Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous Random Variable Estimation is not Optimal for the Witsenhausen Counterexample

Optimal design of distributed decision policies can be a difficult task, illustrated by the famous Witsenhausen counterexample. In this paper we characterize the optimal control designs for the vector-valued setting assuming that it results in an interim state, i.e. the result of the first decision maker action, that can be described by a continuous random variable which has a probability density function. More specifically, we provide a genie-aided outer bound that relies on our previous results for empirical coordination problems. This solution turns out to be not optimal in general, since it consists of a time-sharing strategy between two linear schemes of specific power. It follows that the optimal decision strategy for the original scalar Witsenhausen problem must lead to an interim state that cannot be described by a continuous random variable which has a probability density function.
VSEGAN: Visual Speech Enhancement Generative Adversarial Network

Speech enhancement is an essential task of improving speech quality in noise scenario. Several state-of-the-art approaches have introduced visual information for speech enhancement, since the visual aspect of speech is essentially unaffected by acoustic environment. This paper proposes a novel framework that involves visual information for speech enhancement, by incorporating a Generative Adversarial Network (GAN). In particular, the proposed visual speech enhancement GAN consists of two networks trained in adversarial manner, i) a generator that adopts multi-layer feature fusion convolution network to enhance input noisy speech, and ii) a discriminator that attempts to minimize the discrepancy between the distributions of the clean speech signal and enhanced speech signal. Experiment results demonstrated superior performance of the proposed model against several state-of-the-art models.
Support Theory for Extended Drinfeld Doubles

Following earlier work with Cris Negron on the cohomology of Drinfeld doubles D(G(r)), we develop a “geometric theory” of support varieties for “extended Drinfeld doubles” D̃(G(r)) of Frobenius kernels G(r) of smooth linear algebraic groups G over a field k of characteristic p > 0. To a D̃(G(r))module M we associate the space Π(D̃(G(r)))M of equivalence classes of “pairs of π-points” and prove most of the desired properties of M 7→ Π(D̃(G(r)))M . Namely, this association satisfies the “tensor product property” and admits a natural continuous map Ψ D̃ to cohomological support theory. Moreover, for M finite dimensional and with suitable conditions on G(r), this association provides a “projectivity test”, Ψ D̃ is a homeomorphism, and identifies Π(D̃(G(r)))M with the cohomological support variety of M for various classes of D̃(G(r))-modules M .
Multiple Criss-Cross Deletion-Correcting Codes

This paper investigates the problem of correcting multiple criss-cross deletions in arrays. More precisely, we study the unique recovery of $n\times n$ arrays affected by any combination of $t_{\mathrm{r}}$ row and $t_{\mathrm{c}}$ column deletions such that $t_{\mathrm{r}}+t_{\mathrm{c}}=t$ for a given $t$. We refer to these type of deletions as t-criss-cross deletions. We show that the asymptotic redundancy of a code correcting t-criss-cross deletions is at least $tn+t\log n-\log(t! )$. Then, we present an existential construction of a code capable of correcting t-criss-cross deletions where its redundancy is bounded from above by $tn+\mathcal{O}(t^{2}\log^{2}n)$. The main ingredients of the presented code are systematic binary t-deletion-correcting codes and Gabidulin codes. The first ingredient helps locating the indices of the deleted rows and columns, thus transforming the deletion-correction problem into an erasure-correction problem which is then solved using the second ingredient.
Materializing Knowledge Bases via Trigger Graphs

Thechaseis a well-established family of algorithms used to materialize Knowledge Bases (KBs) for tasks like query answering under dependencies or data cleaning. A general problem of chase algorithms is that they might perform redundant computations. To counter this problem, we introduce the notion ofTrigger Graphs(TGs), which guide the execution of the rules avoiding redundant computations. We present the results of an extensive theoretical and empirical study that seeks to answer when and how TGs can be computed and what are the benefits of TGs when applied over real-world KBs. Our results include introducing algorithms that compute (minimal) TGs. We implemented our approach in a new engine, called GLog, and our experiments show that it can be significantly more efficient than the chase enabling us to materialize Knowledge Graphs with 17B facts in less than 40 min using a single machine with commodity hardware.
Rubidium abundances in solar metallicity stars

Context. Rubidium is one of the few elements produced by the neutron capture s- and r-processes in almost equal proportions. Recently, a Rb deficiency ([Rb/Fe] < 0.0), amounting to a factor of about two with respect to the Sun, has been found in M dwarfs of near-solar metallicity. This stands in contrast to the close-to-solar [Sr, Zr/Fe] ratios derived in the same stars. This deficiency is difficult to understand from the point of view of observations and of nucleosynthesis. Aims. To test the reliability of this Rb deficiency, we study the Rb and Zr abundances in a sample of KM-type giant stars across a similar metallicity range, extracted from the AMBRE Project. Methods. We used high-resolution and high signal-to-noise spectra to derive Rb and Zr abundances in a sample of 54 bright giant stars with metallicities in the range of −0.6 ≲ [Fe/H] ≲ +0.4 dex, via spectral synthesis in both local and non-local thermodynamic equilibrium (LTE and NLTE, respectively). We also studied the impact of the Zeeman broadening in the profile of the Rb I at λ7800 Å line. Results. The LTE analysis also results in a Rb deficiency in giant stars, however, it is considerably lower than that obtained in M dwarfs. However, once NLTE corrections are performed, the [Rb/Fe] ratios are very close to solar (average −0.01 ± 0.09 dex) in the full metallicity range studied here. This stands in contrast to the value found for M dwarfs. The [Zr/Fe] ratios derived are in excellent agreement with those obtained in previous studies in FGK dwarf stars with a similar metallicity. We investigate the effect of gravitational settling and magnetic activity as possible causes of the Rb deficiency found in M dwarfs. Although the former phenomenon has a negligible impact on the surface Rb abundance, the presence of an average magnetic field with an intensity that is typical of that observed in M dwarfs may result in systematic Rb abundance underestimations if the Zeeman broadening is not considered in the spectral synthesis. This may explain the Rb deficiency in M dwarfs, but not fully. On the other hand, the new [Rb/Fe] and [Rb/Zr] versus [Fe/H] relationships can be explained when the Rb production by rotating massive stars and low-to-intermediate mass stars (these latter also producing Zr) are considered, without the need to deviate from the standard s-process nucleosynthesis in asymptotic giant branch stars, as suggested previously.
Invertible DenseNets with Concatenated LipSwish

We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient extension of Residual Flows. The method relies on an analysis of the Lipschitz continuity of the concatenation in DenseNets, where we enforce invertibility of the network by satisfying the Lipschitz constant. Furthermore, we propose a learnable weighted concatenation, which not only improves the model performance but also indicates the importance of the concatenated weighted representation. Additionally, we introduce the Concatenated LipSwish as activation function, for which we show how to enforce the Lipschitz condition and which boosts performance. The new architecture, i-DenseNet, out-performs Residual Flow and other flow-based models on density estimation evaluated in bits per dimension, where we utilize an equal parameter budget. Moreover, we show that the proposed model out-performs Residual Flows when trained as a hybrid model where the model is both a generative and a discriminative model.
Resolving the History of Life on Earth by Seeking Life As We Know It on Mars

An origin of Earth life on Mars would resolve significant inconsistencies between the inferred history of life and Earth's geologic history. Life as we know it utilizes amino acids, nucleic acids, and lipids for the metabolic, informational, and compartment-forming subsystems of a cell. Such building blocks may have formed simultaneously from cyanosulfidic chemical precursors in a planetary surface scenario involving ultraviolet light, wet-dry cycling, and volcanism. On the inferred water world of early Earth, such an origin would have been limited to volcanic island hotspots. A cyanosulfidic origin of life could have taken place on Mars via photoredox chemistry, facilitated by orders-of-magnitude more sub-aerial crust than early Earth, and an earlier transition to oxidative conditions that could have been involved in final fixation of the genetic code. Meteoritic bombardment may have generated transient habitable environments and ejected and transferred life to Earth. Ongoing and future missions to Mars offer an unprecedented opportunity to confirm or refute evidence consistent with a cyanosulfidic origin of life on Mars, search for evidence of ancient life, and constrain the evolution of Mars' oxidation state over time. We should seek to prove or refute a martian origin for life on Earth alongside other possibilities.
Hybrid Adversarial Inverse Reinforcement Learning

—In this paper, we investigate the problem of the inverse reinforcement learning (IRL), especially the beyond-demonstrator (BD) IRL. The BD-IRL aims to not only imitate the expert policy but also extrapolate BD policy based on ﬁnite demonstrations of the expert. Currently, most of the BD-IRL algorithms are two-stage, which ﬁrst infer a reward function then learn the policy via reinforcement learning (RL). Because of the two separate procedures, the two-stage algorithms have high computation complexity and lack robustness. To overcome these ﬂaw, we propose a BD-IRL framework entitled hybrid adversarial inverse reinforcement learning (HAIRL), which successfully integrates the imitation and exploration into one procedure. The simulation results show that the HAIRL is more efﬁcient and robust when compared with other similar state-of-the-art (SOTA) algorithms.
Role of viscoelasticity on the dynamics and aggregation of chemically active sphere-dimers

The impact of complex media on the dynamics of active swimmers has gained a thriving interest in the research community for their prominent applications in various fields. This paper investigates the effect of viscoelasticity on the dynamics and aggregation of chemically powered sphere-dimers by using a coarse-grained hybrid mesoscopic simulation technique. The sphere-dimers perform active motion by virtue of the concentration gradient around the swimmer's surface, produced by the chemical reaction at one end of the dimer. We observe that the fluid elasticity enhances translational and rotational motion of a single dimer, however for a pair of dimers, the clustering in a particular alignment is more pronounced. In case of multiple dimers, the kinetics of cluster formation along with their propulsive nature are presented in detail. The key factors influencing the enhanced motility and the aggregation of dimers are the concentration gradients, hydrodynamic coupling and the microstructures present in the system.
Sovereign Smartphone: To Enjoy Freedom We Have to Control Our Phones

The majority of smartphones either run iOS or Android operating systems. This has created two distinct ecosystems largely controlled by Apple and Google - they dictate which applications can run, how they run, and what kind of phone resources they can access. Barring some exceptions in Android where different phone manufacturers may have influence, users, developers, and governments are left with little to no choice. Specifically, users need to entrust their security and privacy to OS vendors and accept the functionality constraints they impose. Given the wide use of Android and iOS, immediately leaving these ecosystems is not practical, except in niche application areas. In this work, we draw attention to the magnitude of this problem and why it is an undesirable situation. As an alternative, we advocate the development of a new smartphone architecture that securely transfers the control back to the users while maintaining compatibility with the rich existing smartphone ecosystems. We propose and analyze one such design based on advances in trusted execution environments for ARM and RISC-V.
Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models

Driven by the tremendous effort in researching novel deep learning (DL) algorithms, the training cost of developing new models increases staggeringly in recent years. To reduce this training cost and optimize the cluster-wide hardware resource usage, we analyze GPU cluster usage statistics from a well-known research institute. Our study reveals that single-accelerator training jobs can dominate the cluster-wide resource consumption when launched repetitively (e.g., for hyper-parameter tuning) while severely underutilizing the hardware. This is because DL researchers and practitioners often lack the required expertise to independently optimize their own workloads. Fortunately, we observe that such workloads have the following unique characteristics: (i) the models among jobs often have the same types of operators with the same shapes, and (ii) the inter-model horizontal fusion of such operators is mathematically equivalent to other already well-optimized operators. Thus, to help DL researchers and practitioners effectively and easily improve the hardware utilization of their novel DL training workloads, we propose Horizontally Fused Training Array (HFTA). HFTA is a new DL framework extension library that horizontally fuses the models from different repetitive jobs deeply down to operators, and then trains those models simultaneously on a shared accelerator. On three emerging DL training workloads and state-of-the-art accelerators (GPUs and TPUs), HFTA demonstrates strong effectiveness in squeezing out hardware utilization and achieves up to $15.1 \times$ higher training throughput vs. the standard practice of running each job on a separate accelerator.
An end-to-end trainable hybrid classical-quantum classifier

We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks. This architecture allows for the classical and quantum parts of the model to be trained simultaneously, providing an end-to-end training framework. We show that compared to the principal component analysis, a tensor network based on the matrix product state with low bond dimensions performs better as a feature extractor for the input data of the variational quantum circuit in the binary and ternary classification of MNIST and Fashion-MNIST datasets. The architecture is highly adaptable and the classical-quantum boundary can be adjusted according to the availability of the quantum resource by exploiting the correspondence between tensor networks and quantum circuits.
Advances in silicon carbide science and technology at the micro- and nanoscales

Advances in silicon carbide microfabrication and growth process optimization for silicon carbide nanostructures are ushering in new opportunities for microdevices capable of operation in a variety of demanding applications, involving high temperature, radiation, or corrosive environment. This review focuses on the materials science and processing technologies for silicon carbide thin films and low dimensional structures, and details recent progress in manufacturing technology, including deposition, metallization, and fabrication of semiconductor microdevices, with emphasis on sensor technology. The challenges remaining in developing silicon carbide as a mainstay materials platform are discussed throughout.
PDA Indolylmaleimides Induce Anti-Tumor Effects in Prostate Carcinoma Cell Lines Through Mitotic Death

Castrate resistant prostate cancer in men shares several characteristics with canine prostate cancer (PCa). Due to current insufficient therapies, evaluating novel therapeutic agents for late-stage PCa is of considerable interest for both species. PDA indolylmaleimides showed anticancer effects in several neoplastic cell lines. Herein, a comparative characterization of PDA-66 and PDA-377 mediated effects was performed in human and canine PCa cell lines, which is also the first detailed characterization of these agents on cells derived from solid tumors in general. While PDA-377 showed only weak growth inhibition on human PCa cell lines, PDA-66 inhibited proliferation and induced apoptosis in human and canine cell lines with concentrations in the low micromolar range. Morphological characterization and whole transcriptome sequencing revealed that PDA-66 induces mitotic death through its microtubule-depolymerizing ability. PDA-66 appears to be a worthwhile anti-mitotic agent for further evaluation. The similarities in cellular and molecular response observed in the cell lines of both origins form a solid basis for the use of canine PCa in vivo models to gain valuable interchangeable data to the advantage of both species.
Effect of Monthly 100,000 IU Vitamin D Supplementation on Falls and Non-Vertebral Fractures

Introduction Correlation between decreased levels of vitamin D in the blood of elderly patients and incidence of falls and fractures has been assessed in various studies; however, there is still ambiguity in data. In this study, we aim to establish the role of vitamin D supplements in minimizing the burden of falls and non-vertebral fractures in the elderly population in a local setting. Methods This single-blind, placebo-controlled randomized interventional study was conducted in the Internal Medicine Department of a tertiary care hospital in Pakistan from March 2018 to July 2020. Patients between the ages of 50 to 75 years were enrolled in the study and were randomly assigned to receive either placebo or 100,000 IU vitamin D oral tablets and were followed over 24 months, with regular follow-ups every three months. Results There was no significant difference in the probability of one or more falls for those assigned to the vitamin D group compared to those who received placebo (24.70% vs. 24.85%; hazard ratio [HR]: 0.99; 95% CI: 0.68-1.43). Similarly, the probability of non-vertebral fracture was also non-significant between both groups (4.7% vs. 5.7%; HR: 0.81; 95% CI: 0.32-2.01). Conclusion As per the results of this study, vitamin D supplementation had no beneficial effect on the reduction of falls and non-vertebral fractures in elderly patients. Further multi-center studies of longer duration are required to prove the favorable effects of vitamin D supplements.
Dropwise condensation theory and experiment: A review

Abstract The paper reviews progress in dropwise condensation research from 1930 to the present. Particular attention is given to heat transfer measurements, theory, transition and effects of surface material. Although it has been known since the 1930s that heat transfer coefficients for dropwise condensation of steam are much higher than those for film condensation, there were, until the 1960s, wide discrepancies between the results of different investigators. Subsequently, more accurate measurements have shown good consistency and the mechanism and theory of the dropwise condensation have become better understood. There has been considerable controversy over the magnitude of the so-called ‘constriction resistance’ and the effect of the surface thermal conductivity on the heat transfer coefficient. The balance of evidence suggests that this is only significant at very low heat fluxes and for very small condensing surfaces. Measurements have also been made with sufficiently high cooling intensities to cover the range of dropwise to filmwise condensation transition. The detailed mechanism of transition is still not fully understood. Perhaps most importantly, the practical problem of promoting lasting dropwise condensation under industrial conditions remains to be solved despite considerable effort spanning more than 70 years.
Clinical outcomes in patients with native valve infective endocarditis and diabetes mellitus

BACKGROUND There is a lack of data on the clinical outcomes in patients with native valve infective endocarditis (NVIE) and diabetes mellitus (DM). AIM To investigate (1) trends in the prevalence of DM among patients with NVIE; and (2) the impact of DM on NVIE outcomes. METHODS We identified 76385 with NVIE from the 2004 to 2014 National Inpatient Sample, of which 22284 (28%) had DM. We assessed trends in DM from 2004 to 2014 using the Cochrane Armitage test. We compared baseline comorbidities, microorganisms, and in-patients procedures between those with vs without DM. Propensity match analysis and multivariate logistic regression were used to investigate study outcomes in in-hospital mortality, stroke, acute heart failure, cardiogenic shock, septic shock, and atrioventricular block. RESULTS Crude rates of DM increased from in 22% in 2004 to 30% in 2014. There were significant differences in demographics, comorbidities and NVIE risk factors between the two groups. Staphylococcus aureus was the most common organism identified with higher rates in patients with DM (33.1% vs 35.6%; P < 0.0001). After propensity matching, in-hospital mortality (11.1% vs 11.9%; P < 0.0001), stroke (2.3% vs 3.0%; P < 0.0001), acute heart failure (4.6% vs 6.5%; P = 0.001), cardiogenic shock (1.5% vs 1.9%; P < 0.0001), septic shock (7.2% vs 9.6%; P < 0.0001), and atrioventricular block (1.5% vs 2.4%; P < 0.0001), were significantly higher in patients with DM. Independent predictors of mortality in NVIE patients with DM include hemodialysis, congestive heart failure, atrial fibrillation, staphylococcus aureus, and older age. CONCLUSION There is an increasing prevalence of DM in NVIE and it is associated with poorer outcomes. Further studies are crucial to identify the clinical, and sociodemographic contributors to this trend and develop strategies to mitigate its attendant risk.