Miracle-dz/UniFAR-FTUs huggingface dataset:
Equatorial variability and resonance in a wind-driven Indian Ocean model

A numerical isopycnal ocean model has been designed and applied to model the Indian Ocean north of 25°S. Vertical normal modes are used in the open boundary conditions and for selections of initial layer depths. A 21-year integration with a reduced Hellerman-Rosenstein monthly averaged wind stress has been made with 3.5-layer and 1.5-layer versions of the model. Both solutions reproduce the main features of the observed wind-driven seasonal circulation in the Indian Ocean above the main thermocline. The transient semiannual equatorial surface jets are more intense, more coherent, and in better phase agreement with observations when three layers are active. The associated undercurrents below the main thermocline are also included in the 3.5-layer model solution. Second baroclinic-mode, reflecting, equatorial Kelvin and Rossby waves combine to give a semiannual, resonant basin mode. Experiments with an equatorial band of semiannual zonal winds suggest a very strong response of the Indian Ocean to wind forcing with this period. Further, the amplitudes of the 28–30 day oscillations in the western equatorial model region are found to be strongly damped with depth; they have upward phase propagation and downward energy propagation.
Behaviour Discriminator: A Simple Data Filtering Method to Improve Offline Policy Learning

This paper studies the problem of learning a con-trol policy without the need for interactions with the environment; instead, learning purely from an existing dataset. Prior work has demonstrated that ofﬂine learning algorithms (e.g., behavioural cloning and ofﬂine reinforcement learning) are more likely to discover a satisfactory policy when trained using high-quality expert data. However, many real-world/practical datasets can contain signiﬁcant proportions of examples generated us-ing low-skilled agents. Therefore, we propose a behaviour discriminator (BD) concept, a novel and simple data ﬁltering approach based on semi-supervised learning, which can accurately discern expert data from a mixed-quality dataset. Our BD approach was used to pre-process the mixed-skill-level datasets from the Real Robot Challenge (RRC) III, an open competition requiring participants to solve several dexterous robotic manipulation tasks using ofﬂine learning methods 1 ; the new BD method allowed a standard behavioural cloning algorithm to outperform other more sophisticated ofﬂine learning algorithms. Moreover, we demonstrate that the new BD pre-processing method can be applied to a number of D4RL benchmark problems, improving the performance of multiple state-of-the-art ofﬂine reinforcement learning algorithms.
High-quality shape from multi-view stereo and shading under general illumination

Multi-view stereo methods reconstruct 3D geometry from images well for sufficiently textured scenes, but often fail to recover high-frequency surface detail, particularly for smoothly shaded surfaces. On the other hand, shape-from-shading methods can recover fine detail from shading variations. Unfortunately, it is non-trivial to apply shape-from-shading alone to multi-view data, and most shading-based estimation methods only succeed under very restricted or controlled illumination. We present a new algorithm that combines multi-view stereo and shading-based refinement for high-quality reconstruction of 3D geometry models from images taken under constant but otherwise arbitrary illumination. We have tested our algorithm on several scenes that were captured under several general and unknown lighting conditions, and we show that our final reconstructions rival laser range scans.
Extracting Device-Parameter Variations with RO-Based Sensors

SUMMARY Device-parameter estimation sensors inside a chip are gaining its importance as the post-fabrication tuning is becoming of a practical use. In estimation of variational parameters using on-chip sensors, it is often assumed that the outputs of variation sensors are not affected by random variations. However, random variations can deteriorate the accuracy of the estimation result. In this paper, we propose a device-parameter estimation method with on-chip variation sensors explicitly considering random variability. The proposed method derives the global variation parameters and the standard deviation of the random variability using the maximum likelihood estimation. We experimentally verified that the proposed method improves the accuracy of device-parameter estimation by 11.1 to 73.4% compared to the conventional method that neglects random variations.
The MITLL NIST LRE 2007 language recognition system

This paper presents a description of the MIT Lincoln Laboratory language recognition system submitted to the NIST 2007 Language Recognition Evaluation. This system consists of a fusion of four core recognizers, two based on tokenization and two based on spectral similarity. Results for NIST’s 14-language detection task are presented for both the closed-set and open-set tasks and for the 30, 10 and 3 second durations. On the 30 second 14-language closed set detection task, the system achieves a 1% equal error rate.
NELA-GT-2021: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles

In this paper, we present the fourth installment of the NELA-GT datasets, NELA-GT-2021 . The dataset contains 1.8M articles from 367 outlets between January 1st, 2021 and December 31st, 2021. Just as in past releases of the dataset, NELA-GT-2021 includes outlet-level veracity labels from Media Bias/Fact Check and tweets embedded in collected news articles. The NELA-GT-2021 dataset can be found at: https://doi.org/10.7910/DVN/RBKVBM
Efficient LQR-CBF-RRT*: Safe and Optimal Motion Planning

—Control Barrier Functions (CBF) are a powerful tool for designing safety-critical controllers and motion planners. The safety requirements are encoded as a continuously differentiable function that maps from state variables to a real value, in which the sign of its output determines whether safety is violated. In practice, the CBFs can be used to enforce safety by imposing itself as a constraint in a Quadratic Program (QP) solved point-wise in time. However, this approach costs computational resources and could lead to infeasibility in solving the QP. In this paper, we propose a novel motion planning framework that combines sampling-based methods with Linear Quadratic Regulator (LQR) and CBFs. Our approach does not require solving the QPs for control synthesis and avoids explicit collision checking during samplings. Instead, it uses LQR to generate optimal controls and CBF to reject unsafe trajectories. To improve sampling efﬁciency, we employ the Cross-Entropy Method (CEM) for importance sampling (IS) to sample conﬁgurations that will enhance the path with higher probability and store computed optimal gain matrices in a hash table to avoid re-computation during rewiring procedure. We demonstrate the effectiveness of our method on nonlinear control afﬁne systems in simulation.
Report of the Working Party on the classification of the lunar igneous rocks

Abstract— A report is presented for a possible revised classification of lunar igneous rocks that still uses the division of Moon rocks into mare and highland types. It subdivides the mare rocks into basalts depending on TiO2 content and glasses depending on colour, and subdivides the highland rocks principally into KREEP basalts and into coarse‐grained igneous rocks comparable to and using terrestrial igneous rock terminology.
A Formalization of the Security Features of Physical Functions

Physical attacks against cryptographic devices typically take advantage of information leakage (e.g., side-channels attacks) or erroneous computations (e.g., fault injection attacks). Preventing or detecting these attacks has become a challenging task in modern cryptographic research. In this context intrinsic physical properties of integrated circuits, such as Physical(ly) Unclonable Functions~(PUFs), can be used to complement classical cryptographic constructions, and to enhance the security of cryptographic devices. PUFs have recently been proposed for various applications, including anti-counterfeiting schemes, key generation algorithms, and in the design of block ciphers. However, currently only rudimentary security models for PUFs exist, limiting the confidence in the security claims of PUF-based security primitives. A useful model should at the same time (i) define the security properties of PUFs abstractly and naturally, allowing to design and formally analyze PUF-based security solutions, and (ii) provide practical quantification tools allowing engineers to evaluate PUF instantiations. In this paper, we present a formal foundation for security primitives based on PUFs. Our approach requires as little as possible from the physics and focuses more on the main properties at the heart of most published works on PUFs: robustness (generation of stable answers), unclonability (not provided by algorithmic solutions), and unpredictability. We first formally define these properties and then show that they can be achieved by previously introduced PUF instantiations. We stress that such a consolidating work allows for a meaningful security analysis of security primitives taking advantage of physical properties, becoming increasingly important in the development of the next generation secure information systems.
Discount Eye Tracking: The Enhanced Restricted Focus Viewer

This paper discusses the design and implementation of a unique software tool, the enhanced restricted focus viewer (ERFV), for tracking the visual attention of users in hyperlinked environments such as web sites. The software collects data such as mouse clicks along with the path of the user’s visual attention as they browse a site. Unlike traditional eye-tracking procedures, the ERFV requires no hardware other than a personal computer. In addition to cost and time savings, the ERFV also allows the administration of usability testing to groups of subjects simultaneously. The benefits of the ERFV are demonstrated through an experiment that evaluated the usability of two web sites that were equivalent in content but differed in terms of design.
Reinforcement Learning for RoboCup Soccer Keepaway

RoboCup simulated soccer presents many challenges to reinforcement learning methods, including a large state space, hidden and uncertain state, multiple independent agents learning simultaneously, and long and variable delays in the effects of actions. We describe our application of episodic SMDP Sarsa(λ) with linear tile-coding function approximation and variable λ to learning higher-level decisions in a keepaway subtask of RoboCup soccer. In keepaway, one team, “the keepers,” tries to keep control of the ball for as long as possible despite the efforts of “the takers. ” The keepers learn individually when to hold the ball and when to pass to a teammate. Our agents learned policies that significantly outperform a range of benchmark policies. We demonstrate the generality of our approach by applying it to a number of task variations including different field sizes and different numbers of players on each team.
IODP expedition 335: Deep sampling in ODP hole 1256D

Abstract. Observations of the gabbroic layers of untectonized ocean crust are essential to test theoretical models of the accretion of new crust at mid-ocean ridges. Integrated Ocean Drilling Program (IODP) Expedition 335 ("Superfast Spreading Rate Crust 4") returned to Ocean Drilling Program (ODP) Hole 1256D with the intention of deepening this reference penetration of intact ocean crust a significant distance (~350 m) into cumulate gabbros. Three earlier cruises to Hole 1256D (ODP 206, IODP 309/312) have drilled through the sediments, lavas, and dikes and 100 m into a complex dike-gabbro transition zone. Operations on IODP Expedition 335 proved challenging throughout, with almost three weeks spent re-opening and securing unstable sections of the hole. When coring commenced, the comprehensive destruction of the coring bit required further remedial operations to remove junk and huge volumes of accumulated drill cuttings. Hole-cleaning operations using junk baskets were successful, and they recovered large irregular samples that document a hitherto unseen sequence of evolving geological conditions and the intimate coupling between temporally and spatially intercalated intrusive, hydrothermal, contact-metamorphic, partial melting, and retrogressive processes. Hole 1256D is now clean of junk, and it has been thoroughly cleared of the drill cuttings that hampered operations during this and previous expeditions. At the end of Expedition 335, we briefly resumed coring before undertaking cementing operations to secure problematic intervals. To ensure the greatest scientific return from the huge efforts to stabilize this primary ocean lithosphere reference site, it would be prudent to resume the deepening of Hole 1256D in the nearest possible future while it is open to full depth. doi: 10.2204/iodp.sd. 13.04. 2011
BicAT: a biclustering analysis toolbox

SUMMARY Besides classical clustering methods such as hierarchical clustering, in recent years biclustering has become a popular approach to analyze biological data sets, e.g. gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques in terms of a common graphical user interface. Furthermore, BicAT provides different facilities for data preparation, inspection and postprocessing such as discretization, filtering of biclusters according to specific criteria or gene pair analysis for constructing gene interconnection graphs. The possibility to use different biclustering algorithms inside a single graphical tool allows the user to compare clustering results and choose the algorithm that best fits a specific biological scenario. The toolbox is described in the context of gene expression analysis, but is also applicable to other types of data, e.g. data from proteomics or synthetic lethal experiments. AVAILABILITY The BicAT toolbox is freely available at http://www.tik. ee.ethz. ch/sop/bicat and runs on all operating systems. The Java source code of the program and a developer's guide is provided on the website as well. Therefore, users may modify the program and add further algorithms or extensions.
Centralized multi-cell resource and power allocation for multiuser OFDMA networks

Multiuser Orthogonal Frequency Division Multiple Access (OFDMA) networks, such as Long Term Evolution networks, use the frequency reuse-1 model to face the tremendous increase of mobile traffic demands, and to increase network capacity. However, inter-cell interference problems are generated, and they have a negative impact on cell-edge users performance. Resource and power allocation should be managed in a manner that alleviates the negative impact of inter-cell interference on system performance. In this paper, we formulate a novel centralized multi-cell resource and power allocation problem for multiuser OFDMA networks. The objective is to maximize system throughput while guaranteeing a proportional fair rate for all the users. We decompose the joint problem into two independent problems: a resource allocation problem and a power allocation problem. We prove that each of these problems is a convex optimization problem, and that their optimal solution is also an optimal solution to the original joint problem. Lagrange duality theory and subgradient projection method are used to solve the centralized power allocation problem. We study the convergence of our centralized approach, and we find out that it reduces inter-cell interference, and increases system throughput and spectral efficiency in comparison with the frequency reuse-1 model, reuse-3 model, fractional frequency reuse, and soft frequency reuse techniques.
Abandonment of the South Penninic–Austroalpine palaeosubduction zone, Central Alps, and shift from subduction erosion to accretion: constraints from Rb/Sr geochronology

Abstract: We present new age data for the evolution of the suture zone between lower plate South Penninic and upper plate Austroalpine units in the Central European Alps. Rb/Sr deformation ages for mylonitized rocks of the South Penninic palaeosubduction mélange and for deformed Austroalpine basement (Eastern Switzerland) shed light on the pre-Alpine and Alpine deformation history along the suture, as well as on synsubduction interplate mass transfer. Rb/Sr age data define two age groups. The first group reflects pre-Alpine events within the upper plate basement, with varying degree of resetting by subsequent Alpine overprints. The second group marks the waning of subduction-related deformation along the South Penninic–Austroalpine suture zone, at around 50 Ma, and termination at c. 47 Ma. Identical Rb/Sr ages for pervasively deformed Austroalpine and South Penninic lithologies point to tectonic erosion of the upper plate during subduction. We propose that underplating of the Middle Penninic micro-continent at c. 50 Ma led to the cessation of deformation within the South Penninic mélange, and shifted the zone of active deformation into the footwall. This also caused a contemporaneous upper plate surface uplift and shutoff of sedimentation in Alpine Gosau-type forearc basins.
Fast Top-k Area Topics Extraction with Knowledge Base

What are the most representative research topics in Artificial Intelligence (AI)? We formulate the problem as extracting top-k topics that can best represent a given area with the help of knowledge base. We theoretically prove that the problem is NP-hard and propose an optimization model, FastKATE, to address this problem by combining both explicit and latent representations for each topic. We leverage a large-scale knowledge base (Wikipedia) to generate topic embeddings using neural networks and use this kind of representations to help capture the representativeness of topics for given areas. We develop a fast heuristic algorithm to efficiently solve the problem with a provable error bound. We evaluate the proposed model on three real-world datasets. Experimental results demonstrate our model's effectiveness, robustness, real-timeness (return results in <1s), and its superiority over several alternative methods.
BFound: Sensor Enhanced Localization for Internet of Things

Beacons, the backbone of the physical web and location-based services, are widely used to tag objects and places. However, as a beacon's wireless transmission is limited to a ranging technology, the localization information is only available when the beacon is nearby. In this work, we propose BFound, a navigation and room level localization system that enable users to locate beacons within a building to the room level. The scheme is based on expanding the beacons' capability in two ways. First, the system builds upon crowdsourcing using data from smartphones carried by mobile users and infrastructure beacons to search for facilities within an area and navigate to the target region. Next, we utilize sensors on the beacons to further localize beacons to the room level. In order to enable room level localization, the beacon's sensors are leveraged to generate a signature unique to the room it belongs. This is achieved using wavelet transform. Evaluations show that BFound provides sufficient accuracy both for navigation as well as room level localization.
Overview of the 2017 Spoken CALL Shared Task

We present an overview of the shared task for spoken CALL. Groups competed on a prompt-response task using English-language data collected, through an online CALL game, from Swiss German teens in their second and third years of learning English. Each item consists of a written German prompt and an audio file containing a spoken response. The task is to accept linguistically correct responses and reject linguistically incorrect ones, with “linguistically correct” being defined by a gold standard derived from human annotations; scoring was performed using a metric defined as the ratio of the relative rejection rates on incorrect and correct responses. The task received twenty entries from nine different groups. We present the task itself, the results, a tentative analysis of what makes items challenging, a comparison between different metrics, and suggestions for a continuation.
Late Cretaceous Aquatic Angiosperms from Jiayin, Heilongjiang, Northeast China

Abstract: Three taxa of Late Cretaceous aquatic angiosperms, Queruexia angulata (Lesq.) Krysht, Cobbania corrugata (Lesq.) Stockey et al. and Nelumbites cf. extenuinervis Upchurch et al. from Jiayin of Heilongjiang, NE China, are described in detail. Among them, Cobbania and Nelumbites from the Upper Cretaceous in China are reported for the first time. The aquatic angiosperm assemblage of Queruexia‐Cobbania‐Nelumbites appears to imply a seasonal, warm and moist environment in the Jiayin area during the Santonian‐Campanian time.
A chaotic direct-sequence spread-spectrum communication system

The use of chaotic sequences as spectral spreading sequences in direct-sequence spread-spectrum (DS/SS) communication systems is proposed. The error probabilities of such systems are investigated and shown to be, for all practical purposes, identical to the conventional DS/SS systems which use binary signature sequences. Among the advantages of the use of chaotic sequences in DS/SS are the availability of a great number of them, the ease of their generation, as well as their inherent improvement in the security of transmission. >
Developments in Higher-Dimensional Automata Theory

We develop the language theory of higher-dimensional automata (HDAs). We show a pumping lemma which allows us to expose a class of non-regular ipomset languages. We also give an example of a regular language with unbounded ambiguity. Then we pass to decision and closure properties of regular languages. We show that inclusion of regular languages is decidable (hence is emptiness), and that intersections of regular languages are again regular. On the other hand, no universal ﬁnite HDA exists, so complements of regular languages are not regular. We introduce a width-bounded complement and show that width-bounded complements of regular languages are again regular.
Enumeration of first-order queries on classes of structures with bounded expansion

We consider the evaluation of first-order queries over classes of databases with bounded expansion. The notion of bounded expansion is fairly broad and generalizes bounded degree, bounded treewidth and exclusion of at least one minor. It was known that over a class of databases with bounded expansion, first-order sentences could be evaluated in time linear in the size of the database. We first give a different proof of this result. Moreover, we show that answers to first-order queries can be enumerated with constant delay after a linear time preprocessing. We also show that counting the number of answers to a query can be done in time linear in the size of the database.
Prototyping a hybrid main memory using a virtual machine monitor

We use a novel virtualization-based approach for computer architecture performance analysis. We present a case study analyzing a hypothetical hybrid main memory, which consists of a first-level DRAM augmented by a 10-100x slower second-level memory. This architecture is motivated by the recent emergence of lower-cost, higher-density, and lower-power alternative memory technologies. To model such a system, we customize a virtual machine monitor (VMM) with delay-simulation and instrumentation code. Benchmarks representing server, technical computing, and desktop productivity workloads are evaluated in virtual machines (VMs). Relative to baseline all-DRAM systems, these workloads experience widely varying performance degradation when run on hybrid main memory systems which have significant amounts of second-level memory.