Miracle-dz/UniFAR-FTUs huggingface dataset:
pit-Enhancing the Precision of Eye Tracking using Iris Feature Motion Vectors

A new high-precision eye-tracking method has been demonstrated recently by tracking the motion of iris features rather than by exploiting pupil edges. While the method provides high precision, it suffers from temporal drift, an inability to track across blinks, and loss of texture matches in the presence of motion blur. In this work, we present a new methodology $pi_t$ to address these issues by optimally combining the information from both iris textures and pupil edges. With this method, we show an improvement in precision (S2S-RMS & STD) of at least 48% and 10% respectively while fixating a series of small targets and following a smoothly moving target. Further, we demonstrate the capability in the identification of microsaccades between targets separated by 0.2-degree.
DELIS-TR-376 Network Discovery and Veriﬁcation

—Due to its fast, dynamic, and distributed growth process, it is hard to obtain an accurate map of the Internet. In many cases such a map—representing the structure of the Internet as a graph with nodes and links—is a prerequisite when investigating properties of the Internet. A common way to obtain such maps is to make certain local measurements at a small subset of the nodes and then to combine these in order to “discover” (an approximation of) the actual graph. Each of these measurements is potentially quite costly. It is thus a natural objective to minimize the number of measurements which still discover the whole graph. We formalize this problem as a combinatorial optimization problem and consider it for two different models characterized by different types of measurements. We give several upper and lower bounds on the competitive ratio (for the on-line network discovery problem) and the approximation ratio (for the off-line network veriﬁcation problem) in both models. Furthermore, for one of the two models we compare four simple greedy strategies in an experimental analysis.
DDColor: Towards Photo-Realistic and Semantic-Aware Image Colorization via Dual Decoders

Automatic image colorization is a challenging problem. Due to the high illness and multi-modal uncertainty, directly training a deep neural network usually leads to incorrect semantic colors and low color richness. Recent transformer-based methods can deliver better results, but they often rely on manually designed priors, which are hard to implement and suffer from poor generalization ability. Moreover, they tend to introduce serious color bleeding effects since color attention is performed on single-scale features, thus fail to exploit sufﬁcient semantic information. To address these issues, we propose DDColor , a new end-to-end method with d ual d ecoders for image color ization. Our approach includes a multi-scale image decoder and a transformer-based color decoder. The former restores the spatial resolution of the image, while the latter establishes the correlation between color and semantic representations via cross-attention. Rather than using additional priors, our two decoders work together to leverage multi-scale image features to guide optimization of adaptive color queries, signiﬁcantly alleviating color bleeding effects. In addition, a simple yet effective colorfulness loss is introduced to further enhance the color richness of generated results. Our extensive experiments demonstrate that DDColor achieves signiﬁcantly superior performance to existing state-of-the-art works both quantitatively and qualitatively. Codes will
Water Table Management Effects on Denitrification and Nitrous Oxide Evolution

Previous research suggested that using controlled drainage to elevate the water table reduces NO 3 - contamination of surface water by enhancing denitrification. The C 2 H 2 inhibition technique was used to study denitrification and N 2 O evolution using 56-cm-long, undisturbed cores of Cape Fear loam (clayey, mixed, thermic Typic Umbraquult) maintained in the field and subjected to three static water table levels (15, 30, and 45 cm). Results showed that intermittent C 2 H 2 exposure did not (i) affect soil inorganic N distribution between NH 4 + and NO 3 - , (ii) diminish inhibition of N 2 O reduction during subsequent C 2 H 2 exposure, or (iii) induce C 2 H 2 decomposition. Denitrification from 1 Nov. 1993 through 21 Apr. 1994 (172 d) was 341 kg N ha -1 for the 15 cm water table treatment, 260 kg N ha -1 for the 30-cm water table treatment, and 86 kg N ha -1 for the 45-cm water table treatment. Denitrification was maximum at the lowest monitored zone (36-54 cm) for each water table treatment. Total N 2 O evolution was 9 kg N ha -1 for the 15-cm water table treatment, 4 kg N ha -1 for the 30-cm water table treatment, and 2 kg N ha -1 for the 45-cm water table treatment. Nitrous oxide evolution was positively correlated with mean soil temperature (10-cm depth) until low NO 3 - levels appeared to limit denitrification. Since steady-state diffusion was not reached, estimates of N 2 evolution, using N 2 O evolution in the presence of C 2 H 2 , were underestimated 12-fold. Evolved N 2 O-N represented only 2% of denitrification in the soil core (0-54 cm) for each water table treatment. Drainage control to elevate the water table enhanced denitrification and N 2 O evolution, reducing the potential for N transport with subsurface drainage to surface water.
Sherlock: Modeling Structured Knowledge in Images

How to build a machine learning method that can continuously gain structured visual knowledge by learning structured facts? Our goal in this paper is to address this question by proposing a problem setting, where training data comes as structured facts in images with different types including (1) objects(e.g., ), (2) attributes (e.g., ), (3) actions (e.g., ), (4) interactions (e.g., ). Each structured fact has a semantic language view (e.g., ) and a visual view (an image with this fact). A human is able to efficiently gain visual knowledge by learning facts in a never ending process, and as we believe in a structured way (e.g., understanding "playing" is the action part of , and hence can generalize to recognize if just learn additionally). Inspired by human visual perception, we propose a model that is (1) able to learn a representation, we name as wild-card, which covers different types of structured facts, (2) could flexibly get fed with structured fact language-visual view pairs in a never ending way to gain more structured knowledge, (3) could generalize to unseen facts, and (4) allows retrieval of both the fact language view given the visual view (i.e., image) and vice versa. We also propose a novel method to generate hundreds of thousands of structured fact pairs from image caption data, which are necessary to train our model and can be useful for other applications.
Boundary Negotiating Artifacts in Personal Informatics: Patient-Provider Collaboration with Patient-Generated Data

Patient-generated data is increasingly common in chronic disease care management. Smartphone applications and wearable sensors help patients more easily collect health information. However, current commercial tools often do not effectively support patients and providers in collaboration surrounding these data. This paper examines patient expectations and current collaboration practices around patient-generated data. We survey 211 patients, interview 18 patients, and re-analyze a dataset of 21 provider interviews. We find that collaboration occurs in every stage of self- tracking and that patients and providers create boundary negotiating artifacts to support the collaboration. Building upon current practices with patient-generated data, we use these theories of patient and provider collaboration to analyze misunderstandings and privacy concerns as well as identify opportunities to better support these collaborations. We reflect on the social nature of patient-provider collaboration to suggest future development of the stage-based model of personal informatics and the theory of boundary negotiating artifacts.
GREATER SAGE-GROUSE (Centrocercus urophasianus) POPULATION RESPONSE TO NATURAL GAS FIELD DEVELOPMENT IN WESTERN WYOMING

Degradation of nesting habitat has been proposed as a factor contributing to Greater Sage-Grouse (Centrocercus urophasianus) population declines throughout North America. Delineating suitable nesting habitat across landscapes with relatively contiguous sagebrush cover is difficult but important to identify areas for protection. We used radio-telemetry to locate Greater Sage-Grouse nests in relatively contiguous sagebrush habitats in Wyoming to investigate the spatial arrangement of nests relative to lek and other nest locations. Nest distributions were spatially related to lek location within 3 and 5 km of a lek, and a 5-km buffer included 64% of the nests. There was no relationship between lek size and lek-to-nest distance, suggesting that accurate population trend evaluation might require lek surveys in addition to lek counts. Closest known lek-to-nest distance was greater for successfully hatched compared to destroyed nests, and closely spaced nests tended to experience lower success and have higher probabilities of both nests experiencing the same fate compared to isolated nests, suggesting that a mechanism of enhanced prey detection occurred at higher nest densities. A low probability that a given individual’s consecutive-year nest spacing occurred randomly suggested nesting site-area fidelity. Although a grouped pattern of nests occurred within 5 km of a lek, the proportion of nesting females located farther than 5 km could be important for population viability. Managers should limit strategies that negatively influence nesting habitat regardless of lek locations, and preserve adequate amounts of unaltered nesting habitat within treatment boundaries to maintain nest dispersion and provide sites for philopatric individuals.
Designing Artifacts of IT Strategy for Achieving Business/IT Alignment

It is increasingly acknowledged that firms cannot be competitive if their business and information technology strategies are not aligned. A number of proposals have been made for achieving strategic alignment. Despite still being a major concern for business executives there is little published research that attempts to give methodological support for achieving strategic alignment in day-to-day business. Additionally it seems that alignment needs to be investigated in terms of formulating and implementing IT strategy on lower levels of abstraction in order to analyze, monitor and control the desired results. At first this paper covers the design of an IT governance architecture, considering existing approaches of enterprise architecture and strategic alignment. Subsequently an approach for clarifying the domain IT strategy by designing fine grained artifacts is presented. By choosing this approach, alignment is more likely to be achieved in practice and therefore, IT strategy implementation is supported.
Smart-metering for monitoring building power distribution network using instantaneous phasor computations of electrical signals

This paper presents a smart-metering framework based on computations of instantaneous phasors of voltage and current signals measured at a given node. The idea and requirement of electrical transparency inside a building is presented initially. Then the implementation of phasor estimation algorithm is discussed for the purpose of smart-metering. The capability of the smart-meter to do detailed power quality analysis is also presented. The ongoing work of hardware implementation and real-time testing of such smart-metering is also mentioned in the paper.
Inference of gene regulatory networks by integrating gene expressions and genetic perturbations

To elucidate the overall relationships between gene expressions and genetic perturbations, many approaches for SNPs to be involved in gene regulatory network (GRNs) inference have been suggested. In the most of the inferences of networks named as SNP-Gene Regulatory Networks (SGRNs) inference, pairs of SNP-gene are still separately given by performing eQTL mappings but eQTLs are not identified during network constructions. In order to build a SGRN for a given set of genes and SNPs without pre-defined eQTL information, we propose a method that is based on a structural equation model. The method consists of three steps: (i) ridge regression, (ii) elastic net regression, and (iii) iterative adaptive lasso regression. In the inference, it is assumed that each gene has a single unknown eQTL. The first two steps are to remove false positive edges keeping as many true positive edges as possible, and then lastly, final edges are selected by iterative adaptive lasso regression that iteratively gives more weight to the edge whose coefficient value is relatively high. To evaluate the performance, the method is applied to data that is randomly generated from the simulated networks and parameters. The method is also applied to psychiatric disorder data. There are three main contributions in this work. First, the proposed method provides both the gene regulatory inference and the identification of eQTL that affect genes in the network. Second, the simulation result proves that an integrative approach of multiple regression methods can effectively detect true edges as well as filter false positive edges. Lastly, it is demonstrated by applying it to psychiatric disorder data that our inference without eQTL information can discover the SGRNs that partially confirms eQTLs identified by our previous work.
MITA: An Information Extraction Approach to Analysis of Free-Form Text in Life Insurance Applications

MetLife processes over 300,000 life insurance applications a year. Undernriting of these applications is labor intensive. Automation is difficult since they include many free-form text fields. MITA, MetLife's Intelligent Text Analyzer, uses the Infonnation Extraction --IE-- technique of Natural Language Processing to structure the extensive text fields on a life insurance application. Knowledge engineering, with the help of underwriters as domain experts, was performed to elicit significant concepts for both medical and occupational text fields. A corpus of 20,000 life insurance applications provided the syntactical and semantic patterns in which these underwriting concepts occur. The extracted information can then be analyzed by conventional knowledge based systems. We project that MITA and knowledge based analyzers will increase underwriting productivity by 20 to 30%.
Design and Construction of Knowledge Ontology for Thematic Cartography Domain

The paper deals with ontology modelling for the purpose of design and creating of knowledge ontology for thematic cartography. The prepared ontology represents a database of selected declarative cartographical knowledge subsequently employed in the intelligent system for interactive support of thematic map design. The knowledge system pilot project under development is intended for users without necessary cartographical knowledge to whom such system will enable interactive creation of a thematic map and will provide them with support to this aim. The paper brings up information on possibilities of a domain expert (cartographer) in the endeavour to seize domain knowledge of thematic cartography and to express them in a formalized way. OWL ontology concentrates, formalizes and organizes declarative knowledge of thematic cartography domain. The result is the database containing taxonomy of terms hierarchically arranged into categories as well as description of their mutual relations.
A Fundamental Relationship between Bilateral Filtering, Adaptive Smoothing, and the Nonlinear Diffusion Equation

newspapers and past students' theses. These imaged documents will not be OCR'ed as originally planned due to the overwhelming cost involved. The images are available for public viewing and downloading. The present method will provide an automated means of retrieving similar document images from the library website without having to download every image for inspection of its content to decide its relevance. AbstractÐIn this paper, the relationship between bilateral filtering and anisotropic diffusion is examined. The bilateral filtering approach represents a large class of nonlinear digital image filters. We first explore the connection between anisotropic diffusion and adaptive smoothing, and then the connection between adaptive smoothing and bilateral filtering. Previously, adaptive smoothing was considered an inconsistent approximation to the nonlinear diffusion equation. We extend adaptive smoothing to make it consistent, thus enabling a unified viewpoint that relates between nonlinear digital image filters and the nonlinear diffusion equation.
Multiple mantle sources during island arc magmatism: U–Pb and Hf isotopic evidence from the Kohistan arc complex, Pakistan

ABSTRACT This paper presents high‐precision U–Pb ages and initial Hf isotopic compositions of zircon from mafic to felsic rocks of the Kohistan Arc Complex, Pakistan. Three magmatic pulses tapping geochemically different reservoirs are distinguished. Partial melting of mantle with MORB‐type isotopic characteristics generated 99–92‐Ma‐old magmas. Plutonism around 85 Ma tapped a more fertile mantle source, most likely consisting of a >600‐Ma‐old metasomatically enriched mantle, or of mantle contaminated by an old sedimentary component; 82‐Ma‐old felsic peraluminous dykes have MORB‐type isotopic compositions considered to be inherited from remelting earlier magmas in the deep base of the arc. The isotopic results demonstrate several and rather rapid changes in melt source region during arc development. They also show that there was subordinate continental influence and negligible importance of slab components for the Hf budget during the generation of the Kohistan Arc Complex.
Engineering children's physical activity : making active choices easy

Regular participation in physical activity provides physical, social and mental benefits to young peoples' health and well-being; however, there is increasing concern that large numbers of children and adolescents are doing insufficient physical activity to obtain health benefits. The physical environment is a major factor in providing opportunities to be physically active. In order to plan, design and manage cities that make children happy and safe, it is paramount to consider how children experience their environment, and which specific features of the physical environment are related to their physical activity and consequently their health. This review proposes that physical activity has been engineered out of the daily lives of children through transportation systems, land-use patterns and neighbourhood designs that inhibit play and walking or cycling to school. Research suggests that changing the built environment is a promising strategy in fighting youth inactivity. This will be best achieved throug.
Short-Range Microwave Networks to Scale Superconducting Quantum Computation

A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributing a quantum computer across nearby small qubit arrays, known as chiplets, could solve many problems associated with size. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. We model and evaluate the chiplet architecture in a way that bridges the physical and network layers. We ﬁnd concrete evidence that distributed quantum computing may accelerate the path toward useful and ultimately scalable quantum computers. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.
DEMETER Satellite Observations of Plasma Irregularities in the Topside Ionosphere at Low, Middle, and Sub‐Auroral Latitudes and their Dependence on Magnetic Storms

Observations of plasma density structure and electric field irregularities gathered with probes on the Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) satellite are presented to characterize the topside ionosphere at low, middle, and sub-auroral latitudes. Data from successive DEMETER orbits during magnetic storms illustrate how low, mid-, and subauroral latitude plasma density, plasma density structures, and electric field irregularities correlate and evolve with changes in Dst. The observations reveal: (1) electric field irregularities associated with density depletions at mid latitudes are similar to those that characterize equatorial spread F at low latitudes; (2) large, well-defined density depletions that extend to mid-latitude display zonal widths and interdepletion spacings that are similar to spread F density depletion widths and spacings observed at the equator; (3) in some cases, ULF/ELF magnetic field irregularities are observed in association with the electric field irregularities particularly on the walls of the plasma density structures and may be related to finely structured spatial currents and/or Alfven waves; (4) precisely during the main phase of severe geomagnetic storms, increased ambient plasma densities and broad regions of irregularities are observed near 710 km, initially at storm commencement near the magnetic equator and then extending to mid- and sub-auroral latitudes within the ∼8-h period corresponding to the negative Dst excursions; and (5) intense, broadband electric and magnetic field irregularities are often observed at sub-auroral latitudes and are typically associated with the trough region and its poleward plasma density gradient. The observations provide a general framework showing how low, mid-, and sub-auroral latitude plasma density structuring and associated electric field irregularities respond to geomagnetic storms.
Sm–Nd dating of garnet granulites from the Kohistan complex, northern Pakistan

Sm–Nd mineral-isochron ages of garnet granulites in the southern part of the Kohistan complex are determined. The 91.0 ± 6.3 Ma age is obtained from a granulite body of the Jijal complex at Pattan and the 69.5 ± 9.3 Ma age is obtained from a granulite body of the Chilas complex at Zambil. These ages indicate that the granulite bodies at Pattan and at Zambil had cooled to below upper amphibolite facies by about 90 Ma and about 70 Ma respectively. The time of cooling of the granulite of the Jijal complex is comparable to the time-lapse of the Asia–Kohistan collision (102–75 Ma), although that of the Chilas complex is probably younger than the Asia–Kohistan collision and certainly older than the Asia–India collision (c50 Ma).
Scalable Zero-shot Entity Linking with Dense Entity Retrieval

This paper introduces a conceptually simple, scalable, and highly effective BERT-based entity linking model, along with an extensive evaluation of its accuracy-speed trade-off. We present a two-stage zero-shot linking algorithm, where each entity is defined only by a short textual description. The first stage does retrieval in a dense space defined by a bi-encoder that independently embeds the mention context and the entity descriptions. Each candidate is then re-ranked with a cross-encoder, that concatenates the mention and entity text. Experiments demonstrate that this approach is state of the art on recent zero-shot benchmarks (6 point absolute gains) and also on more established non-zero-shot evaluations (e.g. TACKBP-2010), despite its relative simplicity (e.g. no explicit entity embeddings or manually engineered mention tables). We also show that bi-encoder linking is very fast with nearest neighbor search (e.g. linking with 5.9 million candidates in 2 milliseconds), and that much of the accuracy gain from the more expensive cross-encoder can be transferred to the bi-encoder via knowledge distillation. Our code and models are available at https://github.com/facebookresearch/BLINK.