Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting

In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes and performs competitively with C4.5 and other state-of-the-art methods. This classifier has several advantages including robustness and polynomial computational complexity. One limitation of the TAN classifier is that it applies only to discrete attributes, and thus, continuous attributes must be prediscretized. In this paper, we extend TAN to deal with continuous attributes directly via parametric (e.g., Gaussians) and semiparametric (e.g., mixture of Gaussians) conditional probabilities. The result is a classifier that can represent and combine both discrete and continuous attributes. In addition, we propose a new method that takes advantage of the modeling language of Bayesian networks in order to represent attributes both in discrete and continuous form simultaneously, and use both versions in the classification. This automates the process of deciding which form of the attribute is most relevant to the classification task. It also avoids the commitment to either a discretized or a (semi)parametric form, since different attributes may correlate better with one version or the other. Our empirical results show that this latter method usually achieves classification performance that is as good as or better than either the purely discrete or the purely continuous TAN models.
High Prevalence of Antibiotic Resistance and Molecular Characterization of Integrons among Shigella Isolates in Eastern China

ABSTRACT A total of 747 Shigella isolates were collected from hospitals in Jiangsu Province of China. Susceptibilities to antimicrobials and integrons were tested. A total of 78.3% of S. flexneri isolates and a total of 74.3% S. sonei isolates were resistant to at least three antibiotics. Of the Shigella isolates, 74.7% had integron I and 82.6% had integron II. The conjunction of the high prevalence of integrons in Shigella and high resistance to antimicrobials will lead to rapid dissemination of resistant genes in this region.
Analysis of Inhomogeneous Dislocation Distribution in Multicrystalline Si

Grain boundaries and dislocations are major crystallographic defects in multicrystalline Si materials for solar cells. Heavily dislocated grains are detrimental to the photovoltaic performance. This paper attempts to clarify the origin of inhomogeneous defect distribution in multicrystalline Si. The impacts of crystal orientation and grain boundary were investigated. The crystal orientation gives an important geometrical effect in the possibility of initiating slip in a grain when subjected to stress. The presence of grain boundary can also affect dislocation distribution depending on boundary character.
The Effect of Autologous Activated Platelet Rich Plasma (AA-PRP) Injection on Pattern Hair Loss: Clinical and Histomorphometric Evaluation

To investigate the safety and clinical efficacy of AA-PRP injections for pattern hair loss. AA-PRP, prepared from a small volume of blood, was injected on half of the selected patients' scalps with pattern hair loss. The other half was treated with placebo. Three treatments were given for each patient, with intervals of 1 month. The endpoints were hair re-growth, hair dystrophy as measured by dermoscopy, burning or itching sensation, and cell proliferation as measured by Ki-67 evaluation. At the end of the 3 cycles of treatment, the patients presented clinical improvement in the mean number of hairs, with a mean increase of 18.0 hairs in the target area, and a mean increase in total hair density of 27.7 ( number of hairs/cm2) compared with baseline values. Microscopic evaluation showed the increase of epidermis thickness and of the number of hair follicles two weeks after the last AA-PRP treatment compared to baseline value (P < 0.05). We also observed an increase of Ki67+ keratinocytes of epidermis and of hair follicular bulge cells and a slight increase of small blood vessels around hair follicles in the treated skin compared to baseline (P < 0.05).
mDll1 and mDll3 expression in the developing mouse brain: Role in the establishment of the early cortex

The Delta/Notch signalling system is involved in several developmental processes. During fly neurogenesis, Delta expression defines the fate of neuronal precursors and inhibits neighboring Notch‐expressing cells from acquiring a neural fate, a process known as lateral inhibition. In vertebrates, recent evidence demonstrates that Notch activation can positively determine cell fate and affect neuronal process extension. Nevertheless, Delta‐like expression patterns during brain development are relatively unknown. Using a transgenic mouse, which expresses LacZ under the mDll1 promoter, we show by immunofluorescence that in the developing telencephalon mDll1 is expressed in undifferentiated cells in close contact with radial glial cells. Based on in situ hybridization data on mDll1 and mDll3 mRNA expression and on the immunohistochemical detection of β‐galactosidase in the Dll1‐lacZ transgenic mouse, we suggest that mDll1 and mDll3 are involved in the establishment of the early cortical plate and that mDll1‐expressing cells are in close contact with radial glial cells, thereby modulating the latter population, which is known to express Notch1. Furthermore, we suggest that the decrease in mDll1 mRNA found toward the end of gestation could be related, first, to the slowing of neurogenesis and, second, to the differentiation of the radial glial cell population into astrocytes. J. Neurosci. Res. 64:590–598, 2001. © 2001 Wiley‐Liss, Inc.
Thermomechanically Coupled Micromechanical Analysis of Shape Memory Alloy Composites Undergoing Transformation Induced Plasticity

In this investigation, fully thermomechanically coupled constitutive and energy equations for shape memory alloys (SMAs) that include the effect of transformation induced plasticity are presented. This is followed by a micromechanical analysis for the establishment of the fully coupled thermomechanical constitutive equations that model the overall behavior of SMA composites undergoing transformation induced plasticity. The effects of the thermomechanical coupling and permanent inelasticity which arise by the phase transformation were examined. It was found that the response of the monolithic SMA depends upon the thermomechanical coupling. The permanent inelasticity and the resulting induced temperature become significant especially in the case of several repeating cycles. In addition, the induced average temperature caused by the thermomechanical coupling as well as the stress—strain behavior of SMA/epoxy and SMA/aluminum composite materials were determined. A significant thermomechanical coupling, which corresponds to an appreciable temperature increase, was observed for the SMA/aluminum metal matrix composite material. For the case of SMA/epoxy polymeric matrix composite material the thermomechanical coupling was found to be negligible. This results from the absence of inelastic strains in the polymeric matrix in spite of the existence of rate of dilatation effect in the epoxy phase.
Formation and variability of orientation preference maps in visual cortex: an approach based on normalized Gaussian arrays

This work explores formation and variability of orientation preference maps in visual cortex based on normalized Gaussian arrays. An orientation preference map, which has been measured to sketch the orientation preference of neighboring neurons in visual cortex, is emulated by a network of weighted normalized Gaussian arrays. Here the orientation preference map is represented by a set of paired data, each comprising a relative neuron location and the relevant orientation preference, and the mapping structure from the location on a two-dimensional lattice to the orientation preference is then realized by learning a network of normalized Gaussian arrays subject to the paired data. As a result, varieties of mapping structures of different species are essentially characterized by the array number in a network. For example, the icecube structure can be well emulated by using one Gaussian array, the pinwheels structure, that looks like a superposition of two cross icecubes, can be characterized by a network of two Gaussian arrays, and the salt&pepper structure is simply a result of a null Gaussian array, of which the width of each Gaussian unit is set sufficiently large.
2.5.2 Characterization and Application of Innovative Plasmonic Arrays

In order to increase the inherent weak but molecular specific Raman signature the exceptional optical properties of plasmonic nanostructures are used. This technique is termed as surface enhanced Raman spectroscopy (SERS) and combines the fingerprint specificity with potential single molecule sensitivity. However, the non-application of SERS in routine analytics is often linked with the low reproducibility of metallic nanostructures or metallic surfaces. Within this contribution, the fabrication of innovative plasmonic arrays with homogenous signal enhancement is introduced, which is an important contribution towards powerful SERS diagnostics. Here, the application of plasmonic arrays for DNA sensing is demonstrated.
Sentiment Analysis Methodology for Social Web Intelligence

The rapid development and use of Web 2.0 and social media have stimulated user-generated big data. Social and opinion-based websites offer a lot of opportunities for organizations to gather information on their customers’ behavior and needs and sentiment analysis emerged as a technique for analyzing unstructured data. However, there are still problems related to its adoption by businesses. The current study proposes a comparison of two similar methodologies for sentiment analysis which can be utilized by any type of organization. The methods were demonstrated using secondary data from Cars.com, Yelp, and Twitter. The presented methodology provides a detailed guide for practitioners to incorporate sentiment analysis in business operations. It does not require significant investments in infrastructure or specialized software, which makes it much more affordable. Current knowledge on web social intelligence is extended by demonstrating how incorporating a number of methods and tools can be successful for analyzing unstructured text.
A novel moments generation inspired by 3D spherical harmonics for robust 2D shape description

This paper presents a novel 2D region-based shape descriptor inspired by 3D spherical harmonics. We propose an adaptation of the 3D spherical harmonics, which provides a novel set of orthogonal harmonic moments defined on a 2D unit disc. A novel generation of region-based shape descriptors is proposed: the Disk Harmonic Moment Descriptor (DHMD). This new descriptor is compared with other methods from the same category. Set B of the MPEG-7-CE-1-Shape database is used for experimental validation. To benchmark the performance of the compared descriptors precision-recall pair and several statistics provided by the Princeton Shape Benchmark are employed. With its good accuracy in 2D shape retrieval, the proposed descriptor is very useful as a generic shape descriptor for content-based image retrieval applications.
Trend Analysis for Spacecraft Systems Using Multimodal Reasoning

This paper describes some current work at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center’s Advanced Architectures and Automation Branch. Trend analysis refers to the process of examining data from a physical system, developing a mathematical model, analyzing the derived information to formulate an evaluation on the condition of the system, and determining if dangerous trends can be detected. If a trend is detected, corrective or preventive actions are pursued. Our goal is to better understand how to effectively use rulebased, case-based and model-based reasoning, together to realize a more rigorous and automated trend analysis capability. To reach this goal, we plan to develop an automated system to analyze and predict trends, and diagnose spacecraft status telemetry data. This paper describes a concept, architecture and current work in developing a prototype system, called the Automated Model-Based Trend Analysis System (AMTAS). This system uses multimodal reasoning to perform diagnosis and trend analysis. Model-based reasoning is the primary reasoning component which is augmented with other forms of reasoning including rule-based reasoning and case-based reasoning. This prototype may serve as a basis for a full system implementation at a later time if successful. We are in the process of implementing the prototype system using MATLAB.
An RNA toolbox for single-molecule force spectroscopy studies

Precise, controllable single-molecule force spectroscopy studies of RNA and RNA-dependent processes have recently shed new light on the dynamics and pathways of RNA folding and RNA-enzyme interactions. A crucial component of this research is the design and assembly of an appropriate RNA construct. Such a construct is typically subject to several criteria. First, single-molecule force spectroscopy techniques often require an RNA construct that is longer than the RNA molecules used for bulk biochemical studies. Next, the incorporation of modified nucleotides into the RNA construct is required for its surface immobilization. In addition, RNA constructs for single-molecule studies are commonly assembled from different single-stranded RNA molecules, demanding good control of hybridization or ligation. Finally, precautions to prevent RNase- and divalent cation-dependent RNA digestion must be taken. The rather limited selection of molecular biology tools adapted to the manipulation of RNA molecules, as well as the sensitivity of RNA to degradation, make RNA construct preparation a challenging task. We briefly illustrate the types of single-molecule force spectroscopy experiments that can be performed on RNA, and then present an overview of the toolkit of molecular biology techniques at one's disposal for the assembly of such RNA constructs. Within this context, we evaluate the molecular biology protocols in terms of their effectiveness in producing long and stable RNA constructs.
Radiation therapy for primary vaginal carcinoma

Brachytherapy plays a significant role in the management of cervical cancer, but the clinical significance of brachytherapy in the management of vaginal cancer remains to be defined. Thus, a single institutional experience in the treatment of primary invasive vaginal carcinoma was reviewed to define the role of brachytherapy. We retrospectively reviewed the charts of 36 patients with primary vaginal carcinoma who received definitive radiotherapy between 1992 and 2010. The treatment modalities included high-dose-rate intracavitary brachytherapy alone (HDR-ICBT; two patients), external beam radiation therapy alone (EBRT; 14 patients), a combination of EBRT and HDR-ICBT (10 patients), or high-dose-rate interstitial brachytherapy (HDR-ISBT; 10 patients). The median follow-up was 35.2 months. The 2-year local control rate (LCR), disease-free survival (DFS), and overall survival (OS) were 68.8%, 55.3% and 73.9%, respectively. The 2-year LCR for Stage I, II, III and IV was 100%, 87.5%, 51.5% and 0%, respectively (P = 0.007). In subgroup analysis consisting only of T2–T3 disease, the use of HDR-ISBT showed marginal significance for favorable 5-year LCR (88.9% vs 46.9%, P = 0.064). One patient each developed Grade 2 proctitis, Grade 2 cystitis, and a vaginal ulcer. We conclude that brachytherapy can play a central role in radiation therapy for primary vaginal cancer. Combining EBRT and HDR-ISBT for T2–T3 disease resulted in good local control.
Strategies for product-line verification: Case studies and experiments

Product-line technology is increasingly used in mission-critical and safety-critical applications. Hence, researchers are developing verification approaches that follow different strategies to cope with the specific properties of product lines. While the research community is discussing the mutual strengths and weaknesses of the different strategies - mostly at a conceptual level - there is a lack of evidence in terms of case studies, tool implementations, and experiments. We have collected and prepared six product lines as subject systems for experimentation. Furthermore, we have developed a model-checking tool chain for C-based and Java-based product lines, called SPLverifier, which we use to compare sample-based and family-based strategies with regard to verification performance and the ability to find defects. Based on the experimental results and an analytical model, we revisit the discussion of the strengths and weaknesses of product-line-verification strategies.
Wireless device identification based on RF oscillator imperfections

The exploitation of slight imperfections of transmitters' hardware for identification of wireless devices has recently emerged as an effective method for security enhancement in wireless access networks. Previously, we introduced a model-based approach for device identification based on the imperfections of two main wireless transmitter components: the digital-to-analog converter and the power amplifier. Here, motivated by applications with transmit power control mechanisms, we analyze the degree to which a device can be identified from the unique, power mode independent characteristics of a third main component: the RF oscillator. The model-based device identification method introduced here allows for effective device identification even from short time records at relatively low signal-to-noise ratios when exploiting imperfections of commercially used RF oscillators.
Higher State Trellis Coded Modulation for Asymmetric Digital Subscriber Transceivers

A 128 state 4D TCM code for ADSL assuming AWGN is analyzed. The performance is compared with 16 state (3, 2, 5) linear 4D code developed by L. F. Wei [1]. Simulation shows an improvement of 20% in spectral efficiency. We have also analyzed 8-DMT symbol based decoding for Wei's code 16 state (3, 2, 5) in up stream direction and achieved . 9 db gain.
Identity-Based Hybrid Signcryption

Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously, at a cost significantly lower than that required by the traditional signature-then-encryption approach. In this paper, we address a question whether it is possible to construct a hybrid signcryption scheme in identity-based setting. This question seems to have never been addressed in the literature. We answer the question positively in this paper. In particular, we extend the concept of signcryption key encapsulation mechanism to the identity-based setting. We show that an identity-based signcryption scheme can be constructed by combining an identity-based signcryption key encapsulation mechanism with a data encapsulation mechanism. We also give an example of identity-based signcryption key encapsulation mechanism.
Adjacent mutations in the gating loop of Kir6.2 produce neonatal diabetes and hyperinsulinism

KATP channels regulate insulin secretion from pancreatic β‐cells. Loss‐ and gain‐of‐function mutations in the genes encoding the Kir6.2 and SUR1 subunits of this channel cause hyperinsulinism of infancy and neonatal diabetes, respectively. We report two novel mutations in the gating loop of Kir6.2 which cause neonatal diabetes with developmental delay (T293N) and hyperinsulinism (T294M). These mutations increase (T293N) or decrease (T294M) whole‐cell KATP currents, accounting for the different clinical phenotypes. The T293N mutation increases the intrinsic channel open probability (Po(0)), thereby indirectly decreasing channel inhibition by ATP and increasing whole‐cell currents. T294M channels exhibit a dramatically reduced Po(0) in the homozygous but not in the pseudo‐heterozygous state. Unlike wild‐type channels, hetT294M channels were activated by MgADP in the absence but not in the presence of MgATP; however, they are activated by MgGDP in both the absence and presence of MgGTP. These mutations demonstrate the importance of the gating loop of Kir channels in regulating Po(0) and further suggest that Mg‐nucleotide interaction with SUR1 may reduce ATP inhibition at Kir6.2.
Microemulsion route to fabrication of silver and platinum-polymer nanocomposites

Polymethylmethacrylate (PMMA)-platinum and PMMA-silver nanocomposites have been produced using polymerization of W/O microemulsions. MMA monomer was used as the oil or continues phase of the microemulsion system and polymerized following formation of Pt and Ag nanoparticles in the fluid medium. The UV-vis absorption spectra have been used to trace the growth process of the nanoparticles in the microemulsion system. Scanning electron microscopy and transmission electron microscopy (TEM) have been used to determine the morphology and particle size of the Pt and Ag particles in the synthesized nanocomposites. Image analyses of TEM micrographs confirm that the Pt and Ag particles in the synthesized nanocomposites have a narrow size distribution. Meanwhile, Fourier-transform infrared spectroscopy was used to verify polymer-nanoparticles interaction in nanocomposite bulk. POLYM. COMPOS. , 35:2023–2028, 2014. © 2014 Society of Plastics Engineers
Mechanisms of Late-Onset Cognitive Decline after Early-Life Stress

Progressive cognitive deficits that emerge with aging are a result of complex interactions of genetic and environmental factors. Whereas much has been learned about the genetic underpinnings of these disorders, the nature of “acquired” contributing factors, and the mechanisms by which they promote progressive learning and memory dysfunction, remain largely unknown. Here, we demonstrate that a period of early-life “psychological” stress causes late-onset, selective deterioration of both complex behavior and synaptic plasticity: two forms of memory involving the hippocampus, were severely but selectively impaired in middle-aged, but not young adult, rats exposed to fragmented maternal care during the early postnatal period. At the cellular level, disturbances to hippocampal long-term potentiation paralleled the behavioral changes and were accompanied by dendritic atrophy and mossy fiber expansion. These findings constitute the first evidence that a short period of stress early in life can lead to delayed, progressive impairments of synaptic and behavioral measures of hippocampal function, with potential implications to the basis of age-related cognitive disorders in humans.
Environmental Research and Public Health the Need for a Definition of Big Data for Nursing Science: a Case Study of Disaster Preparedness

The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term " Big Data " , which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.