Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxygen vacancies in ZnO

The electronic properties of ZnO have traditionally been explained by invoking intrinsic defects. In particular, the frequently observed unintentional n-type conductivity has often been attributed to oxygen vacancies. We report first-principles calculations showing that the oxygen vacancy VO is not a shallow donor, but has a deep e(2+∕0) level at ∼1.0eV below the conduction band. The negative-U behavior that causes the 1+charge state to be unstable is associated with large local lattice relaxations. We present a detailed configuration coordinate diagram, which allows us to provide a detailed interpretation of recently reported ODEPR (optically detected electron paramagnetic resonance) measurements [L. S. Vlasenko and G. D. Watkins, Phys. Rev. B 71, 125210 (2005)].
Older Adults’ Evaluations of Mobile Apps: Insights from a Mobility App-based Solution

Older adults are a growing segment in society. One of the main challenges that older adults experience relates to mobility. Recognizing this noteworthy challenge, a state-of-the-art mobility app-based solution called the TakeMe app was developed to bring transportation options and volunteers to older adults’ fingertips and thus enabling them to remain mobile outside the home environment to meet their needs. The present study aims to explore older adults’ evaluations of the mobility app-based solution. To do so, the study adopts a qualitative approach to interview older adults’ and a quantitative approach to perform and report on a content analysis of older adults’ evaluations of the mobility app-based solution, thereby leveraging on the benefit of soliciting participant voices in the former and the benefit of objectivity in analysis and reporting in the latter. Findings of the study reveal three key aspects that older adults consider when evaluating mobile apps: learning experience, value perception, and usability. The study concludes with key takeaways and their implications for theory and practice, as well as limitations and future research directions.
Sojourn time test for maximum-length linearly recurring sequences with characteristic primitive trinomials

A new statistical test for random number generators is introduced, which is based on simulations of the arc sine law for sojourn times of 1-dimensional random walks. Results of the tests for maximum-length linearly recurring sequences with characteristic primitive trinomial show statistical biases of those sequences explicitly, when the legnth of sample paths used in the test is somewhat longer than the degree of the characteristic trinomials.
A level set based model for damage growth: The thick level set approach

In this paper, we introduce a new way to model damage growth in solids. A level set is used to separate the undamaged zone from the damaged zone. In the damaged zone, the damage variable is an explicit function of the level set. This function is a parameter of the model. Beyond a critical length, we assume the material to be totally damaged, thus allowing a straightforward transition to fracture. The damage growth is expressed as a level set propagation. The configurational force driving the damage front is non‐local in the sense that it averages information over the thickness in the wake of the front. The computational and theoretical advantages of the new damage model are stressed. Numerical examples demonstrate the capability of the new model to initiate cracks and propagate them even in complex topological patterns (branching and merging for instance). Copyright © 2010 John Wiley & Sons, Ltd.
Adaptive spatiotemporal multiple sensor fusion

We have developed and applied a spatiotemporal fusion framework that uses different fusion strategies across time frames (temporal fusion) as well as between sensors (spatial fusion). We have developed, at the feature level, new and different fusion strategies (additive and minmax fusion) in addition to the traditional strategies (multiplicative, min, and max fusion). These different fusion strategies are compared and predicted by their receiver operating characteristics performance in the likelihood-reading domain. Furthermore, by applying the additive fusion strategy, we have developed methods for adaptive sensor weighting using reliability functions to improve fusion performance. Our simulated test and analysis results show that temporal fusion (as well as spatial fusion) can considerably improve target classification, and also show that the adaptive sensor weighting using reliability functions can significantly improve fusion performance when one sensor is much more reliable than the other. Finally, we propose an optimal integrated spatiotemporal multiple sensor fusion system that includes two new processors: the adaptive processor and the fusion selection processor.
Fixture-Aware DDQN for Generalized Environment-Enabled Grasping

This paper expands on the problem of grasping an object that can only be grasped by a single parallel gripper when a fixture (e.g., wall, heavy object) is harnessed. Preceding work that tackle this problem are limited in that the employed networks implicitly learn specific targets and fixtures to leverage. However, the notion of a usable fixture can vary in different environments, at times without any outwardly noticeable differences. In this paper, we propose a method to relax this limitation and further handle environments where the fixture location is unknown. The problem is formulated as visual affordance learning in a partially observable setting. We present a self-supervised reinforcement learning algorithm, Fixture-Aware Double Deep Q-Network (FA-DDQN), that processes the scene observation to 1) identify the target object based on a reference image, 2) distinguish possible fixtures based on interaction with the environment, and finally 3) fuse the information to generate a visual affordance map to guide the robot to successful Slide-to-Wall grasps. We demonstrate our proposed solution in simulation and in real robot experiments to show that in addition to achieving higher success than baselines, it also performs zero-shot generalization to novel scenes with unseen object configurations.
Epitaxial Mn2.5Ga thin films with giant perpendicular magnetic anisotropy for spintronic devices

We report on epitaxial growth and magnetic properties of Mn2.5Ga thin films, which were deposited on Cr/MgO single crystal substrates by magnetron sputtering. X-ray diffraction results revealed the epitaxial relationships as Mn2.5Ga(001)[100]∥Cr(001)[110]∥MgO(001)[100]. The presence of (002) and (011) superlattice peaks indicates that the films were crystallized into DO22 ordered structures. The perpendicular magnetic anisotropy (PMA) properties were found to be related to the extent of DO22 chemical ordering. A giant PMA (Kueff=1.2×107 erg/cm3) and low saturation magnetization (Ms=250 emu/cm3) can be obtained for the film with highest chemical ordering parameter (S=0.8).
Bayesian Analysis for Robust Synthesis of Nanostructures

Abstract Nanomaterials, because of their unique properties such as extremely small size and increased ratio of surface area to volume, have a great potential in many industrial applications that involve electronics, sensors, solar cells, super-strong materials, coatings, drug delivery, and nanomedicine. They have the potential also to improve the environment by direct applications of these materials to detect, prevent and remove pollutants. While nanomaterials present seemingly limitless possibilities, they bring with them new challenges. Among them is the precise control of the morphology of nanomaterials, which is extremely critical to the development of advanced nanodevices with various functionalities. The one-dimensional nanostructures of Cadmium Selenide (CdSe) have been found to represent morphologies of nanowires, nanobelts, and nanosaws, however, their synthesis is by trial and error. Predictive modeling and control methods are essential to process yield and productivity improvement. The process yield (response) is a vector whose elements correspond to the number of appearances of the different types of nanostructures, namely nanosaws, nanowires, and nanobelts. The goal in this paper is to apply existing Bayesian methodologies to describe the growths of these nanostructures in terms of process variables and to predict the probability of transition from one nanostructure to another when changes are made to one or more process variables. We also propose a Bayesian algorithm to identify the optimal process conditions that maximize the predicted probability of each type of nanostructure.
The Evolution of Droplet Spectra and the Rate of Production of Embryonic Raindrops in Small Cumulus Clouds

Abstract Calculations have been made of the evolution of droplet spectra within small cumulus clouds which are entraining undersaturated environmental air. The mixing process is assumed to be highly inhomogeneous. In the extreme situation considered, environmental air is entrained in discrete blobs or parcels, causing some droplets of all sizes to be completely removed from the condensate spectrum, while others do not change in size. This model, which is based on laboratory experiments, corresponds to a situation in which the time constant for droplet evaporation is small relative to that for turbulent mixing; in the classical (homogeneous) model, which has been used by other workers, the reverse applies. The calculations produce spectral shapes which agree well with those observed in cumulus by Warner (1969), and they indicate that favored droplets may grow very much faster through the condensate spectrum than is predicted classically.
The Larynx–Melon–Vestibular Lips (LMVL) model of the dolphin sonar. II. The melon beam former

The LMVL model of the dolphin sonar is based on the following system components: (1) the Larynx, controlled by the palatopharyngeal sphincter and operating as a ‘‘sawtooth’’ relaxation oscillator, is the source of the echolocation pulses (the so‐called ‘‘clicks’’), and its acoustic output is coupled to the melon through the impedance matching nasal ducts; (2) the Melon, because of its low sound velocity, acts as a ‘‘slow waveguide’’ to form the observed forward‐looking beam patterns; and (3) the residual air in the nasopharyngeal cavity acts as an air‐pressure reservoir to energize relaxation oscillations of the Vestibular Lips, resulting in the lip‐modulated tonal phonations (the so‐called ‘‘whistles’’) that radiate through the corresponding vestibular sac. The larynx sawtooth generator has been treated previously [J. W. Fitzgerald, Part I Oceans ’94, Vol. I, pp. 271–276 (Sept. 1994)]. The measured sound velocity in the melon decreases with temperature from v≂1.39×105 cm/s @10 °C to v≂1.28×105 cm/s @4.
Experimental Assessment of a Control Strategy for Locomotion Assistance Relying on Simplified Motor Primitives

Lower-limb exoskeletons are robotic devices that can provide assistance to human locomotion. Since they are expected to be used in ecological environments, their control strategy should handle different kinds of daily-life situations. Taking inspiration from the human neuromuscular system - and particularly from the socalled motor primitives - may help in adapting the type of delivered assistance to different locomotion tasks. In this work, we validated the combination of simplified primitives and a musculoskeletal model for assisting healthy subjects with a hip exoskeleton. This framework showed adaptation to the user's gait for different slope inclinations, although its effects on the subject's speed and their perceived effort showed no significant improvement compared to wearing the device in transparent mode.
Workplace Arrogance, Need for Power, and Counterproductive Work Behaviors in Corporate Managers: The Mediating Role of Humility

The study investigated the relationship between workplace arrogance, the need for power, and Counterproductive Work Behavior (CWB) in corporate managers. The study was carried out by following the correlational research design. The sample of N = 260 corporate managers (males = 181, females = 79), with an age range from 30 years to 55 years ( M = 41.03, SD = 7.06), was recruited through the purposive sampling strategy from the different cities of Pakistan. In the first step, the authors established a factor structure of the workplace arrogance scale and retained 22 items with well-fitted indices of the one-factor solution model. The results of correlation analysis exhibited significant ( p < .05) positive relationships between workplace arrogance, the personalized need for power (P nPower). The CWB was negatively associated with the socialized need for power (S nPower), humility, and agreeableness in corporate managers. The independent sample t -test indicated that male and female corporate managers had similar scores in terms of all study variables ( p > .05). In addition, results of multiple linear regression analysis revealed that workplace arrogance and personalized need for power with 25% of the variance were found to be significant ( p < .01) predictors of the CWB. Moreover, the path analysis through Structure Equational Modeling (SEM) also suggested that personalized need for power, workplace arrogance, and humility were significant predictors of CWB. Lastly, SEM demonstrated that humility significantly mediated the relationship between workplace arrogance, the need for power, and CWB in corporate managers. Moreover, two demographic variables (i.e., work experience and the corporate sectors) also impact their CWB and the overall model fit indices. The study provides researchers with a validated workplace arrogance scale on the corporate sample. It helps the researchers to expand their understanding of the significance of these constructs in the field of industrial-organizational psychology. In addition, the study seeks to benefit many employees and employers to comprehend the nature and the association of CWB with other undesirable variables in the workplace (i.e
Investigating the Effect of Trust, Motivation, and Reward on the Desire to Share Knowledge through Social Networks by Shiraz University of Medical Sciences Staff

This study investigated the effect of trust, motivation, and reward on the willingness to share knowledge on social networks by the Shiraz University of Medical Sciences (SUMS) staff. The instrument of the present study was a researcher-made questionnaire in which formal-content validity was confirmed, and its reliability, according to Cranach's alpha coefficient, was equal to . 90. The study's statistical population was 27506, including employees and faculty members, according to the Krejcie and Morgan table, the sample size was 379. The results showed that the importance of knowledge sharing among employees and commitment to the university were two effective components of intrinsic motivation. Support of university administrators for knowledge sharing and improving the status of social pages (38.8%) through knowledge sharing were two effective components of external motivation for employee knowledge sharing in social networks. "Fear of employees being replaced" and "fear of losing a job" were two negative and very weak components of the trust variable on knowledge sharing. "Financial incentives" and "job promotion" were among the influential components of the reward variable, which "greatly" affected the sharing of knowledge in social networks. Paying more attention to evaluating the performance of employees and financial rewards by managers can be effective in sharing knowledge and motivation .
Effects of pubertal growth variation on knee mechanics during walking in female and male adolescents

Puberty substantially alters the body's mechanical properties, neuromuscular control, and sex differences therein, likely contributing to increased, sex‐biased knee injury risk during adolescence. Female adolescents have higher risk for knee injuries than male adolescents of similar age engaging in similar physical activities, and much research has investigated sex differences in mechanical risk factors. However, few studies address the considerable variation in pubertal growth (timing, pace), knee mechanics, and injury susceptibility within sexes, or the impact of such growth variation on mechanical injury risk.
{ital Ab initio} estimate of Hubbard model parameters: A simple procedure applied to BEDT-TTF salts

We describe a simple procedure to extract the parameters of the one-band Hubbard model from a set of {ital ab initio} calculations on a dimeric unit. The method applies to narrow band solids with negligible orbital relaxation. In this paper we consider a specific system, {kappa}-(BEDT-TTF){sub 2}Cu[N(CN){sub 2}]Br, but the proposed procedure is of general applicability. From a detailed discussion of the {ital ab initio} data, we extract a few general criteria of wide applicability about the relative magnitude of the empirical model parameters. We prove that the Hubbard model, including both on-site and inter-site electron-electron interactions, is a reliable model for systems with negligible orbital relaxation, apart from particular geometrical arrangements. The hopping parameter (t), as well as the intersite electronic repulsion (V), are barely affected by the chemical environment. On the contrary, the on-site energy and the on-site repulsion (the Hubbard h and U) show an appreciable dependence on the chemical environment, through a dependence of the frontier and core energies on the surrounding potential. {copyright} {ital 1997} {ital The American Physical Society}
KNOWLEDGE AND ATTITUDE TOWARDS EXPRESSED BREAST MILK AMONG WORKING MOTHERS IN HARARI REGIONAL STATE, ETHIOPIA, 2021

Background: World health organization (WHO) rules in the beginning six month the child should be given breast milkonly, so mothers coming back to work should have a good knowledge about appropriate expression of breast milk. The main goal of the research was to determine knowledge and attitude toward expressed breast milk among working mothers in Harari region, Ethiopia, 2021 Methods:A cross-sectional study was done on 385 employed mothers for analysis of data SPSS 22 used. Results: Over all knowledge and attitude about expressed breast milk were 36% and 44%respectivly. Conclusion: the study showed there was knowledge gap in the expressing and storing of breast milk. More exertion is essential to be done by the health professionals ineducating mothers on way of expression, storing and timings of storage of expressed breast milk of breast.
Show, Tell and Rephrase: Diverse Video Captioning via Two-Stage Progressive Training

Describing a video using natural language is an inherently one-to-many translation task. To generate diverse captions, existing VAE-based generative models typically learn factorized latent codes via one-stage training merely from stand-alone video-caption pairs. However, such a paradigm neglects set-level relationships among captions from the same video, not fully capturing the underlying multimodality of the generative process. To overcome this shortcoming, we leverage neighbouring descriptions for the same video that are articulated with noticeable topics and language variations (i.e., paraphrases). To this end, we propose a novel progressive training method by decomposing the learning of latent variables into two stages that are topic-oriented and paraphrase-oriented, respectively. Specifically, the model learns from divergent topic sentences obtained by semantic-based clustering in the first stage. It is then trained again through paraphrases with a cluster-aware adaptive regularization, allowing more intra-cluster variations. Furthermore, we introduce an overall metric DAUM, a Diversity-Accuracy Unified Metric to consider both the precision of the generated caption set and its coverage on the reference set, which has proved to have a higher correlation with human judgment than previous precision-only metrics. Extensive experiments on three large-scale video datasets show that the proposed training strategy can achieve superior performance in terms of accuracy, diversity, and DAUM over several baselines.
Gathering Physical Particles with a Global Magnetic Field Using Reinforcement Learning

For biomedical applications in targeted therapy delivery and interventions, a large swarm of micro-scale particles (“agents”) has to be moved through a maze-like environment (“vascular system”) to a target region (“tumor”). Due to limited on-board capabilities, these agents cannot move autonomously; instead, they are controlled by an external global force that acts uniformly on all particles. In this work, we demonstrate how to use a time-varying magnetic field to gather particles to a desired location. We use reinforcement learning to train networks to efficiently gather particles. Methods to overcome the simulation-to-reality gap are explained, and the trained networks are deployed on a set of mazes and goal locations. The hardware experiments demonstrate fast convergence, and robustness to both sensor and actuation noise. To encourage extensions and to serve as a benchmark for the reinforcement learning community, the code is available at Github.
The Centers of Early- to Intermediate-Type Spiral Galaxies: A Structural Analysis

A recent Hubble Space Telescope (HST)/WFPC2 visual survey of early- and intermediate-type spiral galaxies has unveiled a great complexity in the inner regions of these systems, which include a high fraction of photometrically distinct compact sources sitting at the galactic centers ("nuclei"). The faint nuclei (MV ≳ -12) are typically hosted by rather amorphous, quiescent, bulgelike structures with an exponential (rather than the classical R1/4) light profile. These "exponential bulges" are commonly found inside the intermediate-type disks, consistent with previous studies. Brighter nuclei (MV ≲ -12) are typically found instead in the centers of galaxies with circumnuclear rings/arms of star formation or dust and an active, i.e., H II- or AGN-type, central spectrum at ground-based resolution. On the structural plane of half-light radius (Re) versus mean surface brightness within the half-light radius (μe), faint and bright nuclei overlap with, and fill the region of parameter space between, the old Milky Way globular clusters and the young star clusters, respectively, with typical Re of about a few up to ≈20 pc. On the same plane, the exponential bulges have significantly fainter μe than R1/4 bulges for any given radius and follow a μe-Re relation typical of disks, which strengthens the suggestion that the exponential bulges grow inside the disks as a result of the secular evolution of the latter. Under the likely assumption that the visual light from the faint nuclei embedded in the quiescent exponential bulges is of stellar origin and of a similar (≳1 Gyr) age for the central star clusters and their host bulges, the masses inferred for the former agree with those required to disrupt bars comparable in size to the latter. This offers support to scenarios in which the exponential bulges grow inside the disks owing to the orbital disruption of progenitor bars caused by the growth of a central concentration of mass and suggests that this specific mode of bulge formation is (still) active in the present-day universe. On the other hand, the presence of the massive clusters at the very center of the low-density exponential bulges should prevent any other "nuclear" bar from forming, thereby preventing further infall of dissipative fuel to the nuclear regions. This may argue against the possibility of evolving the exponential bulges into denser, R1/4 bulges by a simple looping for several cycles of the bar formation/disruption mechanism.