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Lactate, the redox-balanced end product of glycolysis, travels within and between cells to fulfill an array of physiologic functions. While evidence for the centrality of this lactate shuttling in mammalian metabolism continues to mount, its application to physical bioenergetics remains underexplored. Lactate represents a metabolic “cul-de-sac,” as it can only re-enter metabolism by first being converted back to pyruvate by lactate dehydrogenase (LDH). Given the differential distribution of lactate producing/consuming tissues during metabolic stresses (e.g., exercise), we hypothesize that lactate shuttling vis-à-vis the exchange of extracellular lactate between tissues serves a thermoregulatory function, i.e., an allostatic strategy to mitigate the consequences of elevated metabolic heat. To explore this idea, the rates of heat and respiratory oxygen consumption in saponin-permeabilized rat cortical brain samples fed lactate or pyruvate were measured. Heat and respiratory oxygen consumption rates, and calorespirometric ratios were lower during lactate vs. pyruvate-linked respiration. These results support the hypothesis of allostatic thermoregulation in the brain with lactate.

The measurement of optical ultrafast laser pulses is done indirectly because the required bandwidth to measure these pulses exceeds the bandwidth of current electronics. As a result, this measurement problem is often posed as a 1-D phase retrieval problem, which is fraught with ambiguities. The phase retrieval method known as ptychography solves this problem by making it possible to measure ultrafast pulses in either the time domain or the frequency domain. One well known algorithm is the principal components generalized projections algorithm (PCGPA) for extracting pulses from Frequency-Resolved Optical Gating (FROG) measurements. Here, we discuss the development of the PCPGA and introduce new developments including an operator formalism that allows for the convenient addition of external constraints and the development of more robust algorithms. A close cousin, the ptychographic iterative engine will also be covered and compared to the PCGPA. Additional developments using other algorithmic strategies will also be discussed along with new developments combining optics and high-speed electronics to achieve megahertz measurement rates., 96 pages; 26 figures

PDF file - 63KB, Supplementary Figure S1. Strategy for PCR amplification of the exonuclease domain region of POLE. Supplementary Table S1. Primers and reaction conditions used to amplify the entire coding sequence of POLE from tumor sample T-04-364 by nested PCR. Supplementary Table S2. Yeast strains used in the study. Supplementary Table S3. Properties of previously characterized yeast pol2 mutators.

Exonucleolytic proofreading and DNA mismatch repair (MMR) act in series to maintain high-fidelity DNA replication and to avoid mutagenesis. MMR defects elevate the overall mutation rate and are associated with increased cancer incidence. Hypermutable colorectal and endometrial tumors with functional MMR were recently reported to carry amino acid substitutions in the exonuclease domain of DNA polymerase ϵ (Polϵ). This created a notion that loss of the proofreading activity of Polϵ is an initiating cause of some sporadic human cancers. In this study, we identified a somatic P286R substitution in the conserved ExoI motif of Polϵ in a collection of 52 sporadic colorectal tumor specimens. This change has been repeatedly observed in colorectal and endometrial tumors in previous studies despite many possible ways to inactivate Polϵ proofreading. To understand the reasons for the recurrent appearance of the P286R variant, we characterized its functional consequences using the yeast model system. An analogous substitution in the yeast Polϵ produced an unusually strong mutator phenotype exceeding that of proofreading-deficient mutants by two orders of magnitude. This argues that the P286R mutation acts at some level other than loss of exonuclease to elevate cancer risk. Heterozygosity for the variant allele caused a strong mutator effect comparable with that of complete MMR deficiency, providing an explanation for why loss of heterozygosity is not required for the development of Polϵ-mutant human tumors. Cancer Res; 74(7); 1895–901. ©2014 AACR.

Although artificial intelligence systems can now outperform humans in a variety of domains, they still lag behind in the ability to arrive at good solutions to problems using limited resources. Recent proposals have suggested that the key to this cognitive efficiency is intelligent selection of the situations in which computational resources are spent. We tested this hypothesis in the domain of complex planning by analyzing how humans managed time available for thinking in over 12 million online chess matches. We found that players spent more time thinking in board positions where planning was more beneficial. This effect was greater in stronger players, and additionally strengthened by considering only the information available to the player at the time of choice. Finally, we found that the qualitative features of this relationship were consistent with a policy that considers the empirically-measured cost of spending time in chess. This provides evidence that human efficiency is supported by intelligent selection of when to apply computation.

In every corner of machine learning and statistics, there is a need for estimators that work not just in an idealized model, but even when their assumptions are violated. Unfortunately, in high dimensions, being provably robust and being efficiently computable are often at odds with each other. We give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian that is able to tolerate a constant fraction of corruptions that is independent of the dimension. Prior to our work, all known estimators either needed time exponential in the dimension to compute or could tolerate only an inverse-polynomial fraction of corruptions. Not only does our algorithm bridge the gap between robustness and algorithms, but also it turns out to be highly practical in a variety of settings.

Background The social determinants of health (SDOH) are the conditions in which people are born, grow, work, live, and age. Lack of SDOH training of dental providers on SDOH may result in suboptimal care provided to pediatric dental patients and their families. The purpose of this pilot study is to report the feasibility and acceptability of SDOH screening and referral by pediatric dentistry residents and faculty in the dental clinics of Family Health Centers at NYU Langone (FHC), a Federally Qualified Health Center (FQHC) network in Brooklyn, NY, USA. Methods Guided by the Implementation Outcomes Framework, 15 pediatric dentists and 40 pediatric dental patient–parent/guardian dyads who visited FHC in 2020–2021 for recall or treatment appointments participated in this study. The a priori feasibility and acceptability criteria for these outcomes were that after completing the Parent Adversity Scale (a validated SDOH screening tool), ≥ 80% of the participating parents/guardians would feel comfortable completing SDOH screening and referral at the dental clinic (acceptable), and ≥ 80% of the participating parents/guardians who endorsed SDOH needs would be successfully referred to an assigned counselor at the Family Support Center (feasible). Results The most prevalent SDOH needs endorsed were worried within the past year that food would run out before had money to buy more (45.0%) and would like classes to learn English, read better, or obtain a high school degree (45.0%). Post-intervention, 83.9% of the participating parents/guardians who expressed an SDOH need were successfully referred to an assigned counselor at the Family Support Center for follow-up, and 95.0% of the participating parents/guardians felt comfortable completing the questionnaire at the dental clinic, surpassing the a priori feasibility and acceptability criteria, respectively. Furthermore, while most (80.0%) of the participating dental providers reported being trained in SDOH, only one-third (33.3%) usually or always assess SDOH for their pediatric dental patients, and most (53.8%) felt minimally comfortable discussing challenges faced by pediatric dental patient families and referring patients to resources in the community. Conclusions This study provides novel evidence of the feasibility and acceptability of SDOH screening and referral by dentists in the pediatric dental clinics of an FQHC network.

Mitochondrial structures were probably observed microscopically in the 1840s, but the idea of oxidative phosphorylation (OXPHOS) within mitochondria did not appear until the 1930s. The foundation for research into energetics arose from Meyerhof’s experiments on oxidation of lactate in isolated muscles recovering from electrical contractions in an O(2) atmosphere. Today, we know that mitochondria are actually reticula and that the energy released from electron pairs being passed along the electron transport chain from NADH to O(2) generates a membrane potential and pH gradient of protons that can enter the molecular machine of ATP Synthase to resynthesize ATP. Lactate stands at the crossroads of glycolytic and oxidative energy metabolism. Based on reported research and our own modeling in silico, we contend that lactate is not directly oxidized in the mitochondrial matrix. Instead, the interim glycolytic products (pyruvate and NADH) are held in cytosolic equilibrium with the products of the lactate dehydrogenase (LDH) reaction and the intermediates of the malate-aspartate and glycerol 3-phosphate shuttles. This equilibrium supplies the glycolytic products to the mitochondrial matrix for OXPHOS. LDH in the mitochondrial matrix is not compatible with the cytoplasmic/matrix redox gradient; its presence would drain matrix reducing power and substantially dissipate the proton motive force. OXPHOS requires O(2) as the final electron acceptor, but O(2) supply is sufficient in most situations, including exercise and often acute illness. Recent studies suggest that atmospheric normoxia may constitute a cellular hyperoxia in mitochondrial disease. As research proceeds appropriate oxygenation levels should be carefully considered.

Soils comprise the largest pool of terrestrial carbon yet have lost significant stocks due to human activity. Changes to land management in cropland and grazing systems present opportunities to sequester carbon in soils at large scales. Uncertainty in the magnitude of this potential impact is largely driven by the difficulties and costs associated with measuring near-surface (0–30 cm) soil carbon concentrations; a key component of soil carbon stock assessments. Many techniques exist to optimize sampling, yet few studies have compared these techniques at varying sample intensities. In this study, we performed ex-ante, high-intensity sampling for soil carbon concentrations at four farms in the eastern United States. We used post hoc Monte-Carlo bootstrapping to investigate the most efficient sampling approaches for soil carbon inventory: K-means stratification, Conditioned Latin Hypercube Sampling (cLHS), simple random, and regular grid. No two study sites displayed similar patterns across all sampling techniques, although cLHS and grid emerged as the most efficient sampling schemes across all sites and strata sizes. The number of strata chosen when using K-means stratification can have a significant impact on sample efficiency, and we caution future inventories from using small strata n, while avoiding even allocation of sample between strata. Our findings reinforce the need for adaptive sampling methodologies where initial site inventory can inform primary, robust inventory with site-specific sampling techniques.

We develop numerical modeling techniques to predict spatiotemporal ultrafast pulse propagation through optical systems. Predicted pulses are verified with downstream measurement. Measurement feedback enhances modeling for hard-to-access locations in ultrafast laser systems.

We construct near optimal linear decision trees for a variety of decision problems in combinatorics and discrete geometry. For example, for any constant $k$, we construct linear decision trees that solve the $k$-SUM problem on $n$ elements using $O(n \log^2 n)$ linear queries. Moreover, the queries we use are comparison queries, which compare the sums of two $k$-subsets; when viewed as linear queries, comparison queries are $2k$-sparse and have only $\{-1,0,1\}$ coefficients. We give similar constructions for sorting sumsets $A+B$ and for solving the SUBSET-SUM problem, both with optimal number of queries, up to poly-logarithmic terms. Our constructions are based on the notion of "inference dimension", recently introduced by the authors in the context of active classification with comparison queries. This can be viewed as another contribution to the fruitful link between machine learning and discrete geometry, which goes back to the discovery of the VC dimension., 18 paged, 1 figure

We study the problem of testing discrete distributions with a focus on the high probability regime. Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and parameters $0< \epsilon, \delta

We study the problem of PAC learning homogeneous halfspaces with Tsybakov noise. In the Tsybakov noise model, the label of every example is independently flipped with an adversarially controlled probability that can be arbitrarily close to 1/2 for a fraction of the examples. We give the first polynomial-time algorithm for this fundamental learning problem. Our algorithm learns the true halfspace within any desired accuracy and succeeds under a broad family of well-behaved distributions including log-concave distributions. This extended abstract is a merge of two papers. In an earlier work, a subset of the authors developed an efficient reduction from learning to certifying the non-optimality of a candidate halfspace and gave a quasi-polynomial time certificate algorithm. In a subsequent work, the authors of the this paper developed a polynomial-time certificate algorithm.

We examine a new variant of the classic prisoners and light switches puzzle: A warden leads his $n$ prisoners in and out of $r$ rooms, one at a time, in some order, with each prisoner eventually visiting every room an arbitrarily large number of times. The rooms are indistinguishable, except that each one has $s$ light switches; the prisoners win their freedom if at some point a prisoner can correctly declare that each prisoner has been in every room at least once. What is the minimum number of switches per room, $s$, such that the prisoners can manage this? We show that if the prisoners do not know the switches' starting configuration, then they have no chance of escape—but if the prisoners do know the starting configuration, then the minimum sufficient $s$ is surprisingly small. The analysis gives rise to a number of puzzling open questions, as well.

We study the problem of PAC learning halfspaces on $\mathbb{R}^d$ with Massart noise under the Gaussian distribution. In the Massart model, an adversary is allowed to flip the label of each point $\mathbf{x}$ with unknown probability $\eta(\mathbf{x}) \leq \eta$, for some parameter $\eta \in [0,1/2]$. The goal is to find a hypothesis with misclassification error of $\mathrm{OPT} + \epsilon$, where $\mathrm{OPT}$ is the error of the target halfspace. This problem had been previously studied under two assumptions: (i) the target halfspace is homogeneous (i.e., the separating hyperplane goes through the origin), and (ii) the parameter $\eta$ is strictly smaller than $1/2$. Prior to this work, no nontrivial bounds were known when either of these assumptions is removed. We study the general problem and establish the following: For $\eta, Comment: Revised presentation

We study the problem of list-decodable mean estimation, where an adversary can corrupt a majority of the dataset. Specifically, we are given a set $T$ of $n$ points in $\mathbb{R}^d$ and a parameter $0< \alpha 0$. All prior algorithms for this problem had additional polynomial factors in $\frac 1 \alpha$. We leverage this result, together with additional techniques, to obtain the first almost-linear time algorithms for clustering mixtures of $k$ separated well-behaved distributions, nearly-matching the statistical guarantees of spectral methods. Prior clustering algorithms inherently relied on an application of $k$-PCA, thereby incurring runtimes of $\Omega(n d k)$. This marks the first runtime improvement for this basic statistical problem in nearly two decades. The starting point of our approach is a novel and simpler near-linear time robust mean estimation algorithm in the $\alpha \to 1$ regime, based on a one-shot matrix multiplicative weights-inspired potential decrease. We crucially leverage this new algorithmic framework in the context of the iterative multi-filtering technique of Diakonikolas et al. '18, '20, providing a method to simultaneously cluster and downsample points using one-dimensional projections -- thus, bypassing the $k$-PCA subroutines required by prior algorithms., Comment: 64 pages, 1 figure. v2 improves results on bounded-covariance clustering, polishes exposition

Let $V$ be any vector space of multivariate degree-$d$ homogeneous polynomials with co-dimension at most $k$, and $S$ be the set of points where all polynomials in $V$ {\em nearly} vanish. We establish a qualitatively optimal upper bound on the size of $\epsilon$-covers for $S$, in the $\ell_2$-norm. Roughly speaking, we show that there exists an $\epsilon$-cover for $S$ of cardinality $M = (k/\epsilon)^{O_d(k^{1/d})}$. Our result is constructive yielding an algorithm to compute such an $\epsilon$-cover that runs in time $\mathrm{poly}(M)$. Building on our structural result, we obtain significantly improved learning algorithms for several fundamental high-dimensional probabilistic models with hidden variables. These include density and parameter estimation for $k$-mixtures of spherical Gaussians (with known common covariance), PAC learning one-hidden-layer ReLU networks with $k$ hidden units (under the Gaussian distribution), density and parameter estimation for $k$-mixtures of linear regressions (with Gaussian covariates), and parameter estimation for $k$-mixtures of hyperplanes. Our algorithms run in time {\em quasi-polynomial} in the parameter $k$. Previous algorithms for these problems had running times exponential in $k^{\Omega(1)}$. At a high-level our algorithms for all these learning problems work as follows: By computing the low-degree moments of the hidden parameters, we are able to find a vector space of polynomials that nearly vanish on the unknown parameters. Our structural result allows us to compute a quasi-polynomial sized cover for the set of hidden parameters, which we exploit in our learning algorithms., Comment: Full version of FOCS'20 paper

Doppler Raman (DR) spectroscopy is a coherent Raman technique that combines impulsive Raman excitation with novel frequency shift detection to enable high-sensitivity Raman spectroscopy in the biological fingerprint region (500cm-1-1500cm-1) and the low frequency regime from 10cm-1 – 500cm-1. Using DR, we demonstrate nonresonant Raman spectroscopy on a suite of biologically significant targets involved in cell respiration including cytochrome c, adenosine triphosphate (ATP), flavin adenine dinucleotide (FAD), and nicotinamide adenine dinucleotide (NADH). High-sensitivity detection of low-to-medium frequency Raman vibrational modes may provide a tool to monitor states of cell respiration along with large molecular structural changes such as protein conformational dynamics.

Sonogram encoding is utilized to measure ultrafast optical pulses at 1550 nm. The optical waveform is divided into narrow-bandwidth frequency bins, which are time multiplexed. The recombined single-shot sonogram signal is acquired using high bandwidth electronics and processed to recover the pulse intensity and phase. Measurement of optical pulses with a variety of phase distortions introduced using a pulse shaper or dispersive optical fiber is demonstrated. One sonogram is acquired within less than 1 microsecond, which allows single-shot pulse measurement at a rate of up to 1 MHz. Capabilities and detailed specifications of the method will be presented.

Soil organic carbon influences several landscape ecological processes, and soils are becoming recognized as a mechanism to mitigate the negative impacts of climate change. There is a need to define methods and technologies for addressing soils’ spatial variability as well as the time and cost of sampling soil organic carbon (SOC). Visible and near-infrared spectroscopy have been suggested as a sampling tool to reduce inventory cost. We sampled nineteen ranch properties totaling 17,347 ha across Oklahoma and Texas in 2019 to evaluate the effectiveness and accuracy of a handheld reflectometer (Our Sci, Ann Arbor, MI, USA) (370–940 nm) and existing remote sensing approaches to estimate SOC in semi-arid grazing lands. Our data suggest that the Our Sci Reflectometer estimated soil organic carbon with a precision of approximately (±0.3% SOC); however, it was least accurate at higher carbon concentrations. The Our Sci reflectometer, although consistently accurate at lower SOC concentrations, was still less accurate than a model built using only remote sensing and digital soil map data as predictors. Combining the two data sources was the most accurate means of determining SOC. Our results indicated that the Our Sci handheld Vis-NIR reflectometer tested may have only limited applications for reducing inventory costs at scale.

Three-dimensional integrated circuit (3D IC) technology offers a potential breakthrough to enable a paradigm-shift strategy, called “more than Moore,” with novel features and advantages over the conventional 2D process technology. By having three-dimensional interconnections, 3D IC provides substantial wirelength reduction and a massive amount of bandwidth, which gives significant performance improvement to overcome many of the nontrivial challenges in semiconductor industry. Moreover, 3D integration technology enables to stack disparate technologies with various functionalities into a single system-in-package (SiP), introducing “true 3D IC” design. As the first physical design (PD) step, IC floorplanning takes a crucial role to determine IC’s overall design qualities such as footprint area, timing closure, power distribution, thermal management, and so on. However, lack of efficient 3D floorplanning algorithms that practically implement advantages of 3D integration technology is a critical bottleneck for PD automation of 3D IC design and implementation. 3D floorplanning (or packing, block partitioning) is a well-known NP-hard problem, and most of 3D floorplanning algorithms rely on heuristics and iterative improvements. Thus, developing complete and efficient 3D floorplan representations is important, since floorplan representation provides the foundation of data structure to search the solution space for 3D IC floorplanning. A well-defined floorplan representation provides a well-organized and cost-effective methodology to design high-performance 3D IC. We propose a new 3D IC floorplan representation methodology using corner links and partial order . Given a fixed number of cuboidal blocks and their volume, algorithmic 3D floorplan representations describe topological structure and physical positions/orientations of each block relative to the origin in the 3D floorplan space. In this article, (1) we introduce our novel 3D floorplan representation, called corner links representation , (2) we analyze the equivalence relation between the corner links representation and its corresponding partial order representation , and (3) we discuss several key properties of the corner links representation and partial order representation. The corner links representation provides a complete and efficient structure to assemble the original 3D mosaic floorplan. Also, the corner links representation for the non-degenerate 3D mosaic floorplan can be equivalently expressed by the four trees representation . The partial order representation defines the topological structure of the 3D floorplan with three transitive closure graphs (TCG) for each direction and captures all stitching planes in the 3D floorplan in the order of their respective directions. We demonstrate that the corner links representation can be reduced to its corresponding partial order representation, indicating that the corner links representation shares well-defined and -studied features/properties of 3D TCG-based floorplan representation. If the partial order representation describes relations between any pairs of blocks in the 3D floorplan, then the floorplan is a valid floorplan. We show that the partial order representation can restore the absolute coordinates of all blocks in the 3D mosaic floorplan by using the given physical dimensions of blocks.

We construct sets A and B in a vector space over $$\mathbb{F}$$ with the property that A is “statistically” almost closed under addition by B in the sense that a + b almost always lies in A when a ∈ A and b ∈ B, but which is extremely far from being “combinatorially” almost closed under addition by B: if A′⊂ A, B′⊂ B and A′ + B′ is comparable in size to A′, then |B′| ⪅ |B|1/2.

Autotaxin (ATX) is an adipokine that generates the bioactive lipid, lysophosphatidic acid (LPA). ATX-LPA signaling has been implicated in diet-induced obesity and systemic insulin resistance. However, it remains unclear whether the ATX-LPA pathway influences insulin function and energy metabolism in target tissues, particularly skeletal muscle, the major site of insulin-stimulated glucose disposal. The objective of this study was to test whether the ATX-LPA pathway impacts tissue insulin signaling and mitochondrial metabolism in skeletal muscle during obesity. Male mice with heterozygous ATX deficiency (ATX(+/−)) were protected from obesity, systemic insulin resistance, and cardiomyocyte dysfunction following high-fat high-sucrose (HFHS) feeding. HFHS-fed ATX(+/−) mice also had improved insulin-stimulated AKT phosphorylation in white adipose tissue, liver, heart, and skeletal muscle. Preserved insulin-stimulated glucose transport in muscle from HFHS-fed ATX(+/−) mice was associated with improved mitochondrial pyruvate oxidation in the absence of changes in fat oxidation and ectopic lipid accumulation. Similarly, incubation with LPA decreased insulin-stimulated AKT phosphorylation and mitochondrial energy metabolism in C2C12 myotubes at baseline and following palmitate-induced insulin resistance. Taken together, our results suggest that the ATX-LPA pathway contributes to obesity-induced insulin resistance in metabolically relevant tissues. Our data also suggest that LPA directly impairs skeletal muscle insulin signaling and mitochondrial function.

Soil-based initiatives to mitigate climate change and restore soil fertility both rely on rebuilding soil organic carbon. Controversy about the role soils might play in climate change mitigation is, consequently, undermining actions to restore soils for improved agricultural and environmental outcomes.

DNA replication fidelity relies on base selectivity of the replicative DNA polymerases, exonucleolytic proofreading, and postreplicative DNA mismatch repair (MMR). Ultramutated human cancers without MMR defects carry alterations in the exonuclease domain of DNA polymerase ε (Polε). They have been hypothesized to result from defective proofreading. However, modeling of the most common variant, Polε-P286R, in yeast produced an unexpectedly strong mutator effect that exceeded the effect of proofreading deficiency by two orders of magnitude and indicated the involvement of other infidelity factors. The in vivo consequences of many additional Polε mutations reported in cancers remain poorly understood. Here, we genetically characterized 13 cancer-associated Polε variants in the yeast system. Only variants directly altering the DNA binding cleft in the exonuclease domain elevated the mutation rate. Among these, frequently recurring variants were stronger mutators than rare variants, in agreement with the idea that mutator phenotype has a causative role in tumorigenesis. In nearly all cases, the mutator effects exceeded those of an exonuclease-null allele, suggesting that mechanisms distinct from loss of proofreading may drive the genome instability in most ultramutated tumors. All mutator alleles were semidominant, supporting the view that heterozygosity for the polymerase mutations is sufficient for tumor development. In contrast to the DNA binding cleft alterations, peripherally located variants, including a highly recurrent V411L, did not significantly elevate mutagenesis. Finally, the analysis of Polε variants found in MMR-deficient tumors suggested that the majority cause no mutator phenotype alone but some can synergize with MMR deficiency to increase the mutation rate.

We present a new approach to constructing unconditional pseudorandom generators against classes of functions that involve computing a linear function of the inputs. We give an explicit construction of a pseudorandom generator that fools the discrete Fourier transforms of linear functions with seed-length that is nearly logarithmic (up to polyloglog factors) in the input size and the desired error parameter. Our result gives a single pseudorandom generator that fools several important classes of tests computable in logspace that have been considered in the literature, including halfspaces (over general domains), modular tests and combinatorial shapes. For all these classes, our generator is the first that achieves near logarithmic seed-length in both the input length and the error parameter. Getting such a seed-length is a natural challenge in its own right, which needs to be overcome in order to derandomize RL - a central question in complexity theory. Our construction combines ideas from a large body of prior work, ranging from a classical construction of [NN93] to the recent gradually increasing independence paradigm of [KMN11, CRSW13, GMRTV12], while also introducing some novel analytic machinery which might find other applications.

Given a finite set $X\subset \mathbb{R}^{d}$ and a binary linear classifier $c:\mathbb{R}^{d}\rightarrow\{0,1\}$ , how many queries of the form $c(x)$ are required to learn the label of every point in $X$ ? Known as point location, this problem has inspired over 35 years of research in the pursuit of an optimal algorithm. Building on the prior work of Kane, Lovett, and Moran (ICALP 2018), we provide the first nearly optimal solution, a randomized linear decision tree of depth $\tilde{O}(d\log(\vert X\vert))$ , improving on the previous best of $\tilde{O}(\overline{d}^{2}\log(\vert X\vert))$ from Ezra and Sharir (Discrete and Computational Geometry, 2019). As a corollary, we also provide the first nearly optimal algorithm for actively learning halfspaces in the membership query model. En route to these results, building on the work of Carlen, Lieb, and Loss (J. Geometric Analysis 2004), as well as Dvir, Saraf, and Wigderson (STOC 2014), we prove a novel characterization of Barthe's Theorem (Inventiones Mathematicae, 1998) of independent interest. In particular, we show that $X$ may be transformed into approximate isotropic position if and only if there exists no $k$ -dimensional subspace with more than a $k/d$ -fraction of $X$ , and provide a similar characterization for exact isotropic position. The below is an extended abstract. The full work can be found at https://arxiv.org/abs/2004.11380

In this work we report on the development of a system for measuring single shot ultrafast laser pulses with a bandwidth greater than 2 THz at 1550 nm. The hybrid optical and electronic system is capable of measurement rates up to greater than 1 MHz. The process is all linear, and single pulses from a mode-locked Erbium fiber laser are characterized.

The degree-d Chow parameters of a Boolean function are its degree at most d Fourier coefficients. It is well-known that degree-d Chow parameters uniquely characterize degree-d polynomial threshold functions (PTFs) within the space of all bounded functions. In this paper, we prove a robust version of this theorem: For f any Boolean degree-d PTF and g any bounded function, if the degree-d Chow parameters of f are close to the degree-d Chow parameters of g in l2-norm, then f is close to g in l1-distance. Notably, our bound relating the two distances is independent of the dimension. That is, we show that Boolean degree-d PTFs are robustly identifiable from their degree-d Chow parameters. No non-trivial bound was previously known for d >1. Our robust identifiability result gives the following algorithmic applications: First, we show that Boolean degree-d PTFs can be efficiently approximately reconstructed from approximations to their degree-d Chow parameters. This immediately implies that degree-d PTFs are efficiently learnable in the uniform distribution d-RFA model. As a byproduct of our approach, we also obtain the first low integer-weight approximations of degree-d PTFs, for d>1. As our second application, our robust identifiability result gives the first efficient algorithm, with dimension-independent error guarantees, for malicious learning of Boolean degree-d PTFs under the uniform distribution. The proof of our robust identifiability result involves several new technical ingredients, including the following structural result for degree-d multivariate polynomials with very poor anti-concentration: If p is a degree-d polynomial where p(x) is very close to 0 on a large number of points in { ± 1 }n, then there exists a degree-d hypersurface that exactly passes though almost all of these points. We leverage this structural result to show that if the degree-d Chow distance between f and g is small, then we can find many degree-d polynomials that vanish on their disagreement region, and in particular enough that forces the l1-distance between f and g to also be small. To implement this proof strategy, we require additional technical ideas. In particular, in the d=2 case we show that for any large vector space of degree-2 polynomials with a large number of common zeroes, there exists a linear function that vanishes on almost all of these zeroes. The degree-d degree generalization of this statement is significantly more complex, and can be viewed as an effective version of Hilbert’s Basis Theorem for our setting.

Optical microscopy and spectroscopy are widely used in multiple research areas relating to biology. Label-free spectroscopy and imaging are valuable tools that permit interrogation of biological samples without the need for exogenous labels, allowing for investigation of unperturbed biological systems. We demonstrate a coherent Raman technique called Doppler Raman (DR) spectroscopy which combines impulsive excitation with a novel frequency shift detection scheme for rapid, high sensitivity detection of low to medium frequency vibrational modes from 10-1800cm-1. Briefly, the DR spectroscope is a pump-probe system where the pump beam generates a time-varying index of refraction proportional to the Raman response of the sample. The time-delayed probe beam undergoes a frequency shift in the sample due to the time-varying index of refraction that is resolved using a novel high-sensitivity detection scheme. Other coherent Raman techniques such as Stimulated Raman Scattering (SRS) and Coherent Anti-Stokes Raman Spectroscopy (CARS) have been used to provide sensitive, label-free contrast for an array of biological targets, but their ability to detect low frequency vibrational modes is limited. Biologically significant targets like cytochrome c (740-760cm-1), DNA (782, 788, 1095cm-1), hydroxyapatite, and numerous pharmaceutical drugs exhibit rich Raman spectra across a range of low frequency modes below the well-known “fingerprint region”. Additionally, many proteins like hemoglobin, insulin, and bovine serum albumin have breathing modes below 50cm-1. Sensitive detection of low-frequency Raman vibrational modes unlocks a suite of potential biological and chemical dynamics like protein conformational changes and protein super complex formation.

Higher levels of soil organic matter improve soil water retention, meaning they could mitigate agricultural yield losses from drought. Yet evidence to support such claims is mixed and incomplete. Using data from 12 376 county-years in the United States of America, we show that counties with higher soil organic matter are associated with greater yields, lower yield losses, and lower rates of crop insurance payouts under drought. Under severe drought, an increase of 1% soil organic matter was associated with a yield increase of 2.2 ± 0.33 Mg ha−1 (32.7 bu ac−1) and a 36 ± 4.76% reduction in the mean proportion of liabilities paid. Similar, yet smaller, effects were found for less severe levels of drought and this effect was reduced as soil clay content increased. Confirmatory pathway analyses indicate that this positive association of soil organic matter and yields under drought is partially explained by positive effects of soil organic matter on available water capacity and cation exchange capacity, but that soil organic matter may be imparting yield protection via mechanisms not fully captured by those metrics. Overall, our results suggest soil organic matter predicts yield resilience at regional scales in the United States. We argue that data on soil organic matter should be used in agricultural policy and financial planning, with our analyses providing quantitative evidence of the co-benefits of soil organic matter believed fundamental to advancing soil health and carbon sequestration initiatives.

We study the variation of the φ-Selmer groups of the elliptic curvesy2=x3−Dxunder quartic twists by square-free integers. We obtain a complete description of the distribution of the size of this group when the integerDis constrained to lie in a family for which the relative Tamagawa number of the isogeny φ is fixed.

Managing the soil nitrogen (N) cycle is a major component of agricultural sustainability. Soil functional zone management (zonal management) is a novel agroecological strategy for managing row-crop agroecosystems. It may improve the efficiency of soil N cycling compared with conventional and no-tillage approaches, by managing the timing and location (crop row vs inter-row) of key soil N cycling processes. We compared N mineralization and availability during the period of maize peak N demand in crop rows and inter-rows in zonal management and conventional chisel plow tillage systems at four sites across the US Corn Belt over three growing seasons. Under zonal management, potential N mineralization and N availability during crop peak N demand were significantly greater in crop rows, where the majority of crop roots are found, compared with inter-rows. Averaged across all site-years, plant-available N in zonal management crop rows was 46 mg kg −1 compared with 21 mg kg −1 in inter-rows. In contrast, in conventional tillage, potential N mineralization and N availability were greater in inter-rows compared with crop rows; averaged across all site-years, plant-available N in conventional tillage crop rows was 24 mg kg −1 compared with 51 mg kg −1 in inter-rows. The results demonstrate that the active management of crop residues under zonal management can enhance the spatiotemporal efficiency of soil N cycling processes, by concentrating N mineralization and availability close to crop roots in synchrony with crop developmental needs. Zonal management therefore has potential to increase crop N-use efficiency compared with conventional tillage, and thereby reduce the impacts of row-crop agricultural production on water resources and greenhouse gas emissions that result from N leaching and denitrification.

Zonal tillage (e.g. ridge tillage, RT) separates management of row and inter-row positions, while non-zonal tillage (e.g. chisel plough, CP) applies management uniformly across a field. This may have large effects on soil hydrothermal properties, affecting soil processes and crop development. We examined the effects of RT versus CP on soil hydrothermal conditions under maize (Zea mays L.) at four sites spanning the US Corn Belt over two growing seasons (2012–2013). We also investigated whether RT, as a result of changes in hydrothermal conditions, could stimulate greater soil nitrogen (N) availability during peak maize N demand. We captured wide variation in soil types and climates, allowing us to generalise tillage effects across a large environmental gradient. Continuous hydrothermal measurements were taken in the centre of row and inter-row positions. Soil cores collected shortly after maize six leaf stage (V6) were analysed for plant-available N and potentially mineralisable N (PMN). We hypothesised: 1) in spring CP and RT both produce warm, dry seedbeds with equivalent accumulations of growing degree days (GDD), but later in season RT holds greater soil moisture, providing better conditions for cover or relay crop establishment; 2) Hydrothermal properties of RT rows are distinct from RT inter-rows, while CP rows and inter-rows are indistinguishable; 3) RT promotes greater soil N mineralisation and availability in crop rows compared with CP. Results largely confirmed all hypotheses. In early spring, rows were drier in RT than CP, and both were similar in warmth (i.e. in accumulated GDD). From V6 to tasselling, CP accumulated more GDD than RT in inter-rows, while row positions remained similar; RT maintained greater soil moisture across both positions. From tasselling to harvest, RT inter-rows held greater soil moisture than CP, but accumulated fewer GDD. Both tillage systems showed zonation of soil moisture between planting and harvest (inter-rows moister than rows); the magnitude of zonation was greatest in RT. Plant-available N and PMN were greater in RT compared with CP at V6, suggesting RT increases synchrony of soil N availability with crop requirements. The results demonstrate that zonal tillage can integrate the seedbed benefits of conventional tillage with increased soil moisture retention across a wide range of climates and soil types. Increased moisture retention may help buffer agricultural systems against drought, and improve seedbed conditions for cover and relay crops in late summer and early autumn, thus potentially improving both sustainability and production in these systems.

We introduce a method to enable optical amplification of a coherent Raman spectroscopy signal, which we call radio frequency (RF) Doppler Raman spectroscopy. In this article, we consider the perturbation of a probe pulse in a sample due to an excited Raman vibrational coherence as a generalized Doppler shift, which connects a time-varying optical path length (the product of the propagation length and refractive index, OPL = n ℓ) with an optical frequency shift. Amplification of a Raman signal outside of the focused interaction is enabled by converting the Doppler frequency shift experienced by a laser probe pulse into a periodic timing jitter. This transit time perturbation is detected through the phase of a RF electronic signal measured at a harmonic of the probe pulse train with a method adapted from precision metrology techniques used to measure laser pulse train timing jitter. Measurement of a timing jitter allows access to much lower noise floors than other coherent Raman techniques, and by exploiting the new capability to scale the signal of a coherent Raman spectroscopic signal, this method opens the potential to detect very weak Raman signals that are currently not observable due to limits of illumination intensity imposed by laser damage to the specimen and noise.

International audience; Quinone reductase 2 (QR2, E.C. 1.10.5.1) is an enzyme with a feature that has attracted attention for several decades: in standard conditions, instead of recognizing NAD(P)H as an electron donor, it recognizes putative metabolites of NADH, such as N-methyl- and N-ribosyl-dihydronicotinamide. QR2 has been particularly associated with reactive oxygen species and memory, strongly suggesting a link among QR2 (as a possible key element in pro-oxidation), autophagy, and neurodegeneration. In molecular and cellular pharmacology, understanding physiopathological associations can be difficult because of a lack of specific and powerful tools. Here, we present a thorough description of the potent, nanomolar inhibitor [2-(2-methoxy-5H-1,4b,9-triaza(indeno[2,1-a]inden-10-yl)ethyl]-2-furamide (S29434 or NMDPEF; IC50 = 5-16 nM) of QR2 at different organizational levels. We provide full detailed syntheses, describe its cocrystallization with and behavior at QR2 on a millisecond timeline, show that it penetrates cell membranes and inhibits QR2-mediated reactive oxygen species (ROS) production within the 100 nM range, and describe its actions in several in vivo models and lack of actions in various ROS-producing systems. The inhibitor is fairly stable in vivo, penetrates cells, specifically inhibits QR2, and shows activities that suggest a key role for this enzyme in different pathologic conditions, including neurodegenerative diseases.

Maximally recoverable codes are codes designed for distributed storage which combine quick recovery from single node failure and optimal recovery from catastrophic failure. Gopalan et al. [Maximally recoverable codes for grid-like topologies, in Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, Philadelphia, 2017, pp. 2092-2108] studied the alphabet size needed for such codes in grid topologies and gave a combinatorial characterization for it. Consider a labeling of the edges of the complete bipartite graph Kn, n, with labels coming from Fd2 that satisfies the following condition: for any simple cycle, the sum of the labels over its edges is nonzero. The minimal d where this is possible controls the alphabet size needed for maximally recoverable codes in n × n grid topologies. Prior to the current work, it was known that d is between (log n)2 and n log n. We improve both bounds and show that d is linear in n. The upper bound is a recursive construction which beats the random construction. The lower bound follows by first relating the problem to the independence number of the Birkhoff polytope graph, and then providing tight bounds for it using the representation theory of the symmetric group.

A natural number is a binary k’ th power if its binary representation consists of k consecutive identical blocks. We prove, using tools from combinatorics, linear algebra, and number theory, an analogue of Waring’s theorem for sums of binary k’th powers. More precisely, we show that for each integer k> 2, there exists an effectively computable natural number n such that every sufficiently large multiple of Ek:=gcd(2k - 1,k) is the sum of at most n binary k’th powers. (The hypothesis of being a multiple of Ek cannot be omitted, since we show that the gcd of the binary k’th powers is Ek.) Furthermore, we show that n = 2O(k3). Analogous results hold for arbitrary integer bases b>2.

We present Doppler Raman, a novel detection technique for coherent Raman scattering microscopy that offers improved sensitivity and readily detects low frequency modes from 10cm−1 to 1500cm−1, for use in studying label-free biological systems.

Alterations in the exonuclease domain of DNA polymerase ε (Polε) cause ultramutated tumors. Severe mutator effects of the most common variant, Polε-P286R, modeled in yeast suggested that its pathogenicity involves yet unknown mechanisms beyond simple proofreading deficiency. We show that, despite producing a catastrophic amount of replication errors in vivo, the yeast Polε-P286R analog retains partial exonuclease activity and is more accurate than exonuclease-dead Polε. The major consequence of the arginine substitution is a dramatically increased DNA polymerase activity. This is manifested as a superior ability to copy synthetic and natural templates, extend mismatched primer termini, and bypass secondary DNA structures. We discuss a model wherein the cancer-associated substitution limits access of the 3’-terminus to the exonuclease site and promotes binding at the polymerase site, thus stimulating polymerization. We propose that the ultramutator effect results from increased polymerase activity amplifying the contribution of Polε errors to the genomic mutation rate., Somatic alterations in the exonuclease domain of DNA polymerase ɛ have been linked to the development of highly mutated cancers. Here, the authors report that a major consequence of the most common cancer-associated Polɛ variant is a dramatically increased DNA polymerase activity.

We study high-dimensional distribution learning in an agnostic setting where an adversary is allowed to arbitrarily corrupt an $\varepsilon$-fraction of the samples. Such questions have a rich hist...

Background Inadequate clinical skills are a significant problem of present day medical education.1Simulation Based Education (SBE) is playing an increasingly important role in healthcare training worldwide to teach invasive procedures. This works aims to evaluate the retention levels of procedural skills taught and assessed by SBE and what re-training is required to restore decayed performance. This study also investigates how skilled performance decays over time and whether certain dimensions of clinical skills are more likely to decay. Summary of education programme A mastery learning approach, using SBE, was employed to teach clinical skills to 3rd and 4th year medical students. Pre course video/procedural guides are provided online asynchronously which students can repeatedly access. 7 skills were taught over 2 years using task trainers. Following a demonstration, students practiced in small groups with tutor facilitated supervision and peer support prior to formal testing. Score sheets with itemised procedure checklists detailing the minimum passing standard (MPS) for each skill were used for assessment. The program provides the necessary educational experiences for self-directed repetitive clinical skill practice that is required to reach competency and remediation when necessary. Unannounced tests to demonstrate proficiency in the skills were completed in the final year by 51 students. Results 55% of the students were deficit in 3 or more skills and 4% were not competent in 5 or more skills. Students were asked by questionnaire how many times and where they had practiced/performed the techniques. A significant number had never practiced some skills. A relationship was noted with the number of time students self-declared that they had practiced and their performance. Discussion, conclusions and recommendations This study attempts to define what procedural skill performance look like at fixed periods of time elapse in an undergraduate medical program. Decay is evident in both psycho-motor and cognitive domains of the skills. Deliberate practice of clinical skills, under supervision of an engaged instructor, is a key component of the mastery model.2 Experiences and assessments in the clinical setting need to be augmented with particular focus on direct observation and focused feedback to reinforce the skills acquired in the simulated setting. References Birdane A, Yazici HU, Aydar Y, et al. Effectiveness of cardiac simulator on the acquirement of cardiac auscultatory skills of medical students. Adv Clin Exp Med2012;21(6):791–8. Ericsson KA. Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Acad Med2004;79(suppl 10):S70–S81.