cssi/SciSciGPT-SciSciNet huggingface dataset:
Conditional Prior Networks for Optical Flow

Classical computation of optical flow involves generic priors (regularizers) that capture rudimentary statistics of images, but not long-range correlations or semantics. On the other hand, fully supervised methods learn the regularity in the annotated data, without explicit regularization and with the risk of overfitting. We seek to learn richer priors on the set of possible flows that are statistically compatible with an image. Once the prior is learned in a supervised fashion, one can easily learn the full map to infer optical flow directly from two or more images, without any need for (additional) supervision. We introduce a novel architecture, called Conditional Prior Network (CPN), and show how to train it to yield a conditional prior. When used in conjunction with a simple optical flow architecture, the CPN beats all variational methods and all unsupervised learning-based ones using the same data term. It performs comparably to fully supervised ones, that however are fine-tuned to a particular dataset. Our method, on the other hand, performs well even when transferred between datasets. Code is available at: https://github.com/YanchaoYang/Conditional-Prior-Networks.
Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image

We propose a computational framework to jointly parse a single RGB image and reconstruct a holistic 3D configuration composed by a set of CAD models using a stochastic grammar model. Specifically, we introduce a Holistic Scene Grammar (HSG) to represent the 3D scene structure, which characterizes a joint distribution over the functional and geometric space of indoor scenes. The proposed HSG captures three essential and often latent dimensions of the indoor scenes: (i) latent human context, describing the affordance and the functionality of a room arrangement, (ii) geometric constraints over the scene configurations, and (iii) physical constraints that guarantee physically plausible parsing and reconstruction. We solve this joint parsing and reconstruction problem in an analysis-by-synthesis fashion, seeking to minimize the differences between the input image and the rendered images generated by our 3D representation, over the space of depth, surface normal, and object segmentation map. The optimal configuration, represented by a parse graph, is inferred using Markov chain Monte Carlo (MCMC), which efficiently traverses through the non-differentiable solution space, jointly optimizing object localization, 3D layout, and hidden human context. Experimental results demonstrate that the proposed algorithm improves the generalization ability and significantly outperforms prior methods on 3D layout estimation, 3D object detection, and holistic scene understanding.
Differential colorimetry measurements of fluctuation growth in nanofilms exposed to large surface thermal gradients

Slender liquid nanofilms exposed to large surface thermal gradients are known to undergo thickness fluctuations, which rapidly self-organize into arrays of nanoprotrusions with a separation distance of tens of microns. We previously reported good agreement between measurements of the characteristic spacing and the wavelength of the most unstable mode predicted by a linear stability analysis based on a long wavelength thermocapillary model. Here, we focus on differential colorimetry measurements to quantify early time out-of-plane growth of protrusions for peak heights spanning 20 to 200 nm. Analysis of peak heights based on shape reconstruction reveals robust exponential growth. Good quantitative agreement of the growth rates with the thermocapillary model is obtained using a single fit constant to account for material parameters of nanofilms that could not be measured directly. These findings lend further support to the conjecture that the array protrusions uncovered almost two decades ago likely stem from a linear instability, whose growth rate is controlled by thermocapillary forces counterbalanced by capillary forces.
The Misrepresentation of Earnings

The authors conducted a survey of nearly 400 chief financial officers on the definition and drivers of earnings quality, with an emphasis on the prevalence and detection of earnings misrepresentation. The respondents believe that the hallmarks of earnings quality are sustainability, absence of one-time items, and backing by actual cash flows. However, they also believe that in any given period, a remarkable 20% of companies intentionally distort earnings, even while adhering to GAAP. The magnitude of the misrepresentation is large: 10% of reported earnings.
Effective leadership practices in language immersion programs

This is a dissertation study regarding effective leadership practices in language immersion programs. Much of the previous research concentrates on students’ academic achievement in immersion programs. The purpose of this research is to discover actions, attitudes, knowledge, and skills that immersion leaders of successful programs exhibit. Using a basic qualitative model, I interviewed principals, assistant principals, teachers, and parents at three schools with Spanish/English dual immersion programs. The findings indicate that the immersion leader must establish a positive culture through building trust, building community with parents and teachers, and showing commitment to the program. In addition, the leader must provide program and teacher support in a variety of ways, including the provision of professional development, differentiated professional development for international teachers, resources, and leadership opportunities. Finally, effective immersion leaders must possess specific knowledge and skills in order to lead a successful immersion program, including program knowledge, advocacy skills, and the ability to apply a shared leadership model. Being bilingual is considered an asset, but not required. Immersion leaders can learn from the applications for practice in their respective settings. Future research in this should include a wider range of program models and a more balanced pool of participants, including native target language speakers in dual immersion programs. Future research should also include a critical pedagogy lens in studying dual immersion programs specifically.
AttentivU: Evaluating the Feasibility of Biofeedback Glasses to Monitor and Improve Attention

Our everyday work is becoming increasingly complex and cognitively demanding. What we pay attention to during our day influences how effectively our brain prepares itself for action, and how much effort we apply to a task. To address this issue we present AttentivU -a system that uses wearable electroencephalography (EEG) to measure the attention of a person in realtime. When the user's attention level is low, the system provides real-time, subtle, haptic or audio feedback to nudge the person to become attentive again. We tested a first version of the system, which uses an EEG headband on 48 adults over several sessions in both a lab and classroom setting. The results show that the biofeedback redirects the attention of the participants to the task at hand and improves their performance on comprehension tests. We next tested the same approach in the form of glasses on 6 adults in a lab setting, as the glasses form factor may be more acceptable in the long run. We conclude with a discussion of an improved third version of AttentivU, currently under development, which combines a custom-made solution of the glasses form-factor with built-in electrooculography (EOG) and EEG electrodes as well as auditory feedback.
Risk and Performance of Mutual Funds’ Securitized Mortgage Investments

We expand the debate on incentives embedded in the originate-to-distribute lending model by presenting evidence on the placement of mortgage-backed securities (MBS) with mutual funds. We do so by capitalizing on a unique testing platform encompassing institutional holdings of private-label MBS and their corresponding underlying collateral risk characteristics. We explore MBS placement based on a funds’ potential access to information underlying deals as measured by affiliation to the deal’s underwriter/issuer and vertical integration in securitization.
Imaging antiferromagnetic antiphase domain boundaries using magnetic Bragg diffraction phase contrast

Manipulating magnetic domains is essential for many technological applications. Recent breakthroughs in Antiferromagnetic Spintronics brought up novel concepts for electronic device development. Imaging antiferromagnetic domains is of key importance to this field. Unfortunately, some of the basic domain types, such as antiphase domains, cannot be imaged by conventional techniques. Herein, we present a new domain projection imaging technique based on the localization of domain boundaries by resonant magnetic diffraction of coherent X rays. Contrast arises from reduction of the scattered intensity at the domain boundaries due to destructive interference effects. We demonstrate this approach by imaging antiphase domains in a collinear antiferromagnet Fe2Mo3O8, and observe evidence of domain wall interaction with a structural defect. This technique does not involve any numerical algorithms. It is fast, sensitive, produces large-scale images in a single-exposure measurement, and is applicable to a variety of magnetic domain types.
Design and Analysis of a Query Processor for Brick

Brick is a recently proposed metadata schema and ontology for describing building components and the relationships between them. It represents buildings as directed labeled graphs using the RDF data model. Using the SPARQL query language, building-agnostic applications query a Brick graph to discover the set of resources and relationships they require to operate. Latency-sensitive applications, such as user interfaces, demand response, and model-predictive control, require fast queries—conventionally less than 100ms. We benchmark a set of popular open source and commercial SPARQL databases against three real Brick models using seven application queries and find that none of them meet this performance target. This lack of performance can be attributed to design decisions that optimize for queries over large graphs consisting of billions of triples but give poor spatial locality and join performance on the small dense graphs typical of Brick. We present the design and evaluation of HodDB, a RDF/SPARQL database for Brick built over a node-based index structure. HodDB performs Brick queries 3--700× faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications. This article is an extension of a previously published work [16].
Stability of diffusively coupled linear systems with an invariant cone

Abstract This paper concerns a question that frequently occurs in various applications: Is any diffusive coupling of stable linear systems, also stable? Although it has been known for a long time that this is not the case, we shall identify a reasonably diverse class of systems for which it is true.
Does Telework Stress Employees Out? A Study on Working at Home and Subjective Well-Being for Wage/Salary Workers

With the expansion of high-speed internet during the recent decades, a growing number of people are working from home. Yet there is no consensus on how working from home affects workers’ well-being in the literature. Using data from the 2010, 2012, and 2013 American Time Use Survey Well-Being Modules, this paper examines how subjective well-being varies among wage/salary workers between working at home and working in the workplace using individual fixed-effects models. We find that compared to working in the workplace, bringing work home on weekdays is associated with less happiness, and telework on weekdays or weekends/holidays is associated with more stress. The effect of working at home on subjective well-being also varies by parental status and gender. Parents, especially fathers, report a lower level of subjective well-being when working at home on weekdays but a higher level of subjective well-being when working at home on weekends/holidays. Non-parents’ subjective well-being does not vary much by where they work on weekdays, but on weekends/holidays childless males feel less painful whereas childless females feel more stressed when teleworking instead of working in the workplace. This paper provides new evidence on the impact of working at home and sheds lights for policy makers and employers to re-evaluate the benefits of telework.
Quantum-resistant authentication algorithms for satellite-based augmentation systems

Cryptography in the form of digital signatures can be part of the solution to the threat of spoofing and is going to be implemented on Galileo and other Global Navigation Satellite Systems. Digital signatures incorporated into the data stream authenticate the integrity of the data as well as the origin of the message. Implementing a digital signature on a satellite-based augmentation system for use in aviation will require the signature to be short and the signing procedure to be cryptographically relevant for the next 30 or more years. With the advent of quantum computing, many state-of-the-art authentication schemes are no longer viable, so an authentication scheme implemented in satellite-based augmentation system will need to be quantum secure. This paper introduces the cryptographic primitives (foundational problems) necessary to understand the vulnerabilities in modern-day cryptography due to quantum computing and investigates the use of TESLA (Timed Efficient Stream Loss-tolerant Algorithm) and EC-Schnorr (Elliptic Curve-Schnorr) algorithms in broadcast systems.
Heterogeneity and Giving: Evidence From U.S. Households Before and After the Great Recession of 2008:

Before the Great Recession of 2008, a stable two-thirds of the U.S. population donated to charitable causes in any given year. However, the fraction of American donors has declined by 11% since the...
Progression of subclinical choroidal neovascularization in age-related macular degeneration

Purpose To use optical coherence tomography angiography (OCTA) to study longitudinal subclinical choroidal neovascularization (CNV) changes and their correlation with progression to exudation in age-related macular degeneration (AMD). Methods This study included a total of 34 patients with unilateral neovascular AMD who were evaluated prospectively using OCTA to detect subclinical CNV in their fellow eye. Eyes with baseline subclinical CNV were followed with serial OCTA for a minimum of one year (15.2±3.27 months) to monitor the development of exudation. Results Of the 34 fellow eyes studied, five were found to have baseline subclinical CNV. One of the five cases of baseline subclinical CNV converted to exudative AMD during the follow up period. The average surface area of baseline subclinical CNV on OCTA was 0.131±0.096 mm2 which progressed to 0.136±0.104 mm2 at the final follow up (P = 0.539). Geographic atrophy grew at a rate of 0.82±1.20mm2/year in four eyes without subclinical CNV and 0.02mm2/year in one eye with subclinical CNV. Conclusion and importance The rate of conversion to exudative AMD in eyes with subclinical CNV of 20% in our study is similar to previous reports and suggests the importance of vigilance in these eyes. The lower growth rate of geographic atrophy may suggest a protective effect of subclinical CNV that deserves further study.
Dynamic multifactor hubs interact transiently with sites of active transcription in Drosophila embryos.

Author(s): Mir, Mustafa; Stadler, Michael R; Ortiz, Stephan A; Hannon, Colleen E; Harrison, Melissa M; Darzacq, Xavier; Eisen, Michael B | Abstract: The regulation of transcription requires the coordination of numerous activities on DNA, yet how transcription factors mediate these activities remains poorly understood. Here, we use lattice light-sheet microscopy to integrate single-molecule and high-speed 4D imaging in developing Drosophila embryos to study the nuclear organization and interactions of the key transcription factors Zelda and Bicoid. In contrast to previous studies suggesting stable, cooperative binding, we show that both factors interact with DNA with surprisingly high off-rates. We find that both factors form dynamic subnuclear hubs, and that Bicoid binding is enriched within Zelda hubs. Remarkably, these hubs are both short lived and interact only transiently with sites of active Bicoid-dependent transcription. Based on our observations, we hypothesize that, beyond simply forming bridges between DNA and the transcription machinery, transcription factors can organize other proteins into hubs that transiently drive multiple activities at their gene targets.Editorial noteThis article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
Comparative analysis of gene expression identifies distinct molecular signatures of bone marrow- and periosteal-skeletal stem/progenitor cells

Periosteum and bone marrow (BM) both contain skeletal stem/progenitor cells (SSCs) that participate in fracture repair. However, the functional difference and selective regulatory mechanisms of SSCs in different locations are unknown due to the lack of specific markers. Here, we report a comprehensive gene expression analysis of bone marrow SSCs (BM-SSCs), periosteal SSCs (P-SSCs), and more differentiated osteoprogenitors by using reporter mice expressing Interferon-inducible Mx1 and NestinGFP, previously known SSC markers. We first defined that the BM-SSCs can be enriched by the combination of Mx1 and NestinGFP expression, while endogenous P-SSCs can be isolated by positive selection of Mx1, CD105 and CD140a (known SSC markers) combined with the negative selection of CD45, CD31, and osteocalcinGFP (a mature osteoblast marker). Comparative gene expression analysis with FACS-sorted BM-SSCs, P-SSCs, Osterix+ preosteoblasts, CD51+ stroma cells and CD45+ hematopoietic cells as controls revealed that BM-SSCs and P-SSCs have high similarity with few potential differences without statistical significance. We also found that CD51+ cells are highly heterogeneous and have little overlap with SSCs. This was further supported by the microarray cluster analysis, where the two SSC populations clustered together but are separate from the CD51+ cells. However, when comparing SSC population to controls, we found several genes that are uniquely upregulated in endogenous SSCs. Amongst these genes, we found KDR (aka Flk1 or VEGFR2) to be most interesting and discovered that it is highly and selectively expressed in P-SSCs. This finding suggests that endogenous P-SSCs are functionally very similar to BM-SSCs with undetectable significant differences in gene expression but there are distinct molecular signatures in P-SSCs, which can be useful to specify P-SSC subset in vivo.
The value of prior knowledge in machine learning of complex network systems

Motivation Our overall goal is to develop machine-learning approaches based on genomics and other relevant accessible information for use in predicting how a patient will respond to a given proposed drug or treatment. Given the complexity of this problem, we begin by developing, testing and analyzing learning methods using data from simulated systems, which allows us access to a known ground truth. We examine the benefits of using prior system knowledge and investigate how learning accuracy depends on various system parameters as well as the amount of training data available. Results The simulations are based on Boolean networks-directed graphs with 0/1 node states and logical node update rules-which are the simplest computational systems that can mimic the dynamic behavior of cellular systems. Boolean networks can be generated and simulated at scale, have complex yet cyclical dynamics and as such provide a useful framework for developing machine-learning algorithms for modular and hierarchical networks such as biological systems in general and cancer in particular. We demonstrate that utilizing prior knowledge (in the form of network connectivity information), without detailed state equations, greatly increases the power of machine-learning algorithms to predict network steady-state node values ('phenotypes') and perturbation responses ('drug effects'). Availability and implementation Links to codes and datasets here: https://gray.mgh.harvard.edu/people-directory/71-david-craft-phd. Contact dcraft@broadinstitute.org. Supplementary information Supplementary data are available at Bioinformatics online.
The thermal reaction of HNCO at moderate temperatures

The thermal reaction of HNCO has been studied in a static cell at temperatures between 873 and 1220 K and a constant pressure of 800 torr under highly diluted conditions. The reaction was measurable above 1000 K by FTIR spectrometry. The products detected include CO, CO2, HCN, NH3, and the unreacted HNCO. In this moderate temperature regime, the rates of product formation and HNCO decay cannot be accounted for by a previously established high-temperature mechanism, assuming HNCO NH + CO (1) as the initiation process. Instead, a new bimolecular reaction, 2HNCO CO2 + HNCNH (2), has been invoked to interpret the disappearance of HNCO as well as the formation of various products, most importantly CO2. The concentration profiles of all measured species can be quantitatively modeled, throughout the temperature range analyzed, by varying k2 using a modified mechanism. The kinetically modeled values of k2 can be effectively represented by This result agrees closely with that computed with the conventional transition-state theory using the TST parameters predicted by the BAC-MP4 method: The bimolecular reaction takes place via a stable 4-membered ring intermediate which is isoelectronic with diketene; viz.
Template-Free Synthesis of Mesoporous Transition Metal Nitride Materials from Ternary Cadmium Transition Metal Oxides

A simple process for preparing mesoporous transition metal nitrides by the ammonolysis of bulk ternary oxides that contain cadmium is reported. Mesoporous NbN, VN, Ta3N5, and TiN have been obtained...
Condition‐Directable Reaction: Regio‐ and Stereoselective Elimination of 2,3‐Dibromo‐2‐methylpropyl Phenyl Sulfone via Base‐solvent Selection

Abstract Diversity‐oriented organic synthesis is an important approach for combinatorial chemistry and drug discovery. An example of this approach is selective elimination of 2,3‐dibromo‐2‐methylpropyl phenyl sulfone 5 to potentially useful vinyl sulfones 6 E/Z and vinyl bromides 7 E/Z , which is achieved by choosing reaction conditions. This work was done during my graduate research under the guidance of Philip L. Fuchs in the Department of Chemistry at Purdue University, West Lafayette, Indiana, USA.
Stability of Hyperlithiated Borides

Structures and energetics of BLin (n = 4−8) clusters are predicted using the SCF, MP2, and B3LYP methods with the 6-31G(d) basis set, including energy evaluations at G2MP2. Cohesive energies, defined as the enthalpies of the BLin → B + Lin reactions, and Li and Li2 elimination reaction enthalpies are also estimated at B3LYP. This level of theory predicts the boron cohesive energy to increase up to the BLi6 cluster after which it levels off. All BLin systems are thermodynamically stable with respect to Li and Li2 dissociations; BLi4 has the largest reaction enthalpies. The energetics of the hyperlithiated borides obtained with B3LYP/6-31G(d) are in reasonable agreement with those at G2MP2 but less satisfactory than those of the smaller BLin (n =1−3) systems. Computations on BLi4 with multiconfigurational quasidegenerate perturbation theory indicate that the B3LYP/6-31G(d) energies may be more reliable for the larger BLin systems.
Three Revolutions of the Modern Era

Abstract The emergence and evolution of modern science since the seventeenth century has led to three major breakthroughs in the human condition. The first, the Industrial Revolution, started in the late eighteenth century and is based chiefly on developments associated with the rise of the natural sciences. The second, the Demographic Revolution, began in the latter half of the nineteenth century and is largely the result of progress in the life sciences. The third is a Happiness Revolution that commenced in the late twentieth century and is the outgrowth of the social sciences. The first two revolutions, both familiar concepts, are summarized briefly; this paper develops the rationale for the third, the Happiness Revolution. It also notes the implications of this perspective for the interpretation of international cross-sectional studies.
Efficient enantioselective syntheses of chloramphenicol and (d)-threo- and (d)-erythro-sphingosine

Abstract The chiral diazaborolidine 1 has been applied to the enantioselective syntheses of chloramphenicol (2) and ( d )-threo-N-acetylsphingosine (3), a synthetic precursor of the diastereomeric ( d )-sphingosines.
Stereodynamics and Asymmetric Hydrosilylation with Chiral Rhodium Complexes Containing a Monodentate N-Heterocyclic Carbene

Imidazolinium salts derived from (1S,2S)-diphenylethylenediamine were used to prepare chiral N-heterocyclic carbene (NHC) complexes of rhodium of the form (cod)Rh(NHC)Cl via silver transmetalation....
Synthesis of Novel Substituted 1,10-Phenanthrolines

Abstract The syntheses of both 5-amino-6-nitro-1,10-phenanthroline and 5,6-diamino-1,10-phenanthroline (starting from 5-nitro-1,10-phenanthroline) are described in detail.
Oxidation of thiols to disulfides with monochloro poly(styrenehydantoin) beads

Various thiols were converted to symmetrical disulfides. This facile and reproducible method uses water as a solvent, and monochloro poly(styrenehydantoin) beads as an oxidizing agent.
Spectroscopic studies on cyanocuprate-catalyzed 3-component couplings: understanding the catalytic cycle

Abstract Low temperature 1 H NMR analysis of a reaction mixture containing a vinylic zirconocene, MeLi, Me 3 ZnLi, 20 mol % Me 2 Cu(CN)Li 2 and an enone, reagents which together lead to the Michael delivery of a vinyl ligand, reveals the presence of a zinc enolate, the species likely to be responsible for the subsequent alkylation or aldol reaction as the final step in 3-component couplings.
Low-intensity focused ultrasound alters the latency and spatial patterns of sensory-evoked cortical responses in vivo.

Objective The use of transcranial, low intensity focused ultrasound (FUS) is an emerging neuromodulation technology that shows promise for both therapeutic and research applications. Among many, one of the most exciting applications is the use of FUS to rehabilitate or augment human sensory capabilities. While there is compelling empirical evidence demonstrating this capability, basic questions regarding the spatiotemporal extent of the modulatory effects remain. Our objective was to assess the basic, yet often overlooked hypothesis that FUS in fact alters sensory-evoked neural activity within the region of the cerebral cortex at the beam's focus. Approach To address this knowledge gap, we developed an approach to optically interrogate patterns of neural activity in the cortex directly at the acoustic focus, in vivo. Implementing simultaneous wide-field optical imaging and FUS stimulation in mice, our experiments probed somatosensory-evoked electrical activity through the use of voltage sensitive dyes (VSDs) and, in transgenic mice expressing GCaMP6f, monitored associated Ca2+ responses. Main results Our results demonstrate that low-intensity FUS alters both the kinetics and spatial patterns of neural activity in primary somatosensory cortex at the acoustic focus. When preceded by 1 s of pulsed ultrasound at intensities below 1 W cm-2 (I sppa), the onset of sensory-evoked cortical responses occurred 3.0 ± 0.7 ms earlier and altered the surface spatial morphology of Ca2+ responses. Significance These findings support the heretofore unconfirmed assumption that FUS-induced sensory modulation reflects, at least in part, altered reactivity in primary sensory cortex at the site of sonication. The findings are significant given the interest in using FUS to target and alter spatial aspects of sensory receptive fields on the cerebral cortex.
Catalytic aldol-transfer reactions with Al-alkoxide trapping

Abstract Al-BINOL catalyzed aldol-transfer reactions of aldehydes with diacetonealcohol conducted with Al-alkoxide trapping gave aldol adducts in good yields. The best yields were obtained with electron-rich aromatic aldehydes (e.g., 83% yield with 3,4,5-trimethoxybenzaldehyde).
Bromine auxiliaries in photosyntheses of [5]helicenes

Abstract Bromine substituents on benzene rings direct photocyclizations away from their ortho positions. This principle prevents [5]helicenes from photocyclizing and methoxyls from photoeliminating. It makes possible the photosynthesis of [5]helicene and of a tetramethoxy-derivative of [5]helicene.
Enantioselective route to α-hydroxy aldehyde and acid derivatives

Abstract Methodology is described for the enantioselective synthesis of chiral O-protected α-hydroxy aldehydes, acids and esters from achiral aldehydes having one less carbon.
Non-line-of-sight Imaging with Partial Occluders and Surface Normals

Imaging objects obscured by occluders is a significant challenge for many applications. A camera that could “see around corners” could help improve navigation and mapping capabilities of autonomous vehicles or make search and rescue missions more effective. Time-resolved single-photon imaging systems have recently been demonstrated to record optical information of a scene that can lead to an estimation of the shape and reflectance of objects hidden from the line of sight of a camera. However, existing non-line-of-sight (NLOS) reconstruction algorithms have been constrained in the types of light transport effects they model for the hidden scene parts. We introduce a factored NLOS light transport representation that accounts for partial occlusions and surface normals. Based on this model, we develop a factorization approach for inverse time-resolved light transport and demonstrate high-fidelity NLOS reconstructions for challenging scenes both in simulation and with an experimental NLOS imaging system.
Thermal cyclization of (2-Ethynylphenyl)triazenes: facile synthesis of substituted cinnolines and isoindazoles

High-temperature intramolecular cyclization of N,N-dialkyl-N‘-(4-substituted-2-ethynylphenyl)triazenes provides under neutral conditions both 6-substituted cinnolines and 5-substituted isoindazoles in moderate to excellent yields.
Hydrozirconation / transmetalation / alkylation: direct one-pot conversion of 1-alkynes to E-1,2-disubstituted alkenes

Abstract Hydrozirconation of terminal acetylenes followed by transmetalation of the intermediate vinyl zirconate with a higher order cyanocuprate affords mixed vinylic cuprates which undergo alkylations with a variety of electrophiles.
Causes and consequences of nuclear gene positioning

The eukaryotic genome is organized in a manner that allows folding of the genetic material in the confined space of the cell nucleus, while at the same time enabling its physiological function. A major principle of spatial genome organization is the non-random position of genomic loci relative to other loci and to nuclear bodies. The mechanisms that determine the spatial position of a locus, and how position affects function, are just beginning to be characterized. Initial results suggest that there are multiple, gene-specific mechanisms and the involvement of a wide range of cellular machineries. In this Commentary, we review recent findings from candidate approaches and unbiased screening methods that provide initial insight into the cellular mechanisms of positioning and their functional consequences. We highlight several specific mechanisms, including tethering of genome regions to the nuclear periphery, passage through S-phase and histone modifications, that contribute to gene positioning in yeast, plants and mammals.
Dietary Lipids Modulate Notch Signaling and Influence Adult Intestinal Development and Metabolism in Drosophila.

Summary Tissue homeostasis involves a complex balance of developmental signals and environmental cues that dictate stem cell function. We found that dietary lipids control enteroendocrine cell production from Drosophila posterior midgut stem cells. Dietary cholesterol influences new intestinal cell differentiation in an Hr96-dependent manner by altering the level and duration of Notch signaling. Exogenous lipids modulate Delta ligand and Notch extracellular domain stability and alter their trafficking in endosomal vesicles. Lipid-modulated Notch signaling occurs in other nutrient-dependent tissues, suggesting that Delta trafficking in many cells is sensitive to cellular sterol levels. These diet-mediated alterations in young animals contribute to a metabolic program that persists after the diet changes. A low-sterol diet also slows the proliferation of enteroendocrine tumors initiated by Notch pathway disruption. Thus, a specific dietary nutrient can modify a key intercellular signaling pathway to shift stem cell differentiation and cause lasting changes in tissue structure and physiology.
Novel reactivity of SeO2 with 1,3-dienes: Selenophene formation

A novel and efficient method for the synthesis of selenophenes is disclosed. Selenophenes were synthesized in high yields in a single operation from 1,3-dienes containing a carbonyl group at the C-1 position and selenium dioxide. The bidirectional synthesis of selenophenes can also be demonstrated using this method. The selenophene is believed to form via a [4 + 2] cycloaddition between diene and selenium dioxide.
Dual Frame Motion Compensation With Uneven Quality Assignment

Video codecs that use motion compensation have shown PSNR gains from the use of multiple frame prediction, in which more than one past reference frame is available for motion estimation. In dual frame motion compensation, one short-term reference frame and one long-term reference frame are available for prediction. In this paper, we explore using dual frame motion compensation in two contexts. We first show that using a single fixed long-term reference frame in the context of a rate switching network can enhance video quality. Next, by periodically creating high-quality long-term reference frames, we show that the performance is superior to a standard dual frame technique that has the same average rate but no high-quality frames.
Virtual Seifert surfaces

A virtual knot that has a homologically trivial representative &#x1d4a6; in a thickened surface Σ × [0, 1] is said to be an almost classical (AC) knot. &#x1d4a6; then bounds a Seifert surface F ⊂ Σ × [0, 1]. Seife...
Multi-party set reconciliation using characteristic polynomials

In the standard set reconciliation problem, there are two parties A 1 and A 2 , each respectively holding a set of elements S 1 and S 2 . The goal is for both parties to obtain the union S 1 U S 2 . In many distributed computing settings the sets may be large but the set difference |S 1 − S 2 | +|S 2 − S 1 | is small. In these cases one aims to achieve reconciliation efficiently in terms of communication; ideally, the communication should depend on the size of the set difference, and not on the size of the sets. Recent work has considered generalizations of the reconciliation problem to multi-party settings, using a framework based on a specific type of linear sketch called an Invertible Bloom Lookup Table. Here, we consider multi-party set reconciliation using the alternative framework of characteristic polynomials, which have previously been used for efficient pairwise set reconciliation protocols, and compare their performance with Invertible Bloom Lookup Tables for these problems.
Modular groups, Hurwitz classes and dynamic portraits of NET maps

An orientation-preserving branched covering $f: S^2 \to S^2$ is a nearly Euclidean Thurston (NET) map if each critical point is simple and its postcritical set has exactly four points. Inspired by classical, non-dynamical notions such as Hurwitz equivalence of branched covers of surfaces, we develop invariants for such maps. We then apply these notions to the classification and enumeration of NET maps. As an application, we obtain a complete classification of the dynamic critical orbit portraits of NET maps.
Adaptive sliding mode control without knowledge of uncertainty bounds

This paper proposes a new adaptation methodology to find the control inputs for a class of nonlinear systems with time-varying bounded uncertainties. The proposed method does not require any prior knowledge of the uncertainties including their bounds. The main idea is developed under the structure of adaptive sliding mode control; an update law decreases the gain inside and increases the gain outside a vicinity of the sliding surface. The semi-global stability of the closed-loop system and the adaptation error are guaranteed by Lyapunov theory. The simulation results show that the proposed adaptation methodology can reduce the magnitude of the controller gain to the minimum possible value and smooth out the chattering.
Relation algebras and groups

Generalizing results of Jonsson and Tarski, Maddux introduced the notion of a pair-dense relation algebra and proved that every pair-dense relation algebra is representable. The notion of a pair below the identity element is readily definable within the equational framework of relation algebras. The notion of a triple, a quadruple, or more generally, an element of size (or measure) $$n>2$$ is not definable within this framework, and therefore it seems at first glance that Maddux’s theorem cannot be generalized. It turns out, however, that a very far-reaching generalization of Maddux’s result is possible if one is willing to go outside of the equational framework of relation algebras, and work instead within the framework of the first-order theory. Moreover, this generalization sheds a great deal of light not only on Maddux’s theorem, but on the earlier results of Jonsson and Tarski. In the present paper, we define the notion of an atom below the identity element in a relation algebra having measure n for an arbitrary cardinal number $$n>0$$ , and we define a relation algebra to be measurable if it’s identity element is the sum of atoms each of which has some (finite or infinite) measure. The main purpose of the present paper is to construct a large class of new examples of group relation algebras using systems of groups and corresponding systems of quotient isomorphisms (instead of the classic example of using a single group and forming its complex algebra), and to prove that each of these algebras is an example of a measurable set relation algebra. In a subsequent paper, the class of examples will be greatly expanded by adding a third ingredient to the mix, namely systems of “shifting” cosets. The expanded class of examples—called coset relation algebras—will be large enough to prove a representation theorem saying that every atomic, measurable relation algebra is essentially isomorphic to a coset relation algebra.
Recurrent Scene Parsing with Perspective Understanding in the Loop

Objects may appear at arbitrary scales in perspective images of a scene, posing a challenge for recognition systems that process images at a fixed resolution. We propose a depth-aware gating module that adaptively selects the pooling field size in a convolutional network architecture according to the object scale (inversely proportional to the depth) so that small details are preserved for distant objects while larger receptive fields are used for those nearby. The depth gating signal is provided by stereo disparity or estimated directly from monocular input. We integrate this depth-aware gating into a recurrent convolutional neural network to perform semantic segmentation. Our recurrent module iteratively refines the segmentation results, leveraging the depth and semantic predictions from the previous iterations. Through extensive experiments on four popular large-scale datasets, we demonstrate this approach achieves competitive semantic segmentation performance with a model which is substantially more compact. We carry out extensive analysis of this architecture including variants that operate on monocular RGB but use depth as side-information during training, unsupervised gating as a generic attentional mechanism, and multi-resolution gating. We find that gated pooling for joint semantic segmentation and depth yields state-of-the-art results for quantitative monocular depth estimation.
Implementing Push-Pull Efficiently in GraphBLAS

We factor Beamer's push-pull, also known as direction-optimized breadth-first-search (DOBFS) into 3 separable optimizations, and analyze them for generalizability, asymptotic speedup, and contribution to overall speedup. We demonstrate that masking is critical for high performance and can be generalized to all graph algorithms where the sparsity pattern of the output is known a priori. We show that these graph algorithm optimizations, which together constitute DOBFS, can be neatly and separably described using linear algebra and can be expressed in the GraphBLAS linear-algebra-based framework. We provide experimental evidence that with these optimizations, a DOBFS expressed in a linear-algebra-based graph framework attains competitive performance with state-of-the-art graph frameworks on the GPU and on a multi-threaded CPU, achieving 101 GTEPS on a Scale 22 RMAT graph.
Mean value theorems for binary Egyptian fractions

Abstract In this paper, we establish two mean value theorems for the number of solutions of the Diophantine equation a n = 1 x + 1 y , in the case when a is fixed and n varies and in the case when both a and n vary.
Parallel Markov chain Monte Carlo for Bayesian hierarchical models with big data, in two stages

Due to the escalating growth of big data sets in recent years, new Bayesian Markov chain Monte Carlo (MCMC) parallel computing methods have been developed. These methods partition large data sets b...
Counting elliptic curves of bounded Faltings height

Because many invariants and properties of elliptic curves are difficult to understand directly, the study of arithmetic statistics instead looks at what happens "on average", using heights to make this notion rigorous. Previous work has primarily used the naive height, which can be calculated easily but is not defined intrinsically. We give an asymptotic formula for the number of elliptic curves over Q with bounded Faltings height. Silverman [34] has shown that the Faltings height for elliptic curves over number fields can be expressed in terms of the minimal discriminant and period of the elliptic curve. We use this to recast the problem as one of counting lattice points in an unbounded region in R2 defined by transcendental equations, and understand this region well enough to give a formula for the number of these lattice points.
CHARACTERS OF PRIME DEGREE

Let G be a finite nilpotent group, χ and ψ be irreducible complex characters of G with prime degree. Assume that χ(1) = p . Then, either the product χψ is a multiple of an irreducible character or χψ is the linear combination of at least distinct irreducible characters.
Scalable $M$ -Channel Critically Sampled Filter Banks for Graph Signals

We investigate a scalable $M$ -channel critically sampled filter bank for graph signals, where each of the $M$ filters is supported on a different subband of the graph Laplacian spectrum. For analysis, the graph signal is filtered on each subband and downsampled on a corresponding set of vertices. However, the classical synthesis filters are replaced with interpolation operators. For small graphs, we use a full eigendecomposition of the graph Laplacian to partition the graph vertices such that the $m{\text{th}}$ set comprises a uniqueness set for signals supported on the $m{\text{th}}$ subband. The resulting transform is critically sampled, the dictionary atoms are orthogonal to those supported on different bands, and graph signals are perfectly reconstructable from their analysis coefficients. We also investigate fast versions of the proposed transform that scale efficiently for large, sparse graphs. Issues that arise in this context include designing the filter bank to be more amenable to polynomial approximation, estimating the number of samples required for each band, performing nonuniform random sampling for the filtered signals on each band, and using efficient reconstruction methods. We empirically explore the joint vertex-frequency localization of the dictionary atoms, the sparsity of the analysis coefficients for different classes of signals, the reconstruction error resulting from the numerical approximations, and the ability of the proposed transform to compress piecewise-smooth graph signals. The proposed filter bank also yields a fast, approximate graph Fourier transform with a coarse resolution in the spectral domain.
Uniformly Efficient Simulation for Extremes of Gaussian Random Fields

In this paper we consider the problem of simultaneously estimating rare-event probabilities for a class of Gaussian random fields. A conventional rare-event simulation method is usually tailored to a specific rare event and consequently would lose estimation efficiency for different events of interest, which often results in additional computational cost in such simultaneous estimation problems. To overcome this issue, we propose a uniformly efficient estimator for a general family of Holder continuous Gaussian random fields. We establish the asymptotic and uniform efficiency of the proposed method and also conduct simulation studies to illustrate its effectiveness.
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-Offs by Selective Execution

We introduce Dynamic Deep Neural Networks (D2NN), a new type of feed-forward deep neural network that allows selective execution. Given an input, only a subset of D2NN neurons are executed, and the particular subset is determined by the D2NN itself. By pruning unnecessary computation depending on input, D2NNs provide a way to improve computational efficiency. To achieve dynamic selective execution, a D2NN augments a feed-forward deep neural network (directed acyclic graph of differentiable modules) with controller modules. Each controller module is a sub-network whose output is a decision that controls whether other modules can execute. A D2NN is trained end to end. Both regular and controller modules in a D2NN are learnable and are jointly trained to optimize both accuracy and efficiency. Such training is achieved by integrating backpropagation with reinforcement learning. With extensive experiments of various D2NN architectures on image classification tasks, we demonstrate that D2NNs are general and flexible, and can effectively optimize accuracy-efficiency trade-offs.
Visualizing and Understanding Atari Agents.

While deep reinforcement learning (deep RL) agents are effective at maximizing rewards, it is often unclear what strategies they use to do so. In this paper, we take a step toward explaining deep RL agents through a case study using Atari 2600 environments. In particular, we focus on using saliency maps to understand how an agent learns and executes a policy. We introduce a method for generating useful saliency maps and use it to show 1) what strong agents attend to, 2) whether agents are making decisions for the right or wrong reasons, and 3) how agents evolve during learning. We also test our method on non-expert human subjects and find that it improves their ability to reason about these agents. Overall, our results show that saliency information can provide significant insight into an RL agent's decisions and learning behavior.