Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal grasp force for robotic grasping and in-hand manipulation with impedance control

Purpose The purpose of this paper is to achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations. Design/methodology/approach To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function. Findings Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand. Originality/value This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.
Pressure shifts in high-precision hydrogen spectroscopy. I. Long-range atom–atom and atom–molecule interactions

We study the theoretical foundations for the pressure shifts in high-precision atomic beam spectrosopy of hydrogen, with a particular emphasis on transitions involving higher excited P states. In particular, the long-range interaction of an excited hydrogen atom in a 4P state with a ground-state and metastable hydrogen atom is studied, with a full resolution of the hyperfine structure. It is found that the full inclusion of the 4P1/2 and 4P3/2 manifolds becomes necessary in order to obtain reliable theoretical predictions, because the 1S ground state hyperfine frequency is commensurate with the 4P fine-structure splitting. An even more complex problem is encountered in the case of the 4P–2S interaction, where the inclusion of quasi-degenerate 4S–2P1/2 state becomes necessary in view of the dipole couplings induced by the van der Waals Hamiltonian. Matrices of dimension up to 40 have to be treated despite all efforts to reduce the problem to irreducible submanifolds within the quasi-degenerate basis. We focus on the phenomenologically important second-order van der Waals shifts, proportional to 1/R6 where R is the interatomic distance, and obtain results with full resolution of the hyperfine structure. The magnitude of van der Waals coefficients for hydrogen atom–atom collisions involving excited P states is drastically enhanced due to energetic quasi-degeneracy; we find no such enhancement for atom–molecule collisions involving atomic nP states, even if the complex molecular spectrum involving ro-vibrational levels requires a deeper analysis.
Towards a Comprehensive Blockchain Architecture Continuum

The increasingly need for companies to keep a high level of synchronization globally and the advent of new technologies are pushing more and more to move decision-making and operational power from the centre of organizations to their edges. The blockchain could be the key technology to make this change possible. However, there is no bridge yet capable of shortening the still long distance between this new technological phenomenon and today's business realities. Our work aims precisely at this goal; we propose a framework of blockchain models to help practitioners understanding and potentially implement new solutions based on this technological paradigm. In particular, we have developed an ontology that helps to identify and clarify in detail what are the concepts and structures revolving around this technology, and built a continuum of blockchain architectural solutions, ranging from a classic centralized IT architecture to one completely distributed within a public ecosystem.
How the West was Lost: Chief Information Officers and the Battle of Jurisdictional Control

Recent research has highlighted the potential downfall of the role and profession of Chief Information Officer (CIO). As the top executive responsible for IT in an organization, this role has gone through several shifts since its advent in the 1980’s. This study addresses how the role has evolved, and, explores how it may evolve in the years to come. The study utilizes a combination of structured literature review and interviews, and is informed by Abbott’s systems of professions perspective. The findings show that after an increase in jurisdictional control prior to the turn of the millennium, the profession has decreased and is continuing to decrease its jurisdictional control. This is in part linked to the imposition of IT Governance frameworks designed to shift risk from the profession of CIOs to neighboring professions. This is discussed in light of calls for future
How hydraulic fracturing triggers fault slip by raising fluid pressure

Earthquakes induced during hydraulic fracturing operations have occurred in a number of locales, but the triggering mechanisms remain poorly understood. Here, we study the fault slip-tendencies of eleven earthquakes that are linked to hydraulic fracturing stimulations of an unconventional hydrocarbon reservoir in a historically aseismic area. We use a recently constructed quantitative model for in-situ stresses and pore pressures to show that the faults could not be stable at the natural high ambient pore pressures extant within the target Duvernay Formation. To retain stability, the fluid pressures acting on the fault must be diminished; but locally these could readily be increased above the critical value if a hydraulic connection exists between the fault and a propagating hydraulic fracture within which pressures in excess of the minimum compression exist. The critical pressures necessary to induce slip are estimated using a probabilistic model that incorporates uncertainties of stress and fault mechanical properties.
Convection initiation and bore formation following the collision of mesoscale boundaries over a developing stable boundary layer: a case study from PECAN

This observational study documents the consequences of a collision between two converging shallow atmospheric boundaries over the central Great Plains on the evening of 7 June 2015. This study uses data from a profiling airborne Raman lidar (the Compact Raman Lidar, or CRL) and other airborne and ground-based data collected during the Plains Elevated Convection At Night (PECAN) field campaign to investigate the collision between a weak cold front and the outflow from a MCS. The collision between these boundaries led to the lofting of high-CAPE, low-CIN air, resulting in deep convection, as well as an undular bore. Both boundaries behaved as density currents prior to collision. Because the MCS outflow boundary was denser and less deep than the cold-frontal airmass, the bore propagated over the latter. This bore was tracked by the CRL for about three hours as it traveled north over the shallow cold-frontal surface and evolved into a soliton. This case study is unique by using the high temporal and spatial resolution of airborne Raman lidar measurements to describe the thermodynamic structure of interacting boundaries and a resulting bore.
Graph pattern detection: hardness for all induced patterns and faster non-induced cycles

We consider the pattern detection problem in graphs: given a constant size pattern graph H and a host graph G, determine whether G contains a subgraph isomorphic to H. We present the following new improved upper and lower bounds: We prove that if a pattern H contains a k-clique subgraph, then detecting whether an n node host graph contains a not necessarily induced copy of H requires at least the time for detecting whether an n node graph contains a k-clique. The previous result of this nature required that H contains a k-clique which is disjoint from all other k-cliques of H. We show that if the famous Hadwiger conjecture from graph theory is true, then detecting whether an n node host graph contains a not necessarily induced copy of a pattern with chromatic number t requires at least the time for detecting whether an n node graph contains a t-clique. This implies that: (a) under Hadwiger’s conjecture for every k-node pattern H, finding an induced copy of H requires at least the time of √k-clique detection and size ω(n√k/4) for any constant depth circuit, and (b) unconditionally, detecting an induced copy of a random G(k,p) pattern w.h. p. requires at least the time of Θ(k/logk)-clique detection, and hence also at least size nΩ(k/logk) for circuits of constant depth. We show that for every k, there exists a k-node pattern that contains a k−1-clique and that can be detected as an induced subgraph in n node graphs in the best known running time for k−1-Clique detection. Previously such a result was only known for infinitely many k. Finally, we consider the case when the pattern is a directed cycle on k nodes, and we would like to detect whether a directed m-edge graph G contains a k-Cycle as a not necessarily induced subgraph. We resolve a 14 year old conjecture of [Yuster-Zwick SODA’04] on the complexity of k-Cycle detection by giving a tight analysis of their k-Cycle algorithm. Our analysis improves the best bounds for k-Cycle detection in directed graphs, for all k>5.
QED Phenomena in an Ultrastrong Magnetic Field. II. Electron–Positron Scattering, e±–Ion Scattering, and Relativistic Bremsstrahlung

This paper continues the approach of Kostenko & Thompson to calculating quantum electrodynamic processes in the ultrastrong magnetic field near some neutron stars, such as magnetars or merging binary neutron stars. Here we consider electron–positron scattering, the Coulomb scattering of electrons and positrons off ions, and relativistic e±–ion bremsstrahlung. The evaluation of differential and total cross sections simplifies considerably when the magnetic field lies in the range 103BQ ≫ B ≫ BQ, where BQ ≡ m2/e = 4.4 × 1013 G. Then, relativistic motion of e± is possible even when restricted to the lowest Landau state. Accurate results for differential and total cross sections are obtained by truncating the sum over intermediate-state Landau levels and otherwise disregarding terms inversely proportional to the magnetic field, which are complicated enough to have inhibited previous attempts to calculate magnetic electron–positron scattering and relativistic bremsstrahlung. A quantitative account is made of the effects of Debye screening.
Extreme Image Compression via Multiscale Autoencoders With Generative Adversarial Optimization

We propose a MultiScale AutoEncoder (MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate. Our method leverages the “priors” at different resolution scale to improve the compression efficiency, and also employs the generative adversarial network (GAN) with multiscale discriminators to perform the end-to-end trainable rate-distortion optimization. We compare the perceptual quality of our reconstructions with traditional compression algorithms using High-Efficiency Video Coding (HEVC) based Intra Profile and JPEG2000 on the public Cityscapes and ADE20K datasets, demonstrating the significant subjective quality improvement.
Blockchain Technology in Supply Chain Management: An Application Perspective

Given the hype around the cryptocurrency Bitcoin, blockchain technology (BCT) has also received considerable attention outside the ﬁnancial sector. Multiple applications of BCT in supply chain management (SCM) are discussed in business practice and there is increasing interest in this topic within the academic community. In this paper, we intend to combine these two perspectives on BCT in SCM to summarize a current state of the art and to derive avenues for further research. For this purpose, a comprehensive framework of use case clusters of BCT in SCM is developed according to the distinctive features of BCT. The framework is used to analyze 53 applications of BCT in SCM which are derived from a systematic literature review and a secondary dataset of blockchain-driven innovations in SCM. We identify ﬁve emerging use case clusters of BCT in SCM which clearly extend the scope beyond frequently mentioned applications such as product tracking and tracing.
Materiality Maps - Process Mining Data Visualization for Financial Audits

Financial audits are a safeguard to prevent the distribution of false information which could detrimentally influence stakeholder decisions. The increasing integration of computer technology for the processing of business transactions create new challenges for auditors who have to deal with increasingly large and complex data. Process mining can be used as a novel Big Data analysis technique to support auditors in this context. A challenge for using this type of technique is the representation of analyzed data. Process mining algorithms usually discover large sets of mined process variants. This study introduces a new approach to visualize process mining results specifically for financial audits in an aggregate manner as materiality maps. Such maps provide an overview about the processes identified in an organization and indicate which business processes should be considered for audit purposes. They reduce an auditor’s information overload and help to improve decision making in the audit process.
Invariant manifolds in stratified turbulence

We present a reduced system of 7 ordinary differential equations that captures the time evolution of spatial gradients of the velocity and the temperature in fluid elements of stratified turbulent flows. We show the existence of invariant manifolds (further reducing the system dimensionality), and compare the results with data stemming from direct numerical simulations of the full incompressible Boussinesq equations in the stably stratified case. Numerical results accumulate over the invariant anifolds of the reduced system, indicating the system lives at the brink of an instability. Finally, we study the stability of the reduced system, and show that it is compatible with recent observations in stratified turbulence of non-monotonic dependence of intermittency with stratification.
An Empirical Analysis on Determinants of Accounting Internal Control Effectiveness: Evidence from Emerging Market

Prior research mentioned internal control as a useful management alternative to improve enterprises’ operation performance and information quality. According to Trenery (2013) internal control can be fundamentally divided into two functions of operating and accounting internal control. The paper aims to identify the determinants of accounting internal control effectiveness that are addressed in existing literature review. Primary data was collected from samples of 109 members of board of directors and chief accountants in Vietnam by direct interview and email survey. The data was analyzed using exploratory factor analysis of SPSS software to illustrate the potential factors of accounting internal control effectiveness. The result shows that there are several determinants of accounting internal control effectiveness such as: good financial ratio, efficient resources deployed, errors found in the financial reports that are convergent into three specific groups of factors, namely: effectiveness and efficiency of accounting activities, reliability of financial reporting and compliance with law and accounting regulations. Based on the research findings, some suggestions are given to enterprises in Vietnam and other emerging markets to improve the effectiveness of accounting internal control.
How May I Help You? - State of the Art and Open Research Questions for Chatbots at the Digital Workplace

Chatbots become quite hyped in recent times as they can provide an intuitive and easy-to-use natural language human-computer interface. Nevertheless, they are not yet widespread in enterprises. Corresponding application areas for collaboration at digital workplaces are lacking and prior research contributions on this topic are limited. In this research paper, we aim at surveying the state of the art as well as showing future research topics. Thus, we conducted a structured literature review and showed that only few first research contributions exist. We also outline current potentials and objectives of chatbot applications. In the discussion of the results of our structured literature review, we show that research gaps are present. To tackle the research gaps, we derive open research questions.
The Role of Institutional Work in Platform Establishment: An Investigation of Digital Innovation Practices for Creating, Maintaining and Disrupting Institutions

While the significance of digital platforms for contemporary organizations has been demonstrated both in theory and practice, how they emerge is less understood. We argue that one source of digital platform emergence is the recombinatorial innovation processes individuals enact in organizational work practices. We draw on the theory of institutional work to empirically examine how innovation processes led to the emergence of a digital platform in the Swedish transport administration. We find that actors engage in work aimed at creating, maintaining and disrupting socio-technical structures. These work practices involve exploring the possibilities of specific digital resources, their combinatorial options, and how new resources can be generated. The analysis contributes to the literature on digital platforms by (1) demonstrating the role of digital malleability in bypassing institutional resistance, (2) identifying temporal patterns and dependencies of activities, and (3) detecting distinct emphasis in types of institutional work.
Vacuum energy in the effective field theory of general relativity. II. Inclusion of fermions and a comment on the QCD contribution

In the framework of an effective field theory of general relativity a model of scalar and vector bosons interacting with the metric field is considered. It is shown in the framework of a two-loop order calculation that for the cosmological constant term which is fixed by the condition of vanishing vacuum energy the graviton remains massless and there exists a self-consistent effective field theory of general relativity coupled to matter fields defined on a flat Minkowski background. This result is obtained under the assumption that the energy-momentum tensor of the gravitational field is given by the pseudotensor of Landau-Lifshitz's classic textbook. Implications for the cosmological constant problem are also briefly discussed.
Microscopic characteristics and tomography scheme of the local Chern marker

The concept of the local Chern marker has gained a lot of attention especially in the field of ultracold quantum gases in optical lattices and artificial gauge fields. We investigate in further detail the microscopic real-space characteristics of the local Chern marker for the two-band Harper- Hofstadter-Hatsugai model and propose a tomographic scheme for the experimental detection of an approximate local Chern marker neglecting higher orders.
Scalable Change Retrieval Using Deep 3D Neural Codes

We present a novel scalable framework for image change detection (ICD) from an on-board 3D imagery system. We argue that existing ICD systems are constrained by the time required to align a given query image with individual reference image coordinates. We utilize an invariant coordinate system (ICS) to replace the time-consuming image alignment with an offline pre-processing procedure. Our key contribution is an extension of the traditional image comparison-based ICD tasks to setups of the image retrieval (IR) task. We replace each component of the 3D ICD system, i.e., (1) image modeling, (2) image alignment, and (3) image differencing, with significantly efficient variants from the bag-of-words (BoW) IR paradigm. Further, we train a deep 3D feature extractor in an unsupervised manner using an unsupervised Siamese network and automatically collected training data. We conducted experiments on a challenging cross-season ICD task using a publicly available dataset and thereby validate the efficacy of the proposed approach.
Is patchy reionization an obstacle in detecting the primordial gravitational wave signal?

The large-scale cosmic microwave background (CMB) B-mode polarization is the direct probe to the low-frequency primordial gravitational wave signal. However, unambiguous measurement of this signal requires a precise understanding of the possible contamination. One such potential contamination arises from the patchiness in the spatial distribution of free electrons during the epoch of reionization. We estimate the B-mode power spectrum due to patchy reionization using a combination of photon-conserving seminumerical simulation and analytical calculation, and compare its amplitude with the primordial B-mode signal. For a reionization history which is in agreement with several latest observations, we find that a stronger secondary B-mode polarization signal is produced when the reionization is driven by the sources in massive haloes and its amplitude can be comparable to the recombination bump for tensor to scalar ratio (r) ≲ 5 × 10^−4. If contamination from patchy reionization is neglected in the analysis of B-mode polarization data, then for the models of reionization considered in this analysis, we find a maximum bias of about |$30{{\ \rm per\ cent}}$| in the value of |$r=\, 10^{-3}$| when spatial modes between l ∈ [50, 200] are used with a delensing efficiency of |$50{{\ \rm per\ cent}}$|⁠. The inferred bias from patchy reionization is not a severe issue for the upcoming ground-based CMB experiment Simons Observatory, but can be a potential source of confusion for proposed CMB experiments which target to detect the value of r < 10^−3. However, this obstacle can be removed by utilizing the difference in the shape of the power spectrum from the primordial signal.
Exploring the Impact of Coordination in Human–Agent Teams

Teaming permits cognitively complex work to be rapidly executed by multiple entities. As artificial agents (AAs) participate in increasingly complex cognitive work, they hold the promise of moving beyond tools to becoming effective members of human–agent teams. Coordination has been identified as the critical process that enables effective teams and is required to achieve the vision of tightly coupled teams of humans and AAs. This paper characterizes coordination on the axes of types, content, and cost. This characterization is grounded in the human and AA literature and is evaluated to extract design implications for human–agent teams. These design implications are the mechanisms, moderators, and models employed within human–agent teams, which illuminate potential AA design improvements to support coordination.