Miracle-dz/UniFAR-FTUs huggingface dataset:
Encoding specificity and retrieval processes in episodic memory.

Recent changes in prctheorclical orientation toward problems of human memory have brought with them a concern with retrieval processes, and a number of early versions of theories of retrieval have been constructed. This paper describes and evaluates explanations offered by these theories to account for the effect of extralist cuing, facilitation of recall of list items by non-list items. Experiments designed to test the currently most popular theory of retrieval, the generation-recognition theory, yielded results incompatible not only with generation-recognition models, but most other theories as well: under certain conditions subjects consistently failed to recognize many recallable list words. Several tentative explanations of this phenomenon of recognition failure were subsumed under the encoding specificity principle according to which the memory trace of an event and hence the properties of effective retrieval cue are determined by the specific encoding operations performed by the system on the input stimuli.
Data path allocation using an extended binding model

Existing approaches to data path allocation in high-level synthesis use a binding model in which values are assigned to the same register for their entire lifetimes. The authors describe an extended binding model in which segments of a value's lifetime may reside in different registers if there is a cost advantage in doing so. In addition, the model supports multiple copies of values and the use of functional units to pass through unmodified values to reduce interconnects. This model was exploited in an allocation tool that used iterative improvement to search for low-cost designs. Results showed that allocation costs can be substantially reduced by using this model. <<ETX>>
Design and evaluation of a parallel-series elastic actuator for lower limb exoskeletons

This paper presented a novel compliant actuator used for lower limb exoskeletons. The compliant joint consists of a series elastic actuator (SEA) and parallel elastic (PE) unit. SEA has various advantages as the actuator of assistive exoskeletons, such as low output impedance, impact absorption, precise force control and high stability. We designed and fabricated a novel SEA as the primary joint actuator which is compact, adjustable and low-cost. Meanwhile an additional elastic unit is installed in parallel with the SEA to improve energy utilization by storing and releasing energy during motion cycles. An adaptive stable controller is designed to realize the joint following motion to a virtual limb. The algorithm can identify and compensate the undetermined contact stiffness between the joint output and the virtual limb. Finally, the performance of the actuator is evaluated through motion tracking and energy-conservation experiments. Preliminary results indicate the validity of the design and imply its potential usage in lower limb exoskeletons.
A Meta-Analysis of the Anomaly Detection Problem

This article provides a thorough meta-analysis of the anomaly detection problem. To accomplish this we first identify approaches to benchmarking anomaly detection algorithms across the literature and produce a large corpus of anomaly detection benchmarks that vary in their construction across several dimensions we deem important to real-world applications: (a) point difficulty, (b) relative frequency of anomalies, (c) clusteredness of anomalies, and (d) relevance of features. We apply a representative set of anomaly detection algorithms to this corpus, yielding a very large collection of experimental results. We analyze these results to understand many phenomena observed in previous work. First we observe the effects of experimental design on experimental results. Second, results are evaluated with two metrics, ROC Area Under the Curve and Average Precision. We employ statistical hypothesis testing to demonstrate the value (or lack thereof) of our benchmarks. We then offer several approaches to summarizing our experimental results, drawing several conclusions about the impact of our methodology as well as the strengths and weaknesses of some algorithms. Last, we compare results against a trivial solution as an alternate means of normalizing the reported performance of algorithms. The intended contributions of this article are many; in addition to providing a large publicly-available corpus of anomaly detection benchmarks, we provide an ontology for describing anomaly detection contexts, a methodology for controlling various aspects of benchmark creation, guidelines for future experimental design and a discussion of the many potential pitfalls of trying to measure success in this field.
Aberrant Functional Connectivity in the Default Mode and Central Executive Networks in Subjects with Schizophrenia – A Whole-Brain Resting-State ICA Study

Neurophysiological changes of schizophrenia are currently linked to disturbances in connectivity between functional brain networks. Functional magnetic resonance imaging studies on schizophrenia have focused on a few selected networks. Also previously, it has not been possible to discern whether the functional alterations in schizophrenia originate from spatial shifting or amplitude alterations of functional connectivity. In this study, we aim to discern the differences in schizophrenia patients with respect to spatial shifting vs. signal amplitude changes in functional connectivity in the whole-brain connectome. We used high model order-independent component analysis to study some 40 resting-state networks (RSN) covering the whole cortex. Group differences were analyzed with dual regression coupled with y-concat correction for multiple comparisons. We investigated the RSNs with and without variance normalization in order to discern spatial shifting from signal amplitude changes in 43 schizophrenia patients and matched controls from the Northern Finland 1966 Birth Cohort. Voxel-level correction for multiple comparisons revealed 18 RSNs with altered functional connectivity, 6 of which had both spatial and signal amplitude changes. After adding the multiple comparison, y-concat correction to the analysis for including the 40 RSNs as well, we found that four RSNs showed still changes. These robust changes actually seem encompass parcellations of the default mode network and central executive networks. These networks both have spatially shifted connectivity and abnormal signal amplitudes. Interestingly the networks seem to mix their functional representations in areas like left caudate nucleus and dorsolateral prefrontal cortex. These changes overlapped with areas that have been related to dopaminergic alterations in patients with schizophrenia compared to controls.
Measuring the angle of a rotating link through compliant driving tendons

Measuring the position of a tendon-driven rotating link, based on the state of the tendons at the proximal end is challenging. Specifically, tendon elasticity and Coulomb friction can cause significant nonlinearities in the relationship between the motion at the proximal end of the tendon and the motion of the link. An extended Kalman filter (EKF) is proposed as a potential method to refine estimates of link position based on proximal measurements. A model link and tendon system is built to demonstrate the impact of these effects on measurement. Sensors are incorporated to allow direct measurement of the link position in addition to the motion of the tendons at their origins. A dynamic model is developed for the resulting system and used in conjunction with an EKF to generate improved estimates of the linkpsilas motion based on proximal measurements alone.
Real-time performance prediction and tuning for interactive volume raycasting

We present an integrated approach for the real-time performance prediction and tuning of volume raycasting. The usage of empty space skipping and early ray termination, among others, can induce significant variations in performance when camera configuration and transfer functions are adjusted. For interactive exploration, this can result in various unpleasant effects like abruptly reduced responsiveness or jerky motions. To overcome those effects, we propose an integrated approach to accelerate the rendering and assess performance-relevant data on-the-fly, including a new technique to estimate the impact of early ray termination. On this basis, we introduce a hybrid model, to achieve accurate predictions with only minimal computational footprint. Our hybrid model incorporates both aspects from analytical performance modeling and machine learning, with the goal to combine their respective strengths. Using our model, we dynamically steer the sampling density along rays with our automatic tuning technique. This approach allows to reliably meet performance requirements like a fixed frame rate, even in the case of large sudden changes to the transfer function or the camera. We finally demonstrate the accuracy and utility of our approach by means of a variety of different volume data sets and interaction sequences.
Tanzanian and Canadian children’s valued school experiences: a cross case comparison

ABSTRACT This study investigates children’s multimodal perspectives on their school experiences in two diverse, international contexts. The research shares data from 45 Canadian and Tanzanian children, and focused on the children’s use of multimodal methods to share what mattered to them at school. The children’s significant interest in their outdoor school spaces was revealed, as well as culturally specific narratives linked to the participants’ local environments and families. In both settings, the majority of the children valued their outdoor experiences at school where they felt a strong sense of autonomy as they engaged in child-initiated play and collaborative games outdoors.
Molecular techniques in the biotechnological fight against halogenated compounds in anoxic environments

Microbial treatment of environmental contamination by anthropogenic halogenated organic compounds has become popular in recent decades, especially in the subsurface environments. Molecular techniques such as polymerase chain reaction‐based fingerprinting methods have been extensively used to closely monitor the presence and activities of dehalogenating microbes, which also lead to the discovery of new dehalogenating bacteria and novel functional genes. Nowadays, traditional molecular techniques are being further developed and optimized for higher sensitivity, specificity, and accuracy to better fit the contexts of dehalogenation. On the other hand, newly developed high throughput techniques, such as microarray and next‐generation sequencing, provide unsurpassed detection ability, which has enabled large‐scale comparative genomic and whole‐genome transcriptomic analysis. The aim of this review is to summarize applications of various molecular tools in the field of microbially mediated dehalogenation of various halogenated organic compounds. It is expected that traditional molecular techniques and nucleic‐acid‐based biomarkers will still be favoured in the foreseeable future because of relative low costs and high flexibility. Collective analyses of metagenomic sequencing data are still in need of information from individual dehalogenating strains and functional reductive dehalogenase genes in order to draw reliable conclusions.
DSD: A schema language for XML

XML (eXtensible Markup Language) is a linear syntax for trees, which has gathered a remarkable amount of interest in industry. The acceptance of XML opens new venues for the application of formal methods such as specification of abstract syntax tree sets and tree transformations. A notation for defining a set of XML trees is called a schema language. Such trees correspond to a specific user domain, such as XHTML, the class of XML documents that make sense as HTML. A useful schema notation must: identify most of the syntactic requirements that the documents in the user domain follow; allow efficient parsing; be readable to the user; allow limited tree transformations corresponding to the insertion of defaults; be modular and extensible to support evolving classes of XML documents.par>In the present paper, we introduce the DSD (Document Structure Description) notation as our bid on how to meet the requirements above.
eHealth Service Support in Future IPv6 Vehicular Networks

Recent vehicular networking activities include novel automotive applications, such as public vehicle to vehicle/infrastructure (V2X), large scale deployments, machine-to-machine (M2M) integration scenarios, and more. The platform described in this paper focuses on the integration of eHealth in a V2I setting. This is to allow the use of Internet from a vehicular setting to disseminate health-related information. From an eHealth viewpoint, the use of remote healthcare solutions to record and transmit a patient’s vital signs is a special telemedicine application that helps hospital resident health professionals to optimally prepare the patient’s admittance. From the automotive perspective, this is a typical vehicle-to-infrastructure (V2I) communication scenario. This proposal provides an IPv6 vehicular platform, which integrates eHealth devices and allows sending captured health-related data to a personal health record (PHR) application server in the IPv6 Internet. The collected data is viewed remotely by a doctor and supports his diagnostic decision. In particular, our work introduces the integration of vehicular and eHealth testbeds, describes related work and presents a lightweight auto-configuration method based on a DHCPv6 extension to provide IPv6 connectivity with a few numbers of messages.
1 A FUZZY-NEURO APPROACH FOR DESIGN OF LIGHT WEIGHT CONCRETE MIXES

Design of lightweight concrete is a process by which human experts arrive at the right proportions of cement, lightweight aggregates, water and admixtures for making the concrete as per the required specifications. Though, there are technical principles that govern mix proportioning, the process is not entirely in the realm of science. This is due to approximate codal guidelines, impreciseness and vagueness in various parameters involved in the design. This paper explains the development of a fuzzy-neuro hybrid model for the design of structural lightweight concrete. The mix design procedure is based on empirical graphs cited in the literature (that have been developed by extensive experimental investigations). Structural lightweight concrete is designed for required minimum cube strength. For this purpose, the minimum cube strength and degree of control have been considered as linguistic variables with appropriate number of partitions in the input (antecedent) space. The fuzzy sets in the output space are constructed using vertex method of extension. Three trained back propagation neural networks have been integrated and interfaced. Four most commonly used lightweight aggregates, namely, Lytag, Leca, Agilite and foamed slag have been considered. The model is coded in Visual Basic and it is highly interactive. The objective of this research is to find out a more natural, tolerant and humanistic way to design lightweight concrete. It is felt that fuzzy logic and neural network would lend themselves in realizing such flexibility.
Age-related changes in hemispheric organization

What are the implications for cognition of the fact that we have two cerebral hemispheres? Although this is one of the most fundamental questions in cognitive neuroscience, no definite answer is presently available. For more than a century, researchers have wondered why we have two hemispheres, how they differ, and how they interact with each other. Anatomical and functional asymmetries have been identified, and different models of hemispheric interaction have been proposed. Recently, studies using positron emission tomography (PET) and functional MRI (fMRI) have revitalized this research domain by discovering new hemispheric asymmetries. Moreover, these studies have identified changes in the lateralization of brain activity as a function of population variables, such as aging. In fact, the most consistent finding in functional neuroimaging studies of cognitive aging is a reduction in the lateralization of prefrontal activations. This is not the first time that aging has been associated with changes in lateralization; for many years, cognitive aging psychologists discussed the possibility that the right hemisphere ages faster than the left. In general, however, these ideas have not been informed by theories regarding hemispheric specialization and interaction. The goal of this chapter is to address this disconnection and to link the topic of lateralization and aging to general issues regarding hemispheric organization.
Performance of Zirconia for Dental Healthcare

The positive results of the performance of zirconia for orthopedics devices have led the dental community to explore possible esthetical and mechanical outcomes using this material. However, questions regarding long-term results have opened strong and controversial discussions regarding the utilization of zirconia as a substitute for alloys for restorations and implants. This narrative review presents the current knowledge on zirconia utilized for dental restorations, oral implant components, and zirconia oral implants, and also addresses laboratory tests and developments, clinical performance, and possible future trends of this material for dental healthcare.
The origin of power laws in Internet topologies revisited

C. Faloutsos et al. (see Proc. ACM SIGCOMM, 1999) found that the inter autonomous system (AS) topology exhibits a power-law vertex degree distribution. This result was quite unexpected in the networking community and stirred significant interest in exploring the possible causes of this phenomenon. The work of A. -L. Barabasi and R. Albert (see Science, p.509-512, 1999) and its application to network topology generation in the work of A. Medina et al. (see Proc. MASCOTS, 2001) have explored a promising class of models that yield strict power-law vertex degree distributions. We re-examine the BGP (border gateway protocol) measurements that form the basis for the results reported by Faloutsos et al. We find that by their very nature (i.e., being strictly BGP-based), the data provides a very incomplete picture of Internet connectivity at the AS level. The AS connectivity maps constructed from this data (original maps) typically miss 20-50% or even more of the physical links in AS maps constructed using additional sources (extended maps). Subsequently, we find that while the vertex degree distributions resulting from the extended maps are heavy-tailed, they deviate significantly from a strict power law. Finally, we show that available historical data does not support the connectivity-based dynamics assumed by Barabasi and Albert. Together, our results suggest that the Internet topology at the AS level may well have developed over time following a very different set of growth processes than those proposed by Barabasi and Albert.
Forgiveness in Javanese collective culture: The relationship between rumination, harmonious value, decisional forgiveness and emotional forgiveness

Forgiveness in Javanese collective culture is examined by considering harmonious value (HV) a subjective value on maintaining social harmony and rumination. In Study 1, we conducted an exploratory sequential mixed-method study to develop a scale measuring HV. In-depth interviews with eight Javanese adolescents revealed three major domains of HV (Study 1a). In a second quantitative study (Study 1b), we developed items and assessed 347 Javanese adolescents in Yogyakarta, Indonesia. Principal component analysis and confirmatory factor analysis supported three factors: cooperation during conflict, forbearing and resolving conflict. After confirming that the translated scales had acceptable reliability, we conducted Study 2 with 424 Javanese adolescents from both urban and village settings. Using hierarchical multiple regression, we found that HV accounted for a variance in decisional forgiveness above and beyond rumination. In addition, decisional forgiveness also accounted for variance in emotional forgiveness above and beyond rumination. In fact, HV accounted for variance in emotional forgiveness above and beyond both rumination and decisional forgiveness together. This revealed the importance of valuing social harmony in this collectivistic culture. Moreover, decisional forgiveness was also important in predicting the Javanese collectivists’ emotional forgiveness.
Pro-Inflammatory and Pro-Oxidant Status of Pancreatic Islet In Vitro Is Controlled by TLR-4 and HO-1 Pathways

Since their isolation until implantation, pancreatic islets suffer a major stress leading to the activation of inflammatory reactions. The maintenance of controlled inflammation is essential to preserve survival and function of the graft. Identification and targeting of pathway(s) implicated in post-transplant detrimental inflammatory events, is mandatory to improve islet transplantation success. We sought to characterize the expression of the pro-inflammatory and pro-oxidant mediators during islet culture with a focus on Heme oxygenase (HO-1) and Toll-like receptors-4 signaling pathways. Rat pancreatic islets were isolated and pro-inflammatory and pro-oxidant status were evaluated after 0, 12, 24 and 48 hours of culture through TLR-4, HO-1 and cyclooxygenase-2 (COX-2) expression, CCL-2 and IL-6 secretion, ROS (Reactive Oxygen Species) production (Dihydroethidine staining, DHE) and macrophages migration. To identify the therapeutic target, TLR4 inhibition (CLI-095) and HO-1 activation (cobalt protoporphyrin,CoPP) was performed. Activation of NFκB signaling pathway was also investigated. After isolation and during culture, pancreatic islet exhibited a proinflammatory and prooxidant status (increase levels of TLR-4, COX-2, CCL-2, IL-6, and ROS). Activation of HO-1 or inhibition of TLR-4 decreased inflammatory status and oxidative stress of islets. Moreover, the overexpression of HO-1 induced NFκB phosphorylation while the inhibition of TLR-4 had no effect NFκB activation. Finally, inhibition of pro-inflammatory pathway induced a reduction of macrophages migration. These data demonstrated that the TLR-4 signaling pathway is implicated in early inflammatory events leading to a pro-inflammatory and pro-oxidant status of islets in vitro. Moreover, these results provide the mechanism whereby the benefits of HO-1 target in TLR-4 signaling pathway. HO-1 could be then an interesting target to protect islets before transplantation.
Contextual texture based bottom-up visual attention

Modeling visual attention provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. In this paper, we propose a robust approach to the modeling bottom-up visual attention. The main contributions are twofold: 1) a novel contextual texture feature is extracted to describe texture consistency of a region globally. And then the salient map can be robustly generated for a variety of nature images; 2) a practicable framework for modeling visual attention is presented based on global information. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that the proposed algorithm is effective and can characterize the human perception well.