cssi/SciSciGPT-SciSciNet huggingface dataset:
Streaming-enhanced flow-mediated transport

We investigate the ability of an active body (master) to manipulate a passive object (slave) purely via contactless flow-mediated mechanisms, motivated by potential applications in microfluidic devices and medicine (drug delivery purposes). We extend prior works on active???passive cylinder pairs by superimposing periodic oscillations to the master???s linear motion. In a viscous fluid, such oscillations produce an additional viscous streaming field, which is leveraged for enhancing slave transport. We see that superimposing oscillations robustly improves transport across a range of Reynolds numbers. Comparison with results without oscillations highlights the flow mechanisms at work, which we capitalize on to design (master) geometries for augmented transport. These principles are found to extend to three-dimensional active???passive shapes as well.
The Caenorhabditis elegans RIG-I Homolog DRH-1 Mediates the Intracellular Pathogen Response upon Viral Infection.

Mammalian retinoic acid-inducible gene I (RIG-I)-like receptors detect viral double-stranded RNA (dsRNA) and 5'-triphosphorylated RNA to activate the transcription of interferon genes and promote antiviral defense. The Caenorhabditis elegans RIG-I-like receptor DRH-1 promotes defense through antiviral RNA interference (RNAi), but less is known about its role in regulating transcription. Here, we describe a role for DRH-1 in directing a transcriptional response in C. elegans called the intracellular pathogen response (IPR), which is associated with increased pathogen resistance. The IPR includes a set of genes induced by diverse stimuli, including intracellular infection and proteotoxic stress. Previous work suggested that the proteotoxic stress caused by intracellular infections might be the common trigger of the IPR, but here, we demonstrate that different stimuli act through distinct pathways. Specifically, we demonstrate that DRH-1/RIG-I is required for inducing the IPR in response to Orsay virus infection but not in response to other triggers like microsporidian infection or proteotoxic stress. Furthermore, DRH-1 appears to be acting independently of its known role in RNAi. Interestingly, expression of the replication-competent Orsay virus RNA1 segment alone is sufficient to induce most of the IPR genes in a manner dependent on RNA-dependent RNA polymerase activity and on DRH-1. Altogether, these results suggest that DRH-1 is a pattern recognition receptor that detects viral replication products to activate the IPR stress/immune program in C. elegans IMPORTANCE C. elegans lacks homologs of most mammalian pattern recognition receptors, and how nematodes detect pathogens is poorly understood. We show that the C. elegans RIG-I homolog DRH-1 mediates the induction of the intracellular pathogen response (IPR), a novel transcriptional defense program, in response to infection by the natural C. elegans viral pathogen Orsay virus. DRH-1 appears to act as a pattern recognition receptor to induce the IPR transcriptional defense program by sensing the products of viral RNA-dependent RNA polymerase activity. Interestingly, this signaling role of DRH-1 is separable from its previously known role in antiviral RNAi. In addition, we show that there are multiple host pathways for inducing the IPR, shedding light on the regulation of this novel transcriptional immune response.
An odd variant of multiple zeta values

For positive integers $i_1,...,i_k$ with $i_1 > 1$, we define the multiple $t$-value $t(i_1,...,i_k)$ as the sum of those terms in the usual infinite series for the multiple zeta value $\zeta(i_1,...,i_k)$ with odd denominators. Like the multiple zeta values, the multiple $t$-values can be multiplied according to the rules of the harmonic algebra. Using this fact, we obtain explicit formulas for multiple $t$-values of repeated arguments analogous to those known for multiple zeta values. Multiple $t$-values can be written as rational linear combinations of the alternating or "colored" multiple zeta values. Using known results for colored multiple zeta values, we obtain tables of multiple $t$-values through weight 7, suggesting some interesting conjectures, including one that the dimension of the rational vector space generated by weight-$n$ multiple $t$-values has dimension equal to the $n$th Fibonacci number. We express the generating function of the height one multiple $t$-values $t(n,1,...,1)$ in terms of a generalized hypergeometric function. We also define alternating multiple $t$-values and prove some results about them.
Dietary salt promotes cognitive impairment through tau phosphorylation

Dietary habits and vascular risk factors promote both Alzheimer’s disease and cognitive impairment caused by vascular factors1–3. Furthermore, accumulation of hyperphosphorylated tau, a microtubule-associated protein and a hallmark of Alzheimer’s pathology4, is also linked to vascular cognitive impairment5,6. In mice, a salt-rich diet leads to cognitive dysfunction associated with a nitric oxide deficit in cerebral endothelial cells and cerebral hypoperfusion7. Here we report that dietary salt induces hyperphosphorylation of tau followed by cognitive dysfunction in mice, and that these effects are prevented by restoring endothelial nitric oxide production. The nitric oxide deficiency reduces neuronal calpain nitrosylation and results in enzyme activation, which, in turn, leads to tau phosphorylation by activating cyclin-dependent kinase 5. Salt-induced cognitive impairment is not observed in tau-null mice or in mice treated with anti-tau antibodies, despite persistent cerebral hypoperfusion and neurovascular dysfunction. These findings identify a causal link between dietary salt, endothelial dysfunction and tau pathology, independent of haemodynamic insufficiency. Avoidance of excessive salt intake and maintenance of vascular health may help to stave off the vascular and neurodegenerative pathologies that underlie dementia in the elderly. A high-salt diet in mice induces cognitive impairment through a signalling cascade that culminates in increased phosphorylation of tau.
Verification and Synthesis of Symmetric Uni-Rings for Leads-To Properties

This paper investigates the verification and synthesis of parameterized protocols that satisfy global leadsto properties ${R}$ ⇝ Q on symmetric unidirectional rings (a.k.a. uni-rings) of deterministic and constant-space processes, where ${R}$ and ${Q}$ denote global state predicates. First, we show that verifying ${R}$ ⇝${Q}$ for parameterized protocols on symmetric uni-rings is undecidable, even for deterministic and constant-space processes, and conjunctive state predicates. Then, we show that surprisingly synthesizing symmetric uni-ring protocols that satisfy ${R}$ ⇝ Q is actually decidable. We identify necessary and sufficient conditions for the decidability of synthesis based on which we devise a sound and complete algorithm that takes the predicates ${R}$ and ${Q}$, and automatically generates a parameterized protocol that satisfies ${R}$ ⇝ Q for unbounded (but finite) ring sizes. We use our algorithm to synthesize some parameterized protocols, including an agreement protocol.
A Similarity Measure for GPU Kernel Subgraph Matching

Accelerator architectures specialize in executing SIMD (single instruction, multiple data) in lockstep. Because the majority of CUDA applications are parallelized loops, control flow information can provide an in-depth characterization of a kernel. CUDAflow is a tool that statically separates CUDA binaries into basic block regions and dynamically measures instruction and basic block frequencies. CUDAflow captures this information in a control flow graph (CFG) and performs subgraph matching across various kernel’s CFGs to gain insights into an application’s resource requirements, based on the shape and traversal of the graph, instruction operations executed and registers allocated, among other information. The utility of CUDAflow is demonstrated with SHOC and Rodinia application case studies on a variety of GPU architectures, revealing novel control flow characteristics that facilitate end users, autotuners, and compilers in generating high performing code.
Molecular profiles of matched primary and metastatic tumor samples support a linear evolutionary model of breast cancer

The interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a linear, branching evolutionary model with two distinct trajectories for malignant progression. Here, we used the progression model as a foundation to investigate the relationships between matched primary and metastasis breast tumor samples. Mapping paired data onto the model confirmed that molecular breast cancer subtypes can shift during progression and supported directional tumor evolution through luminal subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a roadmap of breast cancer progression will facilitate the development of improved cancer diagnostics, prognostics, and targeted therapeutics. SIGNIFICANCE: Analysis of matched primary and metastatic tumor samples supports a unidirectional, linear cancer evolution process and sheds light on longstanding issues regarding the origins of molecular subtypes and their progression relationships.
Giant polarization charge density at lattice-matched GaN/ScN interfaces

Rock-salt ScN is a semiconductor with a small lattice mismatch to wurtzite GaN. Within the modern theory of polarization, ScN has a nonvanishing formal polarization along the [111] direction. As a result, we demonstrate that an interface between (0001) GaN and (111) ScN exhibits a large polarization discontinuity of −1.358 Cm − 2. Interfaces between ScN and wurtzite III-nitrides will exhibit a high-density electron gas at the ( 000 1 ¯) GaN interface or a hole gas at the (0001) GaN interface, with carrier concentrations up to 8.5 × 10 14 cm−2. The large polarization difference and small strain make ScN a desirable choice for polarization-enhanced tunnel junctions within the III-nitride materials system. The large sheet carrier densities may also be useful for contacts or current spreading layers.
Natural By-Passing of Sand at Coastal Inlets

At coastal inlets two main principles in by-passing of littoral-drift sand by natural action occur. These are by-passing on offshore bar and by-passing by tidal flow action. This paper examines the...
The scope of political jurisdictions and violence: theory and evidence from Africa

Is there more violence in areas with many small countries or only a single large one? I build on Bernholz (The international game of power: past, present and future 1985) to create a unifying framework where both internal and external contestants engage in conflict, and then summarize how the spatial configuration of countries affects all types of violence with the Herfindahl–Hirschman Index of state sizes. Empirically, I examine fatalities from the conflict in Africa, where I use the borders set by the colonial powers of Europe to identify the effect of concentration. I find the most fatalities in areas with many small countries, but that violence decreases with concentration at a decreasing rate and eventually increases in areas with only one large country. These findings suggest an important difference between the observed average effect of concentration on violence and the expected marginal effects of further concentration.
The ``Great Debate'': The case for AGNs

We summarize the evidence from multiwavelength observations that the dominant power source in the majority of ultraluminous infrared galaxies (ULIGs) may be an active galactic nucleus (AGN). In the broader context of the debate, we also show that –- 1. ULIGs are indeed a key stage in the transformation of merging gas-rich disks into ellipticals,2. ULIGs are plausibly the precursors of quasi-stellar objects (QSOs), and 3. ULIGs do appear to be local templates of the high luminosity tail of major gas-rich mergers at z ∼ 1–4.
Drones in Distress: A Game-Theoretic Countermeasure for Protecting UAVs Against GPS Spoofing

One prominent security threat that targets unmanned aerial vehicles (UAVs) is the capture via global positioning system (GPS) spoofing in which an attacker manipulates a UAV’s GPS signals in order to capture it. Given the anticipated widespread deployment of UAVs for various purposes, it is imperative to develop new security solutions against such attacks. In this article, a mathematical framework is introduced for analyzing and mitigating the effects of GPS spoofing attacks on UAVs. In particular, system dynamics are used to model the optimal routes that the UAVs will adopt to reach their destinations. The GPS spoofer’s effect on each UAV’s route is also captured by the model. To this end, the spoofer’s optimal imposed locations on the UAVs, are analytically derived; allowing the UAVs to predict their traveling routes under attack. Then, a countermeasure mechanism is developed to mitigate the effect of the GPS spoofing attack. The countermeasure is built on the premise of cooperative localization, in which a UAV can determine its location using nearby UAVs instead of the possibly compromised GPS locations. To better utilize the proposed defense mechanism, a dynamic Stackelberg game is formulated to model the interactions between a GPS spoofer and a drone operator. In particular, the drone operator acts as the leader that determines its optimal strategy in light of the spoofer’s expected response strategy. The equilibrium strategies of the game are then analytically characterized and studied through a novel proposed algorithm. The simulation results show that, when combined with the Stackelberg strategies, the proposed defense mechanism will outperform baseline strategy selection techniques in terms of reducing the possibility of UAV capture.
Answering Impossible Questions: Content Governance in an Age of Disinformation

The governance of online platforms has unfolded across three eras – the era of Rights (which stretched from the early 1990s to about 2010), the era of Public Health (from 2010 through the present), and the era of Process (of which we are now seeing the first stirrings). Rights-era conversations and initiatives amongst regulators and the public at large centered dominantly on protecting nascent spaces for online discourse against external coercion. The values and doctrine developed in the Rights era have been vigorously contested in the Public Health era, during which regulators and advocates have focused (with minimal success) on establishing accountability for concrete harms arising from online content, even where addressing those harms would mean limiting speech. In the era of Process, platforms, regulators, and users must transcend this stalemate between competing values frameworks, not necessarily by uprooting Rights-era cornerstones like CDA 230, but rather by working towards platform governance processes capable of building broad consensus around how policy decisions are made and implemented. Some first steps in this direction, preliminarily explored here, might include making platforms "information" or “content” fiduciaries, delegating certain key policymaking decisions to entities outside of the platforms themselves, and systematically archiving data and metadata about disinformation detected and addressed by platforms.
From high-entropy ceramics to compositionally-complex ceramics: A case study of fluorite oxides

Abstract Using fluorite oxides as an example, this study broadens high-entropy ceramics (HECs) to compositionally-complex ceramics (CCCs) or multi-principal cation ceramics (MPCCs) to include medium-entropy and/or non-equimolar compositions. Nine compositions of compositionally-complex fluorite oxides (CCFOs) with the general formula of (Hf1/3Zr1/3Ce1/3)1-x(Y1/2X1/2)xO2-δ (X = Yb, Ca, and Gd; x = 0.4, 0.148, and 0.058) are fabricated. The phase stability, mechanical properties, and thermal conductivities are measured. Compared with yttria-stabilized zirconia, these CCFOs exhibit increased cubic phase stability and reduced thermal conductivity, while retaining high Young’s modulus (∼210 GPa) and nanohardness (∼18 GPa). Moreover, the temperature-dependent thermal conductivity in the non-equimolar CCFOs shows an amorphous-like behavior. In comparison with their equimolar high-entropy counterparts, the medium-entropy non-equimolar CCFOs exhibit even lower thermal conductivity (k) while maintaining high modulus (E), thereby achieving higher E/k ratios. These results suggest a new direction to achieve thermally-insulative yet stiff CCCs (MPCCs) via exploring non-equimolar and/or medium-entropy compositions.
Lorcaserin maintenance fails to attenuate heroin vs. food choice in rhesus monkeys.

Abstract Background The current opioid crisis has reinvigorated preclinical research in the evaluation of non-opioid candidate treatments for opioid use disorder (OUD). Emerging evidence suggests 5-HT2C receptor agonists may attenuate the abuse-related effects of opioids. This study evaluated effectiveness of 7-day treatment with the clinically available 5-HT2C agonist lorcaserin (Belviq®) on heroin-vs.-food choice in rhesus monkeys. Lorcaserin effects were compared to effects produced by 7-day saline substitution and by 7-day treatment with the opioid antagonist naltrexone. Methods Adult male (1) and female (6) rhesus monkeys were trained to respond under a concurrent schedule of food delivery (1 g pellets, fixed-ratio 100 schedule) and intravenous heroin injections (0-0.032 mg/kg/injection, fixed-ratio 10 schedule) during daily 2 h sessions. Heroin choice dose-effect functions were determined daily before and following 7-day saline substitution or 7-day continuous treatment with naltrexone (0.0032-0.032 mg/kg/h, IV) or lorcaserin (0.032-0.32 mg/kg/h, IV). Results Under baseline conditions, increasing heroin doses maintained a dose-dependent increase in heroin choice. Both saline substitution and 7-day naltrexone treatment significantly attenuated heroin choice and produced a reciprocal increase in food choice. Continuous lorcaserin (0.32 mg/kg/h) treatment significantly increased heroin choice. Conclusions In contrast to saline substitution and naltrexone, lorcaserin treatment was ineffective to reduce heroin-vs.-food choice. These preclinical results do not support the therapeutic potential and continued evaluation of lorcaserin as a candidate OUD treatment.
An Oral Inoculation Infant Rabbit Model for Shigella Infection.

ABSTRACT Shigella species cause diarrheal disease globally. Shigellosis is typically characterized by bloody stools and colitis with mucosal damage and is the leading bacterial cause of diarrheal death worldwide. After the pathogen is orally ingested, it invades and replicates within the colonic epithelium through mechanisms that rely on its type III secretion system (T3SS). Currently, oral infection-based small animal models to study the pathogenesis of shigellosis are lacking. Here, we found that orogastric inoculation of infant rabbits with Shigella flexneri resulted in diarrhea and colonic pathology resembling that found in human shigellosis. Fasting animals prior to S. flexneri inoculation increased the frequency of disease. The pathogen colonized the colon, where both luminal and intraepithelial foci were observed. The intraepithelial foci likely arise through S. flexneri spreading from cell to cell. Robust S. flexneri intestinal colonization, invasion of the colonic epithelium, and epithelial sloughing all required the T3SS as well as IcsA, a factor required for bacterial spreading and adhesion in vitro. Expression of the proinflammatory chemokine interleukin 8 (IL-8), detected with in situ mRNA labeling, was higher in animals infected with wild-type S. flexneri versus mutant strains deficient in icsA or T3SS, suggesting that epithelial invasion promotes expression of this chemokine. Collectively, our findings suggest that oral infection of infant rabbits offers a useful experimental model for studies of the pathogenesis of shigellosis and for testing of new therapeutics. IMPORTANCEShigella species are the leading bacterial cause of diarrheal death globally. The pathogen causes bacillary dysentery, a bloody diarrheal disease characterized by damage to the colonic mucosa and is usually spread through the fecal-oral route. Small animal models of shigellosis that rely on the oral route of infection are lacking. Here, we found that orogastric inoculation of infant rabbits with S. flexneri led to a diarrheal disease and colonic pathology reminiscent of human shigellosis. Diarrhea, intestinal colonization, and pathology in this model were dependent on the S. flexneri type III secretion system and IcsA, canonical Shigella virulence factors. Thus, oral infection of infant rabbits offers a feasible model to study the pathogenesis of shigellosis and to develop and test new therapeutics.
Complement-dependent synapse loss and microgliosis in a mouse model of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory, neurodegenerative disease of the CNS characterized by both grey and white matter injury. Microglial activation and a reduction in synaptic density are key features of grey matter pathology that can be modeled with MOG35-55 experimental autoimmune encephalomyelitis (EAE). Complement deposition combined with microglial engulfment has been shown during normal development and in disease as a mechanism for pruning synapses. We tested whether there is excess complement production in the EAE hippocampus and whether complement-dependent synapse loss is a source of degeneration in EAE using C1qa and C3 knockout mice. We found that C1q and C3 protein and mRNA levels were elevated in EAE mice. Genetic loss of C3 protected mice from EAE-induced synapse loss, reduced microglial activation, decreased the severity of the EAE clinical score, and protected memory/freezing behavior after contextual fear conditioning. C1qa KO mice with EAE showed little to no change on these measurements compared to WT EAE mice. Thus, pathologic expression and activation of the early complement pathway, specifically at the level of C3, contributes to hippocampal grey matter pathology in the EAE.
Destination Intentions of Unauthorized Mexican Border Crossers and Familial Ties to US Citizens

Drawing on random surveys of over 1,100 recently repatriated unauthorized Mexican migrants (the Migrant Border Crossing Study), we examine the relationships between individual-level factors and una...
A Temporally-Aware Interpolation Network for Video Frame Inpainting.

We propose the first deep learning solution to video frame inpainting, a more challenging but less ambiguous task than related problems such as general video inpainting, frame interpolation, and video prediction. We devise a pipeline composed of two modules: a bidirectional video prediction module and a temporally-aware frame interpolation module. The prediction module makes two intermediate predictions of the missing frames, each conditioned on the preceding and following frames respectively, using a shared convolutional LSTM-based encoder-decoder. The interpolation module blends the intermediate predictions, using time information and hidden activations from the video prediction module to resolve disagreements between the predictions. Our experiments demonstrate that our approach produces more accurate and qualitatively satisfying results than a state-of-the-art video prediction method and many strong frame inpainting baselines. Our code is available at https://github.com/sunxm2357/TAI_video_frame_inpainting.
The Zak transform and representations induced from characters of an abelian subgroup

We consider a variant of the Zak transform for a finite group G with respect to a fixed abelian subgroup H, and demonstrate a relationship with representations of G induced from characters of H. We also show how the Zak transform can be used to study right translations by H in L2(G), and give some examples of applications for equiangular tight frames.The purpose of this note is to demonstrate some connections between the Zak transform and the theory of induced representations. We also show some applications for right shift-invariant spaces, and for equiangular tight frames that occur as orbits of induced representations. For the sake of clarity, we restrict our attention to the setting of finite groups, where we can safely ignore convergence issues. However, the results in Sections I and II should also hold (with suitable modification) on locally compact groups.
Reformulating Bell's theorem: The search for a truly local quantum theory

Abstract The apparent nonlocality of quantum theory has been a persistent concern. Einstein et al. (1935) and Bell (1964) emphasized the apparent nonlocality arising from entanglement correlations. While some interpretations embrace this nonlocality, modern variations of the Everett-inspired many worlds interpretation try to circumvent it. In this paper, we review Bell's “no-go” theorem and explain how it rests on three axioms, local causality, no superdeterminism, and one world. Although Bell is often taken to have shown that local causality is ruled out by the experimentally confirmed entanglement correlations, we make clear that it is the conjunction of the three axioms that is ruled out by these correlations. We then show that by assuming local causality and no superdeterminism, we can give a direct proof of many worlds. The remainder of the paper searches for a consistent, local, formulation of many worlds. We show that prominent formulations whose ontology is given by the wave function violate local causality, and we critically evaluate claims in the literature to the contrary. We ultimately identify a local many worlds interpretation that replaces the wave function with a separable Lorentz-invariant wave-field. We conclude with discussions of the Born rule, and other interpretations of quantum mechanics.
Providing Insight into the Relationship Between Constructed Response Questions and Multiple Choice Questions in Introduction to Computer Programming Courses

This Research-to-Practice Work in Progress (WIP) investigates the format of student assessment questions. In particular, the focus is on the relationship between student performance on open-ended, constructed-response questions (CRQs) versus close-ended, multiple-choice-response questions (MCQs) in first-year introductory programming courses. We introduce a study to evaluate whether these different response formats return distinct or comparable results. In order to assess this, we compare and correlate student scores on each question type. Our focus is on assessments (exams and tests) in first-year classes. The paper investigates two first-year programming courses with a total of seven sections and approximately 180 combined students. The subject of the sequential set of courses is the procedural C programming language. Based on extant studies comparing student performance on MCQs to their performance on open-ended questions, we investigate whether MCQ scores predict CRQ scores. Preliminary results on the comparison between student performance on these two question formats are presented to assess whether MCQs produce similar results as CRQs, or whether MCQs yield unique contributions. Possible avenues for future work are also discussed.
Thalamocortical Anatomical Connectivity in Schizophrenia and Psychotic Bipolar Disorder.

Background Anatomical connectivity between the thalamus and cortex, including the prefrontal cortex (PFC), is abnormal in schizophrenia. Overlapping phenotypes, including deficits in executive cognitive abilities dependent on PFC-thalamic circuitry, suggest dysrupted thalamocortical anatomical connectivity may extend to psychotic bipolar disorder. We tested this hypothesis and examined the impact of illness stage to inform when in the illness course thalamocortical dysconnectivity emerges. Methods Diffusion-weighted imaging data were collected on 70 healthy individuals and 124 people with a psychotic disorder (schizophrenia spectrum = 75; psychotic bipolar disorder = 49), including 62 individuals in the early stage of psychosis. Anatomical connectivity between major divisions of the cortex and thalamus was quantified using probabilistic tractography and compared between groups. Associations between PFC-thalamic anatomical connectivity and executive cognitive abilities were examined using regression analysis. Results Psychosis was associated with lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity. Follow-up analyses established that lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity were present in both schizophrenia and psychotic bipolar disorder. Lower PFC-thalamic anatomical connectivity was also present in early-stage and chronic psychosis. Contrary to expectations, lower PFC-thalamic anatomical connectivity was not associated with impaired executive cognitive abilities. Conclusions Altered thalamocortical anatomical connectivity, especially reduced PFC-thalamic connectivity, is a transdiagnostic feature of psychosis detectable in the early stage of illness. Further work is required to elucidate the functional consequences of the full spectrum of thalamocortical connectivity abnormalities in psychosis.
Blind Inference of Centrality Rankings from Graph Signals

We study the blind centrality ranking problem, where our goal is to infer the eigenvector centrality ranking of nodes solely from nodal observations, i.e., without information about the topology of the network. We formalize these nodal observations as graph signals and model them as the outputs of a network process on the underlying (unobserved) network. A simple spectral algorithm is proposed to estimate the leading eigenvector of the associated adjacency matrix, thus serving as a proxy for the centrality ranking. A finite rate performance analysis of the algorithm is provided, where we find a lower bound on the number of graph signals needed to correctly rank (with high probability) two nodes of interest. We then specialize our general analysis for the particular case of dense Erdős-Renyi graphs, where existing graph-theoretical results can be leveraged. Finally, we illustrate the proposed algorithm via numerical experiments on synthetic and real-world networks, with special emphasis on how the network features influence the performance.
Towards an Intelligent Microscope: Adaptively Learned Illumination for Optimal Sample Classification

Recent machine learning techniques have dramatically changed how we process digital images. However, the way in which we capture images is still largely driven by human intuition and experience. This restriction is in part due to the many available degrees of freedom that alter the image acquisition process (lens focus, exposure, filtering, etc). Here we focus on one such degree of freedom - illumination within a microscope - which can drastically alter information captured by the image sensor. We present a reinforcement learning system that adaptively explores optimal patterns to illuminate specimens for immediate classification. The agent uses a recurrent latent space to encode a large set of variably-illuminated samples and illumination patterns. We train our agent using a reward that balances classification confidence with image acquisition cost. By synthesizing knowledge over multiple snapshots, the agent can classify on the basis of all previous images with higher accuracy than from naively illuminated images, thus demonstrating a smarter way to physically capture task-specific information.
Distributionally robust optimization with decision dependent ambiguity sets

We study decision dependent distributionally robust optimization models, where the ambiguity sets of probability distributions can depend on the decision variables. These models arise in situations with endogenous uncertainty. The developed framework includes two-stage decision dependent distributionally robust stochastic programming as a special case. Decision dependent generalizations of five types of ambiguity sets are considered. These sets are based on bounds on moments, covariance matrix, Wasserstein metric, Phi-divergence and Kolmogorov–Smirnov test. For the finite support case, we use linear, conic or Lagrangian duality to give reformulations of these models with a finite number of constraints. Reformulations are also given for the continuous support case for moment, covariance, Wasserstein and Kolmogorov–Smirnov based models. These reformulations allow solutions of such problems using global optimization techniques within the framework of a cutting surface algorithm. The importance of decision dependence in the ambiguity set is demonstrated with the help of a numerical example modeling simultaneous determination of order quantity and selling price for a newsvendor problem.
Encapsulating Knowledge: The Direct Reading Spectrometer

The direct reading emission spectrometer was developed during the1940s. By substituting photo-multiplier tubes and electronics forphotographic film spectrograms, the interpretation of special lineswith a densitometer was avoided. Instead, the instrument providedthe desired information concerning percentage concentration ofelements of interest directly on a dial. Such instruments `de-skill' the job of making such measurements. They do this by encapsulatingin the instrument the skills previously employed by the analyst,by `skilling' the instrument. This paper presents a history of thedevelopment of the Dow Chemical/Baird Associates direct reader. Thishistory is used to argue for a materialist conception of knowledge.The instrument is a material form of knowledge, knowledge of aspectsof spectroscopy, analytical spectrochemistry, electronics, instrumentdesign and construction, and metal production industry economics.
No pharmacodynamic (PD) and pharmacokinetic (PK) interaction of riociguat (BAY 63-2521) and aspirin

Objectives: Riociguat, an oral soluble guanylate cyclase (sGC) stimulator, is a new candidate for treatment of pulmonary hypertension (PH). Riociguat increases cGMP production through a novel dual mode of action: direct NO-independent stimulation of sGC; and increasing sensitivity of sGC to low levels of NO. Riociguat and aspirin are likely to be used together in PH. This randomized, open-label, crossover study investigated potential PD and PK interactions between the 2 drugs. Methods: Participants took 2.5 mg/day riociguat, two morning doses of 500 mg aspirin, or both treatments concomitantly. Results: Eighteen healthy men (mean age 34.8 years) were enrolled. Six of 17 participants in the safety evaluation reported ≥1 treatment-emergent adverse event (AE). All AEs were mild except 1 case of moderate headache following riociguat administration. Fifteen participants were valid for PD/PK analysis. Riociguat PK were independent of aspirin coadministration. One hour after coadministration of riociguat and aspirin, the mean increase in fraction unbound was 19% for riociguat and 24% for its metabolite M-1 (BAY 60-4552) indicating mild displacement by salicylic acid, the main aspirin metabolite. Effects of aspirin on bleeding time, platelet aggregation and plasma thromboxane B2 were not affected by concomitant riociguat. Riociguat alone had no effect on PD variables. Conclusion: Riociguat demonstrated no clinically relevant PD or PK interaction with aspirin. Coadministration of riociguat and aspirin does not require dose adjustment. Phase 3 randomized controlled trials are investigating riociguat in chronic thromboembolic pulmonary hypertension or pulmonary arterial hypertension.
Gold Sterilization and the Recession of 1937-38

The recession of 1937–8 is often cited as illustrating the dangers of withdrawing fiscal and monetary stimulus too early in a weak recovery. Yet our understanding of this severe downturn is incomplete: existing studies find that changes in fiscal policy were small in comparison to the magnitude of the downturn and that higher reserve requirements were not binding on banks. This article focuses on a neglected change in monetary policy, the sterilization of gold inflows during 1937, and finds that it exerted a powerful contractionary force during this period. The transmission of this monetary shock to the real economy appears to have worked through lower asset (equity) prices and higher interest rates.
Do Banks Pass Through Credit Expansions to Consumers Who Want to Borrow

We examine the ability of policymakers to stimulate household spending during the Great Recession by reducing banks’ cost of funds. Using panel data on 8.5 million credit cards and 743 credit limit regression discontinuities, we find that the one-year marginal propensity to borrow (MPB) is declining in credit score, falling from 59% for consumers with FICO scores below 660 to essentially zero for consumers with FICO scores above 740. We use the same credit limit discontinuities, combined with a model of lending, to estimate banks’ marginal propensity to lend (MPL) out of a decrease in their cost of funds. For the lowest FICO score consumers, higher credit limits sharply reduce profits from lending, limiting banks’ incentives to pass through credit expansions to these consumers. We conclude that banks’ MPL is lowest for consumers with the highest MPB and discuss the implications for policies that aim to stimulate the economy through banks.
Survey Sampling Procedures

Survey sampling provides procedures to estimate characteristics of a population based on a sample. Questionnaire design, collection of sample information, sampling methods, and sample size are discussed. Keywords: population; sample; frame; questionnaire design; sampling methods; sample size
The Development of Systems for On-Line Mathematics at Harvard

Project TACT (Technological Aids to Creative Thought), in the Aiken Computation Laboratory of Harvard University, has been designing, implementing, and using on-line systems since 1964. Our investigation has concentrated on a rather small class of interactive systems which are "dedicated," that is, tailored to provide a coherent set of tools for mathematical assistance, and which use fairly powerful terminal facilities: display scopes and natural input.
Chapter 10 – Propellers

Classical momentum theory is applied to the ideal propeller, called an actuator disc, to predict thrust and power performance. A more detailed analysis using blade element theory is used to determine the detailed characteristics of the propeller. The thrust, torque, and power coefficients, the advance ratio, and the blade activity factor are introduced to facilitate use of standard propeller performance charts and the associated empirical methods for performance estimation and propeller selection are discussed. The concept of a variable speed propeller is introduced and the basic method of propeller selection is also introduced. Ducted propellers are described and the performance enhancement they provide is discussed. The turboprop, a combination of the propeller and the gas turbine engine, is analyzed and discussed. Geared turbofan and open rotor engines which possess very high bypass ratios and lie somewhere between conventional turbofans and turboprops are considered.
Learning to Bound the Multi-Class Bayes Error

In the context of supervised learning, meta learning uses features, metadata and other information to learn about the difficulty, behavior, or composition of the problem. Using this knowledge can be useful to contextualize classifier results or allow for targeted decisions about future data sampling. In this paper, we are specifically interested in learning the Bayes error rate (BER) based on a labeled data sample. Providing a tight bound on the BER that is also feasible to estimate has been a challenge. Previous work [1] has shown that a pairwise bound based on the sum of Henze-Penrose (HP) divergence over label pairs can be directly estimated using a sum of Friedman-Rafsky (FR) multivariate run test statistics. However, in situations in which the dataset and number of classes are large, this bound is computationally infeasible to calculate and may not be tight. Other multi-class bounds also suffer from computationally complex estimation procedures. In this paper, we present a generalized HP divergence measure that allows us to estimate the Bayes error rate with log-linear computation. We prove that the proposed bound is tighter than both the pairwise method and a bound proposed by Lin [2] . We also empirically show that these bounds are close to the BER. We illustrate the proposed method on the MNIST dataset, and show its utility for the evaluation of feature reduction strategies. We further demonstrate an approach for evaluation of deep learning architectures using the proposed bounds.
Does publicly subsidized health insurance affect the birth rate

The affordable care act (ACA) greatly expanded subsidized health insurance opportunities for low‐income childless women through Medicaid and the Marketplace. This insurance provides better access to prescription‐based contraception, which could reduce the number of births. At the same time, it lowers childbirth costs for women who previously would not have qualified for Medicaid‐paid pregnancies. I examine how Medicaid and non‐Medicaid subsidized insurance (NMSI) eligibility have impacted insurance enrollment and the birth rate for childless women from 2011 through 2016 using the American Community Survey and birth information from the Vital Statistics. To estimate the causal effects of subsidized insurance, I use simulated eligibility to utilize variation in the timing and income eligibility thresholds for Medicaid, the Marketplace, and other pre‐ACA state subsidized insurance programs. My results indicate expanding Medicaid had no significant effect on the birth rate, but that a 10 percentage point increase in NMSI eligibility increased the birth rate between 1.60 and 2.30%, depending on the age group. These findings indicate that expanding Medicaid to childless adults did not produce cost savings from fewer Medicaid paid births, but improvements in the nongroup insurance market increased births.
The effects of smartphones on well-being: theoretical integration and research agenda.

As smartphones become ever more integrated in people’s lives, a burgeoning new area of research has emerged on their well-being effects. We propose that disparate strands of research and apparently contradictory findings can be integrated under three basic hypotheses, positing that smartphones influence well-being by (1) replacing other activities (displacement hypothesis), (2) interfering with concurrent activities (interference hypothesis), and (3) affording access to information and activities that would otherwise be unavailable (complementarity hypothesis). Using this framework, we highlight methodological issues and go beyond net effects to examine how and when phones boost versus hurt well-being. We examine both psychological and contextual mediators and moderators of the effects, thus outlining an agenda for future research.
Individual Preference Aware Caching Policy Design in Wireless D2D Networks

Cache-aided wireless device-to-device (D2D) networks allow significant throughput increase, depending on the concentration of the popularity distribution of files. Many studies assume that all users have the same preference distribution; however, this may not be true in practice. This work investigates whether and how the information about individual preferences can benefit cache-aided D2D networks. We examine a clustered network and derive a network utility that considers both the user distribution and channel fading effects into the analysis. We also formulate a utility maximization problem for designing caching policies. This maximization problem can be applied to optimize several important quantities, including throughput, energy efficiency (EE), cost, and hit-rate, and to solve different tradeoff problems. We provide a general approach that can solve the proposed problem under the assumption that users coordinate, then prove that the proposed approach can obtain the stationary point under a mild assumption. Using simulations of practical setups, we show that performance can improve significantly with proper exploitation of individual preferences. We also show that different types of tradeoffs exist between different performance metrics and that they can be managed through caching policy and cooperation distance designs.
How do Data Science Workers Collaborate? Roles, Workflows, and Tools

Today, the prominence of data science within organizations has given rise to teams of data science workers collaborating on extracting insights from data, as opposed to individual data scientists working alone. However, we still lack a deep understanding of how data science workers collaborate in practice. In this work, we conducted an online survey with 183 participants who work in various aspects of data science. We focused on their reported interactions with each other (e.g., managers with engineers) and with different tools (e.g., Jupyter Notebook). We found that data science teams are extremely collaborative and work with a variety of stakeholders and tools during the six common steps of a data science workflow (e.g., clean data and train model). We also found that the collaborative practices workers employ, such as documentation, vary according to the kinds of tools they use. Based on these findings, we discuss design implications for supporting data science team collaborations and future research directions.
Temporal flexibility in the structure of plant–pollinator interaction networks

Abstract Ecological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.
Aspects of Quark Orbital Angular Momentum

The difference between the quark orbital angular momentum (OAM) defined in light-cone gauge (Jaffe-Manohar) compared to defined using a local manifestly gauge invariant operator (Ji) is interpreted in terms of the change in quark OAM as the quark leaves the target in a DIS experiment. We also discuss the possibility to measure quark OAM directly using twist 3 GPDs, and to calculate quark OAM in lattice QCD.