cssi/SciSciGPT-SciSciNet huggingface dataset:
Genetic and environmental influences on pubertal hormones in human hair across development.

Abstract Puberty is a complex biopsychosocial process that can affect an array of psychiatric and medical disorders emerging in adolescence. Although the pubertal process is driven by neuroendocrine changes, few quantitative genetic studies have directly measured puberty-relevant hormones. Hair samples can now be assayed for accumulation of hormones over several months. In contrast to more conventional salivary measures, hair measures are not confounded by diurnal variation or hormonal reactivity. In an ethnically and socioeconomically diverse sample of 1286 child and adolescent twins and multiples from 672 unique families, we estimated genetic and environmental influences on hair concentrations of testosterone, DHEA, and progesterone across the period of 8–18 years of age. On average, male DHEA and testosterone were highly heritable, whereas female DHEA, progesterone, and puberty were largely influenced by environmental components. We identified sex-specific developmental windows of maximal heritability in each hormone. Peak heritability for DHEA occurred at approximately 10 years of age for males and females. Peak heritability for testosterone occurred at age 12.5 and 15.2 years for males and females, respectively. Peak heritability for male progesterone occurred at 11.2 years, while the heritability of female progesterone remained uniformly low. The identification of specific developmental windows when genetic signals for hormones are maximized has critical implications for well-informed models of hormone-behavior associations in childhood and adolescence.
Spiking resonances in models with the same slow resonant and fast amplifying currents but different subthreshold dynamic properties

The generation of spiking resonances in neurons (preferred spiking responses to oscillatory inputs) requires the interplay of the intrinsic ionic currents that operate at the subthreshold voltage level and the spiking mechanisms. Combinations of the same types of ionic currents in different parameter regimes may give rise to different types of nonlinearities in the voltage equation (e.g., parabolic- and cubic-like), generating subthreshold (membrane potential) oscillations patterns with different properties. These nonlinearities are not apparent in the model equations, but can be uncovered by plotting the voltage nullclines in the phase-plane diagram. We investigate the spiking resonant properties of conductance-based models that are biophysically equivalent at the subthreshold level (same ionic currents), but dynamically different (parabolic- and cubic-like voltage nullclines). As a case study we consider a model having a persistent sodium and a hyperpolarization-activated (h-) currents, which exhibits subthreshold resonance in the theta frequency band. We unfold the concept of spiking resonance into evoked and output spiking resonance. The former focuses on the input frequencies that are able to generate spikes, while the latter focuses on the output spiking frequencies regardless of the input frequency that generated these spikes. A cell can exhibit one or both types of resonances. We also measure spiking phasonance, which is an extension of subthreshold phasonance (zero-phase-shift response to oscillatory inputs) to the spiking regime. The subthreshold resonant properties of both types of models are communicated to the spiking regime for low enough input amplitudes as the voltage response for the subthreshold resonant frequency band raises above threshold. For higher input amplitudes evoked spiking resonance is no longer present in these models, but output spiking resonance is present primarily in the parabolic-like model due to a cycle skipping mechanism (involving mixed-mode oscillations), while the cubic-like model shows a better 1:1 entrainment. We use dynamical systems tools to explain the underlying mechanisms and the mechanistic differences between the resonance types. Our results demonstrate that the effective time scales that operate at the subthreshold regime to generate intrinsic subthreshold oscillations, mixed-mode oscillations and subthreshold resonance do not necessarily determine the existence of a preferred spiking response to oscillatory inputs in the same frequency band. The results discussed in this paper highlight both the complexity of the suprathreshold responses to oscillatory inputs in neurons having resonant and amplifying currents with different time scales and the fact that the identity of the participating ionic currents is not enough to predict the resulting patterns, but additional dynamic information, captured by the geometric properties of the phase-space diagram, is needed.
Selection of Pairings Reaching Evenly Across the Data (SPREAD): A simple algorithm to design maximally informative fully crossed mating experiments

We present a novel algorithm for the design of crossing experiments. The algorithm identifies a set of individuals (a 'crossing-set') from a larger pool of potential crossing-sets by maximizing the diversity of traits of interest, for example, maximizing the range of genetic and geographic distances between individuals included in the crossing-set. To calculate diversity, we use the mean nearest neighbor distance of crosses plotted in trait space. We implement our algorithm on a real dataset of Neurospora crassa strains, using the genetic and geographic distances between potential crosses as a two-dimensional trait space. In simulated mating experiments, crossing-sets selected by our algorithm provide better estimates of underlying parameter values than randomly chosen crossing-sets.
Recomputing with Permuted Operands: A Concurrent Error Detection Approach.

Naturally occurring and maliciously injected faults reduce the reliability of cryptographic hardware and may leak confidential information. We develop a concurrent error detection (CED) technique called Recomputing with Permuted Operands (REPO). We show that it is cost effective in Advanced Encryption Standard (AES) and a secure hash function Grostl. We provide experimental results and formal proofs to show that REPO detects all single-bit and singlebyte faults. Experimental results show that REPO achieves close to 100% fault coverage for multiple byte faults. The hardware and throughput overheads are compared with those of previously reported CED techinques on two Xilinx Virtex FPGAs. The hardware overhead is 12.4-27.3%, and the throughput is 1.2-23Gbps, depending on the AES architecture, FPGA family, and detection latency. The performance overhead ranges from 10% to 100% depending on the security level. Moreover, the proposed technique can be integrated into various block cipher modes of operation. We also discuss the limitation of REPO and its potential vulnerabilities.
New syntheses of the C,D-ring pyrromethenones of phytochrome and phycocyanin.

Pyrromethenone 7, the C,D-ring segment of phytochrome (Pr, 4), has been prepared in an efficient fashion employing three new strategies. Each of these has potential advantages for the synthesis of labeled material. Our first approach is related to the Gossauer synthesis, with the difference that strong alkali is avoided in the condensation of the C- and D-ring components 8 and 17. The key silyloxypyrrole 17 was readily prepared on multigram scales beginning with inexpensive butyrolactone (10). A second synthesis began with 2-acetylbutyrolactone (41). The key steps involved conversion of 41 to the Z-enoltriflate 42, followed by Pd(0)-catalyzed coupling with trimethylsilylacetylene, p-chlorophenylselenide ring opening, and finally, amidation to afford the ring-D synthon 45 having the proper geometry and oxidation state for conversion to 7. Sonogashira coupling of 45 with the iodopyrrole 22, followed by oxidative elimination, and F--induced 5-exo-dig cyclization of the resultant pyrroloalkyne 47, then comple...
FastID: Extremely fast forensic DNA comparisons

Rapid analysis of DNA forensic samples can have a critical impact on time sensitive investigations. Analysis of forensic DNA samples by massively parallel sequencing is creating the next gold standard for DNA forensic analysis. This technology enables the expansion of forensic profiles from the current 20 short tandem repeat (STR) loci to tens of thousands of single nucleotide polymorphism (SNP) loci. A forensic search scales by the product of the number of loci and the number of profile comparisons. This paper introduces a method (FastID) to address the need for rapid scalable analysis of DNA forensic samples (patent pending)[1]. FastID can search a profile of 2,500 SNP loci against 20 million profiles in 5.08 seconds using a single computational thread on a laptop (Intel i7 4.0 GHz).
Heavier Main Group Dimetallene Reactivity: Effects of Frontier Orbital Symmetry

The major theme of this review concerns the reaction pathways of heavier main group 13 dimetallenes with olefins, cyclic olefins, polyolefins, other unsaturated molecules, and hydrogen. For gallium derivatives, these reactions proceed readily in high yield under ambient conditions. Early investigations showed that the group 13 dimetallenes dissociated to one-coordinate metallanediyl monomers, which suggested that they reacted as monomeric species due to their more open, less hindered structures. However, recent DFT calculations by Tuononen and co-workers show that the reaction of the monomers with olefins or hydrogen involves very large energy barriers and that the dimetallenes react instead as undissociated dimers. In contrast to the corresponding all-carbon systems, where [2 + 2] cycloadditions are forbidden because of π–π* symmetry mismatch, the dimetallenes react with olefins via two stepwise, symmetry-allowed [2 + 2] cycloadditions to give 1,4-digallacyclohexanes. The addition of the H2 proceeds by a...
Practical and Highly Selective Oxazolidinethione-Based Asymmetric Acetate Aldol Reactions with Aliphatic Aldehydes

The utility of a valine-derived oxazolidinethione for auxiliary-based asymmetric acetate aldol reactions is reported. Titanium(IV) chloride, along with (−)-sparteine and N-methylpyrrolidinone, is employed for enolization. Subsequent aldol reaction with aliphatic aldehydes occurs with high diastereoselectivity (from 92:8 to 99:1 dr).
Transcriptomic Profiling of High-Density Giardia Foci Encysting in the Murine Proximal Intestine.

Giardia is a highly prevalent, understudied protistan parasite causing significant diarrheal disease worldwide. Its life cycle consists of two stages: infectious cysts ingested from contaminated food or water sources, and motile trophozoites that colonize and attach to the gut epithelium, later encysting to form new cysts that are excreted into the environment. Current understanding of parasite physiology in the host is largely inferred from transcriptomic studies using Giardia grown axenically or in co-culture with mammalian cell lines. The dearth of information about the diversity of host-parasite interactions occurring within distinct regions of the gastrointestinal tract has been exacerbated by a lack of methods to directly and non-invasively interrogate disease progression and parasite physiology in live animal hosts. By visualizing Giardia infections in the mouse gastrointestinal tract using bioluminescent imaging (BLI) of tagged parasites, we recently showed that parasites colonize the gut in high-density foci. Encystation is also initiated in these foci throughout the entire course of infection, yet how the physiology of parasites within high-density foci in the host gut differs from that of cells in laboratory culture is unclear. Here we use BLI to precisely select parasite samples from high-density foci in the proximal intestine to interrogate in vivo Giardia gene expression in the host. Relative to axenic culture, we noted significantly higher expression (> 10-fold) of oxidative stress, membrane transporter, and metabolic and structural genes associated with encystation in the high-density foci. These differences in gene expression within parasite foci in the host may reflect physiological changes associated with high-density growth in localized regions of the gut. We also identified and verified six novel cyst-specific proteins, including new components of the cyst wall that were highly expressed in these foci. Our in vivo transcriptome data support an emerging view that parasites encyst early in localized regions in the gut, possibly as a consequence of nutrient limitation, and also impact local metabolism and physiology.
Nanoscale Heterogeneities and Oxygen Storage Capacity of Ce0.5Zr0.5O2

Nanocrystalline powders of Ce0.5Zr0.5O2 were synthesized and characterized for the application as a catalyst support and oxygen storage medium in automotive catalysis. Detailed pair-distribution function analysis of the neutron diffraction data revealed an unusual structure of the nanocrystallites, consisting of domains of Ce0.4Zr0.6O2 composition of ∼25−30 A in size in a matrix of Ce0.7Zr0.3O2. The domains cannot be detected by conventional diffraction analysis because the crystallographic structure and orientation of the atomic planes are the same for all ceria- and zirconia-enriched regions within the crystallite, which therefore gives rise to Bragg scattering as a whole. The oxygen storage capacity did not show a correlation with either crystallite size or surface area of the samples. We suggest that the smaller size of zirconia-enriched domains associated with larger interfacial area between ceria- and zirconia-enriched regions is responsible for the increase in oxygen storage capacity.
Halodeboronation of organotrifluoroborates using tetrabutylammonium tribromide or cesium triiodide

Abstract Halodeboronation of organotrifluoroborates using commercially available tetrabutylammonium tribromide (TBATB) or cesium triiodide in aqueous medium is reported. The mild, transition metal-free method has proven to be tolerant of a wide range of functional groups. High regio- and chemoselectivity are observed. Two synthetic routes to (Z)-dibromoalkenes from alkynes, through stereodefined (Z)-2-bromoalkenyltrifluoroborates and (Z)-1,2-bis(boryl)alkenyltrifluoroborates, have been developed using the TBATB mediated bromodeboronation as the key step.
AN INTRAMOLECULAR RADICAL APPROACH TO ANGULAR ELECTROPHORES IN POLYCYCLIC SYSTEMS

Abstract The introduction of an angular C-8 cyano group in polycyclic system 9 has been realized via a stereoselective oxidative radical cyclization of polyene 8 containing an α,β-unsaturated electrophore.
Harnessing a P450 fatty acid decarboxylase from Macrococcus caseolyticus for microbial biosynthesis of odd chain terminal alkenes

Alkenes are industrially important platform chemicals with broad applications. In this study, we report a direct microbial biosynthesis of terminal alkenes from fermentable sugars by harnessing a P450 fatty acid (FA) decarboxylase from Macrococcus caseolyticus (OleTMC). We first characterized OleTMC and demonstrated its in vitro H2O2-independent activities towards linear C10:0-C18:0 FAs, with higher activity for C16:0-C18:0 FAs. Next, we engineered a de novo alkene biosynthesis pathway, consisting of OleTMC and an engineered E. coli thioesterase (TesA) with compatible substrate specificities, and introduced this pathway into E. coli for terminal alkene biosynthesis from glucose. The recombinant E. coli EcNN101 produced a total of 17.78 ± 0.63 mg/L odd-chain terminal alkenes, comprising of 0.9% ± 0.5% C11 alkene, 12.7% ± 2.2% C13 alkene, 82.7% ± 1.7% C15 alkene, and 3.7% ± 0.8% C17 alkene, and a yield of 0.87 ± 0.03 (mg/g) on glucose. To improve alkene production, we identified and overcame the electron transfer limitation in OleTMC, by introducing a two-component redox system, consisting of a putidaredoxin reductase (CamA) and a putidaredoxin (CamB) from Pseudomonas putida, into EcNN101, and demonstrated the alkene production increased ~2.8 fold. Finally, to better understand the substrate specificities of OleTMC observed, we employed in silico protein modeling to illuminate the functional role of FA binding pocket.
Thiophenes in Organotransition Metal Chemistry: Patterns of Reactivity

Thiophenes, including benzothiophenes and dibenzothiophenes, undergo a variety of reactions with transition metal complexes that lead to products in which the thiophene is partially reduced or cleaved at a C−S bond. The specific types of reactivity depend on the modes of thiophene coordination to the metal, which in turn depend on the particular metal and its associated ligands. It is the intent of this review to organize these numerous reactions of thiophenes into categories that illustrate distinct patterns of reactivity. It is hoped that an understanding of such patterns will stimulate the use of thiophene−organotransition metal chemistry in synthetic organic chemistry.
The synthesis of 4‐benzylamino‐6‐methyl‐1H‐pyrrolo[3, 2‐c]pyridine and 4‐benzylamino‐6‐methyl‐1H‐pyrrolo[2, 3‐b]pyridine

4-Benzylamino-6-methyl-1H-pyrrolo[3,2-c]pyridine (2) and 4-benzylamino-6-methyl-1H-pyrrolo[2,3-b]pyridine (3) were synthesized as deaza analogues of the anxiolytic agent 4-benzylamino-2-methyl-7H-pyrrolo[2,3-d]pyrimidine (1). The 1-deaza analogue (2) was prepared via a multi-step procedure from a pyrrole precursor, 1-benzyl-2-formylpyrrole (4) while the 3-deaza analogue 3 was synthesized from a pyridine precursor, 2-amino-3,6-dimethylpyridine (12).
Exfoliated and Restacked MoS2 and WS2: Ionic or Neutral Species? Encapsulation and Ordering of Hard Electropositive Cations

The relationship between charge and structure in restacked MS2 (M = Mo, W) has been probed by cation encapsulation and chemical oxidation and characterized by elemental analysis, electron diffracti...
Transition metal free reductive dimerization of nitrogen containing barbituric acid benzylidenes

Through the NMR monitoring of the reactive intermediates in the condensation of barbituric acid with nitrogen containing heterocyclic 2-carboxaldehydes, a synthetic procedure was developed for the preparation of each of the intermediates. The simple high yield procedure for the preparation of the reductive dimer from corresponding barbituric acid benzylidenes was developed, although we were not able to elucidate the source of the reduction. The structure of the dimer was confirmed by X-ray analysis.
Dining out as cultural trade

Perceptions of Anglo-American dominance in movie and music trade motivate restrictions on cultural trade. Yet, the market for another cultural good, food at restaurants, is roughly ten times larger than the markets for music and film. Using TripAdvisor data on restaurant cuisines, along with Euromonitor data on overall and fast-food expenditure, this paper calculates implicit trade patterns in global cuisines for 52 destination countries. We obtain four results. First, the pattern of cuisine trade resembles the “gravity” patterns in physically traded products. Second, after accounting gravity factors, the most popular cuisines are Italian, Japanese, Chinese, Indian, and American. Third, excluding fast food, the largest net exporters of their cuisines are the Italians and the Japanese, while the largest net importers are the USA—with a 2015 deficit of over $140 billion—followed by Brazil, China, and the UK. With fast food included, the US deficit shrinks to $55 billion but remains the largest net importer along with China and, to a lesser extent, the UK and Brazil. Fourth, cuisine trade patterns more closely resemble migration patterns than patterns of food trade or patterns arising from the extent of arable land in origin countries. Cuisine trade patterns run starkly counter to the audiovisual patterns that have motivated concern about Anglo-American cultural dominance.
Applicability of drug response metrics for cancer studies using biomaterials.

Bioengineers have built models of the tumour microenvironment (TME) in which to study cell–cell interactions, mechanisms of cancer growth and metastasis, and to test new therapies. These models all...
Telomeric small RNAs in the genus Caenorhabditis .

Telomeric DNA is composed of simple tandem repeat sequences and has a G-rich strand that runs 5' to 3' toward the chromosome terminus. Small RNAs with homology to telomeres have been observed in several organisms and could originate from telomeres or from interstitial telomere sequences (ITSs), which are composites of degenerate and perfect telomere repeat sequences found on chromosome arms. We identified Caenorhabditis elegans small RNAs composed of the Caenorhabditis telomere sequence (TTAGGC)n with up to three mismatches, which might interact with telomeres. We rigorously defined ITSs for genomes of C. elegans and for two closely related nematodes, Caenorhabditis briggsae and Caenorhabditis remanei Most telomeric small RNAs with mismatches originated from ITSs, which were depleted from mRNAs but were enriched in introns whose genes often displayed hallmarks of genomic silencing. C. elegans small RNAs composed of perfect telomere repeats were very rare but their levels increased by several orders of magnitude in C. briggsae and C. remanei Major small RNA species in C. elegans begin with a 5' guanine nucleotide, which was strongly depleted from perfect telomeric small RNAs of all three Caenorhabditis species. Perfect G-rich or C-rich telomeric small RNAs commonly began with 5' UAGGCU and 5' UUAGGC or 5' CUAAGC, respectively. In contrast, telomeric small RNAs with mismatches had a mixture of all four 5' nucleotides. We suggest that perfect telomeric small RNAs have a mechanism of biogenesis that is distinct from known classes of small RNAs and that a dramatic change in their regulation occurred during recent Caenorhabditis evolution.
On the powers of the descent set statistic

Abstract We study the sum of the rth powers of the descent set statistic and how many small prime factors occur in these numbers. Our results depend upon the base p expansion of n and r.
Minimization of Transformed $L_1$ Penalty: Theory, Difference of Convex Function Algorithm, and Robust Application in Compressed Sensing

We study the minimization problem of a non-convex sparsity promoting penalty function, the transformed $$l_1$$ (TL1), and its application in compressed sensing (CS). The TL1 penalty interpolates $$l_0$$ and $$l_1$$ norms through a nonnegative parameter $$a \in (0,+\infty )$$ , similar to $$l_p$$ with $$p \in (0,1]$$ , and is known to satisfy unbiasedness, sparsity and Lipschitz continuity properties. We first consider the constrained minimization problem, and discuss the exact recovery of $$l_0$$ norm minimal solution based on the null space property (NSP). We then prove the stable recovery of $$l_0$$ norm minimal solution if the sensing matrix A satisfies a restricted isometry property (RIP). We formulated a normalized problem to overcome the lack of scaling property of the TL1 penalty function. For a general sensing matrix A, we show that the support set of a local minimizer corresponds to linearly independent columns of A. Next, we present difference of convex algorithms for TL1 (DCATL1) in computing TL1-regularized constrained and unconstrained problems in CS. The DCATL1 algorithm involves outer and inner loops of iterations, one time matrix inversion, repeated shrinkage operations and matrix-vector multiplications. The inner loop concerns an $$l_1$$ minimization problem on which we employ the Alternating Direction Method of Multipliers. For the unconstrained problem, we prove convergence of DCATL1 to a stationary point satisfying the first order optimality condition. In numerical experiments, we identify the optimal value $$a=1$$ , and compare DCATL1 with other CS algorithms on two classes of sensing matrices: Gaussian random matrices and over-sampled discrete cosine transform matrices (DCT). Among existing algorithms, the iterated reweighted least squares method based on $$l_{1/2}$$ norm is the best in sparse recovery for Gaussian matrices, and the DCA algorithm based on $$l_1$$ minus $$l_2$$ penalty is the best for over-sampled DCT matrices. We find that for both classes of sensing matrices, the performance of DCATL1 algorithm (initiated with $$l_1$$ minimization) always ranks near the top (if not the top), and is the most robust choice insensitive to the conditioning of the sensing matrix A. DCATL1 is also competitive in comparison with DCA on other non-convex penalty functions commonly used in statistics with two hyperparameters.
Review of Cyber-Physical Attacks and Counter Defense Mechanisms for Advanced Metering Infrastructure in Smart Grid

The Advanced Metering Infrastructure (AMI) is a vital element in the current development of the smart grid. AMI technologies provide electric utilities with an effective way of continuous monitoring and remote control of smart grid components. However, owing to its increasing scale and cyber-physical nature, the AMI has been faced with security threats in both cyber and physical domains. This paper provides a comprehensive review of the crucial cyber-physical attacks and counter defense mechanisms in the AMI. First, two attack surfaces are surveyed in the AMI including the communication network and smart meters. The potential cyber-physical attacks are then reviewed for each attack surface. Next, the attack models and their cyber and physical impacts on the smart grid are studied for comparison. Counter defense mechanisms that help mitigate these security threats are discussed. Finally, several mathematical tools which may help in analysis and implementation of security solutions are summarized.
A clustering approach for detecting implausible observation values in electronic health records data.

Identifying implausible clinical observations (e.g., laboratory test and vital sign values) in Electronic Health Record (EHR) data using rule-based procedures is challenging. Anomaly/outlier detection methods can be applied as an alternative algorithmic approach to flagging such implausible values in EHRs. The primary objectives of this research were to develop and test an unsupervised clustering-based anomaly/outlier detection approach for detecting implausible observations in EHR data as an alternative algorithmic solution to the existing procedures. Our approach is built upon two underlying hypotheses that, (i) when there are large number of observations, implausible records should be sparse, and therefore (ii) if these data are clustered properly, clusters with sparse populations should represent implausible observations. To test these hypotheses, we applied an unsupervised clustering algorithm to EHR observation data on 50 laboratory tests from Partners HealthCare. We tested different specifications of the clustering approach and computed confusion matrix indices against a set of silver-standard plausibility thresholds. We compared the results from the proposed approach with conventional anomaly detection (CAD) approaches, including standard deviation and Mahalanobis distance. We found that the clustering approach produced results with exceptional specificity and high sensitivity. Compared with the conventional anomaly detection approaches, our proposed clustering approach resulted in significantly smaller number of false positive cases. Our contributions include (i) a clustering approach for identifying implausible EHR observations, (ii) evidence that implausible observations are sparse in EHR laboratory test results, (iii) a parallel implementation of the clustering approach on i2b2 star schema, and (3) a set of silver-standard plausibility thresholds for 50 laboratory tests that can be used in other studies for validation. The proposed algorithmic solution can augment human decisions to improve data quality. Therefore, a workflow is needed to complement the algorithm’s job and initiate necessary actions that need to be taken in order to improve the quality of data.
SLAQ: quality-driven scheduling for distributed machine learning

Training machine learning (ML) models with large datasets can incur significant resource contention on shared clusters. This training typically involves many iterations that continually improve the quality of the model. Yet in exploratory settings, better models can be obtained faster by directing resources to jobs with the most potential for improvement. We describe SLAQ, a cluster scheduling system for approximate ML training jobs that aims to maximize the overall job quality. When allocating cluster resources, SLAQ explores the quality-runtime trade-offs across multiple jobs to maximize system-wide quality improvement. To do so, SLAQ leverages the iterative nature of ML training algorithms, by collecting quality and resource usage information from concurrent jobs, and then generating highly-tailored quality-improvement predictions for future iterations. Experiments show that SLAQ achieves an average quality improvement of up to 73% and an average delay reduction of up to 44% on a large set of ML training jobs, compared to resource fairness schedulers.
On the 'Semantics' of Differential Privacy: A Bayesian Formulation

Differential privacy is a definition of privacy for algorithms that analyze and publish information about statistical databases. It is often claimed that differential privacy provides guarantees against adversaries with arbitrary side information. In this paper, we provide a precise formulation of these guarantees in terms of the inferences drawn by a Bayesian adversary. We show that this formulation is satisfied by both epsilon-differential privacy as well as a relaxation known as (epsilon,delta)-differential privacy. Our formulation follows the ideas originally due to Dwork and McSherry. This paper is, to our knowledge, the first place such a formulation appears explicitly. The analysis of the relaxed definition is new to this paper, and provides some guidance for setting the delta parameter when using (epsilon,delta)-differential privacy.
A STRONG LAW FOR THE RATE OF GROWTH OF LONG LATENCY PERIODS IN CLOUD COMPUTING SERVICE

Cloud-computing shares a common pool of resources across customers at a scale that is orders of magnitude larger than traditional multi-user systems. Constituent physical compute servers are allocated multiple "virtual machines" (VM) to serve simultaneously. Each VM user should ideally be unaffected by others' demand. Naturally, this environment produces new challenges for the service providers in meeting customer expectations while extracting an efficient utilization from server resources. We study a new cloud service metric that measures prolonged latency or delay suffered by customers. We model the workload process of a cloud server and analyze the process as the customer population grows. The capacity required to ensure that average workload does not exceed a threshold over long segments is characterized. This can be used by cloud operators to provide service guarantees on avoiding long durations of latency. As part of the analysis, we provide a uniform large- deviation principle for collections of random variables that is of independent interest. Cloud computing is a paradigm shift of multiple orders of magnitude in the pursuit of extracting greater utilization of server resources while serving the computing needs of a large collection of customers. This has been made possible primarily by the concept of workload virtualization wherein individual users operate on virtual machines (VMs), each with modest resource requirements, and multiple VMs are served by a single large computing server. Cloud service providers achieve greater utilization by over-provisioning VMs on compute nodes, acting on the assumption that rarely will multiple customers simultaneously require large quantities of resources. The resources required over time by a user is a stochastic process, modeled here as a discrete-time moving-average (MA) process. We allow for a heterogeneous population of customers, where they are partitioned only by their statistical/stochastic behaviour but are considered equal in terms of priority of service. Service guarantees currently provided by cloud computing providers (Amazon Web Services' EC2 , Google's Web Toolkit, Microsoft's Azure etc.) are weak: Service Level Agreements (SLAs) are available only for quick initial provisioning of a new VM from a user onto a compute node, but no guarantees are provided on the quality of service experienced by the customer over time. Large organizations with significant computing requirements, who are willing to pay for good service guarantees, are thus wary of using this architecture for any activity beyond their non-critical desktop usage;
Belief propagation for structured decision making

Variational inference algorithms such as belief propagation have had tremendous impact on our ability to learn and use graphical models, and give many insights for developing or understanding exact and approximate inference. However, variational approaches have not been widely adoped for decision making in graphical models, often formulated through influence diagrams and including both centralized and decentralized (or multi-agent) decisions. In this work, we present a general variational framework for solving structured cooperative decision-making problems, use it to propose several belief propagation-like algorithms, and analyze them both theoretically and empirically.
The two-parameter free unitary Segal–Bargmann transform and its Biane–Gross–Malliavin identification

Abstract Motivated by a conditional expectation interpretation of the Segal–Bargmann transform, we derive the integral kernel for the large- N limit of the two-parameter Segal–Bargmann–Hall transform over the unitary group U ( N ) , and explore its limiting behavior. We also extend the notion of circular systems to more general elliptic systems , in order to give an alternate construction of our new two-parameter free unitary Segal–Bargmann–Hall transform via a Biane–Gross–Malliavin type theorem.
Maximum Likelihood Estimation for Learning Populations of Parameters

Consider a setting with $N$ independent individuals, each with an unknown parameter, $p_i \in [0, 1]$ drawn from some unknown distribution $P^\star$. After observing the outcomes of $t$ independent Bernoulli trials, i.e., $X_i \sim \text{Binomial}(t, p_i)$ per individual, our objective is to accurately estimate $P^\star$. This problem arises in numerous domains, including the social sciences, psychology, health-care, and biology, where the size of the population under study is usually large while the number of observations per individual is often limited. Our main result shows that, in the regime where $t \ll N$, the maximum likelihood estimator (MLE) is both statistically minimax optimal and efficiently computable. Precisely, for sufficiently large $N$, the MLE achieves the information theoretic optimal error bound of $\mathcal{O}(\frac{1}{t})$ for $t < c\log{N}$, with regards to the earth mover's distance (between the estimated and true distributions). More generally, in an exponentially large interval of $t$ beyond $c \log{N}$, the MLE achieves the minimax error bound of $\mathcal{O}(\frac{1}{\sqrt{t\log N}})$. In contrast, regardless of how large $N$ is, the naive "plug-in" estimator for this problem only achieves the sub-optimal error of $\Theta(\frac{1}{\sqrt{t}})$.
Curvature of Hypergraphs via Multi-Marginal Optimal Transport

We introduce a novel definition of curvature for hypergraphs, a natural generalization of graphs, by introducing a multi-marginal optimal transport problem for a naturally defined random walk on the hypergraph. This curvature, termed coarse scalar curvature, extends a recent definition of Ricci curvature for Markov chains on metric spaces by Ollivier [Journal of Functional Analysis 256 (2009) 810–864], and is related to the scalar curvature when the hypergraph arises naturally from a Riemannian manifold. We investigate basic theoretical properties of the coarse scalar curvature and obtain several bounds. Empirical experiments demonstrate that coarse scalar curvatures detects “bridges” across connected components in hypergraphs, akin to the behavior of coarse Ricci curvatures on graphs.
Error Sensitivity to Environmental Noise in Quantum Circuits for Chemical State Preparation

Calculating molecular energies is likely to be one of the first useful applications to achieve quantum supremacy, performing faster on a quantum than a classical computer. However, if future quantum devices are to produce accurate calculations, errors due to environmental noise and algorithmic approximations need to be characterized and reduced. In this study, we use the high performance qHiPSTER software to investigate the effects of environmental noise on the preparation of quantum chemistry states. We simulated 18 16-qubit quantum circuits under environmental noise, each corresponding to a unitary coupled cluster state preparation of a different molecule or molecular configuration. Additionally, we analyze the nature of simple gate errors in noise-free circuits of up to 40 qubits. We find that, in most cases, the Jordan–Wigner (JW) encoding produces smaller errors under a noisy environment as compared to the Bravyi–Kitaev (BK) encoding. For the JW encoding, pure dephasing noise is shown to produce subs...
A bijective proof of Amdeberhan’s conjecture on the number of (s,s+2)-core partitions with distinct parts

Abstract Amdeberhan conjectured that the number of ( s , s + 2 ) -core partitions with distinct parts for an odd integer s is 2 s − 1 . This conjecture was first proved by Yan, Qin, Jin and Zhou, then subsequently by Zaleski and Zeilberger. Since the formula for the number of such core partitions is so simple one can hope for a bijective proof. We give the first direct bijective proof of this fact by establishing a bijection between the set of ( s , s + 2 ) -core partitions with distinct parts and a set of lattice paths.
Hypergeometric properties of genus 3 generalized Legendre curves

Abstract Inspired by a result of Manin, we study the relationship between certain period integrals and the trace of Frobenius of genus 3 generalized Legendre curves. We show that both of these properties can be computed in terms of “matching” classical and finite field hypergeometric functions, a phenomenon that has also been observed in elliptic curves and many higher dimensional varieties.
Natural Option Critic.

The recently proposed option-critic architecture (Bacon, Harb, and Precup 2017) provides a stochastic policy gradient approach to hierarchical reinforcement learning. Specifically, it provides a way to estimate the gradient of the expected discounted return with respect to parameters that define a finite number of temporally extended actions, called options. In this paper we show how the option-critic architecture can be extended to estimate the natural gradient (Amari 1998) of the expected discounted return. To this end, the central questions that we consider in this paper are: 1) what is the definition of the natural gradient in this context, 2) what is the Fisher information matrix associated with an option’s parameterized policy, 3) what is the Fisher information matrix associated with an option’s parameterized termination function, and 4) how can a compatible function approximation approach be leveraged to obtain natural gradient estimates for both the parameterized policy and parameterized termination functions of an option with per-time-step time and space complexity linear in the total number of parameters. Based on answers to these questions we introduce the natural option critic algorithm. Experimental results showcase improvement over the vanilla gradient approach.
Climbing a Legendrian mountain range without stabilization

We introduce a new braid-theoretic framework with which to understand the Legendrian and transversal classification of knots, namely a Legendrian Markov Theorem without Stabilization which induces an associated transversal Markov Theorem without Stabilization. We establish the existence of a nontrivial knot-type specific Legendrian and transversal MTWS by enhancing the Legendrian mountain range for the (2,3)-cable of a (2,3)-torus knot provided by Etnyre and Honda, and showing that elementary negative flypes allow us to move toward maximal tb value without having to use Legendrian stabilization. In doing so we obtain new ways to visualize convex tori and Legendrian divides and rulings, using tilings and braided rectangular diagrams.
Sexual videos in Internet: a test of 11 hypotheses about intimate practices and gender interactions in Latin America

Existe muy poca literatura sobre causas biologicas de expresiones culturales relacionadas con la sexualidad en Internet, y aun menos sobre videos sexuales latinoamericanos. Aqui presentamos una evaluacion estadistica de once hipotesis basada en 214 videos disponibles en 2010 en el sitio Nereliatube. En la mayoria de los videos ambas partes estaban conscientes de la grabacion y el hombre operaba la camara. La practica mas frecuente fue la felacion, seguida de penetracion vaginal. La mayoria presentaban una mujer y un hombre, siendo escasos los videos de sexo en grupo. Tambien fueron escasas la violencia y las manifestaciones de poder, pero cuando hubo violencia en general era simulada. En conclusion, estos videos latinoamericanos reflejan una sociedad en la que hay variedad de practicas sexuales de mutuo acuerdo que no difieren de lo esperado segun el modelo biologico.PALABRAS CLAVEVideos caseros, videos aficionados, videos de internet, patrones sexuales, papeles sexuales.
Efficient Data Augmentation for Fitting Stochastic Epidemic Models to Prevalence Data

Stochastic epidemic models describe the dynamics of an epidemic as a disease spreads through a population. Typically, only a fraction of cases are observed at a set of discrete times. The absence of complete information about the time evolution of an epidemic gives rise to a complicated latent variable problem in which the state space size of the epidemic grows large as the population size increases. This makes analytically integrating over the missing data infeasible for populations of even moderate size. We present a data augmentation Markov chain Monte Carlo (MCMC) framework for Bayesian estimation of stochastic epidemic model parameters, in which measurements are augmented with subject-level disease histories. In our MCMC algorithm, we propose each new subject-level path, conditional on the data, using a time-inhomogeneous continuous-time Markov process with rates determined by the infection histories of other individuals. The method is general, and may be applied to a broad class of epidemic models with only minimal modifications to the model dynamics and/or emission distribution. We present our algorithm in the context of multiple stochastic epidemic models in which the data are binomially sampled prevalence counts, and apply our method to data from an outbreak of influenza in a British boarding school.
Dynamic vehicle routing for data gathering in wireless networks

We consider a dynamic vehicle routing problem in wireless networks where messages arriving randomly in time and space are collected by a mobile receiver (vehicle or a collector). The collector is responsible for receiving these messages via wireless communication by dynamically adjusting its position in the network. Our goal is to utilize a combination of wireless transmission and controlled mobility to improve the delay performance in such networks. We show that the necessary and sufficient condition for the stability of such a system is given by ρ &#60; 1 where ρ is the average system load. We derive a fundamental lower bound for the delay in the system. We develop algorithms that are stable for all loads ρ &#60; 1 and that have asymptotically optimal delay scaling. We show that the combination of mobility and wireless transmission results in a delay scaling of Θ(1 over 1−ρ) with the system load ρ in contrast to the (1 over (1−ρ)2) delay scaling in the corresponding system where the collector visits each message location.
Safe protocols for generating power pulses with heterogeneous populations of thermostatically controlled loads

Abstract We explore methods to use thermostatically controlled loads (TCLs), such as water heaters and air conditioners, to provide ancillary services by assisting in balancing generation and load. We show that by adding simple imbedded instructions and a small amount of memory to temperature controllers of TCLs, it is possible to design open-loop control algorithms capable of creating short-term pulses of demand response without unwanted power oscillations associated with temporary synchronization of the TCL dynamics. By moving a small amount of intelligence to each of the end point TCL devices, we are able to leverage our knowledge of the time dynamics of TCLs to shape the demand response pulses for different power system applications. A significant benefit of our open-loop method is the reduction from two-way to one-way broadcast communication which also eliminates many basic consumer privacy issues. In this work, we focus on developing the algorithms to generate a set of fundamental pulse shapes that can subsequently be used to create demand response with arbitrary profiles. Demand response control methods, such as the one developed here, open the door to fast, nonperturbative control of large aggregations of TCLs.
Boundary value problems on planar graphs and flat surfaces with integer cone singularities, II: The mixed Dirichlet–Neumann problem

Abstract In this paper we continue the study started in Hersonsky (in press) [16] . We consider a planar, bounded, m-connected region Ω, and let ∂Ω be its boundary. Let T be a cellular decomposition of Ω ∪ ∂ Ω , where each 2-cell is either a triangle or a quadrilateral. From these data and a conductance function we construct a canonical pair ( S , f ) where S is a special type of a (possibly immersed) genus ( m − 1 ) singular flat surface, tiled by rectangles and f is an energy preserving mapping from T ( 1 ) onto S. In Hersonsky (in press) [16] the solution of a Dirichlet problem defined on T ( 0 ) was utilized, in this paper we employ the solution of a mixed Dirichlet–Neumann problem.
The Distribution of the Carlitz Binomial Coefficients Modulo a Prime

For a nonnegative integer n, and a prime $${\mathcal{P}}$$ in $${\mathbb{F}_{q}[T]}$$ , we prove a result that provides a method for computing the number of integers m with $${0 \leq m \leq n}$$ for which the Carlitz binomial coefficients $${(_{m}^{n})_{C}}$$ fall into each of the residue classes modulo $${\mathcal{P}}$$ . Our main result can be viewed as a function field analogue of the Garfield-Wilf theorem.
On homogeneous locally conical spaces

The main result of this article is: THEOREM. Every homogeneous locally conical connected separable metric space that is not a $1$-manifold is strongly $n$-homogeneous for each $n \geq 2$ and countable dense homogeneous. Furthermore, countable dense homogeneity can be proven without assuming the space is connected. This theorem has the following two consequences. COROLLARY 1. If $X$ is a homogeneous compact suspension, then $X$ is an absolute suspension (i.e., for any two distinct points $p$ and $q$ of $X$, there is a homeomorphism from $X$ to a suspension that maps $p$ and $q$ to the suspension points). COROLLARY 2. If there exists a locally conical counterexample $X$ to the Bing-Borsuk Conjecture (i.e., $X$ is a locally conical homogeneous Euclidean neighborhood retract that is not a manifold), then $X$ is strongly $n$-homogeneous for all $n \geq 2$ and countable dense homogeneous.