Miracle-dz/UniFAR-FTUs huggingface dataset:
A multilevel model for movement rehabilitation in Traumatic Brain Injury (TBI) using Virtual Environments

This paper presents a conceptual model for movement rehabilitation of traumatic brain injury (TBI) using virtual environments. This hybrid model integrates principles from ecological systems theory with recent advances in cognitive neuroscience, and supports a multilevel approach to both assessment and treatment. Performance outcomes at any stage of recovery are determined by the interplay of task, individual, and environmental/contextual factors. We argue that any system of rehabilitation should provide enough flexibility for task and context factors to be varied systematically, based on the current neuromotor and biomechanical capabilities of the performer or patient. Thus, in order to understand how treatment modalities are to be designed and implemented, there is a need to understand the function of brain systems that support learning at a given stage of recovery, and the inherent plasticity of the system. We know that virtual reality (VR) systems allow training environments to be presented in a highly automated, reliable, and scalable way. Presentation of these virtual environments (VEs) should permit movement analysis at three fundamental levels of behaviour: (i) neurocognitive bases of performance (we focus in particular on the development and use of internal models for action which support adaptive, on-line control); (ii) movement forms and patterns that describe the patients' movement signature at a given stage of recovery (i.e, kinetic and kinematic markers of movement proficiency), (iii) functional outcomes of the movement. Each level of analysis can also map quite seamlessly to different modes of treatment. At the neurocognitive level, for example, semi-immersive VEs can help retrain internal modeling processes by reinforcing the patients' sense of multimodal space (via augmented feedback), their position within it, and the ability to predict and control actions flexibly (via movement simulation and imagery training). More specifically, we derive four key therapeutic environment concepts (or Elements) presented using VR technologies: Embodiment (simulation and imagery), Spatial Sense (augmenting position sense), Procedural (automaticity and dual-task control), and Participatory (self-initiated action). The use of tangible media/objects, force transduction, and vision-based tracking systems for the augmentation of gestures and physical presence will be discussed in this context
A Conceptual Framework and Propositions for the Acceptance of Mobile Services

Mobile services are heralded to create a tremendous spectrum of business opportunities. User acceptance of these services is of paramount importance. Consequently, a deeper insight into theory-based research is required to better understand the underlying motivations that lead users to adopting mobile services. As mobile services bring additional functional dimensions, including hedonic and experiential aspects, using extant models for predicting mobile services acceptance by individuals may be inadequate. The aim of this paper is to explore, analyse and critically assess the use of existing acceptance theories in the light of the evolving and ubiquitous mobile services and their underlying technologies. Constructs affecting consumer adoption behaviour are discussed and relevant propositions are made. Managerial implications are explored and future research directions are also identified.
Quasi-states and symplectic intersections

We establish a link between symplectic topology and a recently emerg\-ed branch of functional analysis called the theory of quasi-states and quasi-measures (also known as topological measures). In the symplectic context quasi-states can be viewed as an algebraic way of packaging certain information contained in Floer theory, and in particular in spectral invariants of Hamiltonian diffeomorphisms introduced recently by Yong-Geun Oh. As a consequence we prove a number of new results on rigidity of intersections in symplectic manifolds. This work is a part of a joint project with Paul Biran.
INSTRUCTIONAL DESIGN AND ASSESSMENT Transforming a Large-Class Lecture Course to a Smaller-Group Interactive Course

Objective. To transition a large pharmacokinetics course that was delivered using a traditional lecture format into a smaller-group course with a discussion format. Design. An e-book and Web-based multimedia learning modules were utilized to facilitate students’ independent learning which allowed the number of classes they were required to attend to be reduced from 3 to 1 per week. Students were assigned randomly to 1 of 3 weekly class sessions. The majority of lecture time was replaced with active-learning activities including discussion, problem solving, and case studies to encourage higher-order learning. Assessment. Changes in course delivery were assessed over a 4-year period by comparing students’ grades and satisfaction ratings on course evaluations. Although student satisfaction with the course did not improve significantly, students preferred the smaller-group setting to a large lecture-based class. The resources and activities designed to shift responsibility for learning to the students did not affect examination grades even though a larger portion of examination questions focused on higher orders of learning (eg, application) in the smaller-group format. Conclusions. Transitioning to a smaller-group discussion format is possible in a pharmacokinetics course by increasing student accountability for acquiring factual content outside of the classroom. Students favored the smaller-class format over a large lecture-based class.
Modified Max-Log-MAP turbo decoding algorithm using optimized scaling factor

The Max-Log-MAP is a Soft Input Soft Output (SISO) algorithm, which determines the probability of most likely path through the trellis and hence it gives sub optimal performance compared to Log-MAP algorithm. A simple but effective technique to improve the performance of Max-Log-MAP (MLMAP) algorithm is to scale the extrinsic information exchanged between two decoders using appropriate Scaling Factor (SF). Modified Max-Log-MAP (M-MLMAP) algorithm is achieved by fixing an arbitrary SF for inner decoder S2 and an optimized SF for the outer decoder S1. This paper presents the performance of the Modified Max-Log-MAP decoding algorithm by reducing the over estimation of reliability values to achieve low Bit Error Rate (BER). Appropriate mathematical relationship between SF and Eb/N0 is also proposed. The numerical results show that M-MLMAP algorithm improved the performance of turbo decoding over Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. The proposed M-MLMAP algorithm showed a gain of 0.75dB over MLMAP algorithm at BER of 2×10-5 for Rayleigh fading channel.
Retinal Fundus Image Registration via Vascular Structure Graph Matching

Motivated by the observation that a retinal fundus image may contain some unique geometric structures within its vascular trees which can be utilized for feature matching, in this paper, we proposed a graph-based registration framework called GM-ICP to align pairwise retinal images. First, the retinal vessels are automatically detected and represented as vascular structure graphs. A graph matching is then performed to find global correspondences between vascular bifurcations. Finally, a revised ICP algorithm incorporating with quadratic transformation model is used at fine level to register vessel shape models. In order to eliminate the incorrect matches from global correspondence set obtained via graph matching, we proposed a structure-based sample consensus (STRUCT-SAC) algorithm. The advantages of our approach are threefold: (1) global optimum solution can be achieved with graph matching; (2) our method is invariant to linear geometric transformations; and (3) heavy local feature descriptors are not required. The effectiveness of our method is demonstrated by the experiments with 48 pairs retinal images collected from clinical patients.
Laboratory Review: The Role of Gait Analysis in Seniors’ Mobility and Fall Prevention

Walking is a complex motor task generally performed automatically by healthy adults. Yet, by the elderly, walking is often no longer performed automatically. Older adults require more attention for motor control while walking than younger adults. Falls, often with serious consequences, can be the result. Gait impairments are one of the biggest risk factors for falls. Several studies have identified changes in certain gait parameters as independent predictors of fall risk. Such gait changes are often too discrete to be detected by clinical observation alone. At the Basel Mobility Center, we employ the GAITRite electronic walkway system for spatial-temporal gait analysis. Although we have a large range of indications for gait analyses and several areas of clinical research, our focus is on the association between gait and cognition. Gait analysis with walking as a single-task condition alone is often insufficient to reveal underlying gait disorders present during normal, everyday activities. We use a dual-task paradigm, walking while simultaneously performing a second cognitive task, to assess the effects of divided attention on motor performance and gait control. Objective quantification of such clinically relevant gait changes is necessary to determine fall risk. Early detection of gait disorders and fall risk permits early intervention and, in the best-case scenario, fall prevention. We and others have shown that rhythmic movement training such as Jaques-Dalcroze eurhythmics, tai chi and social dancing can improve gait regularity and automaticity, thus increasing gait safety and reducing fall risk.
Learning rules for social foragers: implications for the producer-scrounger game and ideal free distribution theory.

In population games, the optimal behaviour of a forager depends partly on courses of action selected by other individuals in the population. How individuals learn to allocate effort in foraging games involving frequency-dependent payoffs has been little examined. The performance of three different learning rules was investigated in several types of habitats in each of two population games. Learning rules allow individuals to weigh information about the past and the present and to choose among alternative patterns of behaviour. In the producer-scrounger game, foragers use producer to locate food patches and scrounger to exploit the food discoveries of others. In the ideal free distribution game, foragers that experience feeding interference from companions distribute themselves among heterogeneous food patches. In simulations of each population game, the use of different learning rules induced large variation in foraging behaviour, thus providing a tool to assess the relevance of each learning rule in experimental systems. Rare mutants using alternative learning rules often successfully invaded populations of foragers using other rules indicating that some learning rules are not stable when pitted against each other. Learning rules often closely approximated optimal behaviour in each population game suggesting that stimulus-response learning of contingencies created by foraging companions could be sufficient to perform at near-optimal level in two population games.
Design and Analysis of a High-Efficiency DC–DC Converter With Soft Switching Capability for Renewable Energy Applications Requiring High Voltage Gain

Renewable sources like solar photovoltaic (PV) and fuel cell stack are preferred to be operated at low voltages. For applications such as grid-tied systems, this necessitates high voltage boosting resulting in efficiency reduction. To handle this issue, this paper proposes a novel high voltage gain, high-efficiency dc-dc converter based on coupled inductor, intermediate capacitor, and leakage energy recovery scheme. The input energy acquired from the source is first stored in the magnetic field of coupled inductor and intermediate capacitor in a lossless manner. In subsequent stages, it is passed on to the output section for load consumption. A passive clamp network around the primary inductor ensures the recovery of energy trapped in the leakage inductance, leading to drastic improvement in the voltage gain and efficiency of the system. Exorbitant duty cycle values are not required for high voltage gain, which prevents problems such as diode reverse recovery. Presence of a passive clamp network causes reduced voltage stress on the switch. This enables the use of low voltage rating switch (with low “on-state” resistance), improving the overall efficiency of the system. Analytical details of the proposed converter and its hardware results are included.
Survival in Primary Pulmonary Hypertension: The Impact of Epoprostenol Therapy

Background—Primary pulmonary hypertension (PPH) is a severe and progressive disease. Without treatment, the median survival is 2.8 years, with survival rates of 68%, 48%, and 34% at 1, 3, and 5 years, respectively. Intravenous epoprostenol was the first Food and Drug Administration–approved therapy for PPH. The long-term impact that epoprostenol has made on PPH remains to be defined. Methods and Results—One hundred sixty-two consecutive patients diagnosed with PPH and treated with epoprostenol were followed for a mean of 36.3 months (median, 31 months). Data including functional class, exercise tolerance, and hemodynamics were recorded in a customized database. Vital status was verified in each patient. Observed survival with epoprostenol therapy at 1, 2, and 3 years was 87.8%, 76.3%, and 62.8% and was significantly greater than the expected survival of 58.9%, 46.3%, and 35.4% based on historical data. Baseline predictors of survival included exercise tolerance, functional class, right atrial pressure, and vasodilator response to adenosine. Predictors of survival after the first year of therapy included functional class and improvement in exercise tolerance, cardiac index, and mean pulmonary artery pressure. Conclusions—Intravenous epoprostenol improves long-term survival in PPH.
Auto-Tuning Kernel Mean Matching

The Kernel Mean Matching (KMM) algorithm is a mathematically rigorous method that directly weights the training samples such that the mean discrepancy in a kernel space is minimized. However, the applicability of KMM is still limited, due to the existence of many parameters that are difficult to adjust. This paper presents a novel method that automatically tunes the KMM parameters by assessing the quality of distribution matching from a new perspective. While the KMM itself minimizes the mean discrepancy in a reproducing kernel Hilbert space, the tuning of KMM is achieved by adopting a different quality measure which reflects the Normalized Mean Squared Error (NMSE) between the estimated importance weights and the ratio of the estimated test and training densities. This method enables the applicability of KMM to real domains and leads to a generalized routine for the KMM to incorporate different types of kernels. The effectiveness of the proposed method is demonstrated by experiments on both synthetic and benchmark datasets.
Behavioral economic analysis of cue-elicited craving for tobacco: a virtual reality study.

INTRODUCTION Subjective craving is a prominent construct in the study of tobacco motivation; yet, the precise measurement of tobacco craving poses several difficulties. A behavioral economic approach to understanding drug motivation imports concepts and methods from economics to improve the assessment of craving. METHODS Using an immersive virtual reality (VR) cue reactivity paradigm, this study tested the hypothesis that, compared with neutral cues, tobacco cues would result in significant increases in subjective craving and diverse aspects of demand for tobacco in a community sample of 47 regular smokers. In addition, the study examined these motivational indices in relation to a dual-component delay and cigarette consumption self-administration paradigm. RESULTS In response to the VR tobacco cues, significant increases were observed for tobacco craving and the demand indices of Omax (i.e., maximum total expenditure toward cigarettes) and Breakpoint (i.e., price at which consumption is completely suppressed), whereas a significant decrease was observed for Elasticity (i.e., lower cigarette price sensitivity). Continuous analyses revealed trend-level inverse associations between Omax and Intensity in relation to delay duration and significant positive associations between subjective craving, Omax, and Elasticity in relation to the number of cigarettes purchased. CONCLUSIONS The results from this study provide further evidence for the utility of behavioral economic concepts and methods in understanding smoking motivation. These data also reveal the incremental contribution of behavioral economic indices beyond subjective craving in predicting in vivo cigarette consumption. Relationships to previous studies and methodological considerations are discussed.
Superconductivity induced by Ni doping in BaFe2As2 single crystals

A series of 122 phase BaFe2−xNixAs2 (x=0, 0.055, 0.096, 0.18 and 0.23) single crystals was grown by the self-flux method and a dome-like Ni doping dependence of the superconducting transition temperature was discovered. The transition temperature Tcon reaches a maximum of 20.5 K at x=0.096, and it drops to below 4 K as x⩾0.23. The negative thermopower in the normal state indicates that the electron-like charge carrier indeed dominates in this system. This Ni-doped system provides another example of superconductivity induced by electron doping in the 122 phase.
Effect of estrogen and dietary loading on condylar cartilage.

AIMS To study the effect of estrogen deficiency and altered temporomandibular joint loading on the histomorphology of condylar cartilage and on the expression of types II and X collagen and matrix metalloproteinase-3 (MMP-3). METHODS Thirty-six female rats were divided into four groups: ovariectomized rats on a normal diet, nonovariectomized control rats on a normal diet, ovariectomized rats on a soft diet, and nonovariectomized control rats on a soft diet. Ovariectomy was performed at the age of 60 days. Repeated-measures ANOVA was used to analyze the data. RESULTS The condylar cartilage in the ovariectomized normal diet group showed a significantly higher number of cells than in the nonovariectomized control rats (P < .001). The proportional amount of MMP-3 expression was significantly higher in the ovariectomized rats than in the nonovariectomized control rats in both diet groups (P < .001). The area covered by types II and X collagen was significantly higher in the experimental groups than in the control groups (P < .01). CONCLUSION Condylar cartilage is sensitive to both estrogen level and dietary loading.
Finite element method analysis of stress distribution to supporting tissues in a Class IV Aramany removable partial denture (Part II: bone and mucosal membrane).

AIM One of the most important issues in the design of removable partial dentures (RPD) is the location of retentive arms to provide sufficient support. This is a critical factor in patients with less supporting tissue and abutment teeth. Patients classified as Class IV Aramany need special attention in this area of RPD design to minimize the stress distribution in bone and mucosal membrane. Using the finite element method, the aim of this study was to analyze the distribution stress to supporting tissues when a Class IV Aramany RPD is worn. The data presented in this report are the effects of the stress on bone and mucosal membranes. Results on teeth and the periodontal ligament have been previously reported. METHODS AND MATERIALS Three dimensional finite element models were constructed using normal dimensions. Exact physiology and morphology of teeth and the remaining palate were simulated to that of a maxillectomy patient. Three RPD designs with circumferential cast retainers were examined: buccal retention and palatal reciprocation (P1); palatal retention and buccal reciprocation (P2); and buccal and palatal retention (P3). After completion of the models and remaining palate, each RPD design was loaded under 53N and stress was applied in three different directions: vertical to the posterior teeth (premolar and first molars) of the RPD (F1); at a 33 masculine angle to the posterior teeth (premolar and first molars) of the RPD (F2); and vertically on the anterior teeth (central incisors) of the RPD (F3). The stress distribution in the RPD models on cortical and cancellous bone and the mucosal membrane was analyzed using von Mises criterion. RESULTS The maximum tension in cortical bone (70.84 Mpa) was observed when a 53N force was applied in a vertical direction to posterior teeth (F2) using buccal and palatal retention (P3). Minimum tension (15.73 Mpa) in cortical bone was observed using the F3 load on the P2 design. Similar results were seen in cancellous bone, with the highest stress (8.01 Mpa) observed using F2 load on the P3 design and the lowest stress (3.04 Mpa) observed using the F3 load on the P2 design. For mucosal membrane, the maximum (3.57 Mpa) and minimum (3.05 Mpa) stress was observed using the F3 load on the P3 design and the F1 load on the P2 design, respectively. The average stress in all RPD designs was 3 Mpa. CONCLUSION The design demonstrating the least tension in cortical and cancellous bone and mucosal membrane was the P2 design, a RPD with palatal retention and buccal reciprocation. CLINICAL SIGNIFICANCE Palatal retention and buccal reciprocation (P2 design) is recommended for patients with maxillofacial RPDs.
Improvement and transcriptome analysis of root architecture by overexpression of Fraxinus pennsylvanica DREB2A transcription factor in Robinia pseudoacacia L. ‘Idaho’

Summary Transcription factors play a key role to enable plants to cope with abiotic stresses. DREB2 regulates the expression of several stress‐inducible genes and constitutes major hubs in the water stress signalling webs. We cloned and characterized a novel gene encoding the FpDREB2A transcription factor from Fraxinus pennsylvanica, and a yeast activity assay confirmed its DRE binding and transcription activation. Overexpression of FpDREB2A in R. pseudoacacia showed enhanced resistance to drought stress. The transgenic plant survival rate was significantly higher than that of WT in soil drying and re‐watering treatments. Transgenic lines showed a dramatic change in root architecture, and horizontal and vertical roots were found in transgenic plants compared to WT. The vertical roots penetrated in the field soil to more than 60 cm deep, while horizontal roots expanded within the top 20–30 cm of the soil. A physiological test demonstrated that chlorophyll contents were more gradually reduced and that soluble sugars and proline levels elevated more sharply but malondialdehyde level stayed the same (P < 0.05). Plant hormone levels of abscisic acid and IAA were higher than that of WT, while gibberellins and zeatin riboside were found to be lower. The root transcriptomes were sequenced and annotated into 2011 differential expression genes (DEGs). The DEGs were categorized in 149 pathways and were found to be involved in plant hormone signalling, transcription factors, stimulus responses, phenylalanine, carbohydrate and other metabolic pathways. The modified pathways in plant hormone signalling are thought to be the main cause of greater horizontal and vertical root development, in particular.