Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct manipulation scene creation in 3D: estimating hand postures from multiple-camera images

In this alternative approach, the system allows users to create different colors and shapes of virtual objects in 3D spaces by direct manipulation. It is based on a proprietary, multiple-camera-based hand posture estimation method, in which palm poses are estimated from multiple-camera images by a statistical approach regardless of finger bending. Then, hand gestures associated with commands for direct manipulation are recognized by verifying the finger bending.
Aerosols over Delhi during pre‐monsoon months: Characteristics and effects on surface radiation forcing

The surface fluxes in the wavelength range 280–2800 nm were measured during the pre‐monsoon period, April–June 2003 along with the spectral distribution of aerosol optical depth (AOD) in the visible and near infrared wavelengths. The Ångström exponent alpha retrieved from the data showed abundance of desert aerosols over Delhi during this period. The aerosol composition constructed using the OPAC model indicated a typical mixture of two aerosol types: urban and desert. Due to this the aerosol mixture had a very low value of single scattering albedo ∼0.67. The average total radiative forcing efficiency observed at the surface in the broad wavelength band (280–2800 nm) was estimated and compared with the SBDART model calculated values.
A PATTERN IDENTIFICATION APPROACH TO CARTOGRAPHIC VISUALIZATION

Mental visualization and tools that foster it have recently been acknowledged as significant factors in scientific creativity. Cartography occupies a critical position in the growing array of scientific visualization tools, particularly for geographers, earth scientists and atmospheric scientists. Treating the map as a visualization tool leads to a different perspective on cartography than that generally taken when the map is viewed as a communication device. The goal of cartography and cartographic research shifts from a search for the optimal map to a search for spatial data abstraction methods that prompt pattern identification and lead to insight. A model is proposed for cartographic visualization that stresses the role of maps in data exploration. Emphasis is on the potential for maps to stimulate scientific insight by facilitating the discovery of patterns and relationships in spatial data. Following from this pattern identification model for cartographic visualization some perspectives are offered .
Crustal imprints of Precambrian orogenesis in western Laurentia

Crustal low‐velocity zones (LVZs) have been reported in active orogens such as the Himalayas and the Andes but rarely in stable cratonic regions. In this study, we provide compelling evidence for a significant midcrustal LVZ beneath eastern‐central Alberta, an integral part of the Precambrian Canadian Shield covered by thick Phanerozoic sedimentary deposits. This 200 km wide, over 10 km thick midcrustal LVZ is well resolved by shear velocity inversions using P‐to‐S receiver functions from more than 4600 earthquakes. It is generally overlain by a high‐velocity upper crust in the depth range of 8–15 km, especially in western‐central Alberta, which coincides with the previously documented Winagami reflection sequence. We interpret the LVZ to be of granitic composition, potentially in connection with the crystallization of partially molten crust during the Paleoproterozoic eon. In addition to the Precambrian tectonic history of western Laurentia, which featured plate convergence conducive to crustal melting, our crustal model is further supported by (1) a moderate spatial correlation between the LVZ and heat flow, and (2) shear velocities consistent with that of granite. The well preserved Winagami reflection sequence and the LVZ are potential evidence of distinct episodes of magmatism and crust modification in the Precambrian basement of the Western Canada Sedimentary Basin. The existence of a broad crustal LVZ suggests extensive subduction, orogenesis, and crustal melting during the Precambrian assembly of the North American craton.
Crystal chemistry and intracrystalline relationships of orthopyroxene in a suite of high pressure ultramafic nodules from the ‘Newer Volcanics’ of Victoria, Australia

Abstract A suite of orthopyroxenes from spinel Iherzolite xenoliths associated with basanites occurring in the Victorian (Australia) post-Pliocene ‘Newer Volcanics’ province was investigated by means of a crystal chemical methodology which provides accurate site occupancy and site configuration parameters. The M1 configuration is essentially constrained by AlVI rather than Fe2+. In addition, Fe3+, Cr3+ and Ti4+ are confined to M1 (Molin, 1989) and AlIV to TB. M2 is controlled by Fe M2 2+ ⇌ Mg M2, constrained by (Fe2+ + Ca) M2 > 0.14 atoms per formula unit (p.f.u.). Cation substitution in TB and M2 constrains the sum of the volumes of the respective polyhedra V TB +V M2 to remain essentially constant. Therefore, M2 favours the retention of the large Fe2+ up to melting-point, causing non-ideality of this iron-depleted orthopyroxene. As a consequence, the investigated orthopyroxene can be considered an ultimate Fe2+ carrier during partial mantle melting.
Federated NLP in Few-shot Scenarios

Natural language processing (NLP) sees rich mobile applications. To support various language understanding tasks, a foundation NLP model is often fine-tuned in a federated, privacy-preserving setting (FL). This process currently relies on at least hundreds of thousands of labeled training samples from mobile clients; yet mobile users often lack willingness or knowledge to label their data. Such an inadequacy of data labels is known as a few-shot scenario; it becomes the key blocker for mobile NLP applications. For the first time, this work investigates federated NLP in the few-shot scenario (FedFSL). By retrofitting algorithmic advances of pseudo labeling and prompt learning, we first establish a training pipeline that delivers competitive accuracy when only 0.05% (fewer than 100) of the training data is labeled and the remaining is unlabeled. To instantiate the workflow, we further present a system FFNLP , addressing the high execution cost with novel designs. (1) Curriculum pacing, which injects pseudo labels to the training workflow at a rate commensurate to the learning progress; (2) Representational diversity, a mechanism for selecting the most learnable data, only for which pseudo labels will be generated; (3) Co-planning of a model’s training depth and layer capacity. Together, these designs reduce the training delay, client energy, and network traffic by up to 46.0 × , 41.2 × and 3000.0 × , respectively. Through algorithm/system co-design, FFNLP demonstrates that FL can apply to challenging settings where most training samples are unlabeled.
Stochastic Traffic Regulator for End-to-End Network Delay Guarantees

Providing end-to-end network delay guarantees in packet-switched networks such as the Internet is highly desirable for mission-critical and delay-sensitive data transmission, yet it remains a challenging open problem. Due to the looseness of the deterministic bounds, various frameworks for stochastic network calculus have been proposed to provide tighter, probabilistic bounds on network delay, at least in theory. However, little attention has been devoted to the problem of regulating traffic according to stochastic burstiness bounds, which is necessary in order to guarantee the delay bounds in practice. We propose and analyze a stochastic traffic regulator that can be used in conjunction with results from stochastic network calculus to provide probabilistic guarantees on end-to-end network delay. Numerical results are provided to demonstrate the performance of the proposed traffic regulator.11This work was supported in part by the U.S. National Science Foundation under Grant No. 1717033.
Hot contacts of garnet peridotites in middle/upper crustal levels: new constraints on the nature of the late Variscan high‐T/low‐P event in the Moldanubian (Central Vosges/NE France)

P–T paths based on parageneses in the immediate vicinity of former high‐temperature contact zones between mantle peridotites and granulitic country rocks of the Central Vosges (NE France) were derived by applying several conventional thermometers and thermobarometric calculations with an internally consistent dataset. The results indicate that former garnet peridotites and garnet–spinel peridotites were welded together with crustal rocks at depths corresponding to 1–1.2 GPa. The temperature of the crustal rocks was about 650–700 °C at this stage, whereas values of 1100 °C (garnet peridotites) and 800–900 °C (garnet–spinel peridotites) were calculated for the ultramafic rocks. After emplacement of the mantle rocks, exhumation of the lower crust took place to a depth corresponding to 0.2–0.3 GPa. The temperatures of the incorporated peridotite slices were still high (900–1000 °C) at this stage. This is indicated by the presence of high‐T /low‐P parageneses (c. 800 °C, 0.2–0.3 GPa) in a small (1–10 m) contact aureole around a former garnet peridotite. Crustal rocks distant to the peridotites equilibrated in the same pressure range at lower temperature (650–700 °C). High cooling rates (102–103 °C Ma−1) were calculated for a garnet–biotite rock inclusion in the peridotites and for the crustal rocks at the contact by applying garnet–biotite diffusion modelling. Minimum rates of 0.75–7.5 cm a−1 are required for vertical ascent of rock units (30 km vertical distance) derived from the crust–mantle boundary, resulting in a late Variscan (340 Ma) high‐T /low‐P event.
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables

We consider the problem of estimating a sparse Gaussian Graphical Model with a special graph topological structure and more than a million variables. Most previous scalable estimators still contain expensive calculation steps (e.g., matrix inversion or Hessian matrix calculation) and become infeasible in high-dimensional scenarios, where p (number of variables) is larger than n (number of samples). To overcome this challenge, we propose a novel method, called Fast and Scalable Inverse Covariance Estimator by Thresholding (FST). FST first obtains a graph structure by applying a generalized threshold to the sample covariance matrix. Then, it solves multiple block-wise subproblems via element-wise thresholding. By using matrix thresholding instead of matrix inversion as the computational bottleneck, FST reduces its computational complexity to a much lower order of magnitude (O(p2)). We show that FST obtains the same sharp convergence rate O(√(log max{p, n}/n) as other state-of-the-art methods. We validate the method empirically, on multiple simulated datasets and one real-world dataset, and show that FST is two times faster than the four baselines while achieving a lower error rate under both Frobenius-norm and max-norm.
Encoding of Attributes for MPLS LSP Establishment Using Resource Reservation Protocol Traffic Engineering (RSVP-TE)

Multiprotocol Label Switching (MPLS) Label Switched Paths (LSPs) may be established using the Resource Reservation Protocol Traffic Engineering (RSVP-TE) extensions. This protocol includes an object (the SESSION_ATTRIBUTE object) that carries a Flags field used to indicate options and attributes of the LSP. That Flags field has eight bits allowing for eight options to be set. Recent proposals in many documents that extend RSVP-TE have suggested uses for each of the previously unused bits. This document defines a new object for RSVP- TE messages that allows the signaling of further attribute bits and also the carriage of arbitrary attribute parameters to make RSVP-TE easily extensible to support new requirements. Additionally, this document defines a way to record the attributes applied to the LSP on a hop-by-hop basis. The object mechanisms defined in this document are equally applicable to Generalized MPLS (GMPLS) Packet Switch Capable (PSC) LSPs and to GMPLS non-PSC LSPs. This document replaces and obsoletes the previous version of this work published as RFC 4420. The only change is in the encoding of the Type-Length-Variable (TLV) data structures.
Group Decision-making on an Optimal Stopping Problem

We consider group decision-making on an optimal stopping problem, for which large and stable individual differences have previously been established. In the problem, people are presented with a sequence of five random numbers between 0 and 100, one at a time, and are required to choose the maximum of the sequence, without being allowed to return to earlier values in the sequence. We examine group decision-making on these problems in an experimental setting where group members are isolated from one another, and interact solely via networked computers. The group members register their initial accept or reject decision for each value in the sequence, and then providing a potentially revised decision having viewed the recommendations of the other group members. Group decisions are made according to one of three conditions, requiring either consensus to accept from all group members, a majority of accept decisions from the group, or the acceptance of an appointed group leader. We compare individual decision-making to group decision-making under these three conditions, and find that, under some conditions, groups often significantly outperform even their best members. Using a signal detection analysis we provide an account of how the group decision-making conditions differ from one another, and from individual decision-making. Key findings are that people do not often revise their decisions, but, in the consensus and leadership conditions, are more conservative in their initial decisions. This conservatism removes the individual bias towards choosing values too early in the sequence, allowing the groups to perform better than their individual members. In the majority condition, however, people continue to behave as they did individually, and the group shows the same bias in decision-making.
Scheduling en el paradigma GRID

Un sistema grid conforma una red dinamica de recursos de computo heterogeneos que trabajan conjuntamente formando un entorno unico y uniforme. Un sistema grid puede abarcar diferentes dominios administrativos, y puede ser capaz de soportar cambios dinamicos en las organizaciones participantes y en los requerimientos de computo [5]. Para lograr este objetivo, un sistema grid debe ser capaz de proveer acceso a los recursos que los usuarios requieran, incluyendo procesamiento, datos, y aplicaciones. Este acceso debe estar respaldado por una infraestructura de seguridad a nivel del grid, pero que al mismo tiempo permita diversas y cambiantes poĺiticas de seguridad locales. Ademas, el sistema debe ser disenado con la capacidad de tolerar fallas a nivel de nodos individuales y cambios en la composicion del grid (hardware, configuracion de los sistemas y potencialmente sistema operativo). Por ultimo es importante que un sistema con estas caracteŕisticas sea simple de instalar y administrar. Para lograr este prometedor potencial es esencial contar con algoritmos de planificacion (scheduling) eficientes y efectivos. Desafortunadamente, los algoritmos tradicionales de scheduling empleados en sistemas paralelos y distribuidos, los cuales suelen correr sobre recursos homogeneos y dedicados, e.g., clusters de computadoras, no funcionan bien bajo el paradigma grid [2]. En este trabajo exploraremos algunos de los problemas abiertos relacionado con el problema del scheduling distribuido en sistemas grid.
A 40Gb/s TX and RX chip set in 65nm CMOS

Next generation optical and electrical communications such as chip-to-chip serial links or 100GbE require very-high-speed transceivers. At tens of Gb/s, both transmitters and receivers suffer from inadequate bandwidth and high power consumption. One major difficulty arises from the performance degradation of FIR-based FFEs as the FF's CK-Q delay becomes significant to one bit period. Using passive components as delay elements [1][2] can relax this issue to some extent, but the untunable delay is quite vulnerable to PVT variations. Traditional DFEs also suffer from speed limitation in its feedback loop, and parallelization schemes usually introduce complex circuits and high power consumption. This paper presents a full-rate 40Gb/s transceiver prototype significantly alleviating the above issues.
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective

Graph neural networks have shown great ability in representation (GNNs) learning on graphs, facilitating various tasks. Despite their great performance in modeling graphs, recent works show that GNNs tend to inherit and amplify the bias from training data, causing concerns of the adoption of GNNs in high-stake scenarios. Hence, many efforts have been taken for fairness-aware GNNs. However, most existing fair GNNs learn fair node representations by adopting statistical fairness notions, which may fail to alleviate bias in the presence of statistical anomalies. Motivated by causal theory, there are several attempts utilizing graph counterfactual fairness to mitigate root causes of unfairness. However, these methods suffer from non-realistic counterfactuals obtained by perturbation or generation. In this paper, we take a causal view on fair graph learning problem. Guided by the casual analysis, we propose a novel framework CAF, which can select counterfactuals from training data to avoid non-realistic counterfactuals and adopt selected coun-terfactuals to learn fair node representations for node classification task. Extensive experiments on synthetic and real-world datasets show the effectiveness of CAF.
The use of simulation to evaluate hospital operations between the emergency department and a medical telemetry unit

We present a simulation model of the operations in the emergency department (ED) and medical telemetry (Med Tele) units at Rush North Shore Medical Center. The model allows management to see the operations of both units as well as how the processes of each unit impact the other. Due to the large amount of variability that can take place within these units, Rush North Shore Medical Center along with Cap Gemini Ernst & Young sought the use of simulation to help evaluate their operations and provide insight into possible areas for improvement. Rockwell automation created a model which depicts the current operations and evaluates possible alternatives to reduce the length of stay in the ED and improve operations. Using simulation, the hospital was able to select two to three key changes, rather than creating more stress with ten or more changes, to get the same result.
Estimation of average DEM accuracy under linear interpolation considering random error at the nodes of TIN model

The concept of a digital elevation model (DEM) can be used for a digital representation of any single‐valued surface such as a terrain relief model (digital terrain model, DTM). DEMs are widely used in remote sensing, geographical information systems (GIS), and virtual reality. Estimating the accuracy of a DEM is an essential issue in the acquisition of spatial data, particularly for applications that require a highly accurate DEM, such as engineering applications. The accuracy of a DEM is subject to many factors such as the number of sampling points, the spatial distributions of the sampling points, the methods used for interpolating surface elevations, the propagated error from the source data, and other factors. Of these factors, this study will focus on estimating the mean elevation error in a DEM surface that is caused by errors of component nodes in a triangulated irregular network (TIN). This paper will present a newly derived mathematical formula, with the details of the procedure used to derive this formula, to study the relationship between the errors at the TIN nodes and the propagated mean elevation error of a DEM surface that is linearly constructed from the TIN. We have verified the analytical formula by numerical simulation. The experimental results confirm the theoretical derivation of the formula.
Corrigibility

As artiﬁcially intelligent systems grow in intelligence and capability, some of their available options may allow them to resist intervention by their programmers. We call an AI sys-tem “corrigible” if it cooperates with what its creators regard as a corrective intervention, despite default incentives for rational agents to resist attempts to shut them down or modify their preferences. We introduce the notion of corrigibility and analyze utility functions that attempt to make an agent shut down safely if a shutdown button is pressed, while avoiding incentives to prevent the button from being pressed or cause the button to be pressed, and while ensuring propagation of the shutdown behavior as it creates new subsystems or self-modiﬁes. While some proposals are interesting, none have yet been demonstrated to satisfy all of our intuitive desider-ata, leaving this simple problem in corrigibility wide-open.
WeChat AI's Submission for DSTC9 Interactive Dialogue Evaluation Track

We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2 (Interactive Dialogue). In sub-task 1, we employ a pre-trained language model to generate topic-related responses and propose a response ensemble method for response selection. In sub-task2, we propose a novel Dialogue Planning Model (DPM) to capture conversation ﬂow in the interaction with humans. We also design an integrated open-domain dialogue system containing pre-process, dialogue model, scoring model, and post-process, which can generate ﬂuent, coherent, consistent, and human-like responses. We tie 1 st on human ratings and also get the highest Meteor, and Bert-score in sub-task 1, and rank 3 rd on interactive human evaluation in sub-task 2.
Trend detection in river flow series: 1. Annual maximum flow / Détection de tendance dans des séries de débit fluvial: 1. Débit maximum annuel

Abstract Results of a study on change detection in hydrological time series of annual maximum river flow are presented. Out of more than a thousand long time series made available by the Global Runoff Data Centre (GRDC) in Koblenz, Germany, a worldwide data set consisting of 195 long series of daily mean flow records was selected, based on such criteria as length of series, currency, lack of gaps and missing values, adequate geographical distribution, and priority to smaller catchments. The analysis of annual maximum flows does not support the hypothesis of ubiquitous growth of high flows. Although 27 cases of strong, statistically significant increase were identified by the Mann-Kendall test, there are 31 decreases as well, and most (137) time series do not show any significant changes (at the 10% level). Caution is advised in interpreting these results as flooding is a complex phenomenon, caused by a number of factors that can be associated with local, regional, and hemispheric climatic processes. Moreover, river flow has strong natural variability and exhibits long-term persistence which can confound the results of trend and significance tests.