Miracle-dz/UniFAR-FTUs huggingface dataset:
Overweight children, weight-based teasing and academic performance.

BACKGROUND School performance of overweight children has been found to be inferior to normal weight children; however, the reason(s) for this link between overweight and academic performance remain unclear. Psychosocial factors, such as weight-based teasing, have been proposed as having a possible mediating role, although they remain largely unexplored. METHODS Random parental telephone survey data (N=1 071) of public school students collected as part of the statewide evaluation of Arkansas Act 1220, a law to reduce childhood obesity, were used. Overweight status (body mass index > 85th percentile for gender and age) and weight-based teasing were examined as predictors of poorer school performance. RESULTS Overweight status was a significant predictor of poorer school performance (OR=1.51; 95% CI=1.01, 2.25), after adjustment for gender, school level, free and reduced lunch participation, and race. However, the addition of weight-based teasing to the model (with weight category and covariates) reduced the weight category parameter estimate by 24%, becoming non-significant (OR=1.40; 95% CI=0.93, 2.10) and indicating a possible mediating effect of weight-based teasing on the relationship between weight category and school performance. Weight-based teasing was significantly associated with school performance, with lower odds of strong school performance among weight-based teased children (OR=0.44; 95% CI=0.27, 0.74). CONCLUSION Psychosocial variables, such as weight-based teasing, should be considered in future research examining the impact of childhood obesity on school performance and in future intervention studies.
A Super-Resolution Algorithm Based on Adaptive Total Variation Regularization

An algorithm with L1 and L2 mixed norm and bilateral total variation(BTV) regularization is proposed in this paper for image super-resolution. First, the mixed norm is used as the constraint of image fidelity; Secondly, considering the effect of the BTV method is not ideal for reconstruction in the edge and texture region, an adaptive regularization parameter algorithm is proposed. In the proposed algorithm, the local structure information of image is used to control the shape and the regularization parameter, which can be adjusted adaptively according to the local structure information of the image; Finally, a minimum gradient descent algorithm is used to update the algorithm. Experimental results show that the proposed algorithm can not only reduce the mean square error, improve the peak signal to noise ratio, but also can effectively smooth Gaussian noise and salt and pepper noise, maintain the image edges and texture details.
3D Face Recognition Using Two Views Face Modeling and Labeling

The ability to distinguish different people by using 3D facial information is an active research problem being undertaken by the face recognition community. In this paper, we propose to use a generic model to label the 3D facial features. This approach relies on our realistic face modeling technique, by which the individual face model is created using a generic model and two views of a face. In the individualized model, we label the face features by their maximum and minimum curvatures. Among the labeled features, the "good features" are selected by using a Genetic Algorithm based approach. The feature space is then formed by using these new 3D shape descriptors, and each individual face is classified according to its feature space correlation. We applied 72 individual models for the test. The experimental results show that the shape information obtained from the 3D individualized model can be used to classify and identify individual facial surfaces. The rank-four correct recognition rate is about 92%. The 3D individualized model provides consistent and sufficient details to represent individual faces while using a much more simpli? ed representation than the range data models. This work provides the possibility to reduce the complexity of 3D data processing, and is feasible for real applications such as in a non-cooperative imaging circumstance or in the situation when range data using 3D scanners are not possible to acquire.
RNA Polymerase Sigma Factor That Blocks Morphological Differentiation by Streptomyces coelicolor

ABSTRACT The filamentous bacterium Streptomyces coelicolorundergoes a complicated process of morphological differentiation that begins with the formation of an aerial mycelium and culminates in sporulation. Genes required for the initiation of aerial mycelium formation have been termed bld (bald), describing the smooth, undifferentiated colonies of mutant strains. By using an insertional mutagenesis protocol that relies on in vitro transposition, we have isolated a bld mutant harboring an insertion in a previously uncharacterized gene, SCE59.12c, renamed here rsuA. The insertion mutant exhibited no measurable growth defect but failed to produce an aerial mycelium and showed a significant delay in the production of the polyketide antibiotic actinorhodin. The rsuA gene encodes an apparent anti-sigma factor and is located immediately downstream ofSCE59.13c, renamed here sigU, whose product is inferred to be a member of the extracytoplasmic function subfamily of RNA polymerase sigma factors. The absence ofrsuA in a strain that contained sigUcaused a block in development, and the overexpression ofsigU in an otherwise wild-type strain caused a delay in aerial mycelium formation. However, a strain in which bothrsuA and sigU had been deleted was able to undergo morphological differentiation normally. We conclude that thersuA-encoded anti-sigma factor is responsible for antagonizing the function of the sigma factor encoded bysigU. We also conclude that thesigU-encoded sigma factor is not normally required for development but that its uncontrolled activity obstructs morphological differentiation at an early stage.
Analysis of memristive nonlinear circuits

This article presents a substantial review of nonlinear memristive circuits based on Zdenek BIOLEK model alonside an innovator design developed within the Hewlett-Packard laboratories. HP realized a physical implementation of memristors by placing two layers of titanium dioxide between two electrodes. The first layer is partially doped with oxygen gaps and behaves like a semiconductor and the second layer of pure titanium dioxide acts as an insulating layer. Furthermore, this paper describes a possible use of memristors in logic gates construction, the analysis being carried out in LTSpice program using state equations and formulas describing the boundary effects. Two memristors connected in series having opposite polarities are used to implement the logic gates. Such devices are used in this case only to ensure the switching phenomenon and not to store logic states, similar to already existing CMOS logic circuits. The LTspice models of the memristor and memristive logic gates are designed in such a way that it enables easy modification of the nonlinear relations describing the boundary effects by changing the initial parameters. Hence memristors have a high potential for innovation in the electronics industrial applications, especially because these devices can remember the stored information even though they no longer have a voltage supply.
ESR of Fe‐Filled Multi‐Walled Carbon Nanotubes

Abstract The properties of multi‐walled carbon nanotubes filled with iron, which is assembled in nanowires inside the nanotubes, were studied with electron spin resonance and conductivity methods. The low‐temperature decrease of magnetization in zero‐field cooled samples was found depending on the relative orientation of magnetization and the nanotube axes. The azimuthal variation of magnetization can be ascribed to inhomogeneous arrangement of Fe inside the nanotubes, that can be also concluded from the conductivity and spectroscopy measurements.
WAVELET BASED SEGMENTATION USING OPTIMAL STATISTICAL FEATURES ON BREAST IMAGES

Elastography is the emerging imaging modality that analyzes the stiffness of the tissue for detecting and classifying breast tumors. Computer-aided detection speeds up the diagnostic process of breast cancer improving the survival rate. A multiresolution approach using Discrete wavelet transform is employed on real time images, using the low-low (LL), low-high (LH), high-low (HL), and high-high (HH) sub-bands of Daubechies family. Features are extracted, selected and then finally segmented by K-means clustering algorithm. The proposed work can be extended to Classification of the tumors.
Bladder segmentation in MR images with watershed segmentation and graph cut algorithm

Prostate and cervix cancer diagnosis and treatment planning that is based on MR images benefit from superior soft tissue contrast compared to CT images. For these images an automatic delineation of the prostate or cervix and the organs at risk such as the bladder is highly desirable. This paper describes a method for bladder segmentation that is based on a watershed transform on high image gradient values and gray value valleys together with the classification of watershed regions into bladder contents and tissue by a graph cut algorithm. The obtained results are superior if compared to a simple region-after-region classification.
Simulation of Single Particle Displacement Damage in Silicon–Part II: Generation and Long-Time Relaxation of Damage Structure

A statistical study of displacement cascades induced by silicon Primary Knock-on Atoms (PKA) in bulk silicon is performed by running a large number of molecular dynamics (MD) simulations. The choice of the PKA species and energy varying from 1 to 100 keV comes from a previous particle-matter simulation [1]. The electronic stopping power missing in standard MD simulations is here taken into account using the Two Temperature Model (TTM). This prevents from overestimating the number of created defects. The damaged atomic structures obtained after one nanosecond of MD simulation are not representative of what is observed in image sensors for example after several minutes. For this reason, the kinetic Activation Relaxation Technique (k-ART) is used in a second step, allowing to access longer simulation times of up to second. The obtained damaged structures can then be compared with experimental observations. Analyses reveal two possible links between the simulated structures and the measurements in solid-state image sensors. First, the cluster size distribution exhibits a shape similar to the measured exponential distribution of Dark Current (DC). Second, the temporal evolution of metastable atomic configurations resembles experimental DC-Random-Telegraph-Signals.
An Upper Ontology for E-Learning Material Semantic Annotations

Recent research reveals a great interest to introduce the Semantic Web as a promising technology for realizing eLearning requirements. The new, dynamic and distributed business world has motivated the research on developing eLearning. ELearning is efficient, task relevant and just-in-time learning. It gives the learner the ability to efficiently access the related educational resources just-in-time from any place. The vision of the Semantic Web is to make the Web data not only processable but also understandable so it can be used by machines not just for display purposes but for automation, integration and reuse of data across various applications. This study investigates the role of Semantic Web in realizing the e-learning requirements. It proposes an ontology-based e-learning framework that considers the main three component roles of the e-learning architecture: an author, a learner and a repository. The study also shed the light on improving the conventional metadata standards that are used to describe learning materials by proposing a semantic-based ontology to describe three different dimensions of the learning material: content, context and structure. Adopting the proposed ontology would result in facilitating both the process of finding suitable learning materials to build up a certain course and the process of navigating through the learning course.
A Globally Convergent Algorithm for Range Image Registration Based on Consistency Evaluation of Rigid Transformation of Correspondences

In this paper, a globally convergent algorithm for registration of two range images is proposed which ﬁnds the consistent combinations of the corresponding feature point pairs with largest similarity by formulating as graph-based optimization problem. Our algorithm evaluates the consistency of rigid transformations be-tween triplets of feature point pairs. While the number of the all possible triplets of feature point pairs are very large, we reduce the candidates of the triplets based on the shape consistency, one-to-one correspondence assumption, and disntance consistency of all pairs of feature points. By introducing the graph kernel algorithm, the globally optimal combination of the triplets of feature point pairs is found by evaluating the similarity robustly using SIFT.
The Role of Surgery in the Management of American Burkitt's Lymphoma and Its Treatment

Ninety-two patients with American Burkitt's lymphoma were studied retrospectively to elucidate the role of surgery in the complications of treatment of Burkitt's lymphoma. All of the patients reviewed had been treated with at least one chemotherapeutic agent. Seventy-five percent of the patients had predominantly abdominal disease that required a laparotomy for diagnosis and treatment when possible. The postoperative complications, such as infections, were not more frequent when compared with other elective surgical procedures. Ten percent of all the patients had episodes of significant gastrointestinal bleeding secondary to disease or to the chemotherapy. One patient was treated surgically, and two patients had fatal hemorrhages. Further abdominal complications that required surgery included intussusception, cholelithiasis, small bowel obstruction, and bowel perforation. The incidence of renal failure because of electrolyte imbalance from tumor lysis syndrome was 30%. One third of these patients required access for dialysis. Ten percent of patients developed hemorrhagic cystitis, but none required surgery. Surgery was necessary in five patients with life-threatening pericardial effusion. Other surgical treatments are also reviewed. It is concluded that Burkitt's lymphoma has a significant cure rate with the appropriate medical and surgical therapies, and that the surgical approach to the disease and its complications should be optimistic and appropriately aggressive.
Norm-preserving Orthogonal Permutation Linear Unit Activation Functions (OPLU)

We propose a novel activation function that implements piece-wise orthogonal non-linear mappings based on permutations. It is straightforward to implement, and very computationally efficient, also it has little memory requirements. We tested it on two toy problems for feedforward and recurrent networks, it shows similar performance to tanh and ReLU. OPLU activation function ensures norm preservance of the backpropagated gradients, therefore it is potentially good for the training of deep, extra deep, and recurrent neural networks.
Type I Cytokines Synergize with Oncogene Inhibition to Induce Tumor Growth Arrest

Acquavella, Clever, and colleagues show that IFNγ and TNFα synergize with vemurafenib to induce tumor growth arrest, supporting further study of the intersection between immunologic and oncogenic signaling in cancer cells and of treatment strategies combining vemurafenib and T-cell–based immunotherapy. Both targeted inhibition of oncogenic driver mutations and immune-based therapies show efficacy in treatment of patients with metastatic cancer, but responses can be either short lived or incompletely effective. Oncogene inhibition can augment the efficacy of immune-based therapy, but mechanisms by which these two interventions might cooperate are incompletely resolved. Using a novel transplantable BRAFV600E-mutant murine melanoma model (SB-3123), we explored potential mechanisms of synergy between the selective BRAFV600E inhibitor vemurafenib and adoptive cell transfer (ACT)–based immunotherapy. We found that vemurafenib cooperated with ACT to delay melanoma progression without significantly affecting tumor infiltration or effector function of endogenous or adoptively transferred CD8+ T cells, as previously observed. Instead, we found that the T-cell cytokines IFNγ and TNFα synergized with vemurafenib to induce cell-cycle arrest of tumor cells in vitro. This combinatorial effect was recapitulated in human melanoma–derived cell lines and was restricted to cancers bearing a BRAFV600E mutation. Molecular profiling of treated SB-3123 indicated that the provision of vemurafenib promoted the sensitization of SB-3123 to the antiproliferative effects of T-cell effector cytokines. The unexpected finding that immune cytokines synergize with oncogene inhibitors to induce growth arrest has major implications for understanding cancer biology at the intersection of oncogenic and immune signaling and provides a basis for design of combinatorial therapeutic approaches for patients with metastatic cancer. Cancer Immunol Res; 3(1); 37–47. ©2014 AACR. See related commentary by Riddell, p. 23
Hidden Markov Model based Credit Card Fraud Detection System with Time Stamp and IP Address

The evolution of the new technology supports the online transactions to be held with the assistance of different payment cards. Credit card frauds have become increasingly rampant in living years and critical for banks to enhance fraud detection so as to protect their cardholders from financial loss. The simple way to detect such kind of fraud is to decipher the spending pattern on each card and to highlight any irregularity with respect to the “standard” spending pattern. In this paper we try to review Hidden Markov model which works on such technique. The HMM, trained with the normal behavior of a cardholder needs an enough number of normal transactions and fraud transactions for learning fraud patterns. To make it more effective we have enclosed the provision of determining the IP address of intruder machine along with its time stamp. The simulation analysis include different real dataset to identify the fraud and discover the intruder. Form our model it is proven that it works with more efficiency than existing models.
Structure and properties of compatibilized blends of polyamide‐6 and ABS

Mechanical and Morphological properties of polyamide-6/ABS blend systems, compatibilized by styrene-maleic anhydride (SMA) copolymer, have been studied. The strength, modulus, and impact properties improved upon the addition of SMA. Morphological studies, using small angle light scattering, polarizing microscopy, and scanning electron microscopy, showed that SMA acts as a compatibilizer for the above system. © 1993 John Wiley & Sons, Inc.
Multicast-based inference of network-internal delay distributions

Packet delay greatly influences the overall performance of network applications. It is therefore important to identify causes and locations of delay performance degradation within a network. Existing techniques, largely based on end-to-end delay measurements of unicast traffic, are well suited to monitor and characterize the behavior of particular end-to-end paths. Within these approaches, however, it is not clear how to apportion the variable component of end-to-end delay as queueing delay at each link along a path. Moreover, there are issues of scalability for large networks.In this paper, we show how end-to-end measurements of multicast traffic can be used to infer the packet delay distribution and utilization on each link of a logical multicast tree. The idea, recently introduced in [3] and [4], is to exploit the inherent correlation between multicast observations to infer performance of paths between branch points in a tree spanning a multicast source and its receivers. The method does not depend on cooperation from intervening network elements; because of the bandwidth efficiency of multicast traffic, it is suitable for large-scale measurements of both end-to-end and internal network dynamics. We establish desirable statistical properties of the estimator, namely consistency and asymptotic normality. We evaluate the estimator through simulation and observe that it is robust with respect to moderate violations of the underlying model.
Model Estimation of Water Use Efficiency for Soil Conservation in the Lower Heihe River Basin, Northwest China during 2000–2008

There has been very limited research on water use efficiency for soil conservation (WUE-SC) in typical water scarce regions such as the lower Heihe River Basin, where there is serious wind erosion and the soil conservation service plays a key role in guaranteeing the ecological safety of Northern China. The soil conservation service, which was represented by the soil conservation amount (SC), was first estimated with an experiment-based model in this study. Then, the WUE-SC ( i.e. , SC/ET) was calculated on the basis of evapotranspiration (ET) data, and management implications were finally discussed. The results indicated the WUE-SC ranged between 0–98.69 t mm −1 , and it first decreased and then increased on the whole during 2000–2008. Besides, the inter-annual variation of WUE-SC was mainly due to change in the potential soil loss. In addition, the WUE-SC showed significant spatial heterogeneity, and the average WUE-SC of the whole study area was very low due to spatiotemporal inconsistency between the potential soil loss and the vegetation coverage rate. Although there are some uncertainties, these results still can provide local managers with valuable information for water resource utilization and ecosystem management to improve water use efficiency.
Properties of a Primer RNA-DNA Hybrid at the Mouse Mitochondrial DNA Leading-strand Origin of Replication*

Primers for vertebrate mitochondrial leading-strand DNA replication are products of transcription synthesized by mitochondrial RNA polymerase. The precursor primer RNA exists as a persistent RNA-DNA hybrid, known as an R-loop, formed during transcription through the replication origin (Xu, B., and Clayton, D. A. (1996) EMBO J. 15, 3135-3143). In an effort to examine the precise structure of this primer RNA intermediate, we have used two methods to reconstitute model R-loops containing the mouse mitochondrial DNA origin sequence. First, we demonstrate that bacteriophage SP6 RNA polymerase can efficiently catalyze the formation of an R-loop at the mouse mtDNA origin sequence. Second, the R-loop can be assembled by annealing presynthesized RNA and supercoiled DNA template in the presence of formamide. R-loop formation by either method is dependent on specific template sequences. The reconstituted R-loop is exceptionally stable and exhibits an unexpected structure. Structural studies indicate that the RNA strand is organized within the RNA-DNA base-paired region, suggesting that the heteroduplex interaction occurs through a specific conformation. We propose that the organized structure of the R-loop is critical for primer RNA function in vivo with important implications for the RNA processing and DNA replication machinery.