Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and conditions for wireless machine-to-machine communications in industrial environments

Wireless solutions are rapidly growing in machine-to-machine communications in industrial environments. These environments provide challenging conditions in terms of radio wave propagation as well as electromagnetic interference. In this article, results from the characterization of radio channel properties are summarized in order to provide some guidelines for the choice of wireless solutions in industrial environments. In conclusion, it is essential to know the sensitivity of industrial processes to time delay in data transfer. Furthermore, it is important to be aware of the radio interference environment and the manner in which different wireless technologies react upon interference. These steps will minimize the risk of unforeseen expensive disturbances in industrial processes.
Portfolio Rebalancing: A Test of the Markowitz-Van Dijk Heuristic

Institutional investors usually employ mean-variance analysis to determine optimal portfolio weights. Almost immediately upon implementation, however, the portfolioÂ€U³ weights become sub-optimal as changes in asset prices cause the portfolio to drift away from the optimal targets. In an idealized world without transaction costs investors would rebalance continually to the optimal weights. In the presence of transaction costs investors must balance the cost of sub-optimality with the cost of restoring the optimal weights. We apply a quadratic heuristic to address the asset weight drift problem, and we compare it to a dynamic programming solution as well as to standard industry heuristics. Our tests reveal that the quadratic heuristic provides solutions that are remarkably close to the dynamic programming solutions for those cases in which dynamic programming is feasible and far superior to solutions based on standard industry heuristics. In the case of five assets, in fact, it performs better than dynamic programming due to approximations required to implement the dynamic programming algorithm. Moreover, unlike the dynamic programming solution, the quadratic heuristic is scalable to as many as several hundreds assets.
A Method for Trading off Test Time, Area and Fault Coverage in Datapath BIST Synthesis

This paper presents a partitioned and embedded BIST technique for data path like circuits. The BIST scheme is defined at behavioral level for full optimization of both system and BIST modes during High Level Synthesis. Test time, area overhead and fault coverage are under the scope of the method. User-given constraints on fault coverage to achieve on data path operators and on test time are used to guide the BIST insertion technique towards the lowest area overhead solution.
Additional information on Misonne's swollen-nose gecko, Rhinogecko misonnei de Witte, 1973 (Squamata, Geckonidae) in Iran

Three adult specimens of Misonne's swollen-nose gecko (Rhinogecko misonnei) were collected in the west of Dasht-e-Lut desert in eastern Iran during fieldwork conducted April to Au- gust 2009. The new locality of the species is situated about 100 km west of the type locality. Infor- mation on habitat, pholidosis, and coloration is given. This record indicates a wider distribution of Rhinogecko misonnei in southeastern Iran.
An Introduction to Text Mining

The problem of text mining has gained increasing attention in recent years because of the large amounts of text data, which are created in a variety of social network, web, and other information-centric applications. Unstructured data is the easiest form of data which can be created in any application scenario. As a result, there has been a tremendous need to design methods and algorithms which can effectively process a wide variety of text applications. This book will provide an overview of the different methods and algorithms which are common in the text domain, with a particular focus on mining methods. 1. Introduction Data mining is a field which has seen rapid advances in recent years [8] because of the immense advances in hardware and software technology which has lead to the availability of different kinds of data. This is particularly true for the case of text data, where the development of hardware and software platforms for the web and social networks has enabled the rapid creation of large repositories of different kinds of data. In particular, the web is a technological enabler which encourages the
Coulomb stress changes caused by repeated normal faulting earthquakes during the 1997 Umbria‐Marche (central Italy) seismic sequence

[1] We investigate fault interaction through elastic stress transfer among a sequence of moderate-magnitude main shocks (5 < Mw < 6) which ruptured distinct normal fault segments during a seismic sequence in the Umbria-Marche region (central Apennines). We also model the spatial pattern of aftershocks and their faulting mechanisms through Coulomb stress changes. We compute stress perturbations caused by earthquake dislocations in a homogeneous half-space. Our modeling results show that seven out of eight main shocks of the sequence occur in areas of enhanced Coulomb stress, implying that elastic stress transfer may have promoted the occurrence of these moderate-magnitude events. Our modeling results show that stress changes caused by normal faulting events reactivated and inverted the slip of a secondary N-S trending strike-slip fault inherited from compressional tectonics in its shallowest part (1–3 km). Of the 1517 available aftershocks, 82% are located in areas of positive stress changes for optimally oriented planes (OOPs) for Coulomb failure. However, only 45% of the 322 available fault plane solutions computed from polarity data is consistent with corresponding focal mechanisms associated with the OOPs. The comparison does not improve if we compute the optimally oriented planes for Coulomb failure by fixing the strike orientation of OOPs using information derived from structural geology. Our interpretation of these modeling results is that elastic stress transfer alone cannot jointly explain the aftershock spatial distribution and their focal mechanisms.
A ALCA em debate: uma visão desde o sul

Economic integration among countries is an important issue in the debate on contemporary capitalism. This article concentrates on a project of this kind, relating to the Free Trade Area of the Americas (FTAA), being negotiated since 1994 and expected to be implemented from 2005 on. The approach focuses on the perspectives of an integration process involving Latin American countries and the United States, the most powerful nation of the world, emphasizing the problem represented by free pan-American trade, on the one hand, and by the intended liberalization of foreign investments within the trade area, on the other
First‐ and third‐type boundary conditions in two‐dimensional solute transport modeling

This paper presents a general analytical solution for convective-dispersive solute transport in a two-dimensional, semiinfinite porous medium. The solute is assumed to be subject to linear equilibrium sorption and first-order decay. Solutions are derived for several third-type (Cauchy) or flux-type boundary conditions at the input surface. After presenting a generally applicable solution a special solution is given for a strip-type solute source. It is shown that the third-type boundary condition correctly conserves mass in the two-dimensional system and that the first-type (Dirichlet) or concentration-type boundary condition corresponds to a situation that the solute flux at the source decreases with time and at large time approaches to the solute flux of the third-type boundary condition. This can lead to significant discrepancies in the calculated concentrations, especially near the source boundaries.
Efficient, incremental coverage of space with a continuous curve

SUMMARY This paper is concerned with algorithmic techniques for the incremental generation of continuous curves that can efficiently cover an abstract surface. We introduce the notion of low-discrepancy curves as an extension of the notion of low-discrepancy sequences—such that sufficiently smooth curves with low-discrepancy properties can be defined and generated. We then devise a procedure for lifting these curves, that efficiently cover the unit cube, to abstract surfaces, such as nonlinear manifolds. We present algorithms that yield suitable fair mappings between the unit cube and the abstract surface. We demonstrate the application of these ideas using some concrete examples of interest in robotics.
Faulted terrace risers place new constraints on the late Quaternary slip rate for the central Altyn Tagh fault, northwest Tibet

The active, left-lateral Altyn Tagh fault defines the northwestern margin of the Tibetan Plateau in western China. To clarify late Quaternary temporal and spatial variations in slip rate along the central portion of this fault system (85°–90°E), we have more than doubled the number of dated offset markers along the central Altyn Tagh fault. In particular, we determined offset-age relations for seven left-laterally faulted terrace risers at three sites (Kelutelage, Yukuang, and Keke Qiapu) spanning a 140-km-long fault reach by integrating surficial geologic mapping, topographic surveys (total station and tripod–light detection and ranging [T-LiDAR]), and geochronology (radiocarbon dating of organic samples, 230 Th/U dating of pedogenic carbonate coatings on buried clasts, and terrestrial cosmogenic radionuclide exposure age dating applied to quartz-rich gravels). At Kelutelage, which is the westernmost site (37.72°N, 86.67°E), two faulted terrace risers are offset 58 ± 3 m and 48 ± 4 m, and formed at 6.2–6.1 ka and 5.9–3.7 ka, respectively. At the Yukuang site (38.00°N, 87.87°E), four faulted terrace risers are offset 92 ± 12 m, 68 ± 6 m, 55 ± 13 m, and 59 ± 9 m and formed at 24.2–9.5 ka, 6.4–5.0 ka, 5.1–3.9 ka, and 24.2–6.4 ka, respectively. At the easternmost site, Keke Qiapu (38.08°N, 88.12°E), a faulted terrace riser is offset 33 ± 6 m and has an age of 17.1–2.2 ka. The displacement-age relationships derived from these markers can be satisfied by an approximately uniform slip rate of 8– 12 mm/yr. However, additional analysis is required to test how much temporal variability in slip rate is permitted by this data set.
Sequential Deep Learning Operator Network (S-DeepONet) for Time-Dependent Loads

Deep Operator Network (DeepONet), a recently introduced deep learning operator network, approximates linear and nonlinear solution operators by taking parametric functions (inﬁnite-dimensional objects) as inputs and mapping them to solution functions in contrast to classical neural networks (NNs) that need re-training for every new set of parametric inputs. In this work, we have extended the classical formulation of DeepONets by introducing recurrent neural networks (RNNs) in its branch in so-called sequential DeepONets (S-DeepONets) thus allowing accurate solution predictions in the entire domain for parametric and time-dependent loading histories. We have demonstrated this novel formulation’s generality and exceptional accuracy with thermal and mechanical random loading histories applied to highly nonlinear thermal solidiﬁcation and plastic deformation use cases. We show that once S-DeepONet is properly trained, it can accurately predict the ﬁnal solutions in the entire domain and is several orders of magnitude more computationally efﬁcient than the ﬁnite element method for arbitrary loading histories without additional training.
The Impact of Knowledge Codification, Experience Trajectories and Integration Strategies on the Performance of Corporate Acquisitions

This study addresses the following questions: (1) can organizations learn how to manage infrequent and heterogeneous tasks ? (2) If they can, then what are the mechanisms that might explain learning under these circumstances ? , and (3) what are the limitations under which these mechanisms operate ? A model based on explicit knowledge codification and tacit experience accumulation is submitted and tested using data from a sample of 183 acquisitions in the US banking industry. Measures of post-acquisition integration strategies and of pre-acquisition resource characteristics are included in the model. We find that tacit knowledge accumulation significantly impacts performance when the experiences are highly homogeneous, and that knowledge codification improves acquisition performance in the context of high post-acquisition integration, i.e. when the organizational challenge is particularly complex. Also, the level of integration between the two firms involved in the acquisition positively influences performance, while the replacement of top managers in the acquired firm impacts performance in a negative fashion. Implications are drawn for organizational learning theory and for a knowledge-based view of corporate acquisitions.
Is a Companion a Distinctive Kind of Relationship with a Machine? How Was Your Day? Vca: an Experiment with a Multiparty Virtual Chat Agent Vca: an Experiment with a Multiparty Virtual Chat Agent Episodic Memory for Companion Dialogue

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a finegrained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life selfexpressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.
New evidence for Preboreal deglaciation of south-central Norway

Mapping and detailed morphological evidence suggests that mounds and ridges at 1200 to 1350 m in upper Breiseterdalen, western Jotunhcimen probably represent Rogen moraines, ice sheet marginal moraines and a cirque moraine. 14C dates from an intermoraine hollow suggest that peat development began about 8800 BP, confirming a Preboreal age for deglaciation. A need for a revised deglaciation chronology is suggested, with evidence for active ice present comparatively close to the present glacier limits until a late stage of deglaciation. A possible correlation of the Breiseterdalen moraines with similarly dated marginal moraines in southwest Norway is discussed.
Inherently Interpretable Sparse Word Embeddings through Sparse Coding

Word embeddings are a powerful natural language processing technique, but they are extremely difficult to interpret. In order to create more interpretable word embeddings, we transform pretrained dense word embeddings into sparse embeddings. These new embeddings are inherently interpretable: each of their dimensions are created from and represent a natural language word or specific syntactic concept. We construct these embeddings through sparse coding, where each vector in the basis set is itself a word embedding. We show that models trained using these sparse embeddings can achieve good performance and are extremely interpretable.
Learning Spherical Convolution for Fast Features from 360° Imagery

While 360{\deg} cameras offer tremendous new possibilities in vision, graphics, and augmented reality, the spherical images they produce make core feature extraction non-trivial. Convolutional neural networks (CNNs) trained on images from perspective cameras yield "flat" filters, yet 360{\deg} images cannot be projected to a single plane without significant distortion. A naive solution that repeatedly projects the viewing sphere to all tangent planes is accurate, but much too computationally intensive for real problems. We propose to learn a spherical convolutional network that translates a planar CNN to process 360{\deg} imagery directly in its equirectangular projection. Our approach learns to reproduce the flat filter outputs on 360{\deg} data, sensitive to the varying distortion effects across the viewing sphere. The key benefits are 1) efficient feature extraction for 360{\deg} images and video, and 2) the ability to leverage powerful pre-trained networks researchers have carefully honed (together with massive labeled image training sets) for perspective images. We validate our approach compared to several alternative methods in terms of both raw CNN output accuracy as well as applying a state-of-the-art "flat" object detector to 360{\deg} data. Our method yields the most accurate results while saving orders of magnitude in computation versus the existing exact reprojection solution.
GENETIC ALGORITHM MODEL FOR PROFIT MAXIMIZATION OF GENERATING COMPANIES IN DEREGULATED ELECTRICITY MARKETS

In deregulated and rapidly changing electricity markets, there is strong interest on how to solve the new price-based unit commitment (PBUC) problem used by each generating company to optimize its generation schedule in order to maximize its profit. This article proposes a genetic algorithm (GA) solution to the PBUC problem. The advantages of the proposed GA are: 1) flexibility in modeling problem constraints because the PBUC problem is not decomposed either by time or by unit; 2) smooth and easier convergence to the optimum solution thanks to the proposed variable fitness function which not only penalizes solutions that violate the constraints but also this penalization is smoothly increasing as the number of generations increases; 3) easy implementation to work on parallel computers, and 4) production of multiple unit commitment schedules, some of which may be well suited to situations that may arise quickly due to unexpected contingencies. The method has been applied to systems of up to 120 units and the results show that the proposed GA constantly outperforms the Lagrangian relaxation PBUC method for systems with more than 60 units. Moreover, the difference between the worst and the best GA solution is very small, ranging from 0.10% to 0.49%.
Rubyric

It is important that students receive sufficient feedback from exercises. However, writing feedback can be laborious on large courses. We present a rubric-based assessment tool called Rubyric that helps course staff to construct textual feedback effortlessly using grading rubrics. The tool allows teachers to create rubrics, or grading templates that specify the evaluation criteria and contain feedback phrases for typical mistakes. Because many students make similar mistakes, large portions of feedback can be constructed from pre-written blocks making it possible to give detailed feedback with little effort. The use of a rubric also helps to ensure consistency of grading between multiple graders because they are required to give grades based on a detailed list of criteria. Rubyric has been used on multiple computer science courses at Aalto university since year 2008. User satisfaction of both students and teaching assistants have been measured with questionnaires. The results show that teaching assistants find the tool helpful and students have been satisfied with the amount and quality of feedback produced with the system.
Where and when will we observe cloud changes due to climate warming?

Climate models predict that the geographic distribution of clouds will change in response to anthropogenic warming, though uncertainties in the existing satellite record are larger than the magnitude of the predicted effects. Here we argue that cloud vertical distribution, observable by active spaceborne sensors, is a more robust signature of climate change. Comparison of Atmospheric Model Intercomparison Project present day and +4 K runs from Coupled Model Intercomparison Project Phase 5 shows that cloud radiative effect and total cloud cover do not represent robust signatures of climate change, as predicted changes fall within the range of variability in the current observational record. However, the predicted forced changes in cloud vertical distribution (directly measurable by spaceborne active sensors) are much larger than the currently observed variability and are expected to first appear at a statistically significant level in the upper troposphere, at all latitudes.
Anytime Coalition Structure Generation on Scale-Free and Community Networks

We consider the coalition structure generation (CSG) problem on synergy graphs, which arises in many practical applications where communication constraints, social or trust relationships must be taken into account when forming coalitions. We propose a novel representation of this problem based on the concept of edge contraction, and an innovative branch and bound approach (CFSS), which is particularly efficient when applied to a general class of characteristic functions. We evaluate CFSS on two particular synergy graph topologies, i.e., scale-free networks and community networks, which provide an efficient description of many interesting real-world scenarios, e.g., social networks, authorships, collective energy purchasing and carpooling. Our results show that, when the graphs are very sparse, CFSS is 4 orders of magnitude faster than DyCE, the best algorithm to date for CSG on synergy graphs.
Composition and spectral characteristics of ambient aerosol at Mauna Loa Observatory

Ambient aerosol particles were sampled continuously with a time resolution of {approximately}4 hours for a period of 8 days at the Mauna Loa Observatory, Hawaii, in August 1986. The samples were analyzed on-site for their chemical composition by attenuated total internal reflection infrared spectroscopy. The infrared absorption spectra of the samples also provided data on aerosol light absorbance characteristics at 9.1 and 10.6 {mu}m - wavelengths of interest in determining aerosol backscatter coefficients for CO{sub 2} lidars. The chemical species in the ambient aerosol varied considerably during this 8-day period. The aerosol was acidic ((NH{sub 4}){sub 3}H(SO{sub 4}){sub 2},NH{sub 4}HSO{sub 4}, or H{sub 2}SO{sub 4}) rather than neutral ((NH{sub 4}){sub 2}SO{sub 4}) for a major fraction of the sampling time. The samples generally showed much higher absorbance at 9.1 {mu}m than at 10.6 {mu}m. Changes in the chemical composition between (NH{sub 4}){sub 2}SO{sub 4} and the more acidic forms were accompanied by substantial changes in the sample's absorbance at 9.1 {mu}m but lesser changes in the absorbance at 10.6 {mu}m. These variations could have a profound effect on backscatter coefficients of atmospheric aerosol particles at CO{sub 2} wavelengths.