cssi/SciSciGPT-SciSciNet huggingface dataset:
ChIPdig: a comprehensive user-friendly tool for mining multi-sample ChIP-seq data

In recent years, epigenetic research has enjoyed explosive growth as high-throughput sequencing technologies become more accessible and affordable. However, this advancement has not been matched with similar progress in data analysis capabilities from the perspective of experimental biologists not versed in bioinformatic languages. For instance, chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) is at present widely used to identify genomic loci of transcription factor binding and histone modifications. Basic ChIP-seq data analysis, including read mapping and peak calling, can be accomplished through several well-established tools, but more sophisticated analyzes aimed at comparing data derived from different conditions or experimental designs constitute a significant bottleneck. We reason that the implementation of a single comprehensive ChIP-seq analysis pipeline could be beneficial for many experimental (wet lab) researchers who would like to generate genomic data. Here we present ChIPdig, a stand-alone application with adjustable parameters designed to allow researchers to perform several analyzes, namely read mapping to a reference genome, peak calling, annotation of regions based on reference coordinates (e.g. transcription start and termination sites, exons, introns, and 5' and 3' untranslated regions), and generation of heatmaps and metaplots for visualizing coverage. Importantly, ChIPdig accepts multiple ChIP-seq datasets as input, allowing genome-wide differential enrichment analysis in regions of interest to be performed. ChIPdig is written in R and enables access to several existing and highly utilized packages through a simple user interface powered by the Shiny package. Here, we illustrate the utility and user-friendly features of ChIPdig by analyzing H3K36me3 and H3K4me3 ChIP-seq profiles generated by the modENCODE project as an example. ChIPdig offers a comprehensive and user-friendly pipeline for analysis of multiple sets of ChIP-seq data by both experimental and computational researchers. It is open source and available at https://github.com/rmesse/ChIPdig .
The Optimal Packing of Eight Points in the Real Projective Plane

AbstractHow can we arrange n lines through the origin in three-dimensional Euclidean space in a way that maximizes the minimum interior angle between pairs of lines? Conway, Hardin, and Sloane (199...
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium

Self-play methods based on regret minimization have become the state of the art for computing Nash equilibria in large two-players zero-sum extensive-form games. These methods fundamentally rely on the hierarchical structure of the players' sequential strategy spaces to construct a regret minimizer that recursively minimizes regret at each decision point in the game tree. In this paper, we introduce the first efficient regret minimization algorithm for computing extensive-form correlated equilibria in large two-player general-sum games with no chance moves. Designing such an algorithm is significantly more challenging than designing one for the Nash equilibrium counterpart, as the constraints that define the space of correlation plans lack the hierarchical structure and might even form cycles. We show that some of the constraints are redundant and can be excluded from consideration, and present an efficient algorithm that generates the space of extensive-form correlation plans incrementally from the remaining constraints. This structural decomposition is achieved via a special convexity-preserving operation that we coin scaled extension. We show that a regret minimizer can be designed for a scaled extension of any two convex sets, and that from the decomposition we then obtain a global regret minimizer. Our algorithm produces feasible iterates. Experiments show that it significantly outperforms prior approaches and for larger problems it is the only viable option.
Updating estimates of low-streamflow statistics to account for possible trends

Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estima...
Order of fluctuations of the free energy in the SK model at critical temperature

We present an elementary approach to the order of fluctuations for the free energy in the Sherrington-Kirkpatrick mean field spin glass model at and near the critical temperature. It is proved that at the critical temperature the variance of the free energy is of $O((\log N)^2).$ In addition, we show that if one approaches the critical temperature from the low temperature regime at the rate $O(N^{-\alpha})$ for some $\alpha>0,$ then the variance is of $O((\log N)^2+N^{1-\alpha}).$
The expected time to cross extended fitness plateaus

For a population to acquire a complex adaptation requiring multiple individually neutral mutations, it must cross a plateau in the fitness landscape. We consider plateaus involving three mutations, and show that large populations can cross them rapidly via lineages that acquire multiple mutations while remaining at low frequency, much faster than the ∝μ3 rate for simultaneous triple mutations. Plateau-crossing is fastest for very large populations. At intermediate population sizes, recombination can greatly accelerate adaptation by combining independent mutant lineages to form triple-mutants. For more frequent recombination, such that the population is kept near linkage equilibrium, we extend our analysis to find simple expressions for the expected time to cross plateaus of arbitrary width.
Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study.

We focus on low-dimensional non-metric search, where tree-based approaches permit efficient and accurate retrieval while having short indexing time. These methods rely on space partitioning and require a pruning rule to avoid visiting unpromising parts. We consider two known data-driven approaches to extend these rules to non-metric spaces: TriGen and a piece-wise linear approximation of the pruning rule. We propose and evaluate two adaptations of TriGen to non-symmetric similarities (TriGen does not support non-symmetric distances). We also evaluate a hybrid of TriGen and the piece-wise linear approximation pruning. We find that this hybrid approach is often more effective than either of the pruning rules. We make our software publicly available.
Generating photon-added states without adding a photon

A range of non-classical states can be generated using an optical parametric amplifier post-selected to contain a single photon in both the input and output of the idler mode, with no photons added or subtracted.
The Impact of Audit Committee Information Technology Expertise on the Reliability and Timeliness of Financial Reporting

We examine whether information technology expertise on audit committees impacts the reliability and timeliness of financial reporting. We find a reduction in the likelihood of material restatements...
Fecal microbiota transplantation in children does not significantly alter body mass index

Background: Fecal microbiota transplantation (FMT) is nowadays a promising therapy for Clostridium difficile infection (CDI) and a potential treatment for ulcerative colitis. However, it is still unclear whether the changes in intestinal microbiome will affect energy homeostasis or metabolism. This brings an intriguing question whether FMT from healthy donors affects recipient’s body mass index (BMI). Methods: In our randomized placebo-controlled study children patients with CDI or ulcerative colitis were randomly divided into control and FMT groups. The change of post-FMT BMI percentile at 1, 3, 6, 12 months was calculated. The age range of CDI cohort was 1 to 17 years, while the range was 8 to 21 years for ulcerative colitis cohort. Results: We found that the BMI percentile was insignificantly changed by ‒ 0.7%, ‒ 1.8%, 1.3%, 4.6% in CDI, while by 3.6%, ‒ 3.3%, 3.7%, 7.1% in ulcerative colitis at 1, 3, 6, 12 months after FMT (“ ‒ ” means decrease). Conclusions: We concluded that FMT from healthy donors does not significantly alter BMI in children with CDI and ulcerative colitis over 12 months.
Global optimization for accurate determination of EBSD pattern centers.

Abstract Accurate pattern center determination has long been a challenge for the electron backscatter diffraction (EBSD) community and is becoming critically accuracy-limiting for more recent advanced EBSD techniques. Here, we study the parameter landscape over which a pattern center must be fitted in quantitative detail and reveal that it is both “sloppy” and noisy, which limits the accuracy to which pattern centers can be determined. To locate the global optimum in this challenging landscape, we propose a combination of two approaches: the use of a global search algorithm and averaging the results from multiple patterns. We demonstrate the ability to accurately determine pattern centers of simulated patterns, inclusive of effects of binning and noise on the error of the fitted pattern center. We also demonstrate the ability of this method to accurately detect changes in pattern center in an experimental dataset with noisy and highly binned patterns. Source code for our pattern center fitting algorithm is available online.
Gaussian Conditionally Markov Sequences: Algebraically Equivalent Dynamic Models

The conditionally Markov (CM) sequence contains different classes, including Markov, reciprocal, and so-called $\text{CM}_L$ and $\text{CM}_F$ (two CM classes defined in our previous work). Markov sequences are special reciprocal sequences, and reciprocal sequences are special $\text{CM}_L$ and $\text{CM}_F$ sequences. Each class has its own forward and backward dynamic models. The evolution of a CM sequence can be described by different models. For a given problem, a model in a specific form is desired or needed, or one model can be easier to apply and better than another. Therefore, it is important to study the relationship between different models and to obtain one model from another. This article studies this topic for models of nonsingular Gaussian $\text{CM}_L$ , $\text{CM}_F$ , reciprocal, and Markov sequences. Two models are probabilistically equivalent (PE) if their stochastic sequences have the same distribution and are algebraically equivalent (AE) if their stochastic sequences are pathwise identical. A unified approach is presented to obtain an AE forward/backward $\text{CM}_L$ / $\text{CM}_F$ /reciprocal/Markov model from another such model. As a special case, a backward Markov model AE to a forward Markov model is obtained. While existing results are restricted to models with nonsingular state transition matrices, our approach is not. In addition, a simple approach is presented for studying and determining Markov models, whose sequences share the same reciprocal/ $\text{CM}_L$ model.
Academic Motivation Deficits in Adolescents with ADHD and Associations with Academic Functioning.

The present study evaluates differences in self-reported intrinsic and extrinsic academic motivation and amotivation between eighth-grade adolescents with (n = 162) and without (n = 140) ADHD. This study also examines associations between motivation and academic functioning with objective (i.e., grade point average, standardized reading and math scores) and cross-rater measurement (i.e., parent-reported homework performance). Multivariate analysis of variance controlling for sex, intelligence, and medication status found that adolescents with ADHD exhibited a significant motivational deficit compared to adolescents without ADHD across all areas of academic motivation, including intrinsic motivation (d = 0.49), extrinsic motivation (d = 0.43), and amotivation (d = 0.42). To examine whether motivation was differentially associated with academic impairment in the ADHD and comparison groups, a multi-group path analysis was conducted controlling for sex, intelligence, and medication status. Findings showed that motivation was differentially associated with academic impairment for adolescents with and without ADHD. For the comparison group, higher amotivation was associated with poorer homework performance and lower intrinsic motivation was associated with lower reading accuracy. In the ADHD group, higher amotivation was associated with poorer homework performance and math fluency, higher extrinsic motivation was associated with better homework performance and higher GPA, and higher intrinsic motivation was associated with higher reading accuracy. This study builds upon previous research in demonstrating that adolescents with ADHD have academic motivational deficits when compared to their peers without ADHD. Research is needed to understand the longitudinal interplay of academic motivation and academic functioning, with an eye towards developing or modifying interventions to increase academic motivation and academic success.
Higher codimensional alpha invariants and characterization of projective spaces

We generalize the definition of alpha invariant to arbitrary codimension. We also give a lower bound of these alpha invariants for K-semistable ℚ-Fano varieties and show that we can characterize pr...
The Penrose Effect and its acceleration by the war on drugs: a crisis of untranslated neuroscience and untreated addiction and mental illness

In 1939, British psychiatrist Lionel Penrose described an inverse relationship between mental health treatment infrastructure and criminal incarcerations. This relationship, later termed the 'Penrose Effect', has proven remarkably predictive of modern trends which have manifested as reciprocal components, referred to as 'deinstitutionalization' and 'mass incarceration'. In this review, we consider how a third dynamic-the criminalization of addiction via the 'War on Drugs', although unanticipated by Penrose, has likely amplified the Penrose Effect over the last 30 years, with devastating social, economic, and healthcare consequences. We discuss how synergy been the Penrose Effect and the War on Drugs has been mediated by, and reflects, a fundamental neurobiological connection between the brain diseases of mental illness and addiction. This neuroscience of dual diagnosis, also not anticipated by Penrose, is still not being adequately translated into improving clinical training, practice, or research, to treat patients across the mental illness-addictions comorbidity spectrum. This failure in translation, and the ongoing fragmentation and collapse of behavioral healthcare, has worsened the epidemic of untreated mental illness and addictions, while driving unsustainable government investment into mass incarceration and high-cost medical care that profits too exclusively on injuries and multi-organ diseases resulting from untreated addictions. Reversing the fragmentation and decline of behavioral healthcare with decisive action to co-integrate mental health and addiction training, care, and research-may be key to ending criminalization of mental illness and addiction, and refocusing the healthcare system on keeping the population healthy at the lowest possible cost.
Relaxation Dynamics of Hydrated Thymine, Thymidine, and Thymidine Monophosphate Probed by Liquid Jet Time-Resolved Photoelectron Spectroscopy

The relaxation dynamics of thymine and its derivatives thymidine and thymidine monophosphate are studied using time-resolved photoelectron spectroscopy applied to a water microjet. Two absorption bands are studied; the first is a bright ππ* state which is populated using tunable-ultraviolet light in the range 4.74-5.17 eV and probed using a 6.20 eV probe pulse. By reversing the order of these pulses, a band containing multiple ππ* states is populated by the 6.20 eV pulse and the lower energy pulse serves as the probe. The lower lying ππ* state is found to decay in ∼400 fs in both thymine and thymidine independent of pump photon energy, while thymidine monophosphate decays vary from 670 to 840 fs with some pump energy dependence. The application of a computational quantum mechanical/molecular mechanical scheme at the XMS-CASPT2//CASSCF/AMBER level of theory suggests that conformational differences existing between thymidine and thymidine monophosphate in solution account for this difference. The higher lying ππ* band is found to decay in ∼600 fs in all three cases, but it is only able to be characterized when the 5.17 eV probe pulse is used. Notably, no long-lived signal from an nπ* state can be identified in either experiment on any of the three molecules.
Triplet-Aware Scene Graph Embeddings

Scene graphs have become an important form of structured knowledge for tasks such as visual relation detection, visual question answering, and image retrieval. While visualizing and interpreting word embeddings is well understood, scene graph embeddings have not been fully explored. In this work, we train scene graph embeddings in a layout generation task with varying forms of supervision, specifically introducing triplet supervision and data augmentation. We see a significant performance increase in both metrics that measure the goodness of layout prediction, mean intersection-over-union (mIoU) (52.3% vs. 49.2%) and relation score (61.7% vs. 54.1%), after the addition of triplet supervision and data augmentation. To understand how these different methods effect the scene graph representation, we apply several new visualization and evaluation methods to explore the evolution of the scene graph embedding. We find that triplet supervision significantly improves the embedding separability, which is highly correlated with performance of the layout prediction model.
Coming of age before the great expulsion: the story of the CILS-San Diego sample 25 years later

California was transformed by immigration in the 1980s. In 1991, a representative sample of children of immigrants and refugees was drawn from 8th/9th graders in San Diego’s public schools. These C...
Delivering intensive therapies to older adults with hematologic malignancies: strategies to personalize care

Intensive therapies are often medically indicated for older adults with hematologic malignancies. These may include induction chemotherapy for acute myeloid leukemia (AML), as well as autologous hematopoietic cell transplant (autoHCT) and allogeneic hematopoietic cell transplant (alloHCT). However, it is not always clear how to best deliver these therapies, in terms of determining treatment eligibility, as well as adjusting or adding supportive measures to the treatment plan to maximize successful outcomes. Beyond performance status and presence of comorbidities, comprehensive geriatric assessment and individual geriatric metrics have increasingly been used to prognosticate in these settings and may offer the best approach to personalizing therapy. In the setting of AML induction, evidence supports the use of measures of physical function as independent predictors of survival. For patients undergoing alloHCT, functional status, as measured by instrumental activities of daily living (IADL) and gait speed, may be an important pretransplant assessment. IADL has also been associated with post-autoHCT morbidity and mortality. Current best practice includes assessment of relevant geriatric metrics prior to intensive therapy, and work is ongoing to develop complementary interventions.
Molecular Conduction: Paradigms and Possibilities

We discuss the factors that determine the overall shape and magnitude of the current-voltage (I-V) characteristics of a variety of molecular conductors sandwiched between two metallic contacts. We analyze the individual influences of the contact geometry, the molecular chemistry, the electrostatics of the environment, and charging on molecular conduction. Current conduction depends sensitively on the experimental geometry, as well as on the theoretical model for the molecule and the contacts. Computing molecular I-V characteristics will thus require theoretical understanding on several fronts, in particular, in the scheme for calculating the molecular energy levels, as well as on the position of the contact Fermi energy relative to those levels.
Amino and PEG-Amino Graphene Oxide Grids Enrich and Protect Samples for High-resolution Single Particle Cryo-electron Microscopy

Cryo-EM samples prepared using traditional methods often suffer from too few particles, poor particle distribution, strongly biased orientation, or damage from the air-water interface. Here we report that functionalization of graphene oxide (GO) coated grids with amino groups concentrates samples on the grid with improved distribution and orientation. By introducing a PEG spacer, particles are kept away from both the GO surface and the air-water interface, protecting them from potential denaturation.
Wavefunction Collapse and Random Walk

Wavefunction collapse models modify Schrodinger's equation so that it describes the rapid evolution of a superposition of macroscopically distinguishable states to one of them. This provides a phenomenological basis for a physical resolution to the so-called “measurement problem.” Such models have experimentally testable differences from standard quantum theory. The most well developed such model at present is the Continuous Spontaneous Localization (CSL) model in which a universal fluctuating classical field interacts with particles to cause collapse. One “side effect” of this interaction is that the field imparts energy to the particles: experimental evidence on this has led to restrictions on the parameters of the model, suggesting that the coupling of the classical field to the particles must be mass-proportional. Another “side effect” is that the field imparts momentum to particles, causing a small blob of matter to undergo random walk. Here we explore this in order to supply predictions which could be experimentally tested. We examine the translational diffusion of a sphere and a disc, and the rotational diffusion of a disc, according to CSL. For example, we find that the rms distance an isolated 10−5 cm radius sphere diffuses is ≈(its diameter, 5 cm) in (20 sec, a day), and that a disc of radius 2 ⋅ 10−5 cm and thickness 0.5 ⋅ 10−5 cm diffuses through 2πrad in about 70 sec (this assumes the “standard” CSL parameter values). The comparable rms diffusions of standard quantum theory are smaller than these by a factor 10−3±1. It is shown that the CSL diffusion in air at STP is much reduced and, indeed, is swamped by the ordinary Brownian motion. It is also shown that the sphere's diffusion in a thermal radiation bath at room temperature is comparable to the CSL diffusion, but is utterly negligible at liquid He temperature. Thus, in order to observe CSL diffusion, the pressure and temperature must be low. At the low reported pressure of 5 ⋅ 10−17 Torr, achieved at 4.2°K, the mean time between air molecule collisions with the (sphere, disc) is ≈(80, 45)min. This is ample time for observation of the putative CSL diffusion with the standard parameters and, it is pointed out, with any parameters in the range over which the theory may be considered viable. This encourages consideration of how such an experiment may actually be performed, and the paper closes with some thoughts on this subject.
Well-Posedness of a Diffuse Interface model for Hele-Shaw Flows

We study a diffuse interface model describing the motion of two viscous fluids driven by surface tension in a Hele-Shaw cell. The full system consists of the Cahn–Hilliard equation coupled with the Darcy’s law. We address the physically relevant case in which the two fluids have different viscosities (unmatched viscosities case) and the free energy density is the Flory–Huggins logarithmic potential. In dimension two we prove the uniqueness of weak solutions under a regularity criterion, and the existence and uniqueness of global strong solutions. In dimension three we show the existence and uniqueness of strong solutions, which are local in time for large data or global in time for appropriate small data. These results extend the analysis obtained in the matched viscosities case by Giorgini et al. (Ann Inst Henri Poincare Anal Non Lineaire 35:318–360, 2018). Furthermore, we prove the uniqueness of weak solutions in dimension two by taking the well-known polynomial approximation of the logarithmic potential.
Recent progress and problems on the Bartnik quasi-local mass

This paper surveys recent progress on issues related to the Bartnik quasi-local mass $m_B$. In addition, we formulate a number of new problems and conjectures regarding foundational properties of the mass $m_B$. This work is dedicated with pleasure to Robert Bartnik in honor of his 60th birthday.
Review of John Lemos’ A Pragmatic Approach to Libertarian Free Will

In this book, John Lemos shows how to be a libertarian by arguing for libertarianism on pragmatic rather than evidential grounds. Lemos relies heavily on Kantian moral premises, especially the Principle of Ends and the “Ought” implies “Can” precept. Add to these a rejection of compatibilism and we have a formidable line of reasoning that concludes that we morally should adopt libertarianism. Along the way, Lemos argues that libertarians are not hard-hearted in advocating punishment for persons when we have no epistemic evidence of their guilt. In this review, I examine Lemos’ pragmatic approach.
Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction

Deep learning (DL) is increasingly used to solve ill-posed inverse problems in medical imaging, such as reconstruction from noisy and/or incomplete data, as DL offers advantages over conventional methods that rely on explicit image features and hand engineered priors. However, supervised DL-based methods may achieve poor performance when the test data deviates from the training data, for example, when it has pathologies not encountered in the training data. Furthermore, DL-based image reconstructions do not always incorporate the underlying forward physical model, which may improve performance. Therefore, in this work we introduce a novel approach, called fidelity imposed network edit (FINE), which modifies the weights of a pre-trained reconstruction network for each case in the testing dataset. This is achieved by minimizing an unsupervised fidelity loss function that is based on the forward physical model. FINE is applied to two important inverse problems in neuroimaging: quantitative susceptibility mapping (QSM) and under-sampled image reconstruction in MRI. Our experiments demonstrate that FINE can improve reconstruction accuracy.
The Smartphone as a Pacifying Technology

In light of consumers’ growing dependence on their smartphones, this article investigates the nature of the relationship that consumers form with their smartphone and its underlying mechanisms. We propose that in addition to obvious functional benefits, consumers in fact derive emotional benefits from their smartphone, in particular, feelings of psychological comfort and, if needed, actual stress relief. In other words, in a sense, smartphones are not unlike “adult pacifiers.” This psychological comfort arises from a unique combination of properties that turn smartphones into a reassuring presence for their owners: the portability of the device, its personal nature, the subjective sense of privacy experienced while on the device, and the haptic gratification it affords. Results from one large-scale field study and three laboratory experiments support the proposed underlying mechanisms and document downstream consequences of the psychological comfort that smartphones provide. The findings show, for example, that (a) in moments of stress, consumers exhibit a greater tendency to seek out their smartphone (study 2); and (b) engaging with one’s smartphone provides greater stress relief than engaging in the same activity with a comparable device such as one’s laptop (study 3) or a similar smartphone belonging to someone else (study 4).
Radiative transfer in half spaces of arbitrary dimension

We solve the classic albedo and Milne problems of plane-parallel illumination of an isotropically-scattering half-space when generalized to a Euclidean domain Rd for arbitrary d≥1. A continuous fam...
Coastal Resiliency Through Value Capture and Transfer: A Framework Proposal

Coastal property is becoming more dynamic as it is subjected to the forces of climate change. This is particularly true for low-lying coastal areas, where climate-induced change is altering long-st...
Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples

For many important problems the quantity of interest is an unknown function of the parameters, which is a random vector with known statistics. Since the dependence of the output on this random vect...
Distributed Bilayered Control for Transient Frequency Safety and System Stability in Power Grids

This article considers power networks governed by swing nonlinear dynamics and subject to disturbances. We develop a bilayered control strategy for a subset of buses that simultaneously guarantees transient frequency safety of each individual bus and asymptotic stability of the entire network. The bottom layer is a model predictive controller that, based on periodically sampled system information, optimizes control resources to have transient frequency evolve close to a safe desired interval. The top layer is a real-time controller assisting the bottom-layer controller to guarantee that transient frequency safety is actually achieved. We show that control signals at both layers are Lipschitz in the state and do not jeopardize network stability. Furthermore, we carefully characterize the information requirements at each bus necessary to implement the controller and employ saddle-point dynamics to introduce a distributed implementation that only requires information exchange with up to two-hop neighbors in the power network. Simulations on the IEEE 39-bus power network illustrate our results.
Euclidean Forward-Reverse Brascamp-Lieb Inequalities: Finiteness, Structure and Extremals

A new proof is given for the fact that centered Gaussian functions saturate the Euclidean forward–reverse Brascamp–Lieb inequalities, extending the Brascamp–Lieb and Barthe theorems. A duality principle for best constants is also developed, which generalizes the fact that the best constants in the Brascamp–Lieb and Barthe inequalities are equal. Finally, as the title hints, the main results concerning finiteness, structure, and Gaussian-extremizability for the Brascamp–Lieb inequality due to Bennett, Carbery, Christ, and Tao are generalized to the setting of the forward–reverse Brascamp–Lieb inequality.
Development and testing of a novel killer–rescue self-limiting gene drive system in Drosophila melanogaster

Here we report the development and testing of a novel self-limiting gene drive system, Killer-Rescue (K-R), in Drosophila melanogaster. This system is composed of an autoregulated Gal4 Killer (K) and a Gal4-activated Gal80 Rescue (R). Overexpression of Gal4 is lethal, but in the presence of R activation of Gal80 leads to much lower levels of Gal4 and rescue of lethality. We demonstrate that with a single 2 : 1 engineered to wild-type release, K drives R through the population and after nine generations, more than 98% of the population carry R and less than 2% of the population are wild-type flies. We discuss how this simple K-R gene drive system may be readily adapted for population replacement in a human health pest, Aedes aegypti, or for population suppression in an agricultural pest, Drosophila suzukii.
Expanding and diversifying the pool of undergraduates who study economics: Insights from a new introductory course at Harvard

Economics does not attract as broad or diverse a pool of talent as it could. For example, women comprise less than one-third of economics bachelor’s degree recipients, significantly lower than in m...
Single-Cell Tumor Phylogeny Inference with Copy-Number Constrained Mutation Losses.

Motivation: Single-cell DNA sequencing enables the measurement of somatic mutations in individual tumor cells, and provides data to reconstruct the evolutionary history of the tumor.
Lifted inference for relational continuous models

Relational Continuous Models (RCMs) represent joint probability densities over attributes of objects, when the attributes have continuous domains. With relational representations, they can model joint probability distributions over large numbers of variables compactly in a natural way. This paper presents a new exact lifted inference algorithm for RCMs, thus it scales up to large models of real world applications. The algorithm applies to Relational Pairwise Models which are (relational) products of potentials of arity 2. Our algorithm is unique in two ways. First, it substantially improves the efficiency of lifted inference with variables of continuous domains. When a relational model has Gaussian potentials, it takes only linear-time compared to cubic time of previous methods. Second, it is the first exact inference algorithm which handles RCMs in a lifted way. The algorithm is illustrated over an example from econometrics. Experimental results show that our algorithm outperforms both a ground-level inference algorithm and an algorithm built with previously-known lifted methods.
Charge-density waves observed at 4.2 K by scanning-tunneling microscopy

Scanning-tunneling-microscope images of layer structure dichalcogenides exhibiting charge-density-waves (CDW's) have been studied at 4.2 K. CDW amplitudes in the 2H, 1T, and 4Hb phases of ${\mathrm{TaSe}}_{2}$ have been measured with the strongest CDW phase showing only the superlattice modulation while the weaker CDW phases show simultaneous CDW and surface-atom modulations. In 2H-${\mathrm{NbSe}}_{2}$ a well-resolved hexagonal CDW superlattice superimposed on the dominant surface-atom pattern is observed.
Event ticket price prediction with deep neural network on spatial-temporal sparse data

Event ticket price prediction is important to marketing strategy for any sports team or musical ensemble. An accurate prediction model can help the marketing team to make promotion plan more effectively and efficiently. However, given all the historical transaction records, it is challenging to predict the sale price of the remaining seats at any future timestamp, not only because that the sale price is relevant to a lot of features (seat locations, date-to-event of the transaction, event date, team performance, etc.), but also because of the temporal and spatial sparsity in the dataset. For a game/concert, the ticket selling price of one seat is only observable once at the time of sale. Furthermore, some seats may not even be purchased (therefore no record available). In fact, data sparsity is commonly encountered in many prediction problems. Here, we propose a bi-level optimizing deep neural network to address the curse of spatio-temporal sparsity. Specifically, we introduce coarsening and refining layers, and design a bi-level loss function to integrate different level of loss for better prediction accuracy. Our model can discover the interrelations among ticket sale price, seat locations, selling time, event information, etc. Experiments show that our proposed model outperforms other benchmark methods in real-world ticket selling price prediction.
Generalizing in the context of an early algebra intervention (La generalización en el contexto de una intervención algebraica temprana)

This study aims to understand the instructional interactions that foster students’ generalizing. By analysing video-recorded lessons from 13 different Grade 3 classrooms in which an early algebra i...
Sorting Multidimensional Types: Theory and Application

This article studies multidimensional matching between workers and jobs. Workers differ in manual and cognitive skills and sort into jobs that demand different combinations of these two skills. To study this multidimensional sorting problem, I develop a theoretical framework that generalizes the unidimensional notion of assortative matching and sufficient conditions on the technology under which sorting obtains. I derive the equilibrium in closed form and use this explicit solution to study biased technological change. The main finding is that an increase in worker-job complementarities in cognitive relative to manual inputs leads to more pronounced sorting and wage inequality across cognitive relative to manual skills. This can trigger wage polarization and boost aggregate wage inequality. I then estimate the model for the U.S. and identify sizable technology shifts: during the last two decades, worker-job complementarities in cognitive inputs strongly increased, whereas complementarities in manual inputs decreased. In addition to this bias in complementarities, there has been a cognitive skill-bias in production. Counterfactual exercises suggest that these technology shifts (as opposed to changes in skill supply and demand) can account for observed changes in worker-job sorting, wage polarization and a significant part of the increase in U.S. wage dispersion.
Why development matters to (artificial) life: Lessons from human babies

Why do living forms develop? Development, like evolution and culture, is a process that creates complexity by accumulating change. At any moment, the developing agent is a product of all previous developments, and any new change begins with and must build on those previous developments. Biological systems that are flexibly smart have relatively long periods of immaturity. Why is this? This talk will consider answers to this question using evidence from the first two years of life of human infants. The core ideas are that an adaptive system that can succeed in varied and novel contexts is slow does not settle too fast; develops new mechanisms of change and learning processes over the life time; develops in a series of different environments.
Communicating Robot Arm Motion Intent Through Mixed Reality Head-Mounted Displays

Efficient motion intent communication is necessary for safe and collaborative work environments with collocated humans and robots. Humans efficiently communicate their motion intent to other humans through gestures, gaze, and social cues. However, robots often have difficulty efficiently communicating their motion intent to humans via these methods. Many existing methods for robot motion intent communication rely on 2D displays, which require the human to continually pause their work and check a visualization. We propose a mixed reality head-mounted display visualization of the proposed robot motion over the wearer’s real-world view of the robot and its environment. To evaluate the effectiveness of this system against a 2D display visualization and against no visualization, we asked 32 participants to labeled different robot arm motions as either colliding or non-colliding with blocks on a table. We found a 16% increase in accuracy with a 62% decrease in the time it took to complete the task compared to the next best system. This demonstrates that a mixed-reality HMD allows a human to more quickly and accurately tell where the robot is going to move than the compared baselines.
Heterogeneity-induced mesoscale toughening in polymer nanocomposites

Abstract We report a mesoscale toughening mechanism in polymer nanocomposites that is distinct from previously reported ones. Fractography analysis of epoxy composites with nano-silica additives reveals a stochastic dispersion of nanofiller clusters which creates mesoscale stiffness heterogeneity as confirmed by nanoindentation testing. To analyze the effect of heterogeneity, a finite element model where a crack grows through heterogeneous material was created. Simulations and experimental results indicate that inducing stiffness heterogeneity increases toughness by modification of the crack tip fields. Our results indicate that mesoscale toughening (induced by the nanoparticle additives) plays a significant role in influencing fracture toughness in nanocomposite materials.
Interaction of atomic and molecular hydrogen with tholin surfaces at low temperatures.

We study the interaction of atomic and molecular hydrogen with a surface of tholin, a man-made polymer considered to be an analogue of aerosol particles present in Titan’s atmosphere, using thermal programmed desorption at low temperatures below 30 K. The results are fitted and analyzed using a fine-grained rate equation model that describes the diffusion, reaction, and desorption processes. We obtain the energy barriers for diffusion and desorption of atomic and molecular hydrogen. These barriers are found to be in the range of 30−60 meV, indicating that atom/molecule-surface interactions in this temperature range are dominated by weak adsorption forces. The implications of these results for the understanding of the atmospheric chemistry of Titan are discussed.
Look Before You Sweep: Visibility-Aware Motion Planning.

This paper addresses the problem of planning for a robot with a directional obstacle-detection sensor that must move through a cluttered environment. The planning objective is to remain safe by finding a path for the complete robot, including sensor, that guarantees that the robot will not move into any part of the workspace before it has been seen by the sensor. Although a great deal of work has addressed a version of this problem in which the “field of view” of the sensor is a sphere around the robot, there is very little work addressing robots with a narrow or occluded field of view. We give a formal definition of the problem, several solution methods with different computational trade-offs, and experimental results in illustrative domains.
Unmixing the metaphors of Austrian capital theory

A complement of metaphors inherited from the classical era has held back progress in Austrian capital theory (ACT). In particular, the attachment to circulating capital as the paradigmatic capital good, largely motivated by the business cycle theory, has locked ACT into a nonoperational point-output model of production. This paper draws out a distinct flow-output approach from work by Lachmann, Lewin, and Cachanosky, contrasts its associated metaphors and paradigms with those of the canonical Hayek-Garrison model, and argues that the former has the potential to bolster both the analytical coherence and the empirical relevance of ACT that it has so far found elusive. By focusing on the investment project rather than the capital good as the object of planmaking, the flow-output approach affirms the core appeal of ACT – a heterogeneous capital structure and a market process approach – by declaring independence from the business cycle theory.
Language as Obstacle and as Data in Sociological Research

The SSRC’s Committee on Sociolinguistics was committed to furthering attention to language, and linguistic difference, as an “unexploited kind of sociological data” in ethnographic and survey research. The committee convened a conference in 1968 to better understand the intersection of social and linguistic factors, summarized here by Allen D. Grimshaw. The group focused on four topics: the ethnography of asking questions; the meaning of words; the ways in which interviews themselves are “a part of the data” and “don’t know” responses are revealing answers to questions; and improving scholars’ training in framing questions and eliciting answers related to language and communication.
Trapping of swimmers in a vortex lattice

We examine the motion of rigid, ellipsoidal swimmers subjected to a steady vortex flow in two dimensions. Numerical simulations of swimmers in a spatially periodic array of vortices reveal a range of possible behaviors, including trapping inside a single vortex and motility-induced diffusion across many vortices. While the trapping probability vanishes at a sufficiently high swimming speed, we find that it exhibits surprisingly large oscillations as this critical swimming speed is approached. Strikingly, at even higher swimming speeds, we find swimmers that swim perpendicular to their elongation direction can again become trapped. To explain this complex behavior, we investigate the underlying swimmer phase-space geometry. We identify the fixed points and periodic orbits of the swimmer equations of motion that regulate swimmer trapping inside a single vortex cell. For low to intermediate swimming speeds, we find that a stable periodic orbit surrounded by invariant tori forms a transport barrier to swimmers and can trap them inside individual vortices. For swimming speeds approaching the maximum fluid speed, we find instead that perpendicular swimmers can be trapped by asymptotically stable fixed points. A bifurcation analysis of the stable periodic orbit and the fixed points explains the complex and non-monotonic breakdown and re-emergence of swimmer trapping as the swimmer speed and shape are varied.
Understanding Human Hands in Contact at Internet Scale

Hands are the central means by which humans manipulate their world and being able to reliably extract hand state information from Internet videos of humans engaged in their hands has the potential to pave the way to systems that can learn from petabytes of video data. This paper proposes steps towards this by inferring a rich representation of hands engaged in interaction method that includes: hand location, side, contact state, and a box around the object in contact. To support this effort, we gather a large-scale dataset of hands in contact with objects consisting of 131 days of footage as well as a 100K annotated hand-contact video frame dataset. The learned model on this dataset can serve as a foundation for hand-contact understanding in videos. We quantitatively evaluate it both on its own and in service of predicting and learning from 3D meshes of human hands.
Analysis of structural variants in four African cichlids highlights an association with developmental and immune related genes

East African lake cichlids are one of the most impressive examples of an adaptive radiation. Independently in Lake Victoria, Tanganyika, and Malawi, several hundreds of species arose within the last 10 million to 100,000 years. Whereas most analyses in cichlids focused on nucleotide substitutions across species to investigate the genetic bases of this explosive radiation, to date, no study has investigated the contribution of structural variants (SVs) in the evolution of adaptive traits across the three Great Lakes of East Africa. Here, we annotate and characterize the repertoires and evolutionary potential of different SV classes (deletion, duplication, inversion, insertions and translocations) in four cichlid species: Haplochromis burtoni, Metriaclima zebra, Neolamprologus brichardi and Pundamilia nyererei. We investigate the patterns of gain and loss evolution for each SV type, enabling the identification of lineage specific events. Both deletions and inversions show a significant overlap with SINE elements, while inversions additionally show a limited, but significant association with DNA transposons. Inverted regions are enriched for genes regulating behaviour, or involved in skeletal and visual system development. We also find that duplicated regions show enrichment for genes associated with “antigen processing and presentation” and other immune related categories. Our pipeline and results were further tested by PCR validation of selected deletions and inversions, which confirmed respectively 7 out of 10 and 6 out of 9 events. Altogether, we provide the first comprehensive overview of rearrangement evolution in East African cichlids, and some important insights into their likely contribution to adaptation.