Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle Dark Matter: Modified gravity as an alternative to dark matter

The premier alternative to the dark matter paradigm is modified gravity. Following an introduction to the relevant phenomenology of galaxies, I review the MOND paradigm, an effective summary of the observations which any theory must reproduce. A simple nonlinear modified gravity theory does justice to MOND at the nonrelativistic level, but cannot be elevated to the relativistic level in a unique way. I go in detail into the covariant tensorvector-theory (TeVeS) which not only recovers MOND but can also deal in detail with gravitational lensing and cosmology. Problems with MOND and TeVeS at the level of clusters of galaxies are given attention. I also summarize the status of TeVeS cosmology.
Optimal Triangulation Method is Not Really Optimal

Triangulation refers to the problem of finding a 3D point from its 2D projections on multiple camera images. For solving this problem, it is the common practice to use so-called optimal triangulation method, which we call the L2 method in this paper. But, the method can be optimal only if we assume no uncertainty in the camera parameters. Through extensive comparison on synthetic and real data, we observed that the L2 method is actually not the best choice when there is uncertainty in the camera parameters. Interestingly, it can be observed that the simple mid-point method outperforms other methods. Apart from its high performance, the mid-point method has a simple closed formed solution for multiple camera images while the L2 method is hard to be used for more than two camera images. Therefore, in contrast to the common practice, we argue that the simple mid-point method should be used in structure-from-motion applications where there is uncertainty in camera parameters.
Paradoxes: Remarks on some text questions and appended paradoxes

A paradox can be defined as an unacceptable conclusion derived by apparently acceptable reasoning from apparently acceptable premises. Unlike party puzzles or brain teasers, many paradoxes raise serious philosophical problems, and they are associated with crises of thought and revolutionary advances. The expanded and revised third edition of this intriguing book considers a range of knotty paradoxes, including Zeno’s paradoxical claim that the runner can never overtake the tortoise, a new chapter on paradoxes about morals, paradoxes about belief, and, hardest of all, paradoxes about truth. The discussion uses a minimum of technicality but also grapples with complicated and difficult considerations, and is accompanied by helpful questions designed to engage the reader with the arguments. The result is not only an explanation of paradoxes but also an excellent introduction to philosophical thinking.
Slab avalanche release viewed as interface fracture in a random medium

Abstract A theoretical model is formulated to investigate the influence of random variations in strength of the weak layer on slab avalanche release. An equation for slab stability is derived which accounts for stress redistribution between strong and weak regions. The model is first used to re-derive results on shear fractures (shear bands) in a homogeneous slab. It is then applied to the case of a slab with randomly varying peak strength of the weak layer. It is demonstrated that such variation may have a dramatic knock-down effect on the failure strength of a slope. The nature of the critical flaw is studied and precursors to failure are investigated.
Point wise or Feature wise? Benchmark Comparison of Public Available LiDAR Odometry Algorithms in Urban Canyons

Robust and precise localization is essential for the autonomous system with navigation requirements. Light detection and ranging (LiDAR) odometry is extensively studied in the past decades to achieve this goal. Satisfactory accuracy can be achieved in scenarios with abundant environmental features using existing LiDAR odometry (LO) algorithms. Unfortunately, the performance of the LiDAR odometry is significantly degraded in urban canyons with numerous dynamic objects and complex environmental structures. Meanwhile, it is still not clear from the existing literature which LO algorithms perform well in such challenging environments. To fill this gap, this paper evaluates an array of popular and extensively studied LO pipelines using the datasets collected in urban canyons of Hong Kong. We present the results in terms of their positioning accuracy and computational efficiency. Three major factors dominating the performance of LO in urban canyons are concluded, including the ego-vehicle dynamic, moving objects, and degree of urbanization. According to our experiment results, point-wise achieves better accuracy in urban canyons while feature-wise achieves cost-efficiency and satisfactory positioning accuracy.
Posterior sampling for reinforcement learning: worst-case regret bounds

We present an algorithm based on posterior sampling (aka Thompson sampling) that achieves near-optimal worst-case regret bounds when the underlying Markov Decision Process (MDP) is communicating with a finite, though unknown, diameter. Our main result is a high probability regret upper bound of $\tilde{O}(DS\sqrt{AT})$ for any communicating MDP with $S$ states, $A$ actions and diameter $D$. Here, regret compares the total reward achieved by the algorithm to the total expected reward of an optimal infinite-horizon undiscounted average reward policy, in time horizon $T$. This result closely matches the known lower bound of $\Omega(\sqrt{DSAT})$. Our techniques involve proving some novel results about the anti-concentration of Dirichlet distribution, which may be of independent interest.
Geometry, dynamics, and arithmetic of $S$-adic shifts

This paper studies geometric and spectral properties of $S$-adic shifts and their relation to continued fraction algorithms. These shifts are symbolic dynamical systems obtained by iterating infinitely many substitutions in an adic way. Pure discrete spectrum for $S$-adic shifts and tiling properties of associated Rauzy fractals are established under a generalized Pisot assumption together with a geometric coincidence condition. These general results extend the scope of the Pisot substitution conjecture to the $S$-adic framework. They are applied to families of $S$-adic shifts generated by Arnoux-Rauzy as well as Brun substitutions (related to the respective continued fraction algorithms). It is shown that almost all of these shifts have pure discrete spectrum, which proves a conjecture of Arnoux and Rauzy going back to the early nineties in a metric sense. We also prove that each linearly recurrent Arnoux-Rauzy shift with recurrent directive sequence has pure discrete spectrum. Using $S$-adic words related to Brun's continued fraction algorithm, we exhibit bounded remainder sets and natural codings for almost all translations on the two-dimensional torus. Due to the lack of a dominant eigenvector and the fact that we lose the self-similarity properties present for substitutive systems we cannot follow the known arguments from the substitutive case and have to develop new proofs to obtain our results in the $S$-adic setting.
Preliminary results from WOCE hydrographic sections at 80°E and 32°S in the central Indian Ocean

The hydrographic properties and circulation along sections at 80°E and 32°S in March, 1995, in the Indian Ocean are described very briefly. A halocline was well‐developed in the tropics. A westward coastal jet of fresh Bay of Bengal water was present at the sea surface at Sri Lanka with eastward flow of saline Arabian Sea water below. The Equatorial Undercurrent was well developed as were the deep equatorial jets. The Indonesian throughflow jet presented a large dynamic signature at 10 to 14°S coinciding with a strong front in all properties to great depth. Its mid‐depth salinity minimum is separated from that of the Antarctic Intermediate Water. The Subantarctic Mode Water of the southeastern Indian Ocean imparts its high oxygen ventilation signature to the whole of the transects, including the tropical portion. The deepest water in the Central Indian Basin is pooled in the center of the basin, and its principal source appears to be the sill at 11°S through the Ninetyeast Ridge. Northward deep water transports across the 32°S section were similar to those observed in 1987 but the deep water was lower in oxygen and fresher than in 1987. Upper ocean waters at 32°S were more saline and warmer in 1995.
Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray

The aim of this study is to investigate the segmentation accuracies of different segmentation networks trained on 730 manually annotated lateral lumbar spine X-rays. Instance segmentation networks were compared to semantic segmentation networks. The study cohort comprised diseased spines and postoperative images with metallic implants. The average mean accuracy and mean intersection over union (IoU) was up to 3 percent better for the best performing instance segmentation model, the average pixel accuracy and weighted IoU were slightly better for the best performing semantic segmentation model. Moreover, the inferences of the instance segmentation models are easier to implement for further processing pipelines in clinical decision support.
Effect of seed layer thickness on Ta crystalline phase and spin Hall angle

Heavy metal-ferromagnet bilayer structures have attracted great research interest for charge-to-spin interconversion. In this work, we have investigated the effect of the permalloy seed layer on the Ta polycrystalline phase and its spin Hall angle. Interestingly, for the same deposition rates the crystalline phase of Ta deposited on Py seed layer strongly depends on the thickness of the seed layer. We have observed a phase transition from $\alpha$-Ta to ($\alpha$+$\beta$)-Ta while increasing the Py seed layer thickness. The observed phase transition is attributed to the strain at interface between Py and Ta layers. Ferromagnetic resonance-based spin pumping studies reveal that the spin-mixing conductance in the to ($\alpha$+$\beta$)-Ta is relatively higher as compared to the to $\alpha$-Ta. Spin Hall angles of to $\alpha$-Ta and to ($\alpha$+$\beta$)-Ta are extracted from inverse spin Hall effect (ISHE) measurements. Spin Hall angle of the to ($\alpha$+$\beta$)-Ta is estimated to be $\theta$_SH=-0.15 which is relatively higher than that of to $\alpha$-Ta. Our systematic results connecting the phase of the Ta with seed layer and its effect on the efficiency of spin to charge conversion might resolve ambiguities across various literature and open up new functionalities based on the growth process for the emerging spintronic devices.
The MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors: A Retrospective

To facilitate research in the direction of sample-eﬃcient reinforcement learning, we held the MineRL Competition on Sample-Eﬃcient Reinforcement Learning Using Human Pri-ors at the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2019). The primary goal of this competition was to promote the development of algorithms that use human demonstrations alongside reinforcement learning to reduce the number of samples needed to solve complex, hierarchical, and sparse environments. We describe the competition and provide an overview of the top solutions, each of which use deep reinforcement learning and/or imitation learning. We also discuss the impact of our organizational decisions on the competition as well as future directions for improvement.
Lateral variations in D″ below the Caribbean

Broad-band data from the Canadian National Seismograph Network (CNSN) shows evidence for a laterally-varying S-wave discontinuity in the lowermost mantle beneath the Caribbean. The magnitude of the velocity contrast across this D″ discontinuity varies inversely with its distance from the core-mantle boundary (CMB). Clear evidence for a 2.75% increase in shear velocity 250 km above the CMB is observed in a region 10°N and 60–85°W; a thicker D″ layer (290 km) with a less pronounced topside discontinuity (2.45%) is interpreted in the region 80°–90°W and 20°N; and there is no evidence for a D″ discontinuity in the region 65°–80°W and 25°N. Considerable 3D structure within the D″ region is suggested by travel-time scatter in ScS arrivals and S arrivals which turn within D″ . Transverse-component SKS signals due to upper-mantle anisotropy can be confused with D″ signals; however, we show that false interpretations of D″ structure can be mitigated through the careful analysis of travel-time moveout and low-pass filtering.
MultiSAGE: a multiplex embedding algorithm for inter-layer link prediction

Research on graph representation learning has received great attention in recent years. However, most of the studies so far have focused on the embedding of single-layer graphs. The few studies dealing with the problem of representation learning of multilayer structures rely on the strong hypothesis that the inter-layer links are known, and this limits the range of possible applications. Here we propose MultiSAGE, a generalization of the GraphSAGE algorithm that allows to embed multiplex networks. We show that MultiSAGE is capable to reconstruct both the intra-layer and the inter-layer connectivity, outperforming GraphSAGE, which has been designed for simple graphs. Next, through a comprehensive experimental analysis, we shed light also on the performance of the embedding, both in simple and in multiplex networks, showing that either the density of the graph or the randomness of the links strongly influences the quality of the embedding.
Additive energy forward curves in a Heath-Jarrow-Morton framework

One of the peculiarities of power and gas markets is the delivery mechanism of forward contracts. The seller of a futures contract commits to deliver, say, power, over a certain period, while the classical forward is a financial agreement settled on a maturity date. Our purpose is to design a Heath-Jarrow-Morton framework for an additive, mean-reverting, multicommodity market consisting of forward contracts of any delivery period. The main assumption is that forward prices can be represented as affine functions of a universal source of randomness. This allows us to completely characterize the models which prevent arbitrage opportunities: this boils down to finding a density between a risk-neutral measure $\mathbb{Q}$, such that the prices of traded assets like forward contracts are true $\mathbb{Q}$-martingales, and the real world probability measure $\mathbb{P}$, under which forward prices are mean-reverting. The Girsanov kernel for such a transformation turns out to be stochastic and unbounded in the diffusion part, while in the jump part the Girsanov kernel must be deterministic and bounded: thus, in this respect, we prove two results on the martingale property of stochastic exponentials. The first allows to validate measure changes made of two components: an Esscher-type density and a Girsanov transform with stochastic and unbounded kernel. The second uses a different approach and works for the case of continuous density. We apply this framework to two models: a generalized Lucia-Schwartz model and a cross-commodity cointegrated market.
Emulation of Synaptic Plasticity on Cobalt based Synaptic Transistor for Neuromorphic Computing

Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation of artificial intelligence. Towards realizing NC, fabrication, and investigations of hardware elements such as synaptic devices and neurons are essential. Electrolyte gating has been widely used for conductance modulation by massive carrier injections and has proven to be an effective way of emulating biological synapses. Synaptic devices, in the form of synaptic transistors, have been studied using a wide variety of materials. However, studies on metallic channel based synaptic transistors remain vastly unexplored. Here, we have demonstrated a three-terminal cobalt-based synaptic transistor to emulate biological synapse. We realized gating controlled multilevel, nonvolatile conducting states in the proposed device. The device could successfully emulate essential synaptic functions demonstrating short-term and long-term plasticity. A transition from short-term memory to long-term memory has been realized by tuning gate pulse amplitude and duration. The crucial cognitive behavior viz., learning, forgetting, and relearning, has been emulated, showing resemblance to the human brain. Along with learning and memory, the device showed dynamic filtering behavior. These results provide an insight into the design of metallic channel based synaptic transistors for neuromorphic computing.
Petrologic evolution and paleogeography of the Late Cretaceous Nanaimo Basin, Washington and British Columbia: Implications for Cretaceous tectonics

Systematic variations in sandstone petrofacies of the Upper Cretaceous Nanaimo Group are related to basin evolution and uplift of surrounding tectonic provinces. A subaerially exposed horst partially separated southern and northeastern portions of the Nanaimo Basin. Volcaniclastic and arkosic sediment was derived from this horst. The horst subsided below wave base during very early evolution of the Nanaimo Basin, but it controlled sediment dispersal throughout basin development. Lower units of the Nanaimo Group, in the southern Nanaimo Basin, are chert-rich and were derived largely from terranes of the San Juan Islands and North Cascades. Basaltic and plutonic debris from the Insular Belt was deposited into the northwestern Nanaimo Basin during early basin development. Minor deposition of arkosic debris from the Coastal Plutonic Belt also occurred. Upper units of the Nanaimo Group contain abundant plagioclase-rich sediment derived from the Coastal Plutonic Belt. Rocks along the southeastern margin of the basin, however, reflect continued sedimentation from terranes of the San Juan Islands and North Cascades. Arkosic and dacitic debris from Insular Belt sources is recognized in the northwestern Nanaimo Basin. The Nanaimo Basin may have developed as a pull-apart basin within a broad zone of normal and transcurrent faulting in response to oblique convergence or transform faulting between the Kula(? ) plate and the Pacific margin of Washington and British Columbia.
Probabilistic downscaling approaches: Application to wind cumulative distribution functions

A statistical method is developed to generate local cumulative distribution functions (CDFs) of surface climate variables from large‐scale fields. Contrary to most downscaling methods producing continuous time series, our “probabilistic downscaling methods” (PDMs), named “CDF‐transform”, is designed to deal with and provide local‐scale CDFs through a transformation applied to large‐scale CDFs. First, our PDM is compared to a reference method (Quantile‐matching), and validated on a historical time period by downscaling CDFs of wind intensity anomalies over France, for reanalyses and simulations from a general circulation model (GCM). Then, CDF‐transform is applied to GCM output fields to project changes in wind intensity anomalies for the 21st century under A2 scenario. Results show a decrease in wind anomalies for most weather stations, ranging from less than 1% (in the South) to nearly 9% (in the North), with a maximum in the Brittany region.
Simple shear testing for the study of the earthquake response of clay from the Israeli continental slope

Abstract A study was carried out to investigate the simple shear behaviour of a clay from the Israeli continental slope, and to consider the relevance of this behaviour to the stability of the slopes during earthquake conditions. Norweigian simple shear apparatus was modified in order to enable both static and cyclic shearing of undisturbed samples taken from the slope. Static tests performed on virgin samples and on samples which had undergone extensive cycling indicated similar static strengths, despite development of large cyclic shear strains during cycling. This suggests that the stability of the slopes following completion of an earthquake would not be significantly less than it was before the onset of the earthquake; the critical period for instability would be during the earthquake. The results of the cyclic tests indicated that shear strain development accelerated once the cyclic strain reached the order of 3%. A failure criterion for the clay, relevant to cyclic loading conditions, was developed.
Algebraic Structures in M-theory

In this thesis we reformulate the bosonic sector of eleven dimensional supergravity as a simultaneous nonlinear realisation based on the conformal group and an enlarged affine group called G_{11}. The vielbein and the gauge fields of the theory appear as space-time dependent parameters of the coset representatives. Inside the corresponding algebra g_{11} we find the Borel subalgebra of e_7, whereas performing the same procedure for the Borel subalgebra of e_8 we have to add some extra generators. The presence of these new generators lead to a new formulation of gravity, which includes both a vielbein and its dual. We make the conjecture that the final symmetry of M-theory should be described by a coset space, with the global and the local symmetry given by the Lorentzian Kac-Moody algebra e_{11} and its subalgebra invariant under the Cartan involution, respectively. The pure gravity itself in $D$ dimensions is argued to have a coset symmetry based on the very extended algebra A^{+++}_{D-3}. The tensor generators of a very extended algebra are divided into representations of its maximal finite dimensional subalgebra. The space-time translations are thought to be introduced as weights in a basic representation of the Kac-Moody algebra. Some features of the root system of a general Lorentzian Kac-Moody algebra are discussed, in particular those related to even self-dual lattices.
PyODDS: An End-to-End Outlier Detection System

PyODDS is an end-to end Python system for outlier detection with database support. PyODDS provides outlier detection algorithms which meet the demands for users in different fields, w/wo data science or machine learning background. PyODDS gives the ability to execute machine learning algorithms in-database without moving data out of the database server or over the network. It also provides access to a wide range of outlier detection algorithms, including statistical analysis and more recent deep learning based approaches. PyODDS is released under the MIT open-source license, and currently available at (this https URL) with official documentations at (this https URL).
Optimal uniform approximation of Lévy processes on Banach spaces with finite variation processes

For a general c\`adl\`ag L\'evy process on a separable Banach space $V$ we estimate values of $\inf_{Y\in{\cal A}_X} \mathbb{E}\left\{ \psi\left( \Vert X - Y \Vert_\infty\right) + \mathrm{TV}(Y[0,T]) \right\}$, where ${\cal A}_X$ is the family of processes on $V$ adapted to the natural filtration of $X$, $\psi$ has polynomial growth and TV$(Y[0,T])$ denotes the total variation of the process $Y$ on the interval $[0,T]$. Next, we apply obtained estimates in three specific cases: Brownian motion with drift on $\mathbb{R}$, standard Brownian motion on $\mathbb{R}^n$ and a symmetric $\alpha$-stable process ($\alpha\in(1,2)$) on $\mathbb{R}$.