommendations are to combine large sample sizes with strong causal identification strategies, and to study combinations of interventions that have a strong probability of showing large main effects.
Use of independent valuation specialists in valuing employee stock options: evidence from IPOs

We investigate the impact of independent valuation specialists on the downward bias of pre-initial public offering employee stock option valuations. Undervalued stock price estimates underlying firms’ option grants produce option valuations that overstate earnings and provide employees with deep in the money options. We find independent stock price valuations are more likely for firms with a Big Four auditor and an audit committee accounting expert. Furthermore, valuations prepared by independent valuation specialists are less downward biased than those prepared internally. Cross-sectional results suggest the following. First, independent valuations have a stronger effect on reducing downward bias when the board is more independent, suggesting independent boards facilitate independent valuations. Second, independent valuations have a weaker effect on reducing downward bias when an accounting expert sits on the audit committee and when CEO equity ownership is greater, suggesting these factors offset the need for an independent valuation to reduce downward valuation bias.
Newton’s Method and Differential Dynamic Programming for Unconstrained Nonlinear Dynamic Games

Dynamic games arise when multiple agents with differing objectives choose control inputs to a dynamic system. However, compared to single-agent control problems, the computational methods for dynamic games are relatively limited. Only very specialized dynamic games can be solved exactly, so approximation algorithms are required. In this paper, we show how to extend a recursive Newton algorithm and differential dynamic programming (DDP) to the case of full-information non-zero sum dynamic games. We show that the iterates of Newton’s method and DDP are sufficiently close for DDP to inherit the quadratic convergence rate of Newton’s method.
Intermittent access cocaine self-administration produces psychomotor sensitization: effects of withdrawal, sex and cross-sensitization

With repeated administration, the psychomotor activating effects of drugs such as cocaine or amphetamine can change in very different ways—showing sensitization or tolerance—depending on whether they are administered more or less intermittently. This behavioral plasticity is thought to reflect, at least in part, changes in dopamine (DA) neurotransmission, and therefore, may provide insights into the development of substance use disorders. Indeed, the most widely used preclinical model of cocaine addiction, which involves Long Access (LgA) self-administration procedures, is reported to produce tolerance to cocaine’s psychomotor activating effects and effects on DA activity. In contrast, Intermittent Access (IntA) cocaine self-administration is more effective than LgA in producing addiction-like behavior, but sensitizes DA neurotransmission. There is, however, very little information concerning the effects of IntA experience on the psychomotor activating effects of cocaine. The objective of this study was to determine whether IntA experience produces psychomotor sensitization with similar characteristics to that produced by the intermittent, noncontingent administration of cocaine. IntA to cocaine did indeed produce psychomotor sensitization that (1) was greater after a long (30 days) vs. short (1 day) period of withdrawal, (2) was greater in females than males, and (3) resulted in cross-sensitization to another psychomotor stimulant drug, amphetamine. The tolerance sometimes associated with LgA cocaine self-administration has been cited in support of the idea that, in addiction, drug-seeking and drug-taking is motivated to overcome a DA deficiency and associated anhedonia. In contrast, the neurobehavioral sensitization associated with IntA cocaine self-administration favors an incentive-sensitization view.
Waveform Design for One-Bit Radar Systems Under Uncertain Interference Statistics

An important problem in cognitive radar is to enhance the estimation performance of the system by a joint design of its probing signal and receive filter using the a priori information on interference. In such cases, the knowledge of interference statistics (particularly the covariance) plays a vital role in an effective design of the radar waveforms. In most practical scenarios, however, the received signal and interference statistics are available subject to some uncertainty. An extreme manifestation of this practical observation occurs for radars employing one-bit receivers, where only a normalized version of interference covariance matrix can be obtained. In this paper, we formulate a waveform optimization problem and devise an algorithm to design the transmit waveform and the receive filter of one-bit radars given such uncertainties in acquired interference statistics. The effectiveness of the proposed algorithm is corroborated through numerical analysis.
Probabilistic bisection with spatial metamodels

Abstract Probabilistic Bisection Algorithms perform root finding based on knowledge acquired from noisy oracle responses. We consider the generalized PBA setting (G-PBA) where the statistical distribution of the oracle is unknown and location-dependent, so that model inference and Bayesian knowledge updating must be performed simultaneously. To this end, we propose to leverage the spatial structure of a typical oracle by constructing a statistical surrogate for the underlying logistic regression step. We investigate several surrogates, including Binomial Gaussian Processes (B-GP), Polynomial, Kernel, and Spline Logistic Regression. In parallel, we develop sampling policies that adaptively balance learning the oracle distribution and learning the root. One of our proposals mimics active learning with B-GPs and provides a novel look-ahead predictive variance formula. The resulting gains of our Spatial PBA algorithm relative to earlier G-PBA models are illustrated with synthetic examples and a challenging stochastic root finding problem from Bermudan option pricing.
The UCSC repeat browser allows discovery and visualization of evolutionary conflict across repeat families

Nearly half the human genome consists of repeat elements, most of which are retrotransposons, and many of which play important biological roles. However repeat elements pose several unique challenges to current bioinformatic analyses and visualization tools, as short repeat sequences can map to multiple genomic loci resulting in their misclassification and misinterpretation. In fact, sequence data mapping to repeat elements are often discarded from analysis pipelines. Therefore, there is a continued need for standardized tools and techniques to interpret genomic data of repeats. We present the UCSC Repeat Browser, which consists of a complete set of human repeat reference sequences derived from annotations made by the commonly used program RepeatMasker. The UCSC Repeat Browser also provides an alignment from the human genome to these references, uses it to map the standard human genome annotation tracks, and presents all of them as a comprehensive interface to facilitate work with repetitive elements. It also provides processed tracks of multiple publicly available datasets of particular interest to the repeat community, including ChIP-seq datasets for KRAB Zinc Finger Proteins (KZNFs) – a family of proteins known to bind and repress certain classes of repeats. We used the UCSC Repeat Browser in combination with these datasets, as well as RepeatMasker annotations in several non-human primates, to trace the independent trajectories of species-specific evolutionary battles between LINE 1 retroelements and their repressors. Furthermore, we document at https://repeatbrowser.ucsc.edu how researchers can map their own human genome annotations to these reference repeat sequences. The UCSC Repeat Browser allows easy and intuitive visualization of genomic data on consensus repeat elements, circumventing the problem of multi-mapping, in which sequencing reads of repeat elements map to multiple locations on the human genome. By developing a reference consensus, multiple datasets and annotation tracks can easily be overlaid to reveal complex evolutionary histories of repeats in a single interactive window. Specifically, we use this approach to retrace the history of several primate specific LINE-1 families across apes, and discover several species-specific routes of evolution that correlate with the emergence and binding of KZNFs.
On the improvement of anthropometry and pose estimation from a single uncalibrated image

Recently, we developed a technique that allows semi-automatic estimation of anthropometry and pose from a single image. However, estimation was limited to a class of images for which an adequate number of human body segments were almost parallel to the image plane. In this paper, we present a generalization of that estimation algorithm that exploits pairwise geometric relationships of body segments to allow estimation from a broader class of images. In addition, we refine our search space by constructing a fully populated discrete hyper-ellipsoid of stick human body models in order to capture the variance of the statistical anthropometric information. As a result, a better initial estimate can be computed by our algorithm and thus the number of iterations needed during minimization are reduced tenfold. We present our results over a variety of images to demonstrate the broad coverage of our algorithm.
A New Coefficient of Correlation

Abstract–Is it possible to define a coefficient of correlation which is (a) as simple as the classical coefficients like Pearson’s correlation or Spearman’s correlation, and yet (b) consistently es...
Communication Complexity with Small Advantage

We study problems in randomized communication complexity when the protocol is only required to attain some small advantage over purely random guessing, i.e., it produces the correct output with probability at least $$\epsilon$$ greater than one over the codomain size of the function. Previously, Braverman and Moitra (in: Proceedings of the 45th symposium on theory of computing (STOC), ACM, pp 161–170, 2013) showed that the set-intersection function requires $$\Theta(\epsilon{n})$$ communication to achieve advantage $$\epsilon$$ . Building on this, we prove the same bound for several variants of set-intersection: (1) the classic “tribes” function obtained by composing with And (provided $$1/\epsilon$$ is at most the width of the And), and (2) the variant where the sets are uniquely intersecting and the goal is to determine partial information about (say, certain bits of the index of) the intersecting coordinate.