Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model

Low-light image enhancement methods based on classic Retinex model attempt to manipulate the estimated illumination and to project it back to the corresponding reflectance. However, the model does not consider the noise, which inevitably exists in images captured in low-light conditions. In this paper, we propose the robust Retinex model, which additionally considers a noise map compared with the conventional Retinex model, to improve the performance of enhancing low-light images accompanied by intensive noise. Based on the robust Retinex model, we present an optimization function that includes novel regularization terms for the illumination and reflectance. Specifically, we use $\ell _{1}$ norm to constrain the piece-wise smoothness of the illumination, adopt a fidelity term for gradients of the reflectance to reveal the structure details in low-light images, and make the first attempt to estimate a noise map out of the robust Retinex model. To effectively solve the optimization problem, we provide an augmented Lagrange multiplier based alternating direction minimization algorithm without logarithmic transformation. Experimental results demonstrate the effectiveness of the proposed method in low-light image enhancement. In addition, the proposed method can be generalized to handle a series of similar problems, such as the image enhancement for underwater or remote sensing and in hazy or dusty conditions.
Anchorage condition during canine retraction using transpalatal arch with continuous and segmented arch mechanics.

OBJECTIVE To compare anchorage condition in cases in which transpalatal arch was used to enhance anchorage in both continuous and segmented arch techniques. MATERIALS AND METHODS Twenty cases that required first premolar extraction for orthodontic treatment and transpalatal arch to enhance anchorage were included in this study. Ten cases were treated using the continuous arch technique, while the other 10 cases were treated using 0.019 × 0.025-inch TMA T-loops with posterior anchorage bend according to the Burstone and Marcotte description. Lateral cephalometric analysis of before and after canine retraction was performed using Ricketts analysis to measure the anteroposterior position of the upper first molar to the vertical line from the Pt point. Data were analyzed using an independent sample t-test. RESULTS There was a statistically significant forward movement of the upper first molar in cases treated by continuous arch mechanics (4.5 ± 3.0 mm) compared with segmented arch mechanics (-0.7 ± 1.4 mm; P = .01). CONCLUSIONS The posterior anchorage bend to T-loop used to retract the maxillary canine can enhance anchorage during maxillary canine retraction.
Predictive factors of sagittal stability after treatment of Class II malocclusions.

OBJECTIVE To determine the existence of factors permitting the prediction of sagittal stability after orthodontic treatment in patients with Angle Class II malocclusion. MATERIALS AND METHODS PubMed, EMBASE, and the Cochrane Library were searched up to March 2015. Inclusion criteria were longitudinal studies with at least 10 subjects investigating associations between at least one factor and stability, with an average minimum follow-up period of 2 years; stability measured using posttreatment sagittal dental changes; and orthodontic treatment including removable and/or fixed appliances with or without extractions. Two reviewers independently selected and assessed the quality of the articles. RESULTS The search strategy resulted in 1372 articles, of which 17 met the inclusion criteria. Large changes during treatment in molar and canine relationships were the only two factors found to be positively associated with relapse, but with limited evidence. Fourteen factors were found not to be predictive of relapse, also with limited evidence. These factors included treatment characteristics, patient pretreatment characteristics, and final posttreatment characteristics. CONCLUSIONS There is currently limited evidence to support the influence of factors predictive of sagittal stability following Class II malocclusion treatment. More high-quality prospective studies are needed, and functional factors possibly affecting relapse also need to be further assessed.
Performance Optimization of Vertical Nanowire‐based Piezoelectric Nanogenerators

The integrated nanogenerator (NG) based on vertical nanowire (NW) arrays is one of the dominant designs developed to harvest mechanical energy using piezoelectric nanostructures. Finite element method (FEM) simulations of such a NG are developed using ZnO NWs in compression mode to evaluate its performances in term of piezoelectric potential generated, capacitance, induced mechanical energy, output electrical energy, and efficiency. This evaluation is essential to correctly understand NG operation. Three main issues are highlighted. The mechanical and electrical structures of the NG as an integrated system are optimized, and strategies for concentrating the mechanical strain field in the NWs and increasing the force sensitivity are developed. In addition, the influence of NWs length and diameter on NG performances is investigated. The optimization results in a piezoelectric nano composite material where global performances are improved by mean of long and thin NWs.
Liver X Receptor–Binding DNA Motif Associated With Atherosclerosis‐Specific DNA Methylation Profiles of Alu Elements and Neighboring CpG Islands

Background The signals that determine atherosclerosis‐specific DNA methylation profiles are only partially known. We previously identified a 29‐bp DNA motif (differential methylation motif [DMM]) proximal to CpG islands (CGIs) that undergo demethylation in advanced human atheromas. Those data hinted that the DMM docks modifiers of DNA methylation and transcription. Methods and Results We sought to functionally characterize the DMM. We showed that the DMM overlaps with the RNA polymerase III–binding B box of Alu short interspersed nuclear elements and contains a DR2 nuclear receptor response element. Pointing to a possible functional role for an Alu DMM, CGIs proximal (<100 bp) to near‐intact DMM–harboring Alu are significantly less methylated relative to CGIs proximal to degenerate DMM–harboring Alu or to DMM‐devoid mammalian‐wide interspersed repeat short interspersed nuclear elements in human arteries. As for DMM‐binding factors, LXRB (liver X receptor β) binds the DMM in a DR2‐dependent fashion, and LXR (liver X receptor) agonists induce significant hypermethylation of the bulk of Alu in THP‐1 cells. Furthermore, we describe 3 intergenic long noncoding RNAs that harbor a DMM, are under transcriptional control by LXR agonists, and are differentially expressed between normal and atherosclerotic human aortas. Notably, CGIs adjacent to those long noncoding RNAs tend to be hypomethylated in symptomatic relative to stable human atheromas. Conclusions Collectively, the data suggest that a DMM is associated with 2 distinct methylation states: relatively low methylation of in cis CGIs and Alu element hypermethylation. Based on the known atheroprotective role of LXRs, we propose that LXR agonist–induced Alu hypermethylation, a landmark of atherosclerosis, is a compensatory rather than proatherogenic response.
Selenoprotein K deficiency inhibits melanoma by reducing calcium flux required for tumor growth and metastasis

Interest has emerged in the therapeutic potential of inhibiting store operated calcium (Ca2+) entry (SOCE) for melanoma and other cancers because malignant cells exhibit a strong dependence on Ca2+ flux for disease progression. We investigated the effects of deleting Selenoprotein K (SELENOK) in melanoma since previous work in immune cells showed SELENOK was required for efficient Ca2+ flux through the endoplasmic reticulum Ca2+ channel protein, inositol 1,4,5-trisphosphate receptor (IP3R), which is due to the role SELENOK plays in palmitoylating and stabilizing the expression of IP3R. CRISPR/Cas9 was used to generate SELENOK-deficiency in human melanoma cells and this led to reduced Ca2+ flux and impaired IP3R function, which inhibited cell proliferation, invasion, and migration. Ca2+-dependent signaling through calcineurin was inhibited with SELENOK-deficiency, and gene array analyses together with evaluation of transcript and protein levels showed altered transcriptional programs that ultimately disrupted stemness and pro-growth properties. In vivo investigations were conducted using the Grm1-Tg transgenic mouse strain that develops spontaneous metastatic melanoma, which was crossed with SELENOK−/− mice to generate the following littermates: Grm1-Tg/SELENOK−/−, Grm1-Tg/SELENOK−/+, Grm1-Tg/SELENOK+/+. SELENOK-deficiency in Grm1-Tg/SELENOK−/− male and female mice inhibited primary tumor growth on tails and ears and reduced metastasis to draining lymph nodes down to levels equivalent to non-tumor control mice. Cancer stem cell pools were also decreased in Grm1-Tg/SELENOK−/− mice compared to littermates. These results suggest that melanoma requires SELENOK expression for IP3R dependent maintenance of stemness, tumor growth and metastasic potential, thus revealing a new potential therapeutic target for treating melanoma and possibly other cancers.
Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing

Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis’s impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain.
Rainbow particle imaging velocimetry for dense 3D fluid velocity imaging

Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. In this work we tackle this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a "rainbow"), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient for tracking 3D trajectories of particles by combining 2D spatial and 1D color information. For reconstruction, we derive an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. We evaluate our method with both simulations and an experimental prototype setup.
Dynamic Sampling Convolutional Neural Networks

We present Dynamic Sampling Convolutional Neural Networks (DSCNN), where the position-specific kernels learn from not only the current position but also multiple sampled neighbour regions. During sampling, residual learning is introduced to ease training and an attention mechanism is applied to fuse features from different samples. And the kernels are further factorized to reduce parameters. The multiple sampling strategy enlarges the effective receptive fields significantly without requiring more parameters. While DSCNNs inherit the advantages of DFN, namely avoiding feature map blurring by position-specific kernels while keeping translation invariance, it also efficiently alleviates the overfitting issue caused by much more parameters than normal CNNs. Our model is efficient and can be trained end-to-end via standard back-propagation. We demonstrate the merits of our DSCNNs on both sparse and dense prediction tasks involving object detection and flow estimation. Our results show that DSCNNs enjoy stronger recognition abilities and achieve 81.7% in VOC2012 detection dataset. Also, DSCNNs obtain much sharper responses in flow estimation on FlyingChairs dataset compared to multiple FlowNet models' baselines.
Exploring input modalities for interacting with augmented paper maps

Interactive geographic maps are today widely available, but remain mostly limited to standard interaction contexts. We introduce a spatial augmented reality map, in which a virtual map is projected on a physical piece of paper. In a preliminary study we compared interaction techniques based on multi-touch, tangible and spatial modalities for three common map functions: zooming, panning, and changing the basemap. Our results suggest that object-based and spatial interaction may be advantageous over multi-touch in our augmented reality setup.
Bone impacted fibular free flap: A novel technique to increase bone density for dental implantation in osseous reconstruction

Fibular free flap (FFF) bone has thick cortical bone surrounding a fatty marrow. The cortex has sufficient density for dental implantation, but the marrow limits bone stock. A novel technique was devised to increase bone density: the bone‐impacted fibular free flap (BIFFF). The purpose of this study was to: (1) describe the BIFFF technique; (2) evaluate the bone density of BIFFF; and (3) evaluate the stability/success of implants placed in BIFFFs.
Fault Location in Ungrounded Photovoltaic System Using Wavelets and ANN

Identifying ground faults is a significant problem in ungrounded photovoltaic (PV) systems because such earth faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short circuit in the system. This paper proposes a novel fault-location scheme in which high frequency noise patterns are used to identify the fault location. The high-frequency noise is generated due to the switching transients of converters combined with the parasitic capacitance of PV panels and cables. Discrete wavelet transform is used for the decomposition of the monitored signal (midpoint voltage of the converters) and features are extracted. Norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, a three-layer feedforward artificial neural networks classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The proposed fault-location scheme has been primarily developed for fault location in the PV farm (PV panels and dc cables). The method is tested for ground faults as well as line–line faults. These faults are simulated with a real-time digital simulator and the data are then analyzed with wavelets. Finally, the effectiveness of the designed fault locator is tested with varying system parameters. The results demonstrate that the proposed approach has accurate and robust performance even with noisy measurements and changes in operating conditions.
Shoulder pain in hemiplegia revisited: contribution of functional electrical stimulation and other therapies.

OBJECTIVES Post-stroke shoulder pain is probably the most frequent complication in hemiplegia and has repercussions on motor rehabilitation and the psychological equilibrium of the patient. The strategies for prevention and treatment are presented. AETIOLOGY Among the various factors contributing to the occurrence of shoulder pain in hemiplegia, some are related to the joint, such as lesion of the rotator cuff tendons, reflex sympathetic dystrophy, inferior-anterior subluxation of the head of the humerus, whereas others are related to the neurologic lesion such as central post-stroke pain, lack of sensibility, unilateral neglect and spasticity. PREVENTION Efforts should be made from the start to keep the shoulder in an ideal position at all times and movement of the shoulder and upper limb should be carried out with care. TREATMENT Will be aimed to the cause of pain and passive or active range of motion exercises will be encouraged. Physical, medical and surgical treatments have improved over the last few decades. Functional electrical stimulation in patients with shoulder pain and subluxation, applied early after onset of the stroke, has shown beneficial positive effects on subluxation, pain and mobility. Efforts should therefore be made to better understand the post-stroke shoulder pain in order to provide better outcomes of rehabilitation and thus improve quality of life for patients.
Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System

A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, “teeth clenching” state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space. In addition, muscle artifact (EMG) of “teeth clenching” condition recorded from EEG signal was detected and employed as interrupter, which can initialize the statement of SPDTBS. Real-time writing task was implemented to verify the reliability of the proposed noninvasive hybrid EEG-EMG-BCI. Eight subjects participated in this study and succeeded to manipulate a robotic arm in 3D space to write some English letters. The mean decoding accuracy of writing task was 0.93 ± 0.03. Four subjects achieved the optimal criteria of writing the word “HI” which is the minimum movement of robotic arm directions (15 steps). Other subjects had needed to take from 2 to 4 additional steps to finish the whole process. These results suggested that our proposed hybrid noninvasive EEG-EMG-BCI was robust and efficient for real-time multidimensional robotic arm control.
Compartmentalization of an all-E. coli Cell-Free Expression System for the Construction of a Minimal Cell

Cell-free expression is a technology used to synthesize minimal biological cells from natural molecular components. We have developed a versatile and powerful all-E. coli cell-free transcription–translation system energized by a robust metabolism, with the far objective of constructing a synthetic cell capable of self-reproduction. Inorganic phosphate (iP), a byproduct of protein synthesis, is recycled through polysugar catabolism to regenerate ATP (adenosine triphosphate) and thus supports long-lived and highly efficient protein synthesis in vitro. This cell-free TX-TL system is encapsulated into cell-sized unilamellar liposomes to express synthetic DNA programs. In this work, we study the compartmentalization of cell-free TX-TL reactions, one of the aspects of minimal cell module integration. We analyze the signals of various liposome populations by fluorescence microscopy for one and for two reporter genes, and for an inducible genetic circuit. We show that small nutrient molecules and proteins are encapsulated uniformly in the liposomes with small fluctuations. However, cell-free expression displays large fluctuations in signals among the same population, which are due to heterogeneous encapsulation of the DNA template. Consequently, the correlations of gene expression with the compartment dimension are difficult to predict accurately. Larger vesicles can have either low or high protein yields.
Prevalence of Burden, Family Dysfunction and Depression in Primary Caregiver of Pediatric Patients with Disabilities

C l i n M e d International Library Citation: Pineda-Frutos MF, Jiménez-Báez MV, Márquez-González H, Jiménez-Márquez A, Jaime-González H, et al. (2016) Prevalence of Burden, Family Dysfunction and Depression in Primary Caregiver of Pediatric Patients with Disabilities. J Fam Med Dis Prev 2:039 Received: May 13, 2016: Accepted: July 16, 2016: Published: July 18, 2016 Copyright: © 2016 Pineda-Frutos MF, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Pineda-Frutos et al. J Fam Med Dis Prev 2016, 2:039
Using RNA-Seq for Genomic Scaffold Placement, Correcting Assemblies, and Genetic Map Creation in a Common Brassica rapa Mapping Population

Brassica rapa is a model species for agronomic, ecological, evolutionary, and translational studies. Here, we describe high-density SNP discovery and genetic map construction for a B. rapa recombinant inbred line (RIL) population derived from field collected RNA sequencing (RNA-Seq) data. This high-density genotype data enables the detection and correction of putative genome misassemblies and accurate assignment of scaffold sequences to their likely genomic locations. These assembly improvements represent 7.1–8.0% of the annotated B. rapa genome. We demonstrate how using this new resource leads to a significant improvement for QTL analysis over the current low-density genetic map. Improvements are achieved by the increased mapping resolution and by having known genomic coordinates to anchor the markers for candidate gene discovery. These new molecular resources and improvements in the genome annotation will benefit the Brassicaceae genomics community and may help guide other communities in fine-tuning genome annotations.