cssi/SciSciGPT-SciSciNet huggingface dataset:
The linearity of the Mitchell order

We show from an abstract comparison principle (the Ultrapower Axiom) that the Mitchell order is linear on sufficiently strong ultrafilters: normal ultrafilters, Dodd solid ultrafilters, and assuming GCH, generalized normal ultrafilters. This gives a conditional answer to the well-known question of whether a 2κ-supercompact cardinal κ must carry more than one normal measure of order 0. Conditioned on a very plausible iteration hypothesis, the answer is no, since the Ultrapower Axiom holds in the canonical inner models at the finite levels of supercompactness.
FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension

This paper introduces a new neural structure called FusionNet, which extends existing attention approaches from three perspectives. First, it puts forward a novel concept of “history of word” to characterize attention information from the lowest word-level embedding up to the highest semantic-level representation. Second, it identifies an attention scoring function that better utilizes the “history of word” concept. Third, it proposes a fully-aware multi-level attention mechanism to capture the complete information in one text (such as a question) and exploit it in its counterpart (such as context or passage) layer by layer. We apply FusionNet to the Stanford Question Answering Dataset (SQuAD) and it achieves the first position for both single and ensemble model on the official SQuAD leaderboard at the time of writing (Oct. 4th, 2017). Meanwhile, we verify the generalization of FusionNet with two adversarial SQuAD datasets and it sets up the new state-of-the-art on both datasets: on AddSent, FusionNet increases the best F1 metric from 46.6% to 51.4%; on AddOneSent, FusionNet boosts the best F1 metric from 56.0% to 60.7%.
Non-Abelian Topological Order on the Surface of a 3D Topological Superconductor from an Exactly Solved Model

The surface electronic structure of a three-dimensional topological superconductor is characterized by a Majorana cone---Majorana-fermion-like electronic excitations whose energies form a gapless continuum, rendering the surface conducting. It was believed that a gap in that electronic structure could only be created if time-reversal symmetry were broken. Theorists now show that, in the presence of strong electronic interaction, ``gapping'' and time-reversal symmetry can coexist if the surface has a special type of electronic excitations that are ``anyons.''
Simplified model and analysis of a pair of coupled thermo-optical MEMS oscillators

Motivated by the dynamics of microscale oscillators with thermo-optical feedback, a simplified third-order model capturing the key features of these oscillators is developed, where each oscillator consists of a displacement variable coupled to a temperature variable. Further, the dynamics of a pair of such oscillators coupled via a linear spring is analyzed. The analytical procedures used are the variational equation method and the two-variable expansion method. It is shown that the analytical results are in agreement with the results of numerical integration. The bifurcation structure of the system is revealed through a bifurcation diagram.
Phylogeny of Paullinia L. (Paullinieae: Sapindaceae), a diverse genus of lianas with dynamic fruit evolution

Abstract Paullinia L. is a genus of c. 220 mostly Neotropical forest-dwelling lianas that display a wide diversity of fruit morphologies. Paullinia resembles other members of the Paullinieae tribe in being a climber with stipulate compound leaves and paired inflorescence tendrils. However, it is distinct in having capsular fruits with woody, coriaceous, or crustaceous pericarps. While consistent in this basic plan, the pericarps of Paullinia fruits are otherwise highly variable—in some species they are winged, whereas in others they are without wings or covered with spines. With the exception of the water-dispersed indehiscent spiny fruits of some members of Paullinia sect. Castanella, all species are dehiscent, opening their capsules while they are still attached to the branch, to reveal arillate animal-dispersed seeds. Here we present a molecular phylogeny of Paullinia derived from 11 molecular markers, including nine newly-developed single-copy nuclear markers amplified by microfluidics PCR. This is the first broadly sampled molecular phylogeny for the genus. Paullinia is supported as monophyletic and is sister to Cardiospermum L., which together are sister to Serjania Mill + Urvillea Kunth. We apply this novel phylogenetic hypothesis to test previous infrageneric classifications and to infer that unwinged fruits represent the ancestral condition, from which there were repeated evolutionary transitions and reversals. However, because the seeds of both winged and unwinged fruits are dispersed by animals, we conclude that the repeated transitions in fruit morphology may relate to visual display strategies to attract animal dispersers, and do not represent transitions to wind dispersal.
Osteomyelitis of the ribs in children: a rare and potentially challenging diagnosis.

Rib osteomyelitis is rare in children and can mimic other pathologies. Imaging has a major role in the diagnosing rib osteomyelitis. To evaluate clinical presentation and imaging findings in children with rib osteomyelitis. We performed a retrospective (2009–2018) study on children with rib osteomyelitis verified by either positive culture or pathology. We excluded children with multifocal osteomyelitis or empyema necessitans. We reviewed medical charts for clinical, laboratory and pathology data, and treatment. All imaging modalities for rib abnormalities were evaluated for presence and location of osteomyelitis and abscess. We calculated descriptive statistics to compare patient demographics, clinical presentation and imaging findings. The study group included 10 children (6 boys, 4 girls), with an average age of 7.3 years (range, 3 months to 15.9 years). The most common clinical presentations were fever (n=8) and pain (n=5). Eight children had elevated inflammatory indices (leukocytosis, erythrocyte sedimentation rate [ESR], C-reactive protein [CRP]). Localized chest wall swelling was found initially in six children and later in two more children. Rib osteomyelitis was suspected on presentation in only two children. All children had chest radiographs. Rib lytic changes were found on only one chest radiograph, in two of the four ultrasound studies, and in four of eight CTs. Bone marrow signal abnormalities were seen in all eight MRIs. In nine children the osteomyelitis involved the costochondral junction. Six children had an associated abscess. Staphylococcus aureus was cultured in eight children. Osteomyelitis was diagnosed based on pathology in one child with negative cultures. While rib osteomyelitis is rare, imaging findings of lytic changes at the costochondral junction combined with a history of fever, elevated inflammatory markers or localized soft-tissue swelling in the chest should raise suspicion for this disease.
Convergence of the Expectation-Maximization Algorithm Through Discrete-Time Lyapunov Stability Theory

In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space dynamical system. The EM algorithm is widely adopted for data clustering and density estimation in statistics, control systems, and machine learning. This algorithm belongs to a large class of iterative algorithms known as proximal point methods. In particular, we re-interpret limit points of the EM algorithm and other local maximizers of the likelihood function it seeks to optimize as equilibria in its dynamical system representation. Furthermore, we propose to assess its convergence as asymptotic stability in the sense of Lyapunov. As a consequence, we proceed by leveraging recent results regarding discrete-time Lyapunov stability theory in order to establish asymptotic stability (and thus, convergence) in the dynamical system representation of the EM algorithm.
Chromosomal rearrangements as a source of new gene formation in Drosophila yakuba

The origins of new genes are among the most fundamental questions in evolutionary biology. Our understanding of the ways that new genetic material appears and how that genetic material shapes population variation remains incomplete. De novo genes and duplicate genes are a key source of new genetic material on which selection acts. To better understand the origins of these new gene sequences, we explored the ways that structural variation might alter expression patterns and form novel transcripts. We provide evidence that chromosomal rearrangements are a source of novel genetic variation that facilitates the formation of de novo exons in Drosophila. We identify 51 cases of de novo exon formation created by chromosomal rearrangements in 14 strains of D. yakuba. These new genes inherit transcription start signals and open reading frames when the 5' end of existing genes are combined with previously untranscribed regions. Such new genes would appear with novel peptide sequences, without the necessity for secondary transitions from non-coding RNA to protein. This mechanism of new peptide formations contrasts with canonical theory of de novo gene progression requiring non-coding intermediaries that must acquire new mutations prior to loss via pseudogenization. Hence, these mutations offer a means to de novo gene creation and protein sequence formation in a single mutational step, answering a long standing open question concerning new gene formation. We further identify gene expression changes to 134 existing genes, indicating that these mutations can alter gene regulation. Population variability for chromosomal rearrangements is considerable, with 2368 rearrangements observed across 14 inbred lines. More rearrangements were identified on the X chromosome than any of the autosomes, suggesting the X is more susceptible to chromosome alterations. Together, these results suggest that chromosomal rearrangements are a source of variation in populations that is likely to be important to explain genetic and therefore phenotypic diversity.
Synthetic Lung Nodule 3D Image Generation Using Autoencoders

One of the challenges of using machine learning techniques with medical data is the frequent dearth of source image data on which to train. A representative example is automated lung cancer diagnosis, where nodule images need to be classified as suspicious or benign. In this work we propose an automatic synthetic lung nodule image generator. Our 3D shape generator is designed to augment the variety of 3D images. Our proposed system takes root in autoencoder techniques, and we provide extensive experimental characterization that demonstrates its ability to produce quality synthetic images.
Time-reversal invariant scaling of light propagation in one-dimensional non-Hermitian systems

We prove the existence of a universal scaling that gives identical transmittance and reflectance in time-reversed partner systems with arbitrary gain/loss profile. Such robust scaling generalizes the photon-flux conservation in non-Hermitian systems.
Transcriptomic data support a nocturnal bottleneck in the ancestor of gecko lizards

Abstract Gecko lizards are a species-rich clade of primarily-nocturnal squamate reptiles. In geckos, adaptations to nocturnality have dramatically reshaped the eye. Perhaps the most notable change is the loss of rod cells in the retina and subsequent “transmutation” of cones into a rod-like morphology and physiology. While many studies have noted the absence of some rod-specific genes, such as the visual pigment Rhodopsin (RH1), these studies have focused on just a handful of species that are nested deep in the gecko phylogeny. Thus, it is not clear whether these changes arose through convergence, are homologous and ubiquitous across geckos, or restricted to a subset of species. Here, we used de novo eye transcriptomes from five gecko species, and genomes from two additional gecko species, representing the breadth of extant gecko diversity (i.e. 4 of the 7 gecko families, spanning the deepest divergence of crown Gekkota), to show that geckos lost expression of almost the entire suite of necessary rod-cell phototransduction genes in the eye, distinct from all other squamate reptiles. Geckos are the first vertebrate group to have lost their complete rod-cell expression pathway, not just the visual pigment. In addition, all sampled species have also lost expression of the cone-opsin SWS2 visual pigment. These results strongly suggest a single loss of rod cells and subsequent cone-to-rod transmutation that occurred prior to the diversification of extant geckos.
The Equity Premium and the One Percent

We show that in a general equilibrium model with heterogeneity in risk aversion or belief, shifting wealth from an agent who holds comparatively fewer stocks to one who holds more reduces the equity premium. Since empirically the rich hold more stocks than do the poor, the top income share should predict subsequent excess stock market returns. Consistent with our theory, we find that when the income share of top earners in the U.S. rises, subsequent one year excess market returns significantly decline. This negative relation is robust to (i) controlling for classic return predictors such as the price-dividend and consumption-wealth ratios, (ii) predicting out-of-sample, and (iii) instrumenting with changes in estate tax rates. Cross-country panel regressions suggest that the inverse relation between inequality and returns also holds outside of the U.S., with stronger results in relatively closed economies (emerging markets) than in small open economies (Europe).
TGF-β Signaling in Cellular Senescence and Aging-Related Pathology.

Aging is broadly defined as the functional decline that occurs in all body systems. The accumulation of senescent cells is considered a hallmark of aging and thought to contribute to the aging pathologies. Transforming growth factor-β (TGF-β) is a pleiotropic cytokine that regulates a myriad of cellular processes and has important roles in embryonic development, physiological tissue homeostasis, and various pathological conditions. TGF-β exerts potent growth inhibitory activities in various cell types, and multiple growth regulatory mechanisms have reportedly been linked to the phenotypes of cellular senescence and stem cell aging in previous studies. In addition, accumulated evidence has indicated a multifaceted association between TGF-β signaling and aging-associated disorders, including Alzheimer’s disease, muscle atrophy, and obesity. The findings regarding these diseases suggest that the impairment of TGF-β signaling in certain cell types and the upregulation of TGF-β ligands contribute to cell degeneration, tissue fibrosis, inflammation, decreased regeneration capacity, and metabolic malfunction. While the biological roles of TGF-β depend highly on cell types and cellular contexts, aging-associated changes are an important additional context which warrants further investigation to better understand the involvement in various diseases and develop therapeutic options. The present review summarizes the relationships between TGF-β signaling and cellular senescence, stem cell aging, and aging-related diseases.
Analysis of the Frequency and Detectability of Objects Resembling Nuclear/Radiological Threats in Commercial Cargo

AbstractThe detection of smuggled nuclear/radiological materials or weapons in commercial cargo remains a severe technical challenge due to the complexity of the global cargo network, sources of no...
Structural variants exhibit widespread allelic heterogeneity and shape variation in complex traits

It has been hypothesized that individually-rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. Here we identified more than 20,000 euchromatic SVs from 14 Drosophila melanogaster genome assemblies, of which ~40% are invisible to high specificity short-read genotyping approaches. SVs are common, with 31.5% of diploid individuals harboring a SV in genes larger than 5kb, and 24% harboring multiple SVs in genes larger than 10kb. SV minor allele frequencies are rarer than amino acid polymorphisms, suggesting that SVs are more deleterious. We show that a number of functionally important genes harbor previously hidden structural variants likely to affect complex phenotypes. Furthermore, SVs are overrepresented in candidate genes associated with quantitative trait loci mapped using the Drosophila Synthetic Population Resource. We conclude that SVs are ubiquitous, frequently constitute a heterogeneous allelic series, and can act as rare alleles of large effect.
Postexposure Effects of Vaccines on Infectious Diseases

We searched the PubMed database for clinical trials and observational human studies about postexposure vaccination effects, targeting infections with approved vaccines and vaccines licensed outside the United States against dengue, hepatitis E, malaria, and tick-borne encephalitis. Studies of animal models, serologic testing, and pipeline vaccines were excluded. Eligible studies were evaluated by definition of exposure; attempts to distinguish pre- and postexposure effects were rated on a scale of 1 to 4. We screened 4,518 articles and ultimately identified for this review 14 clinical trials and 31 observational studies spanning 7 of the 28 vaccine-preventable diseases. For secondary attack rate, the following medians were found for postexposure vaccination effectiveness: hepatitis A, 85% (interquartile range (IQR), 28; n = 5 sources); hepatitis B, 85% (IQR, 22; n = 5 sources); measles, 83% (IQR, 21; n = 8 sources); varicella, 67% (IQR: 48; n = 9 sources); smallpox, 45% (IQR, 39; n = 4 sources); and mumps, 38% (IQR, 7; n = 2 sources). For case fatality proportions resulting from rabies and smallpox, the median vaccine postexposure efficacies were 100% (IQR, 0; n = 6 sources) and 63% (IQR, 50; n = 8 sources), respectively. Many available vaccines can modify or preclude disease if administered after exposure. This postexposure effectiveness could be important to consider during vaccine trials and while developing new vaccines.
Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings.

Over the past year, the emergence of transfer learning with large-scale language models (LM) has led to dramatic performance improvements across a broad range of natural language understanding tasks. However, the size and memory footprint of these large LMs often makes them difficult to deploy in many scenarios (e.g. on mobile phones). Recent research points to knowledge distillation as a potential solution, showing that when training data for a given task is abundant, it is possible to distill a large (teacher) LM into a small task-specific (student) network with minimal loss of performance. However, when such data is scarce, there remains a significant performance gap between large pretrained LMs and smaller task-specific models, even when training via distillation. In this paper, we bridge this gap with a novel training approach, called generation-distillation, that leverages large finetuned LMs in two ways: (1) to generate new (unlabeled) training examples, and (2) to distill their knowledge into a small network using these examples. Across three low-resource text classification datsets, we achieve comparable performance to BERT while using 300 times fewer parameters, and we outperform prior approaches to distillation for text classification while using 3 times fewer parameters.
Shared mobility and urban form impacts: a case study of peer-to-peer (P2P) carsharing in the US

This paper advances the understanding of peer-to-peer (P2P) carsharing within the broader context of shared mobility and its connection to the built environment in the US through a survey conducted...
Risk factors and clinical characteristics of rectal prolapse in young patients.

Summary Background Rectal prolapse is a relatively common condition in children and elderly patients but uncommon in young adults less than 30 years old. The aim of this study is to identify risk factors and characteristics of rectal prolapse in this group of young patients and determine surgical outcome. Methods Adult patients younger than 30 years old with rectal prolapse treated surgically between September 1994 and September 2012 were identified from an IRB-approved database. Demographics, risk factors, associated conditions, clinical characteristics, surgical management and follow-up were recorded. Results Forty-four (females 32) patients were identified with a mean age of 23 years old. Eighteen (41%) had chronic psychiatric diseases requiring treatment and these patients experienced significantly more constipation than non-psychiatric patients (83% vs. 50%; P = 0.024). Thirteen (30%) patients had previous pelvic surgery. The most common symptom at presentation was a prolapsed rectum in 40 (91%) and hematochezia in 24 (55%). Twenty-four (55%) underwent a laparoscopic rectopexy, 14 (32%) open abdominal repair, and 6 (14%) had perineal surgery. The most common procedure was resection rectopexy in 21 (48%; 7 open; 14 laparoscopic). At a median follow-up of 11 (range 1–165) months, 6 patients (14%) developed a recurrence. Conclusions Medication induced constipation in psychiatric patients and possible pelvic floor weakness in patients with previous pelvic surgery may be contributing factors to rectal prolapse in this group of patients.
Load Balancing in Mobility-on-Demand Systems: Reallocation Via Parametric Control Using Concurrent Estimation

Mobility-on-Demand (MoD) systems require load balancing to maintain consistent service across regions with uneven demand subject to time-varying traffic conditions. The load-balancing objective is to jointly minimize the fraction of lost user requests due to vehicle unavailability and the fraction of time when vehicles drive empty during load balancing operations. In order to bypass the intractability of a globally optimal solution to this stochastic dynamic optimization problem, we propose a parametric threshold-based control driven by the vehicles available in and en route to each region. This is still a difficult parametric optimization problem for which one often resorts to trial-and-error methods where multiple sample paths are generated through simulation. In contrast, this paper utilizes concurrent estimation methods to simultaneously construct multiple sample paths from a single nominal sample path. The performance of the parametric controller for intermediate size systems is compared to that of a simpler single-parameter controller, a state-blind static controller, a policy of no control, and a theoretically-derived lower bound. Simulation results show the value of state information in improving performance.
Towards a Model to Appraise and Suggest Identifier Names

Unknowingly, identifiers in the source code of a software system play a vital role in determining the quality of the system. Ambiguous and confusing identifier names lead developers to not only misunderstand the behavior of the code but also increases comprehension time and thereby causes a loss in productivity. Even though correcting poor names through rename operations is a viable option for solving this problem, renaming itself is an act of rework and is not immune to defect injection. In this study, we aim to understand the motivations that drive developers to name and rename identifiers and the decisions they make in determining the name. Using our results, we propose the development of a linguistic model that determines identifier names based on the behavior of the identifier. As a prerequisite to constructing the model, we conduct multiple studies to determine the features that should feed into the model. In this paper, we discuss findings from our completed studies and justify the continuation of research on this topic through further studies.
Periodic particle arrangements using standing acoustic waves

We determine crystal-like materials that can be fabricated by using a standing acoustic wave to arrange small particles in a non-viscous liquid resin, which is cured afterwards to keep the particles in the desired locations. For identical spherical particles with the same physical properties and small compared to the wavelength, the locations where the particles are trapped correspond to the minima of an acoustic radiation potential which describes the net forces that a particle is subject to. We show that the global minima of spatially periodic acoustic radiation potentials can be predicted by the eigenspace of a small real symmetric matrix corresponding to its smallest eigenvalue. We relate symmetries of this eigenspace to particle arrangements composed of points, lines or planes. Since waves are used to generate the particle arrangements, the arrangement's periodicity is limited to certain Bravais lattice classes that we enumerate in two and three dimensions.
Veblen’s evolutionary methodology and its implications for heterodox economics in the calculable future

Critics have repeatedly claimed that heterodox economics has failed. They blame heterodox economists for their own failure. I subject this claim to critical examination from the perspective of Veblen’s evolutionary methodology. Veblen’s theory of the business enterprise will be used as an example, which exemplifies the case that a ‘blasphemous’ theory is ignored and marginalized even though it provides rich and perspicacious insights into the evolution of economy and society. It is also argued that social science does not follow the biological principle of natural selection and the survival of the fittest. What survives does not necessarily mean the fittest in the social realm. The history of science is replete with paradoxical incidents that an incoherent, irrelevant, or even wrong theory becomes dominant and widely accepted because it is one that serves the vested interests in academia and society. Economics is no exception.
Dynamically defined sequences with small discrepancy

We study the problem of constructing sequences $$(x_n)_{n=1}^{\infty }$$ on [0, 1] in such a way that $$\begin{aligned} D_N^* = \sup _{0 \le x \le 1} \left| \frac{ \#\left\{ 1 \le i \le N: x_i \le x \right\} }{N} - x \right| \end{aligned}$$is small. A result of Schmidt shows that for all sequences sequences $$(x_n)_{n=1}^{\infty }$$ on [0, 1] we have $$D_N^* \gtrsim (\log {N}) N^{-1}$$ for infinitely many N, several classical constructions attain this growth. We describe a type of uniformly distributed sequence that seems to be completely novel: given $$\left\{ x_1, \dots , x_{N-1} \right\} $$, we construct $$x_N$$ in a greedy manner $$\begin{aligned} x_N = \arg \min _{\min _k |x-x_k| \ge N^{-10}} \sum _{k=1}^{N-1}{1-\log {(2\sin {(\pi |x-x_k|)})}}. \end{aligned}$$We prove that $$D_N^* \lesssim (\log {N}) N^{-1/2}$$ and conjecture that $$D_N^* \lesssim (\log {N}) N^{-1}$$. Numerical examples illustrate this conjecture in a very impressive manner. We also establish a discrepancy bound $$D_N^* \lesssim (\log {N})^d N^{-1/2}$$ for an analogous construction in higher dimensions and conjecture it to be $$D_N^* \lesssim (\log {N})^d N^{-1}$$.
Mechanical and Electronic Properties of Diacetylene and Polydiacetylene Self-Assembled Monolayers on Au(111)

Polyacetylene materials, particularly two-dimensional polyacetylene thin films, have widespread applications in modern electronics and energy harvesting devices. One way to fabricate polyacetylene ...
Comment: Reflections on the Deconfounder

I would like to congratulate the authors on their illuminating article, and thank the editors for the opportunity to discuss the article. The deconfounder method that this article presents is appea...
IPO: Interior-Point Policy Optimization under Constraints.

In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints. We propose a novel first-order policy optimization method, Interior-point Policy Optimization (IPO), which augments the objective with logarithmic barrier functions, inspired by the interior-point method. Our proposed method is easy to implement with performance guarantees and can handle general types of cumulative multi-constraint settings. We conduct extensive evaluations to compare our approach with state-of-the-art baselines. Our algorithm outperforms the baseline algorithms, in terms of reward maximization and constraint satisfaction.
Pointwise bounds and blow-up for systems of nonlinear fractional parabolic inequalities

Abstract We investigate nonnegative nonlocal solutions u ( x , t ) and v ( x , t ) of the nonlinear system of inequalities 0 ≤ ( ∂ t − Δ ) α u ≤ v λ 0 ≤ ( ∂ t − Δ ) β v ≤ u σ in R n × R , n ≥ 1 satisfying the initial conditions u = v = 0 in R n × ( − ∞ , 0 ) where λ , σ , α , and β are positive constants. Specifically, using the definition of the fractional heat operator ( ∂ t − Δ ) α given in Taliaferro (2020), we obtain, when they exist, optimal pointwise upper bounds on R n × ( 0 , ∞ ) for nonnegative nonlocal solutions u and v of this initial value problem with particular emphasis on these bounds as t → 0 + and as t → ∞ . When α = β = 1 we compare our results for nonlocal solutions to those of Escobedo and Herrero (1991) for classical pointwise solutions.
ROUGH INTEGERS WITH A DIVISOR IN A GIVEN INTERVAL

We determine, up to multiplicative constants, the number of integers that have a divisor in and no prime factor . Our estimate is uniform in . We apply this to determine the order of the number of distinct integers in the multiplication table, which are free of prime factors , and the number of distinct fractions of the form with and .
Scheduling with Predictions and the Price of Misprediction

In many traditional job scheduling settings, it is assumed that one knows the time it will take for a job to complete service. In such cases, strategies such as shortest job first can be used to improve performance in terms of measures such as the average time a job waits in the system. We consider the setting where the service time is not known, but is predicted by for example a machine learning algorithm. Our main result is the derivation, under natural assumptions, of formulae for the performance of several strategies for queueing systems that use predictions for service times in order to schedule jobs. As part of our analysis, we suggest the framework of the "price of misprediction," which offers a measure of the cost of using predicted information.
Collectively fluctuating assets in the presence of arbitrage opportunities, and option pricing

Methods of functional analysis are applied to describe collectively fluctuating default-free pure discount bonds subject to trading-related noise which generates arbitrage opportunities. Two key elements of the model are: (i) the naturally incorporated fixed bond price at maturity which is achieved by making use of only those fluctuating paths of price motion which terminate at a specified final condition, and (ii) the most attractive arbitrage opportunities between bonds with close maturities, with modeled a local linear approximation. The model can be written in different closed forms as a stochastic partial differential equation. The functional Black–Scholes equation for contingent claims is derived, and a connection with the conventional methods of option valuation is indicated.
A generalization of Gelfand-Naimark-Stone duality to completely regular spaces

Abstract Gelfand-Naimark-Stone duality establishes a dual equivalence between the category KHaus of compact Hausdorff spaces and the category ubal of uniformly complete bounded archimedean l-algebras. We extend this duality to the category CReg of completely regular spaces. This we do by first introducing basic extensions of bounded archimedean l-algebras and generalizing Gelfand-Naimark-Stone duality to a dual equivalence between the category ubasic of uniformly complete basic extensions and the category Comp of compactifications of completely regular spaces. We then introduce maximal basic extensions and prove that the subcategory mbasic of ubasic consisting of maximal basic extensions is dually equivalent to the subcategory SComp of Comp consisting of Stone-Cech compactifications. This yields the desired dual equivalence for completely regular spaces since CReg is equivalent to SComp .
Buy-and-Hold and Constant-Mix May Be Better Allocation Strategies Than You Think

Given mean-reverting equity and interest rate uncertainty, this article shows a relatively low economic cost of using a simple allocation strategy, buy-and-hold or constant-mix, instead of optimal reallocation. Moreover, given the decision to use one of the simple allocation strategies, the article identifies (1) which investors will be better off with buy-and-hold than with constant-mix, and vice versa, and (2) which investors will be better off with a horizon-maturity fixed-income position than with a sequence of short-maturity ones, and vice versa. The article uses illustrations in a three-period binomial model to bridge the academic/practitioner gap and provide useful insights to those interested in applied investment management. TOPICS:Portfolio management/multi-asset allocation, portfolio theory, portfolio construction Key Findings • Given mean-reverting equity and uncertain interest rates, investors sacrifice little in expected utility by replacing the optimal reallocation strategy with a simpler allocation strategy of either buy-and-hold or constant-mix. • Traditional investors, with positive allocations to both equity and fixed income, are better off with constant-mix than with buy-and-hold and with allocating to a horizon-maturity fixed-income instrument rather than a sequence of single-period fixed-income instruments. • More risk-tolerant investors with levered equity positions are better off with buy-and-hold than with constant-mix and with levering by a sequence of single-period fixed-income instruments instead of a horizon-maturity fixed-income instrument.
Heating of Heavy Ions in Low-beta Compressible Turbulence

Enhancement of minor ions such as $^3$He and heavy ions in flare-associated solar energetic particle (SEP) events remains one of the major puzzles in heliophysics. In this work, we use 3D hybrid simulations (kinetic protons and fluid electrons) to investigate particle energization in a turbulent low-beta environment similar to solar flares. It is shown that in this regime the injected large-amplitude Alfven waves develop into compressible and anisotropic turbulence, which efficiently heats thermal ions of different species. We find that temperature increase of heavy ions is inversely proportional to the charge to mass ratio, which is consistent with observations of impulsive SEP events. Further analysis reveals that ions are energized by interacting with nearly perpendicular magnetosonic waves near proton inertial scale.
Bias and stereotyping among research and clinical professionals: Perspectives on minority recruitment for oncology clinical trials.

Background In recent years, extensive attention has been paid to the possibility that bias among health care professionals contributes to health disparities. In its 2003 report, the Institute of Medicine concluded that bias against racial minorities may affect communication or care offered. However, to the authors' knowledge, the role of bias within the context of recruitment of racial and ethnic minorities to cancer clinical trials has not been explored to date. Therefore, the authors assessed the experiences of clinical and research personnel related to factors influencing the recruitment of racial and ethnic minorities for cancer clinical trials. Methods A total of 91 qualitative interviews were conducted at 5 US cancer centers among 4 stakeholder groups: 1) cancer center leaders; 2) principal investigators; 3) referring clinicians; and 4) research staff. Data analysis was conducted using a content analysis approach to generate themes from the transcribed interviews. Results Five prominent themes emerged: 1) recruitment interactions with potential minority participants were perceived to be challenging; 2) potential minority participants were not perceived to be ideal study candidates; 3) a combination of clinic-level barriers and negative perceptions of minority study participants led to providers withholding clinical trial opportunities from potential minority participants; 4) when clinical trial recruitment practices were tailored to minority patients, addressing research misconceptions to build trust was a common strategy; 5) for some respondents, race was perceived as irrelevant when screening and recruiting potential minority participants for clinical trials. Conclusions Not only did some respondents view racial and ethnic minorities as less promising participants, some respondents reported withholding trial opportunities from minorities based on these perceptions. Some providers endorsed using tailored recruitment strategies whereas others eschewed race as a factor in trial recruitment. The presence of bias and stereotyping among clinical and research professionals recruiting for cancer clinical trials should be considered when designing interventions to increase minority enrollment.
Nearby cycles of parahoric shtukas, and a fundamental lemma for base change

Using the Langlands–Kottwitz paradigm, we compute the trace of Frobenius composed with Hecke operators on the cohomology of nearby cycles, at places of parahoric reduction, of perverse sheaves on certain moduli stacks of shtukas. Following an argument of Ngo, we then use this to give a geometric proof of a base change fundamental lemma for parahoric Hecke algebras for $${\text {GL}}_n$$ over local function fields. This generalizes a theorem of Ngo, who proved the base change fundamental lemma for spherical Hecke algebras for $${\text {GL}}_n$$ over local function fields, and extends to positive characteristic (for $${\text {GL}}_n$$) a fundamental lemma originally introduced and proved by Haines for p-adic local fields.
Submodularity in Conic Quadratic Mixed 0–1 Optimization

Although submodularity has played an important role in developing efficient algorithms for numerous combinatorial optimization problems, its use in mixed 0–1 optimization has been rather limited. I...
Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps

Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on all but the most pristine density maps (<2.5 A resolution). Here we introduce a deep learning model that uses a set of cascaded convolutional neural networks (CNNs) to predict Cα atoms along a protein’s backbone structure. The cascaded-CNN (C-CNN) is a novel deep learning architecture comprised of multiple CNNs, each predicting a specific aspect of a protein’s structure. This model predicts secondary structure elements (SSEs), backbone structure, and Cα atoms, combining the results of each to produce a complete prediction map. The cascaded-CNN is a semantic segmentation image classifier and was trained using thousands of simulated density maps. This method is largely automatic and only requires a recommended threshold value for each protein density map. A specialized tabu-search path walking algorithm was used to produce an initial backbone trace with Cα placements. A helix-refinement algorithm made further improvements to the α-helix SSEs of the backbone trace. Finally, a novel quality assessment-based combinatorial algorithm was used to effectively map protein sequences onto Cα traces to obtain full-atom protein structures. This method was tested on 50 experimental maps between 2.6 A and 4.4 A resolution. It outperformed several state-of-the-art prediction methods including Rosetta de-novo, MAINMAST, and a Phenix based method by producing the most complete predicted protein structures, as measured by percentage of found Cα atoms. This method accurately predicted 88.9% (mean) of the Cα atoms within 3 A of a protein’s backbone structure surpassing the 66.8% mark achieved by the leading alternate method (Phenix based fully automatic method) on the same set of density maps. The C-CNN also achieved an average root-mean-square deviation (RMSD) of 1.24 A on a set of 50 experimental density maps which was tested by the Phenix based fully automatic method. The source code and demo of this research has been published at https://github.com/DrDongSi/Ca-Backbone-Prediction.
Zimmer's conjecture for actions of $\mathrm{SL}(m,\mathbb{Z})$

We prove Zimmer’s conjecture for $$C^2$$ actions by finite-index subgroups of $$\mathrm {SL}(m,{\mathbb {Z}})$$ provided $$m>3$$ . The method utilizes many ingredients from our earlier proof of the conjecture for actions by cocompact lattices in $$\mathrm {SL}(m,{\mathbb {R}})$$ (Brown et al. in Zimmer’s conjecture: subexponential growth, measure rigidity, and strong property (T), 2016. arXiv:1608.04995 ) but new ideas are needed to overcome the lack of compactness of the space $$(G \times M)/\Gamma $$ (admitting the induced G-action). Non-compactness allows both measures and Lyapunov exponents to escape to infinity under averaging and a number of algebraic, geometric, and dynamical tools are used control this escape. New ideas are provided by the work of Lubotzky, Mozes, and Raghunathan on the structure of nonuniform lattices and, in particular, of $$\mathrm {SL}(m,{\mathbb {Z}})$$ providing a geometric decomposition of the cusp into rank one directions, whose geometry is more easily controlled. The proof also makes use of a precise quantitative form of non-divergence of unipotent orbits by Kleinbock and Margulis, and an extension by de la Salle of strong property (T) to representations of nonuniform lattices.
Subsequential Scaling Limits for Liouville Graph Distance

For $$0<\gamma <2$$ and $$\delta >0$$ , we consider the Liouville graph distance, which is the minimal number of Euclidean balls of $$\gamma $$ -Liouville quantum gravity measure at most $$\delta $$ whose union contains a continuous path between two endpoints. In this paper, we show that the renormalized distance is tight and thus has subsequential scaling limits at $$\delta \rightarrow 0$$ . In particular, we show that for all $$\delta >0$$ the diameter with respect to the Liouville graph distance has the same order as the typical distance between two endpoints.
VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text

Social media became popular and percolated almost all aspects of our daily lives. While online posting proves very convenient for individual users, it also fosters fast-spreading of various rumors. The rapid and wide percolation of rumors can cause persistent adverse or detrimental impacts. Therefore, researchers invest great efforts on reducing the negative impacts of rumors. Towards this end, the rumor classification system aims to to detect, track, and verify rumors in social media. Such systems typically include four components: (i) a rumor detector, (ii) a rumor tracker, (iii) a stance classifier, and (iv) a veracity classifier. In order to improve the state-of-the-art in rumor detection, tracking, and verification, we propose VRoC, a tweet-level variational autoencoder-based rumor classification system. VRoC consists of a co-train engine that trains variational autoencoders (VAEs) and rumor classification components. The co-train engine helps the VAEs to tune their latent representations to be classifier-friendly. We also show that VRoC is able to classify unseen rumors with high levels of accuracy. For the PHEME dataset, VRoC consistently outperforms several state-of-the-art techniques, on both observed and unobserved rumors, by up to 26.9%, in terms of macro-F1 scores.
Bidding strategies with gender nondiscrimination constraints for online ad auctions

Interactions between bids to show ads online can lead to an advertiser's ad being shown to more men than women even when the advertiser does not target towards men. We design bidding strategies that advertisers can use to avoid such emergent discrimination without having to modify the auction mechanism. We mathematically analyze the strategies to determine the additional cost to the advertiser for avoiding discrimination, proving our strategies to be optimal in some settings. We use simulations to understand other settings.
Straight homogeneous generalized cylinders: differential geometry and uniqueness results

It is well known that certain objects, like ellipsoids or spheres, admit several, sometimes many, different parameterizations by generalized cylinders. Under what conditions does a given surface admit at most one description by a straight homogeneous generalized cylinder (SHGC)? Under what other conditions does a surface admit at most a few such descriptions? To answer these questions, it is first necessary to understand the geometry and intrinsic properties of SHGC's. In this paper, a necessary and sufficient condition for the regularity of the surface described by an SHGC is given, the Gaussian curvature of this surface is calculated, and it is proved that its parabolic lines are either meridians or parallels of the associated SHGC. These results are used in the second part of the paper to prove several new uniqueness results. It is first proved that if a surface is described by two SHGC's with the same cross-section plane and axis, then these SHGC's are necessarily deduced from each other through inverse scalings of their cross-sections and sweeping rule curve, and that the surface associated with an SHGC with at least two parabolic meridians and two parabolic parallels cannot be described by a different SHGC. Shafer's pivot and slant theorems are then extended to prove that the surface associated with a non-linear SHGC does not have any different SHGC parameterization with the same cross-section plane or the same axis. Finally, it is shown that a surface with at least two parabolic lines admits at most three different SHGC descriptions, and that a surface with at least four parabolic lines admits at most one SHGC description. In particular, a closed surface with at least one concave point admits at most three different SHGC descriptions.
Distinct cellular mediators drive the Janus Faces of Toll-like Receptor 4 regulation of network excitability which impacts working memory performance after brain Injury

The mechanisms by which the neurophysiological and inflammatory responses to brain injury contribute to memory impairments are not fully understood. Recently, we reported that the innate immune receptor, toll-like receptor 4 (TLR4) enhances AMPA receptor (AMPAR) currents and excitability in the dentate gyrus after fluid percussion brain injury (FPI) while limiting excitability in controls. Here, we examine the cellular mediators underlying TLR4 regulation of dentate excitability and its impact on memory performance. In ex vivo slices, astrocytic and microglial metabolic inhibitors selectively abolished TLR4 antagonist modulation of excitability in controls, but not in rats after FPI, demonstrating that glial signaling contributes to TLR4 regulation of excitability in controls. In glia-depleted neuronal cultures from naive mice, TLR4 ligands bidirectionally modulated AMPAR charge transfer consistent with neuronal TLR4 regulation of excitability, as observed after brain injury. In vivo TLR4 antagonism reduced early post-injury increases in mediators of MyD88-dependent and independent TLR4 signaling without altering expression in controls. Blocking TNFα, a downstream effector of TLR4, mimicked effects of TLR4 antagonist and occluded TLR4 agonist modulation of excitability in slices from both control and FPI rats. Functionally, transiently blocking TLR4 in vivo improved impairments in working memory observed one week and one month after FPI, while the same treatment impaired memory function in uninjured controls. Together these data identify that distinct cellular signaling mechanisms converge on TNFα to mediate TLR4 modulation of network excitability in the uninjured and injured brain and demonstrate a role for TLR4 in regulation of working memory function.