Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analysis of Leader's Impression Management and Employees' Emotional Attachment

Researchers have found that impression management is related to performance appraisal, emotional attachment, the relationship between superior and subordinates, management efficiency and organizational ethics. However, it is still worth to explore how a leader's impression management strategy influences employees' emotional attachment. For this reason, this paper adopts the method of a questionnaire survey and uses the correlation and regression analysis method to carry out hypothesis testing on 418 valid questionnaires that were collected. The result shows that the impression management of female leader has the significant influence on the leader's charisma and the employees' emotional attachment. The leader's charisma plays the part of a mediating role in the relationship between impression management and emotional attachment.
A Conceptual Model of Tactile Processing across Body Features of Size, Shape, Side, and Spatial Location

The processing of touch depends of multiple factors, such as the properties of the skin and type of receptors stimulated, as well as features related to the actual configuration and shape of the body itself. A large body of research has focused on the effect that the nature of the stimuli has on tactile processing. Less research, however, has focused on features beyond the nature of the touch. In this review, we focus on some features related to the body that have been investigated for less time and in a more fragmented way. These include the symmetrical quality of the two sides of the body, the postural configuration of the body, as well as the size and shape of different body parts. We will describe what we consider three key aspects: (1) how and at which stages tactile information is integrated between different parts and sides of the body; (2) how tactile signals are integrated with online and stored postural configurations of the body, regarded as priors; (3) and how tactile signals are integrated with representations of body size and shape. Here, we describe how these different body dimensions affect integration of tactile information as well as guide motor behavior by integrating them in a single model of tactile processing. We review a wide range of neuropsychological, neuroimaging, and neurophysiological data and suggest a revised model of tactile integration on the basis of the one proposed previously by Longo et al.
Stability Enhancement of Power Systems With High DFIG-Wind Turbine Penetration via Virtual Inertia Planning

Virtual inertia has been extensively implemented in power systems with distributed energy resources, especially wind energy conversion systems. This paper proposes an optimal virtual inertia planning strategy for stability enhancement of power system, which is penetrated with large volume of renewable resources provided by doubly fed induction generators (DFIGs). The stability of DFIG is first analyzed and the concept of critical frequency drop is proposed. Moreover, the intersection area between the two predefined operation curves of DFIG is defined as the stability margin and it is calculated in the form of a function of local virtual inertia. Subsequently, a virtual inertia planning strategy is proposed, wherein a coherency index that considers the homogeneity of the stability margin at each node is presented, followed by a nonconvex optimization problem. The problem is simplified with the Lyapunov function method and resolved. Two case studies are conducted to verify the effectiveness and performance of the proposed approach: a 12-bus system and the IEEE-118 bus system. Both cases show that with the proposed approach, the system stability margin coherency level is enhanced and the general stability is promoted.
Resource-efficient and Automated Image-based Indoor Localization

Image-based indoor localization has aroused much interest recently because it requires no infrastructure support. Previous approaches on image-based localization, due to their computation and storage requirements, often process queries at servers. This does not scale well, incurs round-trip delay, and requires constant network connectivity. Many also require users to manually confirm the shortlisted matched landmarks, which is inconvenient, slow, and prone to selection error. To overcome these limitations, we propose a highly automated (in terms of image confirmation after taking images) image-based localization algorithm (HAIL), distributed in mobile devices. HAIL achieves resource efficiency (in terms of storage and processing) by keeping only distinguishing visual features for each landmark, and employing the efficient k-d tree to search for features. It further utilizes motion sensors and map constraints to enhance the localization accuracy without user operation. We have implemented HAIL on Android platforms and conducted extensive experiments in a food plaza and a premium shopping mall. Experimental results show that it achieves much higher localization accuracy (reducing the localization error by more than 20%) and computation efficiency (by more than 40% in time) as compared with the state-of-the-art approaches.
Evaluation of the Rotor Eddy-Current Losses in High-Speed PMSMs With a Shielding Cylinder for Different Stator Sources

A continuous demand for more efficient and more compact drives is pushing the popularity of high-speed permanent magnet synchronous machines (PMSMs). However, high rotational speeds and extreme power densities imply that an appropriate cooling of the rotor may be difficult. This is all the more important because of the risk of demagnetization when permanent magnets are operated at high temperatures. Therefore, it is paramount to reduce the losses in the rotor of high-speed machines as much as possible. One technique to reduce the eddy-current losses is introducing a shielding cylinder, i.e., a conductive sleeve that is wrapped around the magnets. However, when badly designed, such a shielding cylinder may increase, rather than decrease, the losses. Therefore, an in-depth study of the effect of the shielding cylinder on the eddy-current losses in high-speed PMSMs is required. By studying how the eddy-current losses are affected by the shielding cylinder’s thickness and its conductivity, this paper aims at providing more insight in how the eddy-current losses can be reduced. Moreover, the study of the eddy-current losses is repeated for different stator sources to evaluate the importance of accounting for the actual control strategy during the machine’s design.
An Energy-Efficient 3.7-nV/ $\surd$ Hz Bridge Readout IC With a Stable Bridge Offset Compensation Scheme

This paper describes an energy-efficient bridge readout IC (ROIC), which consists of a capacitively coupled instrumentation amplifier (CCIA) that drives a continuous-time delta–sigma modulator (CT<inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula>). By exploiting the CCIA’s ability to block dc common-mode voltages, the bridge’s bias voltage may exceed the ROIC’s supply voltage, allowing these voltages to be independently optimized. Since bridge output is typically much smaller than bridge offset, a digital to analog converter (DAC) is used to compensate this offset before amplification and thus increase the CCIA’s useful dynamic range. Bridge loading is reduced by using a dual-path positive feedback scheme to boost the CCIA’s input impedance. Furthermore, the CCIA’s output is gated to avoid digitizing its output spikes, which would otherwise limit the ROIC’s linearity and stability. The ROIC achieves an input-referred noise density of 3.7 nV/<inline-formula> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz, a noise efficiency factor (NEF) of 5, and a power efficiency factor (PEF) of 44, which both represent the state of the art. A pressure sensing system, built with the ROIC and a differential pressure sensor (AC4010), achieves 10.1-mPa (<inline-formula> <tex-math notation="LaTeX">$1\sigma$ </tex-math></inline-formula>) resolution in a 0.5-ms conversion time. The ROIC dissipates about 30% of the system’s power dissipation and contributes about 6% of its noise power. To reduce the sensor’s offset drift, a temperature compensation scheme based on an external reference resistor is used. After a two-point calibration, this scheme reduces bridge offset drift by <inline-formula> <tex-math notation="LaTeX">$80\times $ </tex-math></inline-formula> over a 50 °C range.
Deletion of D-Lactate Dehydrogenase A in Neisseria meningitidis Promotes Biofilm Formation Through Increased Autolysis and Extracellular DNA Release

Neisseria meningitidis is a Gram-negative bacterium that asymptomatically colonizes the human nasopharyngeal mucosa. Pilus-mediated initial adherence of N. meningitidis to the epithelial mucosa is followed by the formation of three-dimensional aggregates, called microcolonies. Dispersal from microcolonies contributes to the transmission of N. meningitidis across the epithelial mucosa. We have recently discovered that environmental concentrations of host cell-derived lactate influences N. meningitidis microcolony dispersal. Here, we examined the ability of N. meningitidis mutants deficient in lactate metabolism to form biofilms. A lactate dehydrogenease A (ldhA) mutant had an increased level of biofilm formation. Deletion of ldhA increased the N. meningitidis cell surface hydrophobicity and aggregation. In this study, we used FAM20, which belongs to clonal complex ST-11 that forms biofilms independently of extracellular DNA (eDNA). However, treatment with DNase I abolished the increased biofilm formation and aggregation of the ldhA-deficient mutant, suggesting a critical role for eDNA. Compared to wild-type, the ldhA-deficient mutant exhibited an increased autolytic rate, with significant increases in the eDNA concentrations in the culture supernatants and in biofilms. Within the ldhA mutant biofilm, the transcription levels of the capsule, pilus, and bacterial lysis genes were downregulated, while norB, which is associated with anaerobic respiration, was upregulated. These findings suggest that the absence of ldhA in N. meningitidis promotes biofilm formation and aggregation through autolysis-mediated DNA release.
Computational Model for Human 3D Shape Perception From a Single Specular Image

In natural conditions the human visual system can estimate the 3D shape of specular objects even from a single image. Although previous studies suggested that the orientation field plays a key role for 3D shape perception from specular reflections, its computational plausibility and possible mechanisms have not been investigated. In this study, to complement the orientation field information, we first add prior knowledge that objects are illuminated from above and utilize the vertical polarity of the intensity gradient. Then we construct an algorithm that incorporates these two image cues to estimate 3D shapes from a single specular image. We evaluated the algorithm with glossy and mirrored surfaces and found that 3D shapes can be recovered with a high correlation coefficient of around 0.8 with true surface shapes. Moreover, under a specific condition, the algorithm’s errors resembled those made by human observers. These findings show that the combination of the orientation field and the vertical polarity of the intensity gradient is computationally sufficient and probably reproduces essential representations used in human shape perception from specular reflections.
Code Authorship Attribution

Code authorship attribution is the process of identifying the author of a given code. With increasing numbers of malware and advanced mutation techniques, the authors of malware are creating a large number of malware variants. To better deal with this problem, methods for examining the authorship of malicious code are necessary. Code authorship attribution techniques can thus be utilized to identify and categorize the authors of malware. This information can help predict the types of tools and techniques that the author of a specific malware uses, as well as the manner in which the malware spreads and evolves. In this article, we present the first comprehensive review of research on code authorship attribution. The article summarizes various methods of authorship attribution and highlights challenges in the field.
A multi-subject serious game as an education tool: Analysis from the teacher’s perspective

In recent years, the constant technological development has created different forms of learning which aim to improve the education of students. The formal and centralized academy model, managed some years ago, has evolved allowing new forms of informal and centralized models in the students, breaking down the barriers of time and space reflected in the classroom. Knowledge can be accessed in different ways, depending on each person’s requirements and preferences. On the other hand, the characteristics of video games are opening up a place in the field of education: serious games. Due to their nature of competitiveness, sociabilization and training, they influence the increase of motivation during learning. This paper presents the design of a multi-subject serious game focused on different undergraduate careers, which seeks to improve academic performance. As part of its validation, prior to its use in students, teachers from different scientific areas are surveyed, obtaining satisfactory results.
The Effect of the Superlattice on the Magnetic and Transport Properties of Epitaxial Magnetite Thin Films

The surface structural, transport, and magnetic properties of superlattice films were examined, focusing on the effects of the superlattice periodicity of (Fe<sub>3</sub>O<sub>4</sub>/MgO) layers. The superlattice structures of (Fe<sub>3</sub>O<sub>4</sub>/MgO)<sub><italic>n</italic></sub> ultrathin films were fabricated using molecular-beam epitaxy on MgO(001) substrates, where n is the number of layers. It was observed that these oxide films have a single crystalline quality with the same orientation as the substrates for Fe<sub>3</sub>O<sub>4</sub> as thin as approximately three unit cells. The transport and magnetic results showed that the conductivity and magnetization of the superlattice increase as the number of (Fe<sub>3</sub>O<sub>4</sub>/MgO) layers is increased. Furthermore, a sharp Verwey transition was found in the (Fe<sub>3</sub>O<sub>4</sub>/MgO)<sub><italic>n</italic></sub> superlattices with thickness layer smaller than seen in an earlier study for a single or superlattice film. These results give the indication that Fe<sub>3</sub>O<sub>4</sub> superlattice ultrathin films have better properties than single layers of the same thickness. This artificial growth of superlattice ultrathin films will provide a useful method to realize novel properties for other complex oxide systems.
Consensusability of Discrete-Time Multiagent Systems With Communication Delay and Packet Dropouts

In this paper, we study the mean-square consensusability problem of discrete-time linear multiagent systems over directed networks with constant communication delay and packet dropouts. When the packet dropouts in different communication channels are identical, the consensusability problem is transformed into a simultaneous mean-square stabilization problem of systems with constant time delay and packet dropout. When the packet dropouts are nonidentical, we build the dynamics over edges based on the notion of compressed edge Laplacian for directed graphs to separate the packet dropouts from the network topology. Sufficient consensusability conditions are obtained for both cases in terms of the communication delay, the packet dropout rates, the communication network topology, and the agent dynamics.
Efficient beam allocation strategy for statistical beamforming-based massive multiple-input-multiple-output downlink systems

This study focuses on an efficient fairness aware beam allocation strategy which is based on user position approach. The proposed algorithm is efficient to cope with the effects of user position uncertainties and imperfect channel state information (CSI). It allocates beam to individual users based on directivity and user position with the objective of serving many users simultaneously. On the basis of the user position, individual data rate requirements are also considered in the proposed scheme which is very much important for practical systems thereby considering the fairness issue amongst the users. The proposed scheme is best suited for a system with covariance-based beamforming, where statistical CSI is highly preferred under high dense deployments and the channel coherence time is short. It also requires low average feedback load with less multiuser interference and is of low complexity compared with the searching-based beam allocation strategy. The simulation results are given to show the advantage of the proposed beam allocation on comparing with the prevailing schemes.
Effects of Post-Deposition Vacuum Annealing on the Piezoelectric Properties of AlScN Thin Films Sputtered on 200 Mm Production Wafers

Sc-doped AIN polycrystalline films are attractive active layers for high frequency (GHz range)acoustic resonators owing to the significant rise in the material piezoelectric activity with the increasing Sc content. A1ScN films are sputtered on 200 mm Si wafers using configurable cathode containing a variable number of embedded Sc pellets which allows controlling both the Sc content in the films and the composition homogeneity across the wafer. The method is implemented in an Endeavor-AT™ cluster tool from OEM Group adapted for sputtering on 200 mm wafers. The piezoelectric activity of the as-deposited A1ScN films appears to improve after a 15-minute post-deposition annealing at 600°C, leading to a 20% increase in the electromechanical coupling factor.
On The Integration of CT-Derived Features for Accurate Detection of Lung Cancer

Lung cancer is one of the unsafe maladies that reason enormous disease passing around the world. Early and accurate detection of lung cancer is the main conceivable approach to enhance patients’ survival rate. In this paper, we proposes a new framework for pulmonary nodule diagnosis using various features extracted from a single computed tomography (CT) scan. The proposed system fuse texture and shape features to get an accurate diagnosis for the extracted lung nodules. 3D Local Binary Pattern (LBP) and higher-order Markov Gibbs random field (MGRF) models are utilized to model the texture appearance due to their capability to give a precise description for the spatial non-uniformity in the texture of the nodules. Spherical Harmonic expansion and some basic geometric features are utilized to model the shape features due to their capability to give a full description of the shape complexity of the nodules. Finally, all the modeled features are fused and fed to a stacked autoencoder to differentiate between the malignant and benign nodules. Our framework is evaluated using 727 nodules which are selected from the Lung Image Database Consortium (LIDC) dataset, and achieved classification accuracy, sensitivity, and specificity of 92.66%, 95.70%, and 90.40% respectively.
Where You Are, Not What You See: The Impact of Learning Environment on Mind Wandering and Material Retention

Online lectures are an increasingly popular tool for learning, yet research on instructor visibility during an online lecture, and students' environmental settings, has not been well-explored. The current study addresses this gap in the literature by experimentally manipulating online display format and social learning settings to understand their influence on student learning and mind-wandering experiences. Results suggest that instructor visibility within an online lecture does not impact students' MW or retention performance. However, we found some evidence that students' social setting during viewing has an impact on MW (p = .05). Specifically, students who watched the lecture in a classroom with others reported significantly more MW than students who watched the lecture alone. Finally, social setting also moderated the negative relationship between MW and material retention. Our results demonstrate that learning experiences during online lectures can vary based on where, and with whom, the lectures are watched.
Haptic Inspection of Planetary Soils With Legged Robots

Planetary exploration robots encounter challenging terrain during operation. Vision-based approaches have failed to reliably predict soil characteristics in the past, making it necessary to probe the terrain tactilely. We present a robust, haptic inspection approach for a variety of fine, granular media, which are representative of Martian soil. In our approach, the robot uses one limb to perform an impact trajectory, while supporting the main body with the remaining three legs. The resulting vibration, which is recorded by sensors placed in the foot, is decomposed using the discrete wavelet transform and assigned a soil class by a support vector machine. We tested two foot designs and validated the robustness of this approach through the extensive use of an open-source dataset, which we recorded on a specially designed single-foot testbed. A remarkable overall classification accuracy of more than 98% could be achieved despite various introduced disturbances. The contributions of different sensors to the classification performance are evaluated. Finally, we test the generalization performance on unknown soils and show that the interaction behavior can be anticipated.
Face Reconstruction Using Non-Negative Matrix Factorization and ℓ1 Constrained Optimization

Non-negative matrix factorization (NMF) has received much attention recently, as many of the practical problems inhere the property of being non-negative naturally. NMF has applications in the field of parts-based learning of images, the analysis of hyper-spectral images, text and data mining, artificial neural networks, dimension reduction and many others. Due to the lack of information about the factors with the exception of the property of non-negativity, it is hard to find a global solution for an NMF problem. The problem itself has non-convexity, and finding the solution alternately may introduce convexity in the sub-problems. To find a feasible solution for a particular problem, some specific constraints have been introduced in the previously-developed methods. Approaches include multiplicative updates of the factor matrices, non-negative alternative least squares, gradient-based solving methods and geometric approaches to the problem. In this paper a new alternating optimization method is proposed. Following from the revisited and new interpretations of the geometric properties of NMF, an algorithm is proposed which alternately minimize the Frobenius norm of the basis matrix while maximize the Frobenius norm of the co-efficient matrix in a unitized ℓ1-space. The proposed alternating solving converges faster than the methods currently available and provides better performance at the same time for facial recognition. The claim has been supported by related example.