Miracle-dz/UniFAR-FTUs huggingface dataset:
CPG-based control of smooth transition for body shape and locomotion speed of a snake-like robot

In this paper, a lightweight central pattern generator(CPG) model is designed for a snake-like robot, to achieve smooth transition of body shape and locomotion speed. First, based on the convergence behavior of the gradient system, a lightweight CPG model with fast computing time is designed and compared with other widely adopted CPG models. Then, the body shape and locomotion speed transitions in rolling gait are simulated based on the proposed CPG model. Compared with the sinusoid-based method, a smooth transition process can be achieved, without generating undesired movement or abnormal torque. Finally, extensive prototype experiments are conducted to demonstrate that the CPG-based control can effectively ensure smooth transition process and avoid abnormal torque, when the body shape and locomotion speed are changed.
On the Performance of a PRP-WLAN Enabled Wireless Backbone

This paper investigated a 1-out-of-2 controller fault-tolerant system composed of two industrial workcells. Improving the performance and the reliability of the employed IEEE 802.11g wireless backbone was the main focus of this study. The approach taken to achieve this goal is the application of parallel redundant diverse wireless communication. A parallel redundant wireless backbone that interconnects two industrial workcells with a large number of sensors and actuators is modeled and simulated with the OPNET Network Modeler and its performance characteristics evaluated. For all studied system performance metrics, it was shown that the PRP-WLAN backbone is superior to a single-channel implementation under all investigated interference scenarios. Key-Words: Parallel Redundancy, Wi-Fi, PRP-WLAN Backbone, OPNET, Factory Automation, 802.11
Animal Models of Episodic Memory

People retrieve episodic memories about specific earlier events that happened to them. Accordingly, researchers have sought to evaluate the hypothesis that nonhumans retrieve episodic memories. The central hypothesis of an animal model of episodic memory is that, at the moment of a memory assessment, the animal retrieves a memory of the specific earlier event. Testing this hypothesis requires the elimination of nonepisodic memory hypotheses. A number of case studies focus on the development of animal models of episodic memory, including what-where-when memory, source memory, item-in-context memory, and unexpected questions. Compelling evidence for episodic memory comes from studies in which judgments of familiarity cannot produce accurate choices in memory assessments. These approaches may be used to explore the evolution of cognition.
SAL: an explicitly pluralistic cognitive architecture

The SAL cognitive architecture is a synthesis of two well-established constituents: ACT-R, a hybrid symbolic-subsymbolic cognitive architecture, and Leabra, a neural architecture. These component architectures have vastly different origins yet suggest a surprisingly convergent view of the brain, the mind and behaviour. Furthermore, both of these architectures are internally pluralistic, recognising that models at a single level of abstraction cannot capture the required richness of behaviour. In this article, we offer a brief principled defence of epistemological pluralism in cognitive science and artificial intelligence, and elaborate on the SAL architecture as an example of how pluralism can be highly effective as an approach to research in cognitive science.
Person-supervisor fit, needs-supplies fit, and team fit as mediators of the relationship between dual-focused transformational leadership and well-being in scientific teams

ABSTRACT Team-based work structures have become prevalent in science. Scientific teams, however, are characterized by competing individual-level and team-level needs (i.e., by mixed-motive situations). This makes leading scientific teams particularly challenging: Balancing competing individual-level goals and common team-level goals requires a specific type of leadership that simultaneously considers both satisfying individual-level needs as well as team-level needs. The current study addresses this issue by combining the dual-focused model of transformational leadership with person-environment fit theory. Specifically, we investigated needs-supplies fit, person-supervisor fit, and team fit as mediators of the relationship between transformational leadership and scientific team members’ job satisfaction and work-related strain. In doing so, we provide a new perspective on leadership in scientific teams by explicitly differentiating individual-level and team-level effects of transformational leadership. We tested our hypotheses using a three-wave design with a sample of 134 members of 42 scientific teams. The relationships between individual-focused transformational leadership, job satisfaction, and work-related strain were mediated by needs-supplies fit and person-supervisor fit. Team-focused transformational leadership was positively related to job satisfaction and negatively related to work-related strain. Our findings contribute to further clarifying the mechanisms underlying the relationship between transformational leadership and members’ well-being in scientific teams.
LATITUDINAL AND CLIMATIC VARIATION IN BODY SIZE AND DORSAL SCALE COUNTS IN SCELOPORUS LIZARDS:A PHYLOGENETIC PERSPECTIVE

Squamates often follow an inverse Bergmann's rule, with larger‐bodied animals occurring in warmer areas or at lower latitudes. The size of dorsal scales in lizards has also been proposed to vary along climatic gradients, with species in warmer areas exhibiting larger scales, putatively to reduce heat load. We tested for these patterns in the diverse and widespread lizard genus Sceloporus. Among 106 species or populations, body size was associated positively with maximum temperature (consistent with the inverse of Bergmann's rule) and aridity, but did not covary with latitude. Scale size (inferred from the inverse relation with numbers of scales) was positively related to body size. Controlling for body size via multiple regression, scale size was associated negatively with latitude (best predictor), positively with minimum temperature, and negatively with aridity (similar results were obtained using scores from a principal components analysis of latitude and climatic indicators). Thus, lizards with larger scales are not necessarily found in areas with higher temperatures. Univariate analyses indicated phylogenetic signal for body size, scale counts, latitude, and all climate indicators. In all cases, phylogenetic regression models fit the data significantly better than nonphylogenetic models; thus, residuals for log10 number of dorsal scale rows exhibited phylogenetic signal.
Gilmore Girls generations: disrupting generational belonging in long-term fandom

ABSTRACT This article is a study of fans of the television series Gilmore Girls (2000–2007) in the context of the revival series Gilmore Girls: A Year in the Life (2016), when the series returned with a four-episode special on Netflix after being off the air for nine years. The series revolves around a single mother and her daughter, and this article shows how fans use representations of familial relationships, generations and transitional life stages in their own life course as long-term fans. The article combines theory on long-running serial narratives, media generations and cultural gerontology with fan studies theory, and analyses email interviews with 27 long-time fans of Gilmore Girls aged between 21 and 67 years. This article argues that being a long-term fan with an intense relationship to a media text (e.g. constantly re-watching old episodes) disrupts fans’ experience of generational belonging through: (1) what is experienced as nostalgic or a lack of nostalgia; (2) shifting character identifications across the life course and cross-generational identification; and (3) constantly ascribing new meaning to the media text as fans experience transitional stages in their own lives.
Pathways for remembering and recognizing indigenous thought in education: Philosophies of Iethi’nihsténha Ohwentsia’kékha

Dr. Sandra Styres (2017) deftly examines the interwoven tapestry that is often framed as Indigenous knowledge, philosophy, and education. Situated in the proverbial institution of reason, Professor Styres wrestles with the hegemony of dominant Western practices within education to re-present an Indigenous philosophy of education that is rooted in the central tenets of disparate Indigenous communities, reflecting and capturing diverse ecological, epistemic, historical, and contemporary realities. In a dialogical approach to episteme and ontology, she endeavors to map the ethical quandaries faced by the Indigenous scholar and the larger community. Early in the text, Styres situates this work rightly in ethical space(s) that are “fluid, interconnected, and iterative . continually evolving and changing” (p. 29) in a process of (re) centering, (re)membering, (re)cognizing, (re)generating, and (re)actualizing. The journey undertaken in this work is as expansive as (re)imag(in)(ing) homo sapiens captured in an albeit revelatory moment of perception.
Allelic variation in the VMD2 gene in best disease and age-related macular degeneration.

PURPOSE To assess the allelic variation of the VMD2 gene in patients with Best disease and age-related macular degeneration (AMD). METHODS Three hundred twenty-one AMD patients, 192 ethnically similar control subjects, 39 unrelated probands with familial Best disease, and 57 unrelated probands with the ophthalmoscopic findings of Best disease but no family history were screened for sequence variations in the VMD2 gene by single-strand conformation polymorphism (SSCP) analysis. Amplimers showing a bandshift were reamplified and sequenced bidirectionally. In addition, the coding regions of the VMD2 gene were completely sequenced in six probands with familial Best disease who showed no SSCP shift. RESULTS Forty different probable or possible disease-causing mutations were found in one or more Best disease or AMD patients. Twenty-nine of these variations are novel. Of the 39 probands with familial Best disease, mutations were detected in all 39 (33 by SSCP and 6 by DNA sequencing). SSCP screening of the 57 probands with a clinical diagnosis of Best disease but no family history revealed 16 with mutations. Mutations were found in 5 of 321 AMD patients (1.5%), a fraction that was not significantly greater than in control individuals (0/192, 0%). CONCLUSIONS Patients with the clinical diagnosis of Best disease are significantly more likely to have a mutation in the VMD2 gene if they also have a positive family history. These findings suggest that a small fraction of patients with the clinical diagnosis of AMD may actually have a late-onset variant of Best disease, whereas at the same time, a considerable fraction of isolated patients with the ophthalmoscopic features of Best disease are probably affected with some other macular disease.
Finding the Silver Lining: How Positive Psychology Can Help You Use Critical Feedback to Flourish

We all need feedback to grow professionally and improve our skills. Our cognitive biases and limited perspective mean it is imperative that we draw on others to help us see what we cannot, and point us to new strategies to achieve our goals. But, even if you agree with that sentiment, you might find it emotionally wrenching to hear that your work falls short or could be improved: many of us avoid or reject beneficial, but critical, feedback. And, sometimes negative feedback is inexpertly delivered, making it even harder to hear. Positive psychology aims to help people flourish; while it’s sometimes hard to remember this, critical feedback is usually intended to promote flourishing, too. This capstone describes a model for thinking about how to flourish from feedback. It provides tools which can be used to make us more receptive to feedback and influence our feedback environment; these same tools can be used to prepare for, engage in, and process feedback conversations. Finally, the model offers guidance for selecting the right tools to help everyone reap the benefits that can come from hearing the wisdom that others can share with us.
Lower Risk of Stroke after Deformity Surgery: Long Term Benefit Demonstrated by a National Cohort Study

Objectives: This study aimed to investigate the long-term risk of stroke in adult patients with spinal deformity. Specifically, the study addressed the possible protective effect of surgery for spinal deformity against stroke. Methods: Using the National Health Insurance Research Database (NHIRD), a monopolistic national database in Taiwan, this retrospective cohort study analyzed the incidence of stroke in patients with adult spinal deformity (ASD) in a 11-year period. A total of 13,503 patients, between 55 and 75 years old, were identified for the diagnosis of ASD. The patients were grouped into two: the surgical group (n = 10,439) who received spinal fusion surgery, and the control group (n = 2124) who received other medical treatment. The incidence rates of all subsequent cerebrovascular accidents, including ischemic and hemorrhagic strokes, were calculated. Hazard ratios for stroke were calculated use a full cohort and a propensity score matched cohort. Adjustments for co-morbidities that may predispose to stroke, including hypertension, diabetes mellitus, arrhythmia and coronary heart disease were conducted. Kaplan-Meier and Cox regression analyses were performed to compare the risk of stroke between the two groups. Results: During the total observation period of 50,450 person-years, the incidence rate of stroke in the surgical group (15.55 per 1000 person-years) was significantly lower than that of the control group (20.89 per 1000 person-years, p < 0.001). Stroke was more likely to occur in the control group than in the surgical group (crude hazard ratio 1.34, p < 0.001; adjusted HR 1.28, p < 0.001, by a propensity score matched model). Conclusions: In this national cohort of more than 13,000 ASD patients covering 10 years, stroke was approximately 25% less likely to happen in patients who underwent spinal fusion surgery than those who received medical management. Therefore, spinal fusion surgery may provide a protective effect against stroke in adult patients with spinal deformity.
UBEV - A More Practical Algorithm for Episodic RL with Near-Optimal PAC and Regret Guarantees

We present UBEV, a simple and efficient reinforcement learning algorithm for fixed-horizon episodic Markov decision processes. The main contribution is a proof that UBEV enjoys a sample-complexity bound that holds for all accuracy levels simultaneously with high probability, and matches the lower bound except for logarithmic terms and one factor of the horizon. A consequence of the fact that our sample-complexity bound holds for all accuracy levels is that the new algorithm achieves a sub-linear regret of Õ( √ SAT ), which is the first time the dependence on the size of the state space has provably appeared inside the square root. A brief empirical evaluation shows that UBEV is practically superior to existing algorithms with known samplecomplexity guarantees.
Design and Simulation Low Voltage Single-Phase Transformerless Photovoltaic Inverter

The last Deckard years developing Inverter technology for renewable energy and high efficiency and more improvement solar and wind power plant. Transformer less inverter technology is best and improves efficiency, power quality and reduces switching loss. single-phase grid connected transformerless photovoltaic (PV) inverter for residential application is presented. The inverter is derived from a boost cascaded with buck converter along with a line frequency unfolding circuitIn this research paper transformer less photovoltaic (PV) inverter is going to be more adopted in order to achieve high benefit. The selected inverters are the full-bridge inverter with bipolar modulation, full-bridge inverter with DC bypass and the Highly Efficient and Reliable Inverter Concept (HERIC). A low voltage single-phase grid-connected PV system is analyzed to verify the discussions. Full Text: PDF DOI: http://dx.doi. org/10.11591/telkomnika.v12i7. 6013
Robustness of recommender systems

The possibility of designing user rating profiles to deliberately and maliciously manipulate the recommendation output of a collaborative filtering system was first raised in 2002. One scenario proposed was that an author, motivated to increase recommendations of his book, might create a set of false profiles that rate the book highly, in an effort to artificially promote the ratings given by the system to genuine users. Several attack models have been proposed and the performance of these attacks in terms of influencing the system predictions has been evaluated for a number of memory-based and model-based collaborative filtering algorithms. Moreover, strategies have been proposed to enhance the robustness of existing algorithms and new algorithms have been proposed with built-in attack resistance. This tutorial will review the work that has taken place in the last decade on robustness of recommendation algorithms and seek to examine the question of the importance of robustness in future research.
DYNAMIC SCENE MODELING FOR OBJECT DETECTION USING SINGLE-CLASS SVM

Scene modeling is the starting point and thus the most crucial stage for many vision based systems involving tracking, or recognition. Most of the existing approaches attempt at solving this problem by making some simplifying assumptions such as that of a stationary background. However, this is not always the case, as swaying trees, or ripples in the water etc often violate these assumptions. In this paper, we present a novel method for modeling a dynamic scene, i.e. scenes that contain “non-stationary” background motions, such as periodic motions (e.g. pendulums or escalators) or dynamic textures (e.g. water fountain in the background, swaying trees, or water ripples etc). The proposed method introduces singleclass Support Vector Machines (SVM), and we show why it is preferable to other scene modeling techniques currently in use for this particular problem. Using a rectangular region around a pixel, spatial and appearance based features are extracted from the images, used for learning the SVMs. We experiment on a diverse set of dynamic scenes and present both qualitative and quantitative results; indicating the practicality and the effectiveness of the proposed method.
Accumulative Interference Modeling for Cognitive Radios with Distributed Channel Access

A cognitive radio (CR) network should be able to sense its environment and adapt its communication to utilize unused licensed spectrum without interfering with incumbents. Properly modeling the expected interference from the CR network is therefore very important in the definition of coexistence rules to efficiently protect the incumbents. In this paper we model the accumulative interference generated from a large-scale CR network and investigate how this affects the sensing requirements of the CRs to meet an interference constraint. More specifically, our model considers the impact of discrete topology and the impact of the distributed channel access scheme. As an instantiation of our model, we consider a CR network based on the IEEE 802.11 standard. We show that the interference generated is large, since collisions cannot be avoided.
Preparing for a Literature Survey of Software Architecture using Formal Concept Analysis

The scientific literature on Software Architecture (SA) is extensive and dense. With no preparation, surveying this literature can be a daunting task for novices in the field. This paper resorts to the technique of Formal Concept Analysis (FCA) in organizing and structuring such a body of knowledge. We start by surveying a set of 38 papers bearing in mind the following questions: “What are the most supported definitions of software architecture? ”, “What are the most popular research topics in software architecture? ”, “What are the most relevant quality attributes of a software architecture? ” and “What are the topics that researchers point out as being more interesting to explore in the future? ”. To answer these questions we classify each paper with appropriate keywords and apply FCA to such a classification. FCA allows us to structure our survey in the form of lattices of concepts which give evidence of main relationships involved. We believe our results will help in guiding a more comprehensive, in-depth study of the field, to be carried out in the future. Keywords-Introductory and Survey; Software Architectures; Formal Concept Analysis;
Grey Wolves Optimizer-based localization approach in WSNs

Localization is one of the main challenge in wireless sensor networks (WSNs). Since both routing establishment and coverage performance of a sensor network are directly affected by the nodes' localizations. While knowing the position of each node is important, a small number of researches had considered the importance of the localization of the sink node. Therefore this paper presents a sink node localization approach based on Grey Wolves Optimizer (GWO). The approach was evaluated against the performance of specific protocols of WSNs (Topology Control Protocols). Through a number of simulation based experiments for different sized nodes' deployment scenarios, it is obviously that the proposed approach had minimized the average of energy cost and the number of active nodes along with the time required to construct a reduced topology.
Segmentation of Dental Radiographs Using a Swarm Intelligence Approach

One of the most complex tasks in digital image processing is image segmentation. This paper proposes a novel image segmentation algorithm that uses a biologically inspired technique based on swarm intelligence and a cellular automata model. The proposed swarm intelligence-based algorithm operates on the image pixel data and a region/neighborhood map to form a context in which they can merge. The swarm intelligent algorithm also tries to find similar pixels using a sensor function, which is then utilized by swarm agents to determine the next appreciate pixel in the region/segment area. In addition, the paper introduces a cellular automata-based dynamic flow algorithm to guide swarm agents to choose the best possible advancing direction to avoid traffic jam and inconsistency. The suggested image segmentation strategy is tested on a set of dental radiographs
Lay attitudes to trade with low-wage countries

Three studies presented scenarios to lay people to investigate their willingness to restrict imports. Greater restriction was preferred when similar goods were made at home, when the owners of the foreign businesses made very good profits, and, less consistently, when the goods came from a low wage country. Particular reluctance to import from a low-wage country did not vary with whether a home firm was likely to lose business or the level of understanding of comparative advantage, but was related to the profits made by foreign business owners. The results show that lay people views are based on concern for people in other countries as well as in their own.