Miracle-dz/UniFAR-FTUs huggingface dataset:
Electron‐impact excitation and emission cross sections of the H2 Lyman and Werner Systems

Excitation functions of the H2 Lyman (Ly) ( B1∑∑u - X1∑∑g) and Werner (W) (C1∏u - X1∑∑g ) band systems have been reanalyzed using a combination of measurements and theoretical considerations. These systems are prominent emitters in outer planet atmospheric dayglow and auroral activity and can be used to infer energy deposition and heating rates. Earlier measurements of the cross sections reported by Shemansky et al. [1985a] have been found to be inaccurate in the threshold energy region. A combination of high-resolution spectral and shape function measurements obtained at the Jet Propulsion Laboratory (JPL) in low- and medium-energy regions have been used to obtain relative excitation shape functions of the two systems. At energies above 250 eV, we have used the measurements obtained earlier by De Heer and Carriere [1971] in order to define the first two terms of the Born electric dipole collision strength. The complete set of collision strength terms is obtained by combining the JPL and De Heer and Carriere [1971] data. We have found that, contrary to results of Shemansky et al. [1985a], the shape functions of the H2 Ly and W systems, expressed in units of threshold energy, are the same within experimental error. Absolute cross sections of the H2 Ly and W systems are established using the theoretical oscillator strengths of Abgrall et al. [1987, 1993a, b, c] and Abgrall and Roueff [1989]. The atomic hydrogen H Ly α emission cross section resulting from dissociative excitation of H2 at 100 eV obtained from relative intensities of H2 W emission lines is also derived and compared with other experimental measurements. At a gas temperature of 300 K and electron energy of 100 eV, the cross sections for the H Ly α, H2 Ly, and W emissions are (0.716 ± 0.095) × 10−17, (2.62 ± 0.34) × 10−17, and (2.41 ± 0.31) × 10−17 cm2, respectively. The accuracy of the absolute values and shape functions is limited primarily by electron gun performance, as was the case for Shemansky et al. The rotational dependence of the transition dipole matrix elements and perturbations between the B 1∑+u and C1∏+u states have a significant effect on the cross sections.
A Simple Sequential Algorithm for Approximating Bayesian Inference

People can apparently make surprisingly sophisticated inductive inferences, despite the fact that there are constraints on cognitive resources that would make performing exact Bayesian inference computationally intractable. What algorithms could they be using to make this possible? We show that a simple sequential algorithm, Win-Stay, Lose-Shift (WSLS), can be used to approximate Bayesian inference, and is consistent with human behavior on a causal learning task. This al-gorithm provides a new way to understand people’s judgments and a new efﬁcient method for performing Bayesian inference.
No Video Left Behind: A Utility-Preserving Obfuscation Approach for YouTube Recommendations

Online content platforms optimize engagement by providing personalized recommendations to their users. These recommendation systems track and proﬁle users to predict relevant content a user is likely interested in. While the personalized recommendations provide utility to users, the tracking and proﬁling that enables them poses a privacy issue because the platform might infer potentially sensitive user interests. There is increasing interest in building privacy-enhancing obfuscation approaches that do not rely on cooperation from online content platforms. However, existing obfuscation approaches primarily focus on enhancing privacy but at the same time they degrade the utility because obfuscation introduces unrelated recommendations. We design and implement D E -H ARPO , an obfuscation approach for YouTube’s recommendation system that not only obfuscates a user’s video watch history to protect privacy but then also denoises the video recommendations by YouTube to preserve their utility. In contrast to prior obfus-cation approaches, D E -H ARPO adds a denoiser that makes use of a “secret” input (i.e., a user’s actual watch history) as well as information that is also available to the adversarial recommendation system (i.e., obfuscated watch history and corresponding “noisy" recommendations). Our large-scale evaluation of D E -H ARPO shows that it outperforms the state-of-the-art by a factor of 2 × in terms of preserving utility for the same level of privacy, while maintaining stealthiness and robustness to de-obfuscation.
Comunidades microplanctônicas no Oceano Atlântico Sul Ocidental: biomassa e distribuição em novembro de 1992

A distribuicao quantitativa e a biomassa do microplâncton (1O-200J.lffi) foram investigadas ao longo de um transecto entre 8ao Paulo (25o30'8) e a Peninsula Antartica (62o05'8) em novembro de 1992. Aumentos de biomassa fitoplanctonica ocorreram na Frente Polar (FP) e Zona de Confluencia Brasil-Malvinas (ZCBM) (0,84-1,23J.1g Chl.a/l). A biomassa foi menor nas massas de agua adjacentes, com valores medios semelhantes de clorofila-a para a Agua 8ubtropical (0,27J.1g/1), onde ocorreu florescimento de Trichodesmium erythraeum, e Agua de 8uperficie Antartica (O, 18J.1g11). A area central oceânica na Agua 8ubantartica ao largo da plataforma patagonica (46o8-54o8) constituiu notavel excecao, com florescimentos significativos do fitoplâncton (ate 2,46J.1g Chl.a/1). As diatomaceas dominaram as areas de crescimento intensivo nas duas fTentes, onde os valores de abundância e biomassa do fitoplâncton foram semelhantes, indicando que ambientes com caracteristicas hidrograficas e biologicas distintas suportam florescimentos de mesma magnitude. Ao norte da ZCBM dominaram especies com menor quantidade de silica, refletindo concentracoes menores deste nutriente naquelas aguas. Em contrapartida, especies com paredes celulares espessadas dominaram a comunidade durante o florescimento na FP. Estes representantes parecem ser recorrentes e com distribuicao circumpolar na FP em diferentes longitudes. Ciliados e dinoflagelados dominaram na Agua 8ubtropical e norte da Confluencia, parecendo responder rapidamente as elevacoes de densidade do fitoplâncton. A Prymnesiophyceae Phaeocystis aft: globosa foi abundante em algumas estacoes.
The mechanism of the Deep Bolivia Earthquake of June 9, 1994

We analyzed the IRIS broad-band seismograms for the June 9, 1994, Bolivia earthquake, the largest deep-focus earthquake ever recorded. We inverted the record sections with a duration of 330 sec which include P, pP and sP phases, and obtained a dip-slip mechanism: (dip(δ), rake(λ), strike(ф)) = (13°, −4°, 1°) or (89°, −103°, 95°), with a scalar moment of Mo=2.9×10^(21) Nm (Mw=8.2). This mechanism is similar to that obtained from long-period (175 to 250 sec) Rayleigh and Love waves: (δ, λ, ф) =(83°, −100°, 90°); Mo=3.0×10^(21) Nm (Mw=8.3). The main rupture was preceded by about 10 sec by a cluster of smaller events with a total moment of 1.2×10^(20) Nm (Mw=7.3). The main rupture starts at about 20 km east or northeast of the initial break, and propagates horizontally in the east to northeast direction. The source duration is 40 sec, and the rupture dimension is about 40km. If a fault area of 40×40km² is assumed, the stress drop is 110 MPa. An inversion of body waves (P, pP, and sP) with 6 basis moment tensors yielded a best-fit solution with a 10% implosive component. This result is of marginal significance and its confirmation would require more detailed information on the structures near the source region, pP bounce points and stations. The observed amplitude of the radial mode, _0S_0, (1226 sec) is consistent with a double couple model with less than 2 % isotropic component.
Investigations of tilt measurements using shallow borehole tiltmeters

An array of shallow borehole tiltmeters has been operated at Pinon Flat Observatory since early in 1977. The data from this array are examined for coherence between the individual instruments and compared with the corresponding data from three 732-m laser strainmeters. In general, there is no significant coherence between the signals from the tiltmeters outside the microseismic and tidal bands even though they are spaced as closely as 10 m apart. Comparisons with the strain records show that the observed tilt noise power exceeds the strain noise power by 25–40 dB over the band from 10−6 to 1 Hz. Analysis of the coherence estimates establishes the necessity for an unacceptably large (≃1000) array of instruments in order to determine the common tectonic signals. The observed secular tilt rates are from 40 to 450 times the observed secular strain rates for the same period. The theoretical noise power limit of the tilt transducer renders the instrument incapable of recording background noise at a quiet site over the band from 10−4 to 10−1 Hz.
Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction

MOTIVATION Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. RESULTS A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. AVAILABILITY The pipeline software components are freely available on request to the authors. CONTACT dstates@umich.edu SUPPLEMENTARY INFORMATION http://stateslab.bioinformatics. med.umich.edu/software.html.
EvoX: A Distributed GPU-accelerated Library towards Scalable Evolutionary Computation

—During the past decades, evolutionary computation (EC) has demonstrated promising potential in solving various complex optimization problems of relatively small scales. Nowa- days, however, ongoing developments in modern science and engineering are bringing increasingly grave challenges to the con- ventional EC paradigm in terms of scalability. As problem scales increase, on the one hand, the encoding spaces (i.e., dimensions of the decision vectors) are intrinsically larger; on the other hand, EC algorithms often require growing numbers of function evaluations (and probably larger population sizes as well) to work properly. To meet such emerging challenges, not only does it require delicate algorithm designs, but more importantly, a high-performance computing framework is indispensable. Hence, we develop a distributed GPU-accelerated algorithm library — EvoX . First, we propose a generalized workﬂow for implementing general EC algorithms. Second, we design a scalable computing framework for running EC algorithms on distributed GPU devices. Third, we provide user-friendly interfaces to both researchers and practitioners for benchmark studies as well as extended real-world applications. To comprehensively assess the performance of EvoX , we conduct a series of experiments, including: (i) scalability test via numerical optimization benchmarks with problem dimensions/population sizes up to millions; (ii) acceleration test via a neuroevolution task with multiple GPU nodes; (iii) extensibility demonstration via the application to reinforcement learning tasks on the OpenAI Gym. The code of EvoX is available at https://github.com/EMI-Group/EvoX.
Ground target tracking with STAP radar

The problem of tracking ground moving targets by a moving radar (airborne, spaceborne) is addressed. Tracking of low Doppler targets within a strong clutter background is of special interest. The motion of the radar platform induces a spreading of the clutter Doppler spectrum so that low Doppler target echoes may be buried in the clutter band. Detection of such targets can be much alleviated by space–time adaptive processing (STAP), which implicitly compensates for the Doppler spread effect caused by the platform motion. Even if STAP is applied, low Doppler targets can be masked by the clutter notch. This physical phenomenon is frequently observed and results in a series of missing detections which may seriously degrade the tracking performance. A new sensor model adapted to STAP is proposed and its benefits to tracking well-separated targets are discussed. By exploiting a priori information on the sensor specific clutter notch, the model in particular provides a more appropriate treatment of missing detections. In this context, the minimum detectable velocity (MDV) proves to be an important sensor parameter, explicitly entering into ground moving target indication (GMTI) tracking.
3D keypoint detectors and descriptors for 3D objects recognition with TOF camera

The goal of this work is to evaluate 3D keypoints detectors and descriptors, which could be used for quasi real time 3D object recognition. The work presented has three main objectives: extracting descriptors from real depth images, obtaining an accurate degree of invariance and robustness to scale and viewpoints, and maintaining the computation time as low as possible. Using a 3D time-of-flight (ToF) depth camera, we record a sequence for several objects at 3 different distances and from 5 viewpoints. 3D salient points are then extracted using 2 different curvatures-based detectors. For each point, two local surface descriptors are computed by combining the shape index histogram and the normalized histogram of angles between the normal of reference feature point and the normals of its neighbours. A comparison of the two detectors and descriptors was conducted on 4 different objects. Experimentations show that both detectors and descriptors are rather invariant to variations of scale and viewpoint. We also find that the new 3D keypoints detector proposed by us is more stable than a previously proposed Shape Index based detector.
New feature selection algorithm based on multiple heuristics

In order to enhance the operation speed,reduce the memory space occupied and filter out irrelevant or low-degree relevant features,feature selection algorithm must be used.One novel feature selection algorithm named as selection method using multiple heuristic rules was presented.The algorithm comprehensively considered features,so features could be selected more effectively and accurately.Experimental results show that the algorithm is better than mutual information,chi-square statistic and document frequency that are the three best conventional feature selection measures.
One-dimensional inversion of natural source magnetotelluric observations

Natural source magnetotelluric (MT) data are inverted to find a subsurface resistivity which is isotropic and a continuous function of depth. The inversion consists of two parts. In the first, our concern is to construct a resistivity structure whose responses are acceptably close to the observations, that is, the measured amplitudes and/or phases. This construction proceeds iteratively and is realized through an automated algorithm which is characterized by numerical stability and rapid convergence. In the second part, we attempt to investigate the degree of nonuniqueness inherent in the problem. This is accomplished by considering only spatial averages of the resistivity because all models linearly close to the constructed model will have the same average resistivity. The predictions of this statement are examined quantitatively in an example where the averages from five different models which reproduce the observations are compared. In an example using data from a moderately complex layered model, we h.
Fast Joint Space Model-Predictive Control for Reactive Manipulation

—Sampling-based model predictive control (MPC) is a promising tool for feedback control of robots with complex and non-smooth dynamics and cost functions. The computationally demanding nature of sampling-based MPC algorithms is a key bottleneck in their application to high-dimensional robotic manipulation problems. Previous methods have addressed this issue by running MPC in the task space while relying on a low-level operational space controller for joint control. However, by not using the joint space of the robot in the MPC formulation, existing methods cannot directly account for non-task space related constraints such as avoiding joint limits, singular conﬁgurations, and link collisions. In this paper, we develop a joint space sampling-based MPC for manipulators that can be efﬁciently parallelized using GPUs. Our approach can handle task and joint space constraints while taking less than 0.02 seconds (50Hz) to compute the next control command. Further, our method can integrate perception into the control problem by utilizing learned cost functions from raw sensor data. We validate our approach by deploying it on a Franka Panda robot for a variety of common manipulation tasks. We study the effect of different cost formulations and MPC parameters on the synthesized behavior and provide key insights that pave the way for the application of sampling-based MPC for manipulators in a principled manner. Videos of experiments can be found at:
A static analyzer for finding dynamic programming errors

There are important classes of programming errors that are hard to diagnose, both manually and automatically, because they involve a program's dynamic behavior. This article describes a compile‐time analyzer that detects these dynamic errors in large, real‐world programs. The analyzer traces execution paths through the source code, modeling memory and reporting inconsistencies. In addition to avoiding false paths through the program, this approach provides valuable contextual information to the programmer who needs to understand and repair the defects. Automatically‐created models, abstracting the behavior of individual functions, allow inter‐procedural defects to be detected efficiently. A product built on these techniques has been used effectively on several large commercial programs. Copyright © 2000 John Wiley & Sons, Ltd.
Insider power and wage determination in Bulgaria: an econometric investigation

Using a unique three‐digit firm‐level data set of all medium‐ and large‐sized manufacturing enterprises in Bulgaria covering the years 1997/1998, and investigation is conducted into how wage determination is related to ownership status. Building on a slightly modified version of the right‐to‐manage model, the pooled OLS, panel and first‐difference TSLS estimates show statistically significant differences in the share of rents taken by workers employed in state, private domestic and foreign firms. Taking account of firm heterogeneity, it is found that rent sharing is nearly non‐existent in foreign‐owned firms, while the level of pay is higher compared with state‐owned companies. Further, rent sharing seems to be highly pronounced in state‐owned enterprises, while on average domestically private‐owned companies are characterised by less rent sharing. Overall, the robustness checks confirm these findings.
Production Data Analysis in Eagle Ford Shale Gas Reservoir

ve analysis technology to analyse the production behaviour and to estimate the essential parameters for this reservoir. This type curve was constructed based on transient production rate with constant well pressure in a closed boundary of stimulated reservoir volume (SRV) with double porosity approach. In order to analyse the early production data we used Bello’s and Nobakht’s approach to account for apparent skin. In this study, three flow regimes were identified consisting of 1- bilinear flow; 2- matrix linear flow; and 3- boundary dominated flow. For the analysis of early flow regime, two possibilities of transition flow and apparent skin have been considered. First, the fracture permeability was estimated to be around 820 nano Darcy based on transition flow analysis. Second, the matrix permeability was estimated to be either 181 or 255 nano Darcy based on two different approaches in matrix linear flow regime. Furthermore, original gas in place (OGIP) and SRV were estimated from the boundary dominated flow regime. To validate the estimated matrix permeability, a single porosity numerical model with high permeability transverse fractures was built to match the production history. The permeability from simulation was in a good agreement with type curve analysis. Production forecasting has also been carried out using different adsorption isotherms. The results showed that the effect of desorption depends on the reservoir pressure and the shape of adsorption isotherm curve. In early time of production, desorption is usually not effective, however, for long-term production forecasting, it is necessary to account for this phenomenon by providing an accurate isotherm
KINet: Keypoint Interaction Networks for Unsupervised Forward Modeling

Object-centric representation is an essential abstraction for forward prediction. Most existing forward models learn this representation through extensive supervision (e.g., object class and bounding box) although such ground-truth information is not readily accessible in reality. To address this, we introduce KINet (Keypoint Interaction Network)—an end-to-end unsupervised framework to reason about object interactions based on a keypoint representation. Using visual observations, our model learns to associate objects with keypoint coordinates and discovers a graph representation of the system as a set of keypoint embeddings and their relations. It then learns an action-conditioned forward model using contrastive estimation to predict future keypoint states. By learning to perform physical reasoning in the keypoint space, our model automatically generalizes to scenarios with a different number of objects, novel backgrounds, and unseen object geometries. Experiments demonstrate the effectiveness of our model in accurately performing forward prediction and learning plannable object-centric representations which can also be used in downstream robotic manipulation tasks.