Miracle-dz/UniFAR-FTUs huggingface dataset:
A System for Learning Basic Object Affordances using a Self-Organizing Map

When a cognitive system encounters particular objects, it needs to know what effect each of its possible actions will have on the state of each of those objects in order to be able to make effective decisions and achieve its goals. Moreover, it should be able to generalize effectively so that when it encoun- ters novel objects, it is able to estimate what effect its actions will have on them based on its experiences with previously encountered similar objects. This idea is encapsulated by the term "affordance", e.g. "a ball affords being rolled to the right when pushed from the left. " In this paper, we discuss the development of a cognitive vision platform that uses a robotic arm to interact with household objects in an attempt to learn some of their basic affordance properties. We outline the various sensor and effector module competencies that were needed to achieve this and describe an experiment that uses a self-organizing map to integrate these modalities in a working affordance learning system.
Sparsity Invariance for Convex Design of Distributed Controllers

We address the problem of designing optimal linear time-invariant (LTI) sparse controllers for LTI systems, which corresponds to minimizing a norm of the closed-loop system subjected to sparsity constraints on the controller structure. This problem is NP-hard in general and motivates the development of tractable approximations. We characterize a class of convex restrictions based on a new notion of sparsity invariance (SI). The underlying idea of SI is to design sparsity patterns for transfer matrices <inline-formula><tex-math notation="LaTeX">$\mathbf {Y}(s)$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathbf {X}(s)$</tex-math></inline-formula> such that any corresponding controller <inline-formula><tex-math notation="LaTeX">$\mathbf {K}(s)=\mathbf {Y}(s)\mathbf {X}(s)^{-1}$</tex-math></inline-formula> exhibits the desired sparsity pattern. For sparsity constraints, the approach of SI goes beyond the notion of quadratic invariance (QI): 1) the SI approach always yields a convex restriction and 2) the solution via the SI approach is guaranteed to be globally optimal when QI holds and performs at least, considering the nearest QI subset. Moreover, the notion of SI naturally applies to designing structured static controllers, while QI is not utilizable. Numerical examples show that even for non-QI cases, SI can recover solutions that are: 1) globally optimal and 2) strictly more performing than previous methods.
Termination of Inward Migration for a Gap-opening Planet through Dust Feedback

Planetary migration due to disk–planet interaction is one of the most important processes determining the architecture of planetary systems. A sufficiently massive planet forms a density gap, and migrates together with the gap. By carrying out two-dimensional and two-fluid (gas and dust grains) hydrodynamic simulations, we investigated the effects of dust feedback on the migration of the gap-opening planet, which has not been considered in previous studies. We found that the gas surface density at the outer edge of the gap becomes smaller due to dust feedback, and thus the torque exerted from the outer disk decreases. This mechanism becomes more effective as the gap becomes wider and deeper. In particular, when the mass of the planet is Jupiter-sized and the turbulent viscosity is α = 3 × 10−4, the planet can migrate outward due to the reduction of the torque exerted from the outer disk. Even for a smaller planet, the migration slows down significantly. This termination of the inward migration triggered by dust feedback may explain why ring and gap structures can be frequently observed within protoplanetary disks.
Mochizuki's anabelian variation of ring structures and formal groups

I show that there is a universal formal group (over a suitable (non-zero) ring) which is equipped with an action of the multiplicative monoid $\mathcal{O}^\triangleright$ of non-zero elements of the ring of integers of a $p$-adic field. Lubin-Tate formal groups also arise from this universal formal group. If two $p$-adic fields have isomorphic multiplicative monoids $\mathcal{O}^\triangleright$ then the additive structure of one arises from that of the other by means of this universal formal group law (in a suitable manner). In particular if two $p$-adic fields have isomorphic absolute Galois groups then it is well-known that the two respective monoids $\mathcal{O}^\triangleright$ are isomorphic and so this construction can be applied to such $p$-adic fields. In this sense this universal formal group law provides a single additive structure which binds together $p$-adic fields whose absolute Galois groups are isomorphic (this anabelian variation of ring structure is studied and used extensively by Shinichi Mochizuki). In particular one obtains a universal (additive) expression for any non-zero $p$-adic integer (in a given $p$-adic field) which is independent of the ring structure of the $p$-adic field (this is also inspired by Mochizuki's results). These ideas extend to geometric situations: for a smooth curve $X/K$ there is a universal $K(X)^*$-formal group (here $K(X)^*$ is the monoid of non-zero meromorphic functions on a smooth curve $X/K$ over a $p$-adic field $K$, which binds together all the additive structures on $K(X)^*\cup \{0\}$ compatibly with the universal additive structure on $K^*\cup\{0\}$ and hence a non-zero meromorphic function on $X$ is given by a universal additive expression which is independent of the ring structure of $K(X)^*\cup\{0\}$ (this is also inspired by Mochizuki's results on Theta functions). Also see Theorem 7.6.
Applying the resonant-state expansion to realistic materials with frequency dispersion

The dispersive resonant-state expansion, developed for an accurate calculation of the resonant states in open optical systems with frequency dispersion, is applied here to realistic materials, such as metallic nanoparticles and semiconductor microspheres. The material permittivity is determined by fitting the measured indices of refraction and absorption with a generalized Drude-Lorentz model containing a number of poles in the complex frequency plane. Each Drude or Lorentz pole generates an infinite series of resonant states. Furthermore, for small nanoparticles, each of these poles produces a distinct surface plasmon polariton mode. The evolution of these multiple surface modes with increasing radius traces the transition from the electrostatic limit to significant retardation and radiation. Treating the optical phonon range in a semiconductor microsphere, a reststrahlen band separating the resonant states is found. Considering a small energy range around the semiconductor band gap, the transition from absorption to gain is described by inverting the Lorentz pole weight, which results in the formation of lasing resonant states. Interestingly, the series of resonant states converging towards the absorption pole from the lower frequency side reshapes for a gain pole into a clockwise loop approaching the pole from the higher frequency side, being separated from a series spanning from low to high frequencies and containing the lasing modes.
One-RM: An Improved One-Rule Classifier

One-R algorithm is a simple algorithm which exhibits quite good predictive accuracy for a large class of data. When compared to the more complex algorithms having better predictive accuracy, One-R provides the baseline accuracy for testing new machine learning algorithms. However, the simplicity of One-R means that it has there is a compromise between accuracy and complexity. Often, the accuracy of One- R can be further increased without making it significantly complex. The resulting algorithm as proposed in this paper, One-RM performs equal to One-R in most of the cases and sometimes outperforms One-R by significant margin. Theoretical analysis suggests that One-RM used in conjunction with One-R always performs either better or equal to One-R. Experimental analysis shows that One-RM is a viable alternative to One-R when used as a separate classification rule. Key words : One-RM, One-R algorithm, Algorithm, Accuracy and Complexity. DOI: 10.3329/bjsir.v44i2. 3668 Bangladesh J. Sci. Ind. Res. 44(2), 171-180, 2009
The impacts of benefit plans on employee turnover: a firm-level analysis approach on Taiwanese manufacturing industry

Employee turnover is a serious problem and the question of how to retain highly talented and valued people is very important. Previous employee turnover studies were mostly focused on the individual level but rarely from the standpoint of the business or firm. This study examines the impacts of four kinds of benefit plans on firm-level employee turnover issues, namely, retirement fund, pension, severance pay and fringe benefit. The present study uses the Census Bureau Employment Movement Survey of the Directorate General of Budget, Accounting and Statistics in Taiwan. The two models used to examine the overall manufacturing industry were: (1) the inducement model which tests the ‘with or without’ effect; and (2) the investment model which tests the ‘the more the better’ effect. Results reveal that, with respect to the firm's employee turnover rate, retirement fund and fringe benefits are negative while severance plans are significantly positive. These results are consistent with the transaction costs theory that total expenditure on these plans to retain employees (bureaucratic cost) is less than the market arrangements (transaction cost). In addition, the impact of pension plans is negative in respect of employee turnover in larger or more highly educated firms, but positive in firms with a lower educational level. Moreover, the firm size is negative while the firm's average employees' educational level is positive with respect to the workforce leaving their jobs. These results are consistent with the perspective of resource-based theory and human capital theory. Incidentally, this study also reveals insignificant differences between the ‘with or without’ effect and the ‘the more the better’ effect existing as a sub-group industry rather than across the entire industry.
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding

Image captioning has attracted considerable attention in recent years. However, little work has been done for game image captioning which has some unique characteristics and requirements. In this work we propose a novel game image captioning model which integrates bottom-up attention with a new multi-level residual top-down attention mechanism. Firstly, a lower-level residual top-down attention network is added to the Faster R-CNN based bottom-up attention network to address the problem that the latter may lose important spatial information when extracting regional features. Secondly, an upper-level residual top-down attention network is implemented in the caption generation network to better fuse the extracted regional features for subsequent caption prediction. We create two game datasets to evaluate the proposed model. Extensive experiments show that our proposed model outperforms existing baseline models.
Learning Correlated Latent Representations with Adaptive Priors

Variational Auto-Encoders (VAEs) have been widely applied for learning compact, low-dimensional latent representations of high-dimensional data. When the correlation structure among data points is available, previous work proposed Correlated Variational Auto-Encoders (CVAEs), which employ a structured mixture model as prior and a structured variational posterior for each mixture component to enforce that the learned latent representations follow the same correlation structure. However, as we demonstrate in this work, such a choice cannot guarantee that CVAEs capture all the correlations. Furthermore, it prevents us from obtaining a tractable joint and marginal variational distribution. To address these issues, we propose Adaptive Correlated Variational Auto-Encoders (ACVAEs), which apply an adaptive prior distribution that can be adjusted during training and can learn a tractable joint variational distribution. Its tractable form also enables further refinement with belief propagation. Experimental results on link prediction and hierarchical clustering show that ACVAEs significantly outperform CVAEs among other benchmarks.
Quantum signatures in the quantum Carnot cycle

The Carnot cycle combines reversible isothermal and adiabatic strokes to obtain optimal efficiency, at the expense of a vanishing power output. Quantum Carnot-analog cycles are constructed and solved, operating irreversibly with positive power. Swift thermalization is obtained in the isotherms utilizing shortcut to equilibrium protocols and the adiabats employ frictionless unitary shortcuts. The working medium in this study is composed of a particle in a driven harmonic trap. For this system, we solve the dynamics employing a generalized canonical state. Such a description incorporates both changes in energy and coherence. This allows comparing three types of Carnot-analog cycles, Carnot-shortcut, Endo-shortcut and Endo-global. The Carnot-shortcut engine demonstrates the trade-off between power and efficiency. It posses a maximum in power, a minimum cycle-time where it becomes a dissipator and for a diverging cycle-time approaches the ideal Carnot efficiency. The irreversibility of the cycle arises from non-adiabatic driving, which generates coherence. To study the role of coherence we compare the performance of the shortcut cycles, where coherence is limited to the interior of the strokes, with the Endo-global cycle where the coherence never vanishes. The Endo-global engine exhibits a quantum signature at a short cycle-time, manifested by a positive power output while the shortcut cycles become dissipators. If energy is monitored the back action of the measurement causes dephasing and the power terminates.
Phenotypic flexibility during migration: optimization of organ size contingent on the risks and rewards of fueling and flight?

Avian long-distance migration involves the storage and expenditure of very large fuel loads. Birds may double in weight before take-off on flights of many 1000 km, and they may lose half their body mass over the subsequent few days that such trips take. Recent studies indicate that in addition to the storage and depletion of fat, the muscles and belly organs also undergo considerable changes in size in the course of such migrations. Such intraindividual and repeatedly reversed changes in stores and organ sizes represent a class of phenotypic plasticity called 'phenotypic flexibility'. Using preliminary comparative data for different populations of Bar-tailed Godwits Limosa lapponica, and several other shorebird species adding variation to the migration strategies sampled (Golden Plover Pluvialis apricaria, Ruff Philomachus pugnax, Red Knot Calidris canutus and Bristle-thighed Curlew Numenius tahitiensis), the thesis is developed that the size of the organs carried during take-off represent evolutionary compromises between their functions during the storage, flight and post-arrival phases of migration. In all cases fat-free tissue along with fat is deposited during fuel storage, but the proportions vary a great deal between similarly sized species. Just before departure on long-distance flights, exercise organs (pectoral muscle and heart) tend to show hypertrophy and nutritional organs (stomach, intestine and liver) tend to show atrophy. Reductions in nutritional organs appear most pronounced in (sub-) species that are about to overfly barren oceans with few or no opportunities for emergency landings. Migrant birds seem to show a great deal of adaptive flexibility, and the study of this flexibility may shed light on (presently unknown) physiological mechanisms as well as on correlated ecological constraints on bird migration.
A Web Survey Analysis of the Subjective Well-Being of Spanish Workers

This paper makes use of a large sample of individual data obtained from web surveys in the WageIndicator project. Data includes extensive information on the quality of working conditions together with different well-being indicators. The paper emphasizes the role of work-related characteristics as a specific and very important aspect of life. In our analysis, we demonstrate the role of working conditions in the following three domains: overall life-satisfaction; satisfaction with one’s job; and satisfaction with the combination of family and work. The paper also contributes to the ongoing debate on web survey data quality, reliability, and validity for scientific use. It demonstrates how social sciences can benefit from the use of web survey data in order to overcome the limits of traditional information sources.
Discrete calculus with cubic cells on discrete manifolds

This work is thought as an operative guide to discrete exterior calculus (DEC), but at the same time with a rigorous exposition. We present a version of (DEC) on cubic cell, defining it for discrete manifolds. An example of how it works, it is done on the discrete torus, where usual Gauss and Stokes theorems are recovered.
Fixing Gaussian Mixture VAEs for Interpretable Text Generation

Variational auto-encoder (VAE) with Gaussian priors is effective in text generation. To improve the controllability and interpretability, we propose to use Gaussian mixture distribution as the prior for VAE (GMVAE), since it includes an extra discrete latent variable in addition to the continuous one. Unfortunately, training GMVAE using standard variational approximation often leads to the mode-collapse problem. We theoretically analyze the root cause --- maximizing the evidence lower bound of GMVAE implicitly aggregates the means of multiple Gaussian priors. We propose Dispersed-GMVAE (DGMVAE), an improved model for text generation. It introduces two extra terms to alleviate mode-collapse and to induce a better structured latent space. Experimental results show that DGMVAE outperforms strong baselines in several language modeling and text generation benchmarks.
Fast reconstruction of single-shot wide-angle diffraction images through deep learning

Single-shot x-ray imaging of short-lived nanostructures such as clusters and nanoparticles near a phase transition or non-crystalizing objects such as large proteins and viruses is currently the most elegant method for characterizing their structure. Using hard x-ray radiation provides scattering images that encode two-dimensional projections, which can be combined to identify the full three-dimensional object structure from multiple identical samples. Wide-angle scattering using XUV or soft x-rays, despite yielding lower resolution, provides three-dimensional structural information in a single shot and has opened routes towards the characterization of non-reproducible objects in the gas phase. The retrieval of the structural information contained in wide-angle scattering images is highly non-trivial, and currently no efficient rigorous algorithm is known. Here we show that deep learning networks, trained with simulated scattering data, allow for fast and accurate reconstruction of shape and orientation of nanoparticles from experimental images. The gain in speed compared to conventional retrieval techniques opens the route for automated structure reconstruction algorithms capable of real-time discrimination and pre-identification of nanostructures in scattering experiments with high repetition rate—thus representing the enabling technology for fast femtosecond nanocrystallography.
Regional integration and foreign direct investment in east African countries

This study investigates the effect of regional integration on Foreign Direct Investment in East Africa Community countries. We apply Generalised Least Squares to examine this relationship. Regional integration did not have any effect on Foreign Direct Investment flows into the region. The degree of political risk and financial stability were positive and significant. The study recommends that Kenya and the other East Africa Community countries should institute political reforms to accompany integration in order to improve the country’s ratings in terms of the degree of political risk. They should also maintain a stable exchange rate regime.
Detecting 
 p‐Hacking

We theoretically analyze the problem of testing for p‐hacking based on distributions of p‐values across multiple studies. We provide general results for when such distributions have testable restrictions (are non‐increasing) under the null of no p‐hacking. We find novel additional testable restrictions for p‐values based on t‐tests. Specifically, the shape of the power functions results in both complete monotonicity as well as bounds on the distribution of p‐values. These testable restrictions result in more powerful tests for the null hypothesis of no p‐hacking. When there is also publication bias, our tests are joint tests for p‐hacking and publication bias. A reanalysis of two prominent data sets shows the usefulness of our new tests.
Substitutions of soybean meal with enriched palm kernel meal in laying hens diet.

A series of experiment was conducted in order to substitute soybean meal (SBM) with palm kernel cake (PKC) as a protein source in laying hens diet. First experiment was to increase its protein and amino acids content by fermentation process and followed by enzymes supplementation to improve nutrient digestibilities. Second experiment was conducted to evaluate the effectiveness of enzyme- supplemented fermented palm kernel cake (EFPKC) to replace SBM in laying hens diet. The energy (AME) of the PKC, the fermented PKC (FPKC) and the EFPKC was measured by ileal amino acids digestibility (IAAD) in broilers. The AME and the IAAD values of the EFPKC were used for diet formulation in the feeding trial. A feeding trial was performed in laying hens, aged 51 weeks for 8 weeks egg production. Five diets with different levels of substitution of SBM with EFPKC but similar nutrient contents were formulated, i.e.: 1. Control (without EFPKC), 2. 25% of SBM in control diet substituted with EFPKC, 3. 50% of SBM in control diet substituted with EFPKC, 4. 75% of SBM in control diet substituted with EFPKC and 5. 100% of SBM in control diet substituted with EFPKC. Each diet was fed to 24 hens (6 replicates of 4 birds/ replicate). Results of the experiment showed that the fermentation of PKC increased the crude protein and most of the amino acids contents except the threonine and arginine, but decreased its AME. Supplementation of enzymes (BS4 or CE) improved the ileal amino acid digestibilities of the fermented PKC. However, only BS4 enzymes increased the AME of the EFPKC. About 25% to 50% of the SBM in the diet could be substituted with the EFPKC without any detrimental effect on the performances of laying hens.