Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of XBRL adoption on financial reporting quality: a global evidence

Purpose This paper aims to examine the effect of eXtensible Business Reporting Language (XBRL) adoption on financial reporting quality at the country-level (developing and developed countries). Design/methodology/approach This study uses data from 98 developed and developing countries between 2005 and 2018. This study collected data from various sources such as the World Economic Forum, World Development Indicators, World Governance Indicators and XBRL website. Findings The results show that XBRL is associated with an increased financial reporting quality. However, the relationship is stronger in developing countries than in developed countries. This study also finds that the results remain the same after accounting for years of XBRL experience and the effect of accounting globalisation. The results are consistent with the assumption that XBRL-formatted financial statements improve information efficiency through increased searching efficiency, quality of display and comparability. The results are robust to alternative econometric modifications such as controlling for country, year effects and endogeneity. Practical implications The results can potentially assist the XBRL promoters and regulators in expeditiously assessing the benefits of XBRL and advocating its adoption by many countries. The findings offer more motivations for regulators around the world to mandate this new filing standard format. Originality/value This study contributes to the literature by providing empirical evidence on the consequences of XBRL at the country level. This study provides evidence on an important question of whether the XBRL, new information technology in the accounting field, can play a useful role in improving financial reporting.
Control Strategies of a Smart Topology of EVs Charging Station Based Grid Tied RES-Battery

In this paper, control strategies of a smart topology of EV charging station based on grid tied renewable energy sources and battery are designed and analyzed. The renewable energy sources (RES) that power EV charging station are composed by photovoltaic system and wind energy conversion system (WECS). Thus, a dc/dc boost converter based on a maximum power tracking controller is connected to the photovoltaic array, the WECS is tied to the DC link through a single ended primary inductor converter (SEPIC), and four charging points are associated to four dc/dc converters in order to secure a large scale of power to charge electric vehicles battery. However, the PV/WECS is tied both to the grid and to the battery storage buffer (BSB) of the charging station via a three-phase bidirectional inverter and a bidirectional dc/dc converter respectively. The aim of this work is to achieve an improved power management approach, that consists of an optimization algorithm set to mind the gap of energy deficiencies of a multi sources system, for instance an unfavorable weather conditions for RES, an overloading phenomena of the grid and a limited capacity of the BSB. Simulation results in Matlab/Simulink have shown the effectiveness of the proposed power management strategy via seven operating modes.
Accurate Low-Frequency Approximation for Wires Within a Conducting Half-Space

The most popular approximate models for the analysis of vertical and horizontal wires within a conducting half-space are based on image theory. However, their accuracy is often confined within some low-frequency (LF) range. Such models are often based on the integral equation technique with the so-called “traditional” choice of potentials. In this letter, a new LF approximation is derived from an alternative choice of potentials, i.e., “formulation B. ” The accuracy of the proposed approximation and the traditional image approximations is evaluated by comparison with the electromagnetic simulation software FEKO for different wire geometries and different values of earth resistivity in a frequency range up to 10 MHz. It is shown that the new LF approximation is consistently more accurate in all analyzed cases, which widens its applicable frequency range in relation to the image approximations based on the traditional choice of potentials.
Multi-Agent Reinforcement Learning with Pointer Networks for Network Slicing in Cellular Systems

In this paper, we present a multi-agent deep reinforcement learning (deep RL) framework for network slicing in a dynamic environment with multiple base stations. We first introduce the wireless network virtualization (WNV) and the interference channel model. Then, we formulate the network slicing problem in the dynamic environment in which fading varies, users have mobility, and requests are randomly generated over time. Subsequently, we propose a deep RL framework with multiple actors and centralized critic (MACC) to maximize the reward over all base stations instead of pursuing local optimization. The actors are implemented as pointer networks to fit the varying dimension of input. Finally, we evaluate the performance of the proposed deep RL algorithm via simulations to demonstrate its effectiveness.
Stochastic analysis of fatigue of concrete bridges

Abstract A novel method is proposed in this work for the assessment of the remaining fatigue life and fatigue reliability of concrete bridges subjected to random loads. The fatigue reliability of a bridge is a function of the fatigue damage accumulation; a stochastic fatigue damage model (SFDM) with physical mechanism is introduced for deriving the fatigue damage process. In order to implement the probabilistic analysis, based on the probability density evolution method (PDEM), the generalised density evolution equation (GDEE) for the remaining fatigue life is developed. Finally, a prestressed concrete continuous beam bridge located in China is illustrated. The random fatigue load acting on the bridge is modelled as the compound Poisson process, and the simulation of the random load uses the stochastic harmonic function (SHF) method. To simplify the reliability analysis, an equivalent constant-amplitude (ECA) load process is introduced based on energy equivalence. By employing SFDM, the finite element analysis of the bridge under the fatigue loading is performed. Then, the fatigue damage accumulation process of the bridge under the fatigue loading is obtained. Through solving the probability density evolution equation for the remaining fatigue life, the probability density functions (PDFs) of the remaining fatigue life evolving with time is obtained. The fatigue reliability is then calculated by integrating the PDF of the corresponding remaining life.
A Historical Experience Surrogate Model Assisted Particle Swarm Optimization for Expensive Black-box Problems

This paper proposed a new historical experience surrogate model assisted particle swarm optimization method. This method extends the particle swarm optimization by adding new surrogate-based phase. In the classic phase, the particle swarm optimization runs the same way as the original algorithm, and the real function value evaluated are collected into the global database. In the surrogate phase, sub-swarms are generated following the distribution of the history data and evaluated by the surrogate model(s). The purpose of the surrogate phase is to explore the possible better solutions of the searching history. Also, the surrogate model(s) have the ability of accelerating the intelligence algorithms. Nevertheless, considering the time complexity of training and evaluating the surrogate model(s), the original problem should be expensive to evaluate or driven by data, which are same as many real-world problems.
Acute Generalized Exanthematous Pustulosis following SARS-CoV-2 Virus: Remdesivir as a Suspected Culprit

Acute generalized exanthematous pustulosis (AGEP) is an exanthematous condition, predominantly occurring as a result of drug reactions. We, hereby, present the first case of AGEP following treatment with remdesivir in a patient with COVID-19, without hydroxychloroquine use, which serves as a reminder to consider remdesivir as a possible causative agent when dealing with AGEP presentation in COVID patients.
A Joint Optimization of Sensor Activation and Mobile Charging Scheduling in Industrial Wireless Rechargeable Sensor Networks

In this paper, a joint optimization of sensor activation and mobile charging scheduling for industrial wireless rechargeable sensor networks (IWRSNs) is studied. In the considered model, an optimal sensor set is selected to collaboratively execute a bundle of heterogeneous tasks of production-line monitoring, meeting the quality-of-monitoring (QoM) of each individual task. There is a mobile charger vehicle (MCV) which is scheduled for recharging sensors before their charging deadlines (i.e., the time instant of running out of their energy). Our goal is to jointly optimize the sensor activation and MCV scheduling for minimizing the energy consumption of the entire IWRSN, subjected to tasks’ QoM requirements, sensor charging deadlines and the energy capacity of the MCV. Unfortunately, solving this problem is non-trivial, because it involves solving two tightly coupled NP-hard problems. To address this issue, we design an efficient algorithm integrating deep reinforcement learning and marginal product based approximation algorithm. Simulations are conducted to evaluate the performance of the proposed solution and demonstrate its superiority over counterparts.
Deep Learning-Based Cooperative CSI Feedback via Multiple Receiving Antennas in Massive MIMO

Deep learning (DL)-based channel state information (CSI) feedback can provide high downlink CSI reconstruction accuracy for massive multiple-input multiple-output (MIMO) systems. However, existing DL-based CSI feedback methods assume that a single receiving antenna is deployed at the user equipment side so that they ignore the CSI correlation among multiple receiving antennas. In this paper, we propose a (m)ultiple (r)eceiving antennas cooperative CSI feedback network, named MRNet, with 3-dimensional convolutional layers to extract the correlation features among different receiving antennas. We further propose a layer reuse scheme for the improvement of storage efficiency of MRNet in the feedback system. Simulation results show that, via the cooperative CSI feedback of multiple receiving antennas, MRNet outperforms DL-based single receiving antenna CSI feedback approaches by at most 5.27dB in terms of the reconstruction accuracy. Moreover, MRNet is applicable to massive MIMO systems with different numbers of receiving antennas while the number of trainable parameters of the network is unchanged. The open source codes of MRNet are available at https://github.com/ch28/MRNet
Proactive Migration for Dynamic Computation Load in Edge Computing

The advent of the Internet-of-Things (IoT), which streams a wide range of computation-intensive applications with strict Quality of Service (QoS) requirements, has caused a paradigm shift from cloud computing to edge computing. Edge computing can drastically reduce latency and improve QoS. However, various dynamic changes can affect service continuity, thus requiring service migration. The dynamic computation load is one of the changes that are typically overlooked in service migration. In this paper, we propose the Dynamic Load-based Proactive Migration (DLPM) scheme. DLPM adopts a finite-state machine (FSM) that models the dynamic computation load, and proactively migrates computation tasks based on the associated transition probabilities. We formulate the service migration problem as an integer linear programming (ILP) optimization problem that aims to minimize the delay. We provide an analytical solution to the optimization problem using the KKT conditions and Lagrangian analysis. Performance evaluation shows that DLPM yields significant improvements in terms of delay and number of migrations compared to the reactive migration approach.
A Partial Homogenization Result for Nonconvex Viscous Hamilton-Jacobi Equations

We provide a general result concerning the homogenization of nonconvex viscous Hamilton-Jacobi equations in the stationary, ergodic setting. In particular, we show that homogenization occurs for a non-empty set of points within every level set of the effective Hamiltonian, and for every point in the minimal level set of the effective Hamiltonian. In addition, these methods provide a new proof of homogenization, in full, for convex equations and, for a class of level-set convex equations. Finally, we prove that the question of homogenization for first order equations reduces to the case that the nonconvexity of the Hamiltonian is localized in the gradient variable.
Beam-Pattern Assisted Low-Complexity Beam Alignment for Fixed Wireless mmWave xHaul

This paper presents the design of two-stage beam alignment methods employing a hybrid analog-digital antenna array and exploiting the beam pattern in a point-to-point millimeter-wave (mmWave) radio for mmWave massive multiple-input multiple-output systems. We investigate an antenna deactivating approach that generates wider beams at the coarse alignment stage and exploit the theoretical beam pattern at the fine alignment stage. Our numerical results show that the proposed two-stage methods can achieve a better beam alignment than existing exhaustive methods and avail measurements/complexity reductions by tuning key parameters governing the alignment performance.
Determinants of evolving responsible tourism behavior: Evidences from supply chain

Abstract Aim: The purpose of the study was to identify and investigate the determinants of “responsible tourism behavior” with a view to suggest policy implications contextualizing Pakistan. Research Methods: The quantitative research was structured to determine the prevailing levels of tourism behavior and its corresponding determinants as observed along the continuum between irresponsible and responsible tourism. Data was collected from 700 positively retrieved questionnaires out of the 800 self-administered questionnaire amongst respondents from the tourism stakeholders. The reliability and validity were checked through Cronbach-Alpha and the CFA model followed by correlation analyses verifying the set of hypotheses. Findings: The study determined that quality of responsible behavior is dependent upon: quality of institutional policies, purpose built environmental friendly infrastructure, tourism carrying capacity, community involvement, interconnected network of diverse tourism support services, destination-specific promotion and growth strategies, development of human capital, and satisfaction of tourists across tourism supply chain. The study found negative footprints of tourism behavior along the destinations located close to the urban centers, whereas, remote destinations were found positively sustaining their environmental capitals. Implications: The study implications suggested measures to prevent negative footprints of tourism influx, regenerate the natural capital and spread socio-economic benefits across communities and destinations.
Traffic-Weighted Availability-Guaranteed Network Slice Composition with VNF Replications

In this work, we consider the network slice composition problem for Service Function Chains (SFCs), which addresses the issue of allocating bandwidth and VNF resources in a way that guarantees the availability of the SFC while minimizing cost. For the purpose of satisfying the availability requirement of the SFC, we adapt a traffic-weighted availability model which ensures that the long-term fraction of traffic supported by the slice topology remains above a desired threshold. We propose a method for composing a single or multi-path slice topology and for properly dimensioning VNF replicas and bandwidth on the slice paths. Through simulations, we show that our proposed algorithm can reduce the total cost of establishment compared to a dedicated protection approach in 5G networks.
Topics in Intersection Graph Theory

Preface 1. Intersection Graphs. Basic Concepts Intersection Classes Parsimonious Set Representations Clique Graphs Line Graphs Hypergraphs 2. Chordal Graphs. Chordal Graphs as Intersection Graphs Other Characterizations Tree Hypergraphs Some Applications of Chordal Graphs Split Graphs 3. Interval Graphs. Definitions and Characterizations Interval Hypergraphs Proper Interval Graphs Some Applications of Interval Graphs 4. Competition Graphs. Neighborhood Graphs Competition Graphs Interval Competition Graphs Upper Bound Graphs 5. Threshold Graphs. Definitions and Characterizations Threshold Graphs as Intersection Graphs Difference Graphs and Ferrers Digraphs Some Applications of Threshold Graphs 6. Other Kinds of Intersection. p-Intersection Graphs Intersection Multigraphs and Pseudographs Tolerance Intersection Graphs 7. Guide to Related Topics. Assorted Geometric Intersection Graphs Bipartite Intersection Graphs, Intersection Digraphs, and Catch (Di)Graphs Chordal Bipartite and Weakly Chordal Graphs Circle Graphs and Permutation Graphs Clique Graphs of Chordal Graphs and Clique-Helly Graphs Containment, Comparability, Cocomparability, and Asteroidal Triple-Free Graphs Infinite Intersection Graphs Miscellaneous Topics P4-Free Chordal Graphs and Cographs Powers of Intersection Graphs Sphere-of-Influence Graphs Strongly Chordal Graphs Bibliography Index.
Wideband microstrip magnetoelectric dipole antenna with stripline aperture-coupled excitation

A novel wideband microstrip magnetoelectric (ME) dipole antenna excited by a stripline aperture-coupled feeding structure is proposed and demonstrated. An antenna prototype is fabricated with low-cost standard printed circuit board process on three substrates and tested. Measured results show that an impedance bandwidth for voltage standing wave ratio (VSWR) <; 2 is ~42% (10.2-15.6 GHz), and a measured boresight gain is ~7.8 ± 0.7 dBi. Almost stable and symmetrical unidirectional radiation patterns with low in cross-polarization and backward radiation are obtained over the entire operating frequency band. By employing the proposed radiating element, two types of cavity (one is a square cavity, the other is a circular cavity) are introduced for enhancing the antenna gain and investigated. After analysis, a better one is chosen to be fabricated and measured. A measured impedance bandwidth for VSWR <; 2 is ~45% (10.1-15.9GHz), and a measured boresight gain is ~8.9 ± 0.5 dBi. The measured average gain is ~1.1 dBi larger than that of the radiating element. The measured radiation patterns, cross-polarization levels and half power beam width are almost the same as that of the radiating element except that the measured front-to-back ratios are improved several decibels.
Robust hybrid observer design based on reconstructability conditions for piecewise linear systems

In this article, a robust hybrid observer is proposed to estimate the state of piecewise linear systems (PWL) that fulfill the reconstructability conditions. The design of this observer uses a high order sliding mode differentiator and is based on the reconstructability conditions for the discrete state of PWL systems. Additionally, the design takes into account the case when the differentiator output does not converge exactly to the actual derivatives of the system output. This could be due to the system output being affected by unknown but bounded perturbations or the differentiator being implemented on a digital device. The applicability of the results is illustrated by a numerical example.
Energy-based Proportional Fairness for Task Offloading and Resource Allocation in Edge Computing

By executing offloaded tasks from mobile users, edge computing augments mobile devices with computing/communications resources from edge nodes (ENs), enabling new services/applications (e.g., real-time gaming, virtual/augmented reality). However, despite being more resourceful than mobile devices, allocating ENs’ computing/communications resources to given favorable sets of users may block other devices from their service. This is often the case for most existing task offloading and resource allocation approaches that only aim to maximize the network social welfare (e.g., minimizing the total energy consumption) but not consider the computing/battery status of each mobile device. This work develops a proportional fair task offloading and resource allocation framework for a multi-layer cooperative edge computing network to serve all user equipment (UEs) while considering both their service requirements and individual energy/battery levels. The resulting optimization involves both binary (offloading decisions) and real variables (resource allocations), making it NP-hard. To tackle it, we leverage the fact that the relaxed problem is convex and propose a distributed algorithm, namely the dynamic branchand-bound Benders decomposition (DBBD). DBBD decomposes the original problem into a master problem (MP) for the offloading decision and subproblems (SPs) for resource allocation. The SPs can either find their closed-form solutions or be solved in parallel at ENs, thus help reduce the complexity. The numerical results show that the DBBD returns the optimal solution of the problem maximizing the fairness between UEs. The DBBD has higher fairness indexes, i.e., Jain’s index and min-max ratio, in comparing with the existing ones that minimize the total consumed energy.
Real-Time Trajectory Control of Deterministically Produced Ions

The major challenge to improve deterministic single ion sources is to control the position and momentum of each ion. Based on the extra information given by the electron created in a photoionization process, the trajectory of the correlated ion can be controlled using a fast real time feedback system. In this paper, we report on a proof-of-principle experiment that demonstrates the performances of this feedback control with individual cesium ions. The produced electron is detected with a time and position sensitive detector, whose information are used to quickly infer the position of the corresponding ion. Then the feedback system drives the ion trajectory through steering plates. Individual ion can thus be send to any dedicated location. This enables us to perform deterministic patterning and reach a factor 1000 improvement in spot area. The single ion feedback control is versatile and can be applied to different kind of ion sources. It provides a powerful tool to optimize the ion beam and offers new area for quantum systems and applications of materials science.