Miracle-dz/UniFAR-FTUs huggingface dataset:
0 Stability Boundary and Transparency for Haptic Rendering Iñaki Díaz and

Over the past years haptic interfaces have been successfully integrated into a wide range of fields such as engineering (Borro et al., 2004) or surgery (Basdogan et al., 2004). Haptic devices allow users to interact with a certain environment, either remote or virtual, by the sense of touch. In these applications—unlike in conventional robotic systems—the user shares workspace with the device. Therefore, an unstable behaviour can damage the device, or even worse, harm the operator. Thus, stability must be guaranteed to ensure user safety and achieve high haptic performance. Unfortunately, preserving haptic stability usually implies reducing the range of dynamic impedances achievable by the system. Hence, rigid virtual objects cannot be perceived as stiff as real ones, and the overall haptic performance and transparency perception are considerably degraded. Developing stable controllers able to exhibit a wide dynamic range of impedances is a persistent challenge in the field of haptics. This chapter describes main research carried out by the authors on stability issues for haptic rendering, as well as on the development of transparent haptic controllers. In a haptic system, the stability boundary for haptic rendering depends on many factors, such as inherent interface dynamics, motor saturation, sensor resolution or time delay. Section 2 introduces the state-of-the-art on stability studies showing the influence of many of these phenomena. Beyond related work, Section 3 analyses the influence of viscous damping and delay on the stability boundary for haptic rendering. Although the shape of the stability boundaries found is quite complex, a linear condition which summarises the relation between virtual stiffness, viscous damping and delay is proposed. Section 4 analyses the influence of the first vibration mode of the system on the stability boundary. The majority of haptic models used to analyse stability do not consider the existence of internal vibration modes. However, it will be shown that for certain interfaces vibration modes must be taken into account to correctly obtain the range of impedances achievable by the system. 5
Global Asymptotic Stability and Naimark-Sacker Bifurcation of Certain Mix Monotone Difference Equation

We investigate the global asymptotic stability of the following second order rational difference equation of the form xn+1 = (Bxnxn−1 + F)/(bxnxn−1 + cx2n−1), n = 0, 1, . , where the parameters B, F, b, and c and initial conditions x−1 and x0 are positive real numbers. The map associated with this equation is always decreasing in the second variable and can be either increasing or decreasing in the first variable depending on the parametric space. In some cases, we prove that local asymptotic stability of the unique equilibrium point implies global asymptotic stability. Also, we show that considered equation exhibits the Naimark-Sacker bifurcation resulting in the existence of the locally stable periodic solution of unknown period.
EMPAT — Evolvable Modularity Patterns: From Inconvenient Truth to Evolvable Engineering

—Modularity, or the division of systems into interrelated and hierarchical subsystems, has been considered to be a powerful concept in many domains for many decades. While modular artifacts are believed to have the potential to exhibit several beneﬁcial characteristics, including evolvability, the actual realization of this evolvability — or adaptability over time — remains challenging. Systems in almost all domains, both physical artefacts and administrative and/or information systems, face severe evolvability issues, which are closely related to some of the most pressing challenges of our time. The availability of design rules and patterns, allowing the design of systems that exhibit higher levels of evolvability than currently known, could lead to huge beneﬁts in terms of productivity, sustainability, and innovation. In the PATTERNS 2021 conference in Porto, Portugal, a ﬁfth special session on Evolvable Modularity Patterns is included. Three papers explore architectural patterns that could contribute to attaining evolvable modular structures, and therefore to the beneﬁts that such architectures could entail.
Line attractor dynamics in recurrent networks for sentiment classiﬁcation

Recurrent neural networks (RNNs) are a powerful tool for modeling sequential data. Despite their widespread usage, understanding how RNNs solve complex problems remains elusive. Here, we characterize how popular off-the-shelf architectures (including LSTMs, GRUs, and vanilla RNNs) perform document-level sentiment classification. Despite their theoretical capacity to implement complex, high-dimensional computations, we find that all architectures converge to highly interpretable, low-dimensional representations. We identify a simple mechanism, integration along an approximate line attractor, and find this mechanism present across RNN architectures (including LSTMs, GRUs, and vanilla RNNs). Overall, these results demonstrate that surprisingly universal and human interpretable computations can arise across a range of RNNs.
Slice-by-slice prospective hardware motion correction in EPI and simultaneous multislice sequences

Target Audience Researchers using EPI based sequences (BOLD/diffusion), particularly those studying populations that exhibit head motion. Purpose A considerable amount of recent research has shown that head motion can cause spurious group differences in functional as well as structural connectivity analyses. These differences persist even in the presence of compensatory retrospective techniques (such as volume-based retrospective motion correction and regression of motion estimates). Both analysis techniques rely on MRI data acquired with an echo planar imaging (EPI) readout. This abstract examines slice-by-slice prospective hardware motion correction in EPI based sequences in order to mitigate such spurious group differences. Methods A system designed for interventional-MRI tool tracking (Endoscout; Robin Medical, Baltimore MD) has been repurposed to track head motion. A sensor, which consists
Development of Neuropathic Pain Behavior and Expression of CCL 2 / CCR 2 and CX 3 CL 1 / CX 3 CR 1 after Spinal Cord Hemisection

Hea-Woon Park, MD, PhD; Jo-Young Son, MS; Yun-Woo Cho, MD, PhD; Se-Jin Hwang, MD, PhD; Su-Jeong Kim, PhD; Sang-Ho Ahn, MD, PhD; Sung-Ho Jang, MD, PhD; Yong-Jae Jung, MD Department of Rehabilitation Medicine, School of Medicine, Catholic University of Deagu; Department of Rehabilitation Medicine, College of Medicine, Yeungnam University; Department of Anatomy and Cell Biology, College of Medicine, Hanyang University; Institute of Medical Science, Yeungnam University
Investment Sensitivity to Conditional Uncertainty : Nesting Alternative Theoretical Specifications

We present an empirical model for the investment-uncertainty relationship that encompasses the frictionless neoclassical benchmark, as well as its friction-including variants, taking the form of imperfect competition, irreversibility and decreasing returns-to-scale. We generate conditional volatility in a panel framework applying a Pooled Panel GARCH method. We document significant nonlinearities, since the magnitude and sign of investment’s sensitivity to uncertainty change dramatically across alternative economic environments, as defined by different combinations of irreversibility, market power, and returns-to-scale. In general, as the severity of deviations from the benchmark progresses, investment elasticity eventually crosses the zero line and attains negative values.
Investor Sentiment, Innovation Investment and Cash Dividend

Investor sentiment plays a critical role in corporate innovation investment. Firms resort to innovation in their attempts to satisfying the demands of their investors. We argue empirically in our study that investor sentiment has impact on firms’ innovation decisions. We also argue that, strong negative sentiment has higher propensity to foster corporate innovation investment. We analyzed a nine- year panel data ranging from 2009-2017, which consisted of 3,558 Chinese listed firms. A verification of the impact of dividend policy on firms’ innovation investment was conducted. We found that, favorable dividend policy would trigger corporate innovation investment. We also found a statistically significant relationship between innovation investment and firm performance. Our findings showed a positive association between corporate innovation investment and firm performance. We also conducted a series of robustness checks on our empirical models and then discussed the contribution of our study, theoretically and practically.
Synthesis Lectures on Information Concepts , Retrieval , and Services

Many information retrieval (IR) systems suffer from a radical variance in performance when responding to users’ queries. Even for systems that succeed very well on average, the quality of results returned for some of the queries is poor. Thus, it is desirable that IR systems will be able to identify "difficult" queries so they can be handled properly. Understanding why some queries are inherently more difficult than others is essential for IR, and a good answer to this important question will help search engines to reduce the variance in performance, hence better servicing their customer needs. Estimating the query difficulty is an attempt to quantify the quality of search results retrieved for a query from a given collection of documents. This book discusses the reasons that cause search engines to fail for some of the queries, and then reviews recent approaches for estimating query difficulty in the IR field. It then describes a common methodology for evaluating the prediction quality of those estimators, and experiments with some of the predictors applied by various IR methods over several TREC benchmarks. Finally, it discusses potential applications that can utilize query difficulty estimators by handling each query individually and selectively, based upon its estimated difficulty.
THE EFFECTS OF HUMAN RESOURCE , MARKETING AND MANUFACTURING PERFORMANCE ON FINANCIAL PERFORMANCE

In today’s competitive environment, in order for a company to exist, it must continually improve its performance by reducing cost, improving quality and productivity, and easy access to market. Therefore, businesses have to know the factors which affect their performance and manage these factors effectively in order to survive and face an ever increasing competitive pressure. The purpose of this article is to explore the effects of the human resource management, marketing and manufacturing performance on financial performance by considering marketing performance and manufacturing performance as mediating variables in the relationships between human resource management and financial performance. For this purpose, data were obtained from 110 firms within and around the Kocaeli Industrial Region. In order to test the hypotheses of this study, correlation and regression analyses were performed. Results of correlation analysis revealed that all variables are positively related to both financial performance and to each other. The findings from regression analysis reveal that both marketing and manufacturing performance have statistically significant positive effect on a firm’s financial performance. Human resource management does not have any statistically significant effect on a firm’s financial performance. The effect of human resource management on financial performance is overshadowed. The results of regression analysis shows that manufacturing performance fully mediates and marketing performance partially mediates the relationship between the human resource management and financial performance
UNDERSTANDING EMITTANCE DILUTING EFFECTS IN HIGHLY OPTIMIZED ULTRAFAST ELECTRON DIFFRACTION BEAMLINES

The application of Multiobjective Genetic Algorithm optimization (MOGA) to photoemission based ultrafast electron diffraction (UED) beamlines featuring extremely low cathode mean transverse energies has lead to designs with emittances as low as 1 nm for sub-picosecond bunches with 10 electrons [1]. Analysis of these results shows significant emittance growth during transport: with emittance dilution as high as a factor of 200-4000% for various designs and optics settings. In this study we quantify and model the individual sources of emittance growth (slice mismatches and space charge), and explore the use of the core emittance as a strong invariant.
Effect of the combination between organic and mineral N along with or without biofertilizers and yeast extract on potato growth and productivity

This field experiment was carried out on potato, Solanum tuberosum L. , cv. Sponta, at the Experimental Farm of the Environmental Studies & Research Institute in El-Sadat city, Minufiya University, Egypt, during the summer seasons of 2009 and 2010 in sandy loam soil. The study aimed to investigate the effect of organic/mineral nitrogen combination with or without biofertilizer inoculation and with or without foliar application by yeast extract on growth, yield and tuber quality of potato. The treatments used were 150 kg mineral-N /feddan as ammonium nitrate, 100 kg mineralN + 50 kg organic-N as chicken manure, 75 kg mineral-N + 75 kg organicN, 50 kg mineral-N + 100 kg organic-N and 150 kg/feddan organic-N with or without biofertilizer "N-free living bacteria (Azotobacter and Azospirillium) and a phosphate dissolving bacteria (Bacillus megatherium)" and with or without foliar application by yeast extract (50 ml/l). Results showed that using 75 kg mineral-N + 75 kg organic-N, enhanced plant growth increased yield and imbroved tuber quality than other organic-mineral N combination. Also, inoculating tubers with biofertilizer gave good results than when no biofertilizer was added. Also, sprayed potato plants with yeast extract gave good results (in most cases) in termes of vigour growth, higher yield and tuber quality as compared with those untreated. Therefore, using 75 Kg mineral-N + 75 Kg organic-N /feddan combined with biofertilizer and spray with yeast extract treatments gave the
Setup of a Wireless Surface-EMG System

To derive the intention of motion the electrical signals can be used, which actuate the muscles. The measuring procedure is known as electromyography (EMG). An overview of available EMG systems and applications for rehabilitation robotics will be given. The setup for a system is presented, which measures two muscles by surface-EMG with 100 samples/s. For transmission of the data, a wireless Bluetooth HM-10 module and Texas Instruments MSP 430 are used. Further the analog preprocessing and a primary software to display the measured data is described.
n evaluation of implementing long-term MSY in ecosystem-based sheries management : Incorporating trophic interaction , bycatch and ncertainty

Maximum sustainable yield (MSY), often defined in relation to a single species considered in isolation, has long been considered a cornerstone in fisheries management. It is difficult to expand the concept of MSY for the purpose of ecosystem-based fisheries management (EBFM). Here we consider MSY for a fishery in a multispecies fish community by addressing issues of trophic interaction and bycatch, along with parameter uncertainty. A size-spectrum model, which fully considers trophic interactions within the fish community, was used for simulating various fisheries scenarios including a single species fishery, a multispecies stow-net fishery, and a multispecies trawl fishery. Population biomasses, yields, and ecological indicators were used to assess the dynamics of the fishery and fish community status. The single species fishery with no bycatch resulted in a low impact on non-target stocks, but led to the collapse of the target stock at low fishing mortality rates. The stow-net and trawl fisheries had broader ecosystem impacts, but allowed target stocks to be fished at much higher fishing mortality rates with higher yields. Ecological indicators were related non-linearly to fishing mortality, possibly diminishing their effectiveness as management tools. Background resource carrying capacity was found to be a greater source of uncertainty than reproductive efficiency. This study demonstrates that bycatch mortality can play an important role in trophic interactions likely via predation release and depensation, and thus influence the resilience of fisheries to fishing pressure. The study indicates that the combination of mixed fisheries and multispecies effects lead to complex fish community dynamics that may present additional challenges for fisheries management. © 2015 Elsevier B.V. All rights reserved.
Integrating VM Selection Criteria in Distributed Dynamic VM Consolidation Using Fuzzy Q-Learning

Distributed dynamic VM consolidation can be an effective strategy to improve energy efficiency in cloud environments. In general, this strategy can be decomposed into four decision-making tasks: (1) Host overloading detection, (2) VM selection, (3) Host underloading detection, and (4) VM placement. The goal is to consolidate virtual machines dynamically in a way that optimizes the energy-performance tradeoff online. In fact, this goal is achieved when each of the aforementioned decisions are made in an optimized fashion. In this paper we concentrate on the VM selection task and propose a Fuzzy QLearning (FQL) technique so as to make optimal decisions to select virtual machines for migration. We validate our approach with the CloudSim toolkit using real world PlanetLab workload. Experimental results show that using FQL yields far better results w.r. t. the energy-performance trade-off in cloud data centers in comparison to state of the art algorithms.
Australasian Conference on Information Systems Attar & Kang 2018 , Sydney , Australia Organisational Culture and Knowledge Sharing 1 The Effect of Organisational Culture and Knowledge Environment on Organisational Success : Directions for Future Research

Increasingly, organisations strive to shape their knowledge environment and organisational culture for improved performance and organisational success. Despite that, existing evidence recounts the individual role of organisational culture, knowledge management and intellectual capital towards organisational performance and success, a comprehensive explanation of the effect of multiple dimensions of these factors on organisational success remains unexplored. This paper adds to existing literature by proposing that an organisation’s knowledge environment combines its knowledge sharing practices (i.e. knowledge types, knowledge sharing approaches and knowledge sharing processes) and its intellectual capital. This paper presents a conceptual model on the relationship between organisational culture, knowledge environment and organisational success. The model proposes the role of organisational culture in shaping knowledge sharing practices, intellectual capital and organisational success. This research-in-progress concludes with directions for future research on the effect of organisational culture, knowledge sharing practices and intellectual capital on organisational success.
Adversarial Learning for Age-Invariant Face Recognition

There has been an increasing research interest in ageinvariant face recognition. However, matching faces with big age gaps remains a challenging problem, primarily due to the significant discrepancy of face appearance caused by aging. To reduce such discrepancy, in this paper we present a novel algorithm to remove age-related components from features mixed with both identity and age information. Specifically, we factorize a mixed face feature into two uncorrelated components: identity-dependent component and age-dependent component, where the identitydependent component contains information that is useful for face recognition. To implement this idea, we propose the Decorrelated Adversarial Learning (DAL) algorithm, where a Canonical Mapping Module (CMM) is introduced to find maximum correlation of the paired features generated by the backbone network, while the backbone network and the factorization module are trained to generate features reducing the correlation. Thus, the proposed model learns the decomposed features of age and identity whose correlation is significantly reduced. Simultaneously, the identity-dependent feature and the age-dependent feature are supervised by ID and age preserving signals respectively to ensure they contain the correct information. Extensive experiments have been conducted on the popular public-domain face aging datasets (FG-NET, MORPH Album 2, and CACD-VS) to demonstrate the effectiveness of the proposed approach.
Structure Shifts of Conjunctive Relations in the Translation of Animal Farm from English into Hausa

The aim of this study is to find out if structure shifts exist in the translation of the intersentential conjunctive relations in the novel, Animal Farm, from English into Hausa, based on Catford’s (1965) notion of shifts in translation. The two novels used as the sources of data for this study were the source text in English, Animal Farm, and its target language translation in Hausa, Gandun Dabbobi. Two hundred and fifty-two sentences containing inter-sentential conjunctive relations were extracted from each text, making the total number of 504 sentences from both texts. Halliday and Hasan’s (1976) Table of Conjunctive Relations was used to identify the different conjunctive relations. The effects of the shifts on the target language were also studied and explained in the data. This was done using Nida’s (1964) theory of formal and functional equivalence. The study found that there are seven forms of structure shifts in the translation of conjunctive relations from English into Hausa. This study also revealed that all the categories of conjunctive relations i.e. additives, adversatives, causal and temporal were shifted in the translation but their shifts differed between one class of conjunction to another.