Miracle-dz/UniFAR-FTUs huggingface dataset:
Kernel and Range Approach to Analytic Network Learning

The problem of machine learning has been traditionally formulated as an optimization task where an error metric is minimized. In terms of solving the system of linear equations, an approximation is often sought-after according to a least error metric because it is difficult to have an exact match between the sample size and the number of model parameters. Such an approximation to the least error metric, particularly in the squared error form, can be determined analytically either in the primal solution space or in the dual solution space depending on the rank property of the covariance matrix. This optimization approach has been a popular choice due to its simplicity and tractability in analysis and implementation. The approach is predominant in engineering applications as evident from its pervasive adoption in statistical and shallow network learning.
Exploring Model-to-Model Transformations for RIA Architectures by means of a Systematic Mapping Study

This study focuses on model-to-model – M2M – transformations, as part of the Model-Driven Development – MDD – approach, for Rich Internet Applications – RIA. The main aim of this study is to identify ﬁelds that require further contributions, and/or research opportunities in the previously mentioned context. We applied mapping studies techniques, since these techniques use the same basic methodology as reviews but are more general and aimed at discovering what the research trends are, allowing to identify gaps in the literature. From an initial set of 132 papers, we selected 30 papers ﬁrst. Then, thanks to experts’ suggestion, we added 3 additional papers. Therefore, we considered 33 research papers. The performed analysis led to various considerations. Among the important ones, we can mention: there are many newly proposed methods, the scarcity of rigorous and formal validation of such methods, the problem of the portability of Platform Independent Models – PIM, and the low number of tools available for MDD.
Pedestrian detection with dilated convolution, region proposal network and boosted decision trees

With the rapid development of driverless cars, pedestrian detection has been a canonical instance of object detection. Although recent deep learning detectors such as RPN+BF and MS-CNN have shown excellent performance for pedestrian detection, they have limited success for detecting pedestrian, and the importance of final feature receptive field has been awared by previous leading deep learning pedestrian detectors. Applying the dilated convolution to the feature learning of pedestrian detection, we constructed a pedestrian detection framework along with the region proposal network and boosted decision trees. Pipeline of our proposed framework can be briefly generalized as follows: firstly, the fine-tuned RPN with specified aspect ratio is used to get boxes and scores. Secondly, the designed dilated convolution feature extraction model is used to get features. As different dilation factors provide different receptive field scales, we concat the features of different layers with the dilated convolutional features to get the final features. Finally, the candidate boxes are sent to the boosted decision trees to be classified using the scores and features. We evaluated our method on the Caltech Pedestrian Detection Benchmark. Comparing with other state-of-the-art detection methods, the proposed framework with dilated convolution has better performance.
Exploration and optimization of a homogeneous Mesh of Clusters-based FPGA architectures

This paper presents an efficient interconnect network for Mesh of Clusters (MoC) Field-Programmable Gate Array (FPGA) architecture. Compared to conventional MoC-based FPGA, proposed architecture improves the MoC-based interconnect in 2 ways. First, we optimize the intra-cluster interconnect topology by depopulating the intra-cluster full crossbar. Then, we propose a new multi-levels interconnect for the Switch Box (SB) which unifies a downward and an upward unidirectional networks based on the Butterfly-Fat-Tree (BFT) topology. The comparison with the common MoC-based VPR-Style shows that the proposed MoC-based architecture has better area and power efficiency. To optimize the interconnect flexibility of the proposed MoC-based FPGA, we explored and analysed the effect of different architecture parameters on performance, power consumption and density. Experimental results show that architecture parameters can be tuned and adapted to satisfy different specific applicative constraints. Results also show that cluster size 8 presents the best trade-off.
Syntactic probabilities affect pronunciation variation in spontaneous speech

Abstract Speakers frequently have a choice among multiple ways of expressing one and the same thought. When choosing between syntactic constructions for expressing a given meaning, speakers are sensitive to probabilistic tendencies for syntactic, semantic or contextual properties of an utterance to favor one construction or another. Taken together, such tendencies may align to make one construction overwhelmingly more probable, marginally more probable, or no more probable than another. Here, we present evidence that acoustic features of spontaneous speech reflect these probabilities: when speakers choose a less probable construction, they are more likely to be disfluent, and their fluent words are likely to have a relatively longer duration. Conversely, words in more probable constructions are shorter and spoken more fluently. Our findings suggest that the differing probabilities of a syntactic construction in context are not epiphenomenal, but reflect a part of a speakers' knowledge of their language.
Self-Generated Dataset for Category and Pose Estimation of Deformable Object

This work considers the problem of garment handling by a general household robot that focuses on the task of classification and pose estimation of a hanging garment in unfolding procedure. Classification and pose estimation of deformable objects such as garment are considered a challenging problem in autonomous robotic manipulation because these objects are in different sizes and can be deformed into different poses when manipulating them. Hence, we propose a self-generated synthetic dataset for classifying the category and estimating the pose of garment using a single manipulator. We present an approach to this problem by first constructing a garment mesh model into a piece of garment that crudely spread-out on the flat platform using particle-based modeling and then the parameters such as landmarks and robotic grasping points can be estimated from the garment mesh model. Later, the spread-out garment is picked up by a single robotic manipulator and the 2D garment mesh model is simulated in 3D virtual environment. A dataset of hanging garment can be generated by capturing the depth images of real garment at the robotic platform and also the images of garment mesh model from offline simulation respectively. The synthetic dataset collected from simulation shown the approach performed well and applicable on a different of similar garment. Thus, the category and
Developing a Short Multidimensional Measure of Pain Self-efficacy: The Chronic Pain Self-efficacy Scale-Short Form.

BACKGROUND AND OBJECTIVES The 22-item Chronic Pain Self-efficacy Scale (CPSS) measures three domains of pain self-efficacy: pain management, physical functioning, and coping with symptoms. This study aims to develop a short form (CPSS-SF) that retains the multidimensional structure of the instrument. RESEARCH DESIGN AND METHODS Six hundred sixty-four community-dwelling Chinese older adults aged 60-95 years with chronic pain completed a survey. Confirmatory factor analysis (CFA) was conducted on the 22-item CPSS. Regression analyses were performed to examine the items' correlations with criterion variables. After CPSS-SF items were selected, the performance of CPSS-SF subscales in terms of accounting for pain-related outcomes was compared with the full version. RESULTS CFA supported a modified 3-factor model of the CPSS. On the basis of factor loadings on the 3 dimensions and the items' correlations with pain intensity and pain disability, 11 items were selected for the CPSS-SF, which correlated at . 97 with the full version. Regression analyses showed that the associations of the CPSS-SF subscales with pain intensity, pain disability, depressive symptoms, instrumental activities of daily living, and physical and mental health-related quality of life, were indistinguishable from their full-version counterparts. DISCUSSION AND IMPLICATIONS The CPSS-SF is a valid instrument that can be used in lieu of the full scale. Its availability will facilitate the assessment of pain self-efficacy in research and clinical settings due to its brevity but strong psychometric properties. However, the current evidence is limited to Chinese older adults; more research is needed to ascertain its validity in other age and cultural groups.
Eliciting Life Priorities of Older Adults Living in Permanent Supportive Housing.

BACKGROUND AND OBJECTIVES Adults who have experienced chronic homelessness are considered to be "old" by age 50 due to accelerated aging. While permanent supportive housing (PSH) has been found effective for these individuals, there is limited focus on the needs of adults "aging in place" in PSH. This study examined (1) how older adults in PSH identify and rank their life priorities, (2) how they describe these priorities in their own words, and (3) how life course adversity deepens an understanding of these priorities. RESEARCH DESIGN AND METHODS A convergent parallel mixed methods design was used in which qualitative case study analyses informed by a life course perspective provided a deeper understanding of how 14 older residents of PSH viewed their life priorities using quantitative card-sort rankings of 12 life domains. RESULTS Housing, family, mental health, physical health, and partner were the most frequently endorsed life priorities. Four themes emerged from the cross-case analyses: "aging in, aging out," "carefully restoring relationships," "life goes on," and "housing is fundamental. " Convergent findings indicated that life adversity-social losses and interrupted lives-influenced both the high- and low-ranked card-sort priorities. DISCUSSION AND IMPLICATIONS This study demonstrated that participants were aware of their advancing years yet they sought to overcome adversity and losses through maintaining mental health and sobriety, improving physical health, and cautiously rebuilding relationships. As the numbers of older homeless rise, the inclusion of age-related services will be an important component of PSH services for residents as they age.
Prediction of Human Pharmacokinetics of Antibody–Drug Conjugates From Nonclinical Data

Prediction of human pharmacokinetics (PK) based on preclinical information for antibody–drug conjugates (ADCs) provide important insight into first‐in‐human (FIH) study design. This retrospective analysis was conducted to identify an appropriate scaling method to predict human PK for ADCs from animal PK data in the linear range. Different methods for projecting human clearance (CL) from animal PK data for 11 ADCs exhibiting linear PK over the tested dose ranges were examined: multiple species allometric scaling (CL vs. body weight), allometric scaling with correction factors, allometric scaling based on rule of exponent, and scaling from only cynomolgus monkey PK data. Two analytes of interest for ADCs, namely total antibody and conjugate (measured as conjugated drug or conjugated antibody), were assessed. Percentage prediction errors (PEs) and residual sum of squares (RSS) were compared across methods. Human CL was best estimated using cynomolgus monkey PK data alone and an allometric scaling exponent of 1.0 for CL. This was consistently observed for both conjugate and total antibody analytes. Other scaling methods either underestimated or overestimated human CL, or produced larger average absolute PEs and RSS. Human concentration‐time profiles were also reasonably predicted from the cynomolgus monkey data using species‐invariant time method with a fixed exponent of 1.0 for CL and 1.0 for volume of distribution. In conclusion, results from this retrospective analysis of 11 ADCs indicate that allometric scaling of CL with an exponent of 1.0 using cynomolgus monkey PK data alone can successfully project human PK profiles of an ADC within linear range.
Construction of 4D infant cortical surface atlases with sharp folding patterns via spherical patch‐based group‐wise sparse representation

4D (spatial + temporal) infant cortical surface atlases covering dense time points are highly needed for understanding dynamic early brain development. In this article, we construct a set of 4D infant cortical surface atlases with longitudinally consistent and sharp cortical attribute patterns at 11 time points in the first six postnatal years, that is, at 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, and 72 months of age, which is targeted for better normalization of the dynamic changing early brain cortical surfaces. To ensure longitudinal consistency and unbiasedness, we adopt a two‐stage group‐wise surface registration. To preserve sharp cortical attribute patterns on the atlas, instead of simply averaging over the coregistered cortical surfaces, we leverage a spherical patch‐based sparse representation using the augmented dictionary to overcome the potential registration errors. Our atlases provide not only geometric attributes of the cortical folding, but also cortical thickness and myelin content. Therefore, to address the consistency across different cortical attributes on the atlas, instead of sparsely representing each attribute independently, we jointly represent all cortical attributes with a group‐wise sparsity constraint. In addition, to further facilitate region‐based analysis using our atlases, we have also provided two widely used parcellations, that is, FreeSurfer parcellation and multimodal parcellation, on our 4D infant cortical surface atlases. Compared to cortical surface atlases constructed with other methods, our cortical surface atlases preserve sharper cortical folding attribute patterns, thus leading to better accuracy in registration of individual infant cortical surfaces to the atlas.
Metabolic equivalents of body weight resistance exercise with slow movement in older adults using indirect calorimetry.

We examined the METs of body weight resistance exercise with slow movement in older adults using indirect calorimetry. Thirteen men and seven women participated (mean age, 70.8 ± 4.8 years); they performed four exercises (squat, knee push-up, crunch, and heel-raise). Squat was categorized 3.6 to 3.8 METs, whereas knee push-up, crunch, and heel-raise were categorized 2.1 to 3.2 METs based on aerobic energy expenditure. Those values are comparative with those of younger adults.
Psychometric properties of the Cognitive and Behavioural Responses Questionnaire (CBRQ) in adolescents with chronic fatigue syndrome

Abstract Background: To better understand the maintenance of chronic fatigue syndrome (CFS), a valid and reliable measure of cognitive and behavioural responses to symptoms is required. Such a measure could also assess beliefs and coping behaviours in the context of fatigue in other somatic conditions. Aims: We aimed to establish the psychometric properties of both the Cognitive and Behavioural Responses Questionnaire (CBRQ) and its shortened version (CBRQ-S) in adolescents with CFS. Method: The full questionnaire was completed by a clinical cohort of adolescents (n = 121) presenting to specialist CFS units in the UK. Results: Both the CBRQ and CBRQ-S had good internal consistency. The CBRQ scores were strongly associated with depression, anxiety, school and social functioning, but weakly associated with fatigue and physical functioning, providing evidence of validity. Conclusion: Both the 40-item and the 18-item versions of the CBRQ were found to be reliable and valid in adolescents with CFS. To minimize unnecessary burden, the 18-item version is favoured. Using this assessment tool in future studies, including intervention studies, may help to better target interventions during clinical practice and improve outcomes.
Plant traits moderate pollen limitation of introduced and native plants: a phylogenetic meta-analysis of global scale.

•The role of pollination in the success of invasive plants needs to be understood because invasives have substantial effects on species interactions and ecosystem functions. Previous research has shown both that reproduction of invasive plants is often pollen limited and that invasive plants can have high seed production motivating the questions: how do invasive populations maintain reproductive success in spite of pollen limitation? What species traits moderate pollen limitation for invaders? •We conducted a phylogenetic meta-analysis with 68 invasive, 50 introduced non-invasive, and 1931 native plant populations, across a total of 1249 species. •We found that invasive populations with generalist pollination or pollinator dependence were less pollen limited than natives, but invasives and introduced non-invasives did not differ. Invasive species produced 3× fewer ovules/flower and >250× more flowers/plant, compared with their native relatives. While these traits were negatively correlated, consistent with a tradeoff, this did not differ with invasion status. •Invasive plants that produce many flowers and have floral generalization are able to compensate for or avoid pollen limitation, potentially helping explain invaders' reproductive success. This article is protected by copyright. All rights reserved.
Pig Brains Have Homologous Resting-State Networks with Human Brains

Many neurological and psychiatric diseases in humans are caused by disruptions to large-scale functional properties of the brain, including functional connectivity. There has been growing interest in discovering the functional organization of brain networks in larger animal models. As a result, the use of translational pig models in neuroscience has significantly increased in the past decades. The gyrencephalic pig brain resembles the human brain more in anatomy, growth, and development than the brains of commonly used small laboratory animals such as rodents. In this work, resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) data were acquired from a group of pigs (n = 12). rs-fMRI data were analyzed for resting-state networks (RSNs) by using independent component analysis and sparse dictionary learning. Six RSNs (executive control, cerebellar, sensorimotor, visual, auditory, and default mode) were detected that resemble their counterparts in human brains, as measured by Pearson spatial correlations and mean ratios. Supporting evidence of the validity of these RSNs was provided through the evaluation and quantification of structural connectivity measures (mean diffusivity, fractional anisotropy, fiber length, and fiber density) estimated from the DTI data. This study shows that as a translational, large animal model, pigs demonstrate great potential for mapping connectome-scale functional connectivity in experimental modeling of human brain disorders.
The effect of ferulic acid on experimental traumatic brain damage in rats.

AIM Traumatic brain injury is an important social health problem due to the fact that young adults are more likely to be affected, and advanced functional limitations are observed in survivors. In this study, we aimed to investigate the protective effect of ferulic acid in an experimental trauma model. MATERIAL AND METHODS This study was performed in March 2016 at Dokuz Eylül University Experimental Animal Laboratory. Subjects were randomly divided into 4 groups Control, Ethyl Alcohol, Trauma, Trauma/Ferulic Acid groups. For histological findings, Cresyl violet; for immunohistochemical analysis, TUNEL and Active Caspase-3 staining were used. For biochemical analysis, Superoxide dismutase, Malondialdehyde, and Glutathione values ​​were examined. RESULTS The application of ferulic acid has been shown to primarily reduce neuronal apoptosis, the levels of free radicals, and to effect oxidant/antioxidant balance positively by increasing the levels of antioxidants, such as Superoxide dismutase and Glutathione that are developed due to brain damage. Our study group has shown that ferulic acid decreased nerve tissue pathologies after generated brain trauma compared to injury groups. CONCLUSION Addition of ferulic acid to the traditional head trauma treatment has the strength, and ability to increase the rate, and percentage of healing (Tab. 2, Fig. 4, Ref. 28).
Recurrent dislocation of the shoulder.

A review of the pathology, mechanism, and operative treatment of recurrent dislocation of the shoulder, based on an analysis of 180 cases, with 159 operations, is presented. From this analysis the following conclusions have been made and appear to be substantiated: 1. The pathology comprises two important elements: ( a ) anterior detachment of the glenoid labrum from the bone margin of the glenoid, associated with some degree of stripping of the anterior part of the capsule from the front of the neck of the scapula, found in 87 per cent. of cases examined adequately at operation; ( b ) defect or flattening of the posterolateral aspect of the articular surface of the head of the humerus which engages with the glenoid cavity when the arm is in external rotation and abduction; this defect is demonstrated most readily in antero-posterior radiographs taken with the humerus in 60 to 70 degrees of internal rotation and was shown to be present in 82 per cent. of cases which had been subjected to adequate radiographic examination. 2. The frequency of the humeral head defect has been under-estimated in the past, because of the difficulty of demonstrating it, particularly when the defect is small. 3. Either type of lesion alone may predispose to recurrence of the dislocation. 4. Both types of lesion are often present in the same shoulder. When this is the case the tendency to redislocation is great. 5. The initial dislocation, which results in the development of one or both these persistent structural abnormalities, may be due to very different types of injury, the commonest of which is a fall on the outstretched hand. The factor common to all these injuries is a resultant force acting on the humeral head in the direction of the anterior glenoid margin. 6. In the treatment of recurrent dislocation of the shoulder joint the Nicola operation is unreliable, and it may be associated with a recurrence rate as high as 36 per cent. It is believed that continued instability after this operation is usually due to the presence of a defect of the humeral head. 7. Operative treatment should aim at repairing, or nullifying, the effects of both types of lesion. For anterior detachment of the labrum this involves either suturing the labrum back to the glenoid margin, or constructing some form of anterior buttress, fibrous or bony: for humeral head defects it necessitates some procedure designed to limit external rotation, thus preventing the defect from coming into engagement with the glenoid cavity. Such limitation of external rotation does not constitute a significant disability.