Miracle-dz/UniFAR-FTUs huggingface dataset:
The Still Life(s) of Chantal Akerman: Akerman’s Moving Images and Dutch 17th-Century Painting

ABSTRACT Throughout her career, the Belgian filmmaker Chantal Akerman accelerated the erosion of boundaries separating the visual arts that has fuelled our current moment of mixed media. This article, though, takes different approach to Akerman’s work. It argues that her cinema borrows from a historical type of viewing experience just as much as it pioneered new ones. Specifically, I argue that Akerman drew on the painterly language of seventeenth-century Dutch still-lifes through her use of stillness, texture, space, light, and (self-)portraiture that undermines mainstream modes of visual representation as developed by Renaissance art. Relying on contemporary film theory, art history, and Akerman’s own idiosyncratic style and biography, this essay yields a productive, if unexpected, point of comparison between the aesthetic practices of early modern Dutch painting and Akerman’s moving images. Comparing several of Akerman’s pictures to a handful of masterpieces of seventeenth-century Dutch art, this work joins a growing discourse among visual theorists in exploring connections between cinema and painting more broadly.
One-thumb Text Acquisition on Force-assisted Miniature Interfaces for Mobile Headsets

Touchscreen interfaces are shrinking and even dis-appearing on mobile headsets. The existing approaches for text acquisition on mobile headsets, for instance, speech commands and hand gestures, are cumbersome and coarse. In this paper, we show the feasibility of interaction on a miniature area as small as 12 * 13 mm2 that offers an input alternative on small form-factor devices such as smartwatches, smart rings, or the spectacles frames of mobile headsets. To this end, we propose and implement two interaction approaches, namely FRS and DupleFR, for acquiring textual contents on mobile headsets. Both approaches leverage force-assisted interaction on a miniature-size interface. They enable the user to acquire textual content with various granularities such as characters, words, sentences, paragraphs, and the entire text. After 8 sessions, 22 participants with FRS and DupleFR achieve the peak performance of respectively 11.455 and 10.611 seconds per textual acquisition with accuracy rates of 91.41% and 94.95%. Although FRS and DupleFR as indirect manipulations are disadvantageous, they are at least 37.06% faster than the commercial standards designated to direct manipulation on touchscreens.
Determinants of the Capital Structure of Companies Listed on the Stock Exchanges of Argentina, Brazil and Chile: An Empirical Analysis of the Period from 2007 to 2016

The present investigation refers to the determinants of the capital structure, using the technique of multiple regression through Panel Data of open capital companies in the stock exchanges of Argentina, Brazil and Chile, in order to know the behavior of determinants of the capital structure in relation to Trade-Off Theory (TOT) and Pecking Order Theory (POT). The POT offers the existence of a hierarchy in the use of sources of resources, while the TOT considers the existence of a target capital structure that would be pursued by the company. Sixteen accounting variables were used, in which five are dependent (related to indebtedness) and eleven are independent variables (explaining the determinants of the capital structure). It is observed that, with the use of the Panel Data, the determinants that seem to influence in a more accentuated way the levels of debt of the companies are: current liquidity, tangibility, return to shareholders, return of assets, sales growth, asset growth, market-to-book and business risk measured by the volatility of benefits. Suggestions for future research include the use of Panel Data to analyze other factors that may influence indebtedness, mainly taxes and dividends, as well as a deeper analysis of factors that may influence the speed of adjustment towards the supposed objective level.
Decoding chemical information from vibrational spectroscopy data: Local vibrational mode theory

Modern vibrational spectroscopy is more than just an analytical tool. Information about the electronic structure of a molecule, the strength of its bonds, and its conformational flexibility is encoded in the normal vibrational modes. On the other hand, normal vibrational modes are generally delocalized, which hinders the direct access to this information, attainable only via local vibration modes and associated local properties. Konkoli and Cremer provided an ingenious solution to this problem by deriving local vibrational modes from the fundamental normal modes, obtained in the harmonic approximation of the potential, via mass‐decoupled Euler–Lagrange equations. This review gives a general introduction into the local vibrational mode theory of Konkoli and Cremer, elucidating how this theory unifies earlier attempts to obtain easy to interpret chemical information from vibrational spectroscopy: (a) the local mode theory furnishes bond strength descriptors derived from force constant matrices with a physical basis, (b) provides the highly sought after extension of the Badger rule to polyatomic molecules, (c) and offers a simpler way to derive localized vibrations compared to the complex route via overtone spectroscopy. Successful applications are presented, including a new measure of bond strength, a new detailed analysis of infrared/Raman spectra, and the recent extension to periodic systems, opening a new avenue for the characterization of bonding in crystals. At the end of this review the LMODEA software is introduced, which performs the local mode analysis (with minimal computational costs) after a harmonic vibrational frequency calculation optionally using measured frequencies as additional input.
Qualitative Analysis of the Phytochemical Contents of Different Anatomical Parts of Ripe Solanum aethiopicum Linneaus Fruits

Aims: To determine qualitatively the amount of alkaloids, saponin, tannin, volatile oil, phenol and flavonoids in the different anatomical parts of ripe Solanum aethiopicum Linn fruits. Methodology: Solanum aethiopicum Linn fruits were purchased from Sabo market, Ogbomoso, Nigeria. The fruits were separated with a razor into four (4) anatomical parts (the epicarp, mesocarp, endocarp, and seed) after washing with distilled water. 1gram of each anatomical parts of the fruit were soaked in 20mls of distilled water,1% volume per volume (v/v), 2% v/v, 3%v/v, 4%v/v and 5%v/v of ethanol, ethylacetate and methanol separately. The mixtures were left for 24 hours after which they were sieved to obtain the extracts. The presence of alkaloid, tannin, Original Research Article Tunwagun et al.; JOCAMR, 9(3): 14-22, 2020; Article no.JOCAMR. 56868 15 saponin, volatile oil, phenol and flavonoid were determined qualitatively in the extracts at selected concentrations. Results: The results obtained showed that alkaloids are more concentrated in the mesocarp of Solanum aethiopicum Linn; volatile (essential) oil is more pronounced in the mesocarp and endocarp of Solanum aethiopicum Linn; saponin is confirmed in all anatomical parts of the fruit at reasonable quality except in the seed; tannin is found to be moderately present only in the aqueous extract of mesocarp of Solanum aethiopicum Linn fruit while the presence of phenol and flavonoids were confirmed in trace amount at few tested concentrations of the extracts. Conclusion: Taken together, the presence of a variety of phytochemicals in the different anatomical parts of Solanum aethiopicum Linn fruit indicate that the fruit might be pharmacologically active against a number of diseases. However, this should be subjected to subsequent researches.
Liquid crystal integrated metalens with tunable chromatic aberration

Abstract. Overcoming chromatic aberrations is a vital concern in imaging systems in order to facilitate full-color and hyperspectral imaging. By contrast, large dispersion holds opportunities for spectroscopy and tomography. Combining both functions into a single component will significantly enhance its versatility. A strategy is proposed to delicately integrate two lenses with a static resonant phase and a switchable geometric phase separately. The former is a metasurface lens with a linear phase dispersion. The latter is composed of liquid crystals (LCs) with space-variant orientations with a phase profile that is frequency independent. By this means, a broadband achromatic focusing from 0.9 to 1.4 THz is revealed. When a saturated bias is applied on LCs, the geometric phase modulation vanishes, leaving only the resonant phase of the metalens. Correspondingly, the device changes from achromatic to dispersive. Furthermore, a metadeflector with tunable dispersion is demonstrated to verify the universality of the proposed method. Our work may pave a way toward active metaoptics, promoting various imaging applications.
Genome‐based prediction of Bayesian linear and non‐linear regression models for ordinal data

Linear and non‐linear models used in applications of genomic selection (GS) can fit different types of responses (e.g., continuous, ordinal, binary). In recent years, several genomic‐enabled prediction models have been developed for predicting complex traits in genomic‐assisted animal and plant breeding. These models include linear, non‐linear and non‐parametric models, mostly for continuous responses and less frequently for categorical responses. Several linear and non‐linear models are special cases of a more general family of statistical models known as artificial neural networks, which provide better prediction ability than other models. In this paper, we propose a Bayesian Regularized Neural Network (BRNNO) for modelling ordinal data. The proposed model was fitted using a Bayesian framework; we used the data augmentation algorithm to facilitate computations. The proposed model was fitted using the Gibbs Maximum a Posteriori and Generalized EM algorithm implemented by combining code written in C and R programming languages. The new model was tested with two real maize datasets evaluated for Septoria and GLS diseases and was compared with the Bayesian Ordered Probit Model (BOPM). Results indicated that the BRNNO model performed better in terms of genomic‐based prediction than the BOPM model.
Analysis of the Influence Factors of Climate Change on the Mangrove and Relevant Solutions

This article is aimed to study how climate change affects mangroves and how to prevent them from being damaged by climate change. Nowadays, the climate is becoming more and more unstable, and extreme weather occurs frequently, such as hail in the Tropics. However, the stability of climate is very important for human beings, because climate comes from nature, and nature is the basis of human survival. Therefore, in order to better observe climate change and improve current climate, the mangrove has become the Savior to human, which means that the mangrove is also significant to human beings. While some group of the mangrove have been damaged by climate change. Therefore, this paper will analyze the impact of climate change on mangroves from the perspective of climate factors of acid rain and global warming. The conclusion is that strengthening monitoring and creating more habitats for mangroves may be the appropriate solution. At last, this paper will be useful to cope with climate change better and be helpful for the future research.
INVESTOR ATTENTION AND STOCK RETURNS UNDER NEGATIVE SHOCKS: AN EMPIRICAL ANALYSIS BASED ON “DRAGON AND TIGER” LIST IN CHINA

Using the “Dragon and Tiger” list, we construct a clean indicator that directly measures investor attention, empirically test the effect of investor attention on stock return under negative shocks and whether the effect is affected by the bull or bear market, the industry, firm size, age and state ownership, institutional shareholder holding percentage. The results show that i) an increase in investor attention negatively predicts stock returns when cumulative daily return of a stock listed on “Dragon and Tiger” list on listing day is negative; ii) Investor attention is negatively correlated with stock returns when the stock entered in “Dragon and Tiger” list experienced current cumulative monthly return is negative; iii) Investor attention is negatively correlated with stock returns when monthly cumulative net purchase amount of top 10 institution to the stock listed in “Dragon and Tiger” list is negative; iv) Investor attention is negatively correlated with stock returns when the stock listed in “Dragon and Tiger” list, the ratio of monthly cumulative trading amount of the top 10 institutional traders to total trading amount of the secondary market is in the bottom 30 percentile. These findings not only contribute to the academic research about the relationship between investor attention and stock return, but also provide some guidance to the financial regulatory agencies as to the capital market stability.
Advanced three-dimensional geomechanical and hydrogeological modelling for a deep open pit

The Ellatzite open pit mine, located in Bulgaria, is a large copper mine with a current mining depth in excess of 500 m. During the last few years, Ellatzite-Med AD and Itasca International Inc. have jointly conducted a large slope stability analysis project utilising an integrated geomechanical and hydrogeological approach with the overall goal of assessing the stability of the open pit slopes for current and future mining. The conducted work has included developing a Geomechanical Framework Model to describe the rock mass in quantitative terms. This model is based on extensive data collection from active open pit walls, boreholes, and drainage tunnels, and includes a detailed interpretation of the lithological and structural characteristics of the site. The structural geology of the site is complex, with a large number of lithological contacts and faults, all interpreted as discontinuities with the potential to slip. Hence, a 3D discontinuum approach was required to represent the geomechanical environment in a numerical model for stability assessment. The approach used enabled including all lithological contacts and faults (more than 50 largescale, undulating, discontinuities) in a mine-scale 3DEC model. A hydrogeological model was developed in parallel to quantify pore pressure conditions in the rock mass. Faults were also included also in the hydro-model, and calculated pore pressures were then exported to the 3DEC model for stability assessment. Joint fabric, simulated as ubiquitous joints, were also included in the geomechanical model. The model results were compared against observations and deformation measurements from the open pit. Near-future mining scenarios were investigated and various mitigating measures, such as drainage and/or slope geometry alterations were developed. The modelling work is at the forefront of what is possible in discontinuum 3D slope stability analysis of complex structural-geological conditions and for practical open pit stability assessments.
A internet da indústria das coisas

The Industrial Internet of Things, IIoT is an in-process innovation based on the application of the Internet of Things in industry, which will increase the efficiency of machines, reduce costs, adjust production processes, monitor fleets, gains in scale , product improvement and market opening This article aims to point out the types of innovation resulting from the industrial internet IIoT of things, as well as to support the concept of IIoT and to point out the gains from IIoT and understand its application, with emphasis on Brazil. To carry out the study, a bibliographic review was made, based on the following authors: Oliveira et al. (2016), Waka (2015), Keller (2016), Romano (2017), Rocha (2017), Trindade (2013) and Fortino et al (2017) We conclude that it is the industrial internet of things, an innovation in process, is a fundamental tool not only for creating and sustaining competitive advantage for industries, but above all for nations that claim to be competitive in the 21st century. Keywords: Industrial Automation. Internet of Things. Industrial Internet of Things.
Biochemical quality of crop residues and carbon and nitrogen mineralization kinetics under nonlimiting nitrogen conditions

Statistical relationships were established between the fate of C and N from 47 types of crop residues and their biochemical characteristics during a soil incubation at 15°C. The incubations were carried out under nonlimiting N in order to differentiate the effects of biochemical characteristics of residues from those of soil N availability. Depending on the residue, the apparent mineralization of residue C after 168 d varied from 330 to 670 g kg -1 of added C. Mineralization kinetics were described using a two-compartment decomposition model that decomposes according to first-order kinetics. Amounts of C mineralized after 7 d and the decomposition rate coefficient of the labile fraction were related mainly to the soluble C forms of the residue. No statistical relationship was established between the N concentration of residues and their decomposition in the soil. The incorporation of crop residues into soil led to various soil mineral N dynamics. Two residues caused net N mineralization from the time of their incorporation, whereas all the others induced net N immobilization (1-33 g N kg -1 of added C). After 168 d, only residues with a C/N ratio <24 induced a surplus of mineral N compared with the control soil. The mineral N dynamics were related mainly to the organic N concentration of the residues and to their C/N ratio. At the start of incubation, these dynamics were also influenced by the presence of polyphenols in the plant tissues. Finally, this study showed the need to include the biochemical quality of crop residues in any C and N transformation models that describe decomposition. In contrast, the N concentration or C/N ratio of the residues are sufficient to predict the net effects of crop residues on soil mineral N dynamics.
Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations

Advances in the availability of multi-temporal, remote sensing-derived global built-/human-settlements datasets can now provide globally consistent definitions of “human-settlement” at unprecedented spatial fineness. Yet, these data only provide a time-series of past extents and urban growth/expansion models have not had parallel advances at high-spatial resolution. Here our goal was to present a globally applicable predictive modelling framework, as informed by a short, preceding time-series of built-settlement extents, capable of producing annual, near-future built-settlement extents. To do so, we integrated a random forest, dasymetric redistribution, and autoregressive temporal models with open and globally available subnational data, estimates of built-settlement population, and environmental covariates. Using this approach, we trained the model on a 11 year time-series (2000–2010) of European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover “Urban Areas” class and predicted annual, 100m resolution, binary settlement extents five years beyond the last observations (2011–2015) within varying environmental, urban morphological, and data quality contexts. We found that our model framework performed consistently across all sampled countries and, when compared to time-specific imagery, demonstrated the capacity to capture human-settlement missed by the input time-series and the withheld validation settlement extents. When comparing manually delineated building footprints of small settlements to the modelled extents, we saw that the modelling framework had a 12 percent increase in accuracy compared to withheld validation settlement extents. However, how this framework performs when using different input definitions of “urban” or settlement remains unknown. While this model framework is predictive and not explanatory in nature, it shows that globally available “off-the-shelf” datasets and relative changes in subnational population can be sufficient for accurate prediction of future settlement expansion. Further, this framework shows promise for predicting near-future settlement extents and provides a foundation for forecasts further into the future.
Egg size variation in European Satyrine butterflies (Nymphalidae, Satyrinae)

The interspecific relationships between egg size and female size, sexual size dimorphism, latitude, preoviposition and egg-laying behaviour, was investigated in European Satyrine butterflies by controlling for taxonomic relatedness and by simple cross-species comparisons. Egg size scales positively to female size, although the relationship is not significant (but nearly so) when taxonomic effects are controlled for. Egg size is correlated with latitude. When the effects of latitude are removed, the relationship between egg and female size becomes more evident. Sexual size dimorphism is negatively correlated with egg size, but the effect disappears when adult size is controlled for. Small egg size is related to long preoviposition. No relationship between egg laying mode and egg size appears. The results are interpreted as evidence for positive scaling of egg to female size, with superimposed effects of egg size radiation. The correlation of egg size with latitude suggests that temperature, or season length, is likely to have made an important contribution to egg size selection within this geographic area.
Low cycle fatigue damage model and sensitivity analysis of fatigue crack initiation by finite element approach

To meet the design requirements, different types of defects are often machined on the surface of fatigue components. Local stress concentration formed at the notch accelerate the initiation of fatigue crack, therefore greatly shorten the service lives of such components. Based on the theory of continuous damage mechanics and the principle of irreversible thermodynamics, the damage evolution model of low cycle fatigue is investigated. By programming the damage evolution model as UMAT subroutine and coupling it to ABAQUS, the fatigue damage and crack initiation life of notched P92 steel samples under specific loads are simulated, and the crack initiation location is determined. Furthermore, the damage evolution and crack initiation sensitivity of notch morphology are considered. The results show that the crack initiation occurs easily in the notch root where the damage is greatest and the plastic strain accumulates fastest under cyclic loading. The fatigue damage accumulates slowly at the initial stage, but the damage accumulates rapidly after the cumulative damage reaches a critical value. The fatigue damage evolution and fatigue initiation life are very sensitive to the notch morphology parameters. The notch morphology need to be carefully analyzed, to improve the fatigue life of the notched samples.
Prey selectivity of wolves in Banff National Park. I. Prey species

I examined the components generating selectivity in wolves preying on five ungulate species in Banff National Park, Alberta. Overall selectivity for elk and deer species, and apparent avoidance of bighorn sheep and mountain goats, were due primarily to lower habitat overlap of wolves with the latter two species, and therefore lower encounter rates. For social ungulates, I argue that the herd should be considered the unit of encounter, with encounter rates proportional to the number of herds rather than the number of individuals. However, large herds predictably associated with certain areas may be visited intentionally by wolves, increasing effective encounter rates. Foraging theory suggests that all ungulate prey should be equally profitable to wolves upon encounter and therefore the factors affecting encounter rates are critical in determining prey selectivity. A simple model incorporating different habitat overlap, herd sizes, and predictable herds predicts qualitatively different functional responses .