Miracle-dz/UniFAR-FTUs huggingface dataset:
How Organizational Culture Moderate the Effect of Total Productive Maintenance Practice on Operational Performance? Evidences from Indonesian Mining Industry

The industry needed a system to support its operation when most of the processes were done by equipment or machines. Total Productive Maintenance (TPM) was a system to ensure all equipment or machines run in optimal performance for long period by fully supported by top management until the bottom level. Implementation of this system in the mining industry was still seldom due to some factors and organizational culture was one of the reasons. The purpose of this research was to analyze the influence of TPM implementation on operational performance by moderating the effect of organizational culture in the mining industry by using a two-step approach of structural equation model (SEM). The research type was under explanative research with hypothesis testing from primary data that was obtained from distributing questionnaires and direct interviews in the field which was analyzed by using Lisrel 8.7. This research showed that the construct of TPM has a significant impact to influence operation performance directly in the mining industry with a t-value of 3.54 and organization culture also increases the significance by moderating effect with t-value of interaction 5.28 was higher than 1.96 while organizational culture was not significant to influence operational performance directly that was showed by t-value 1.22. This research had a novelty for studying TPM practice in Indonesian mining by using SEM to analyze the moderating effect of organizational culture. The managerial implication of this research was a guideline for decisionmakers to implement TPM by considering developing, group, hierarchical, and rationale culture to improve operational performance in the Indonesian mining industry.
A research work on Action Quality Assessment of Physiotherapy Rehabilitation Exercises

While the onset of the pandemic scenario had moved the world on a precarious perch, technology has by far proved itself to be highly effective to ensure the betterment of humankind by providing cutting-edge solutions in every possible field. Now, more than ever before, it is vital to look after both physical and psychological health. Although many of the doctor’s consultations have moved to virtual platforms, there do exist many more possibilities which can enhancing better ways for some forms of virtual treatments such as physiotherapy rehabilitation. One of the emerging technological areas of deep learning have been observed to assist significantly while on a lookout for solutions to such problems relating to image classification, human pose estimation etc. Despite the ongoing work of many big technology giants on human pose estimation, there is only one well-known research published back in 2020 to utilise deep learning for action quality assessment of physiotherapy rehabilitation exercises. This dissertation has made an attempt to gain particular knowledge for advancing that research in a way to establish a possible pipeline for action quality assessment on camera-captured videos. This research is split majorly into 2 phases, namely, pose estimation (for test data preparation) and model training (for preparing the model to take test data as input). For the same, a review of the previous work done in the field of physiotherapy, human pose estimation, deep learning is made and a framework for preparing test data by 2D pose extraction to 3D pose estimation of smartphone captured video datasets has been established by using HRNET with COCO dataset and VideoPose3D inference using Detectron library. The mapping of the obtained coordinates to 3D joints is then examined wherein it is observed that the final test data preparation can only be accomplished with licensed access to Human3.6M in order to utilise the actual inferences of VideoPose3D with Human3.6M. III On the other hand, the recent work on action quality assessment with 2D markers has been reestablished with their existing UIPRMD dataset of squats for understanding and then enhancements to the work have been made from scratch to ensure that it takes into account the 3D joint positions for action quality assessment. The obtained results have shown that the model can take 3D joint positions as an input while providing near-to-similar results as for the one with 2D markers. Note: The reader of the research document is requested to view the document in Acrobat Reader in order to have an insight to the animated gif files which are added in the last chapters.
The systemic nature of action learning programmes

A lot of attention has been paid to action learning in the last three decades or so and the success of such programmes has also been widely publicized. But why have these programmes been so effective in helping organizations cope with change? Many writers state that the success of such programmes is due to the fact that they link learning to actions. Yet others claim that action learning programmes succeed because they involve employee empowerment and provide a much greater learning curve. In this paper the authors hold that action learning programmes succeed because they are partly systemic and can be made even more effective if they are fully designed and implemented systemically. The essential features of a systemic method include the ability to help organizations deal with organic, cultural and power complexity. The conclusion that action learning programmes can succeed if they are fully designed and implemented systemically is reached by comparing the essential features of a systemic method with that of an action learning programme. The authors make use of a case study to support their conclusion. Copyright © 2000 John Wiley & Sons, Ltd.
A semicircular band‐notch ultra‐wideband printed antenna based on CSRR

In this article, a semicircular band‐notch monopole antenna based on CSRR with band‐notch function is presented. A rectangular slit is cut at the top center of the ground to obtain desired operation frequency bandwidth, and a complementary split‐ring resonator is embedded in feed line to realize band‐notch function. Experiment results show that the proposed antenna has a sharp stop‐band of 4.89 GHz–6.12 GHz and one ultra‐wideband from 2 GHz to 12 GHz. During operated frequency band, the proposed antenna exhibits excellent radiation characteristics. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52:2387–2390, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25463
An Epidemiologic Investigation of Health Effects in Air Force Personnel Following Exposure to Herbicides. Volume 2. First Followup Examination Results.

Abstract : This report represent the result of the health assessment of the 1,016 Ranch Hands and the 1,293 Comparisons who participated in the 1985 followup examination of the Air Force health Study. The purpose of the study is to determine whether long-term health effects exist and can be attributed to occupational exposure to herbicides. The results show a subtle but consistent narrowing of medical differences between the two groups since the Baseline study in 1982, however, the Ranch Hands continue to manifest slightly more minor adverse health conditions than the Comparisons. Continued surveillance of these groups is indicated. The report concludes that there is not sufficient evidence to implicate a causal relationship between herbicide exposure and adverse health in the Ranch Hand group. Keywords: Epidemiologic investigation, Phenoxy herbicides, Herbicide orange, Dioxin, Morbidity, Health surveys, Air Force health study.
Innovation and Foreign Technology in Italy, 1861-2011

The paper explores the long run evolution of Italy's performance in technological innovation as a function of international technology transfer, reconstructing the different phases and dimensions of Italian innovative activity, tracking the transfer of foreign technological knowledge through a number of channels, analysing the impact of imported technology. The study is based on a newly constructed dataset, over the 1861-2009 period, composed of variables related to: innovation activity performance; foreign technology transfer; domestic absorptive and innovative capability. The analysis highlights, also by econometric assessment, the significant contribution of foreign technology both to innovation activity results and to productivity growth. Differences across channels of technology transfer and historical phases emerge, also in connection with the evolution of human capital endowment and domestic innovative capacity. Machinery imports contributed positively both to innovation activity and to productivity growth; inward FDI contributed positively to productivity growth, but not to indigenous innovation activity; the accumulation of technical human capital fuelled both. In the long Italian Golden Age, for the first time the association of foreign technological knowledge with indigenous innovation processes strengthened productivity significantly. More recently instead the dismal productivity growth is negatively associated with formalised innovation activity under-performance and reduced imports of disembodied technology
Generative Adversarial Networks for Synthetic Data Generation: A Comparative Study

Generative Adversarial Networks (GANs) are gaining increasing attention as a means for synthesising data. So far much of this work has been applied to use cases outside of the data confidentiality domain with a common application being the production of artificial images. Here we consider the potential application of GANs for the purpose of generating synthetic census microdata. We employ a battery of utility metrics and a disclosure risk metric (the Targeted Correct Attribution Probability) to compare the data produced by tabular GANs with those produced using orthodox data synthesis methods.
Inertial-range Magnetic-fluctuation Anisotropy Observed from Parker Solar Probe’s First Seven Orbits

Solar wind turbulence is anisotropic with respect to the mean magnetic field. Anisotropy leads to ambiguity when interpreting in situ turbulence observations in the solar wind because an apparent change in the measurements could be due to either the change of intrinsic turbulence properties or to a simple change of the spacecraft sampling direction. We demonstrate the ambiguity using the spectral index and magnetic compressibility in the inertial range observed by the Parker Solar Probe during its first seven orbits ranging from 0.1 to 0.6 au. To unravel the effects of the sampling direction, we assess whether the wave-vector anisotropy is consistent with a two-dimensional (2D) plus slab turbulence transport model and determine the fraction of power in the 2D versus slab component. Our results confirm that the 2D plus slab model is consistent with the data and the power ratio between 2D and slab components depends on radial distance, with the relative power in 2D fluctuations becoming smaller closer to the Sun.
Semantic Segmentation of Legal Documents via Rhetorical Roles

Legal documents are unstructured, use legal jargon, and have considerable length, making them difficult to process automatically via conventional text processing techniques. A legal document processing system would benefit substantially if the documents could be segmented into coherent information units. This paper proposes a new corpus of legal documents annotated (with the help of legal experts) with a set of 13 semantically coherent units labels (referred to as Rhetorical Roles), e.g., facts, arguments, statute, issue, precedent, ruling, and ratio. We perform a thorough analysis of the corpus and the annotations. For automatically segmenting the legal documents, we experiment with the task of rhetorical role prediction: given a document, predict the text segments corresponding to various roles. Using the created corpus, we experiment extensively with various deep learning-based baseline models for the task. Further, we develop a multitask learning (MTL) based deep model with document rhetorical role label shift as an auxiliary task for segmenting a legal document. The proposed model shows superior performance over the existing models. We also experiment with model performance in the case of domain transfer and model distillation techniques to see the model performance in limited data conditions.
Independent dynamic acousto-mechanical and electrostatic control of individual quantum dots in a LiNbO3-GaAs hybrid

We demonstrate tuning of single quantum dot emission lines by the combined action of the dynamic acoustic field of a radio frequency surface acoustic wave and a static electric field. Both tuning parameters are set all-electrically in a LiNbO3-GaAs hybrid device. The surface acoustic wave is excited directly on the strong piezoelectric LiNbO3 onto which a GaAs-based p-i-n photodiode containing a single layer of quantum dots was epitaxially transferred. We demonstrate dynamic spectral tuning with bandwidths exceeding 3 meV of single quantum dot emission lines due to deformation potential coupling. The center energy of the dynamic spectral oscillation can be independently programmed simply by setting the bias voltage applied to the diode.
Neural Head Avatars from Monocular RGB Videos

We present Neural Head Avatars, a novel neural representation that explicitly models the surface geometry and appearance of an animatable human avatar that can be used for teleconferencing in AR/VR or other applications in the movie or games industry that rely on a digital human.11philgras. github.io/neural_head_avatars/neural_head_avatars. html Our representation can be learned from a monocular RGB portrait video that features a range of different expressions and views. Specifically, we propose a hybrid representation consisting of a morphable model for the coarse shape and expressions of the face, and two feed-forward networks, predicting vertex offsets of the underlying mesh as well as a view- and expression-dependent texture. We demonstrate that this representation is able to accurately extrapolate to unseen poses and view points, and generates natural expressions while providing sharp texture details. Compared to previous works on head avatars, our method provides a disentangled shape and appearance model of the complete human head (including hair) that is compatible with the standard graphics pipeline. Moreover, it quantitatively and qualitatively outperforms current state of the art in terms of reconstruction quality and novel-view synthesis.
Towards a consistent lattice Boltzmann model for two-phase fluids

Abstract We revisit the construction of discrete kinetic models for single-component isothermal two-phase flows. Starting from a kinetic model for a non-ideal fluid, we show that, under conventional scaling, the Navier–Stokes equations with a non-ideal equation of state are recovered in the hydrodynamic limit. A scaling based on the smallness of velocity increments is then introduced, which recovers the full Navier–Stokes–Korteweg equations. The proposed model is realized on a standard lattice and validated on a variety of benchmarks. Through a detailed study of thermodynamic properties including co-existence densities, surface tension, Tolman length and sound speed, we show thermodynamic consistency, well-posedness and convergence of the proposed model. Furthermore, hydrodynamic consistency is demonstrated by verification of Galilean invariance of the dissipation rate of shear and normal modes and the study of visco-capillary coupling effects. Finally, the model is validated on dynamic test cases in three dimensions with complex geometries and large density ratios such as drop impact on textured surfaces and mercury drops coalescence.
Topology of black hole thermodynamics

A critical point is an important structure in the phase diagram of a thermodynamic system. In this work, we introduce topology to the study of the black hole thermodynamics for the first time by following Duan's topological current $\phi$-mapping theory. Each critical point is endowed with a topological charge. We find that critical points can be divided into two classes, the conventional and the novel. Further study shows that the first-order phase transition can extend from the conventional critical point, while the presence of the novel critical point cannot serve as an indicator of the presence of the first-order phase transition near it. Moreover, the charged anti-de Sitter black hole and the Born-Infeld anti-de Sitter black hole have different topological charges, which indicates they are in different topological classes from the viewpoint of thermodynamics. These give the first promising study on the topology of the black hole thermodynamics. Such approach is also expected to be extended to other black holes, and much more topological information remains to be disclosed.
Generalised quasilinear approximations of turbulent channel flow. Part 2. Spanwise triadic scale interactions

Abstract Continuing from Part 1 (Hernández et al., J. Fluid Mech., vol. 936, 2022, A33), a generalised quasilinear (GQL) approximation is studied in turbulent channel flow using a flow decomposition defined with spanwise Fourier modes: the flow is decomposed into a set of low-wavenumber spanwise Fourier modes and the rest high-wavenumber modes. This decomposition leads to the nonlinear low-wavenumber group that supports the self-sustaining process within the given integral length scales, whereas the linearised high-wavenumber group is not able to do so, unlike the GQL models in Part 1, which place a minimal mathematical description for the self-sustaining process across all integral scales. Despite the important physical difference, it is shown that the GQL models in this study share some similarities with those in Part 1, i.e. the reduced multi-scale behaviour and anisotropic turbulent fluctuations. Furthermore, despite not being able to support the self-sustaining process in the high-wavenumber group, the GQL models in the present study are found to reproduce some key statistical features in the high-wavenumber group solely through the ‘scattering’ mechanism proposed by previous studies. Finally, using the nature of the GQL approximation, a further set of numerical experiments suppressing certain triadic nonlinear interactions are carried out. This unveils some key roles played by certain types of triadic interactions, including energy cascade and inverse energy transfer in the near-wall region. In particular, the inhibition of inverse energy transfer in the spanwise direction leads to suppression of the near-wall positive turbulent transport at large scales.
A compact charge ratio expression for the emitter delay of polysilicon emitter bipolar transistors

A compact solution for the ratio of the excess minority carrier charge stored into the polysilicon to the charge stored in the single crystal part of the emitter of a polysilicon emitter bipolar transistor is derived. The solution is based on an existing comprehensive model which takes into account the interfacial oxide and an arbitrary number of grains in the polysilicon layer. The emitter charge partition in polysilicon and single crystal emitter components is summarized in contour plots for constant values of the ratio. >
The Seventeenth Data Release of the Sloan Digital Sky Surveys: The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data Complete Release of MaNGA, MaStar, and APOGEE-2 Data

This paper documents the seventeenth data release ( DR17 ) from the Sloan Digital Sky Surveys; the ﬁ fth and ﬁ nal release from the fourth phase ( SDSS-IV ) . DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory ( MaNGA ) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey ( eBOSS ) , as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-ﬁ ber optical spectroscopy released in DR17 is from the SPectroscipic IDenti ﬁ cation of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its ﬁ fth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys. Uni ﬁ ed Astronomy Thesaurus concepts: Astronomy data acquisition ( 1860 ) ; Astronomy databases ( 83 ) ; Surveys ( 1671 )
Hybrid Instance-aware Temporal Fusion for Online Video Instance Segmentation

Recently, transformer-based image segmentation methods have achieved notable success against previous solutions. While for video domains, how to effectively model temporal context with the attention of object instances across frames remains an open problem. In this paper, we propose an online video instance segmentation framework with a novel instance-aware temporal fusion method. We first leverage the representation, \ie, a latent code in the global context (instance code) and CNN feature maps to represent instance- and pixel-level features. Based on this representation, we introduce a cropping-free temporal fusion approach to model the temporal consistency between video frames. Specifically, we encode global instance-specific information in the instance code and build up inter-frame contextual fusion with hybrid attentions between the instance codes and CNN feature maps. Inter-frame consistency between the instance codes is further enforced with order constraints. By leveraging the learned hybrid temporal consistency, we are able to directly retrieve and maintain instance identities across frames, eliminating the complicated frame-wise instance matching in prior methods. Extensive experiments have been conducted on popular VIS datasets, i.e. Youtube-VIS-19/21. Our model achieves the best performance among all online VIS methods. Notably, our model also eclipses all offline methods when using the ResNet-50 backbone.
Divergence of Majorana-Phonon Scattering in Kitaev Quantum Spin Liquid

Haoxiang Li, A. Said, J.Q. Yan, D.M. Mandrus, 3 H. N. Lee, S. Okamoto, Gábor B. Halász, ∗ and H. Miao † Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, USA Department of Materials Science and Engineering, University of Tennessee at Knoxville, Knoxville, Tennessee 37996, USA (Dated: December 6, 2021)