Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of antiepileptic drugs on oral health.

OBJECTIVE Long-term use of phenytoin (PHT) causes gingival hyperplasia; however, little is known about the oral side effects of other antiepileptic drugs (AEDs). Through a systematic review of the literature, we explored the effects of AEDs on the oral health of patients with epilepsy. METHODS We searched PubMed, EMBASE and the Cochrane library between January 1963 and August 2010. The search strategy retrieved 170 abstracts. We included studies that involved original research and had ≥ 10 patients in our review. We also checked the reference lists of reviews, letters and other manuscripts to find studies that met our selection criteria. RESULTS Only 15 articles were included in the final analysis. Gingival hyperplasia was very common in patients taking PHT (16%-94% of patients). Alveolar bone loss occurred in patients taking carbamazepine or PHT. Patients taking valproate, carbamazepine or phenobarbital also had gingival hyperplasia. We found no published studies of newer-generation AEDs. CONCLUSION Although several studies examined the effects of PHT on oral health, none have studied those of the newer generation of AEDs. Studies exploring oral side effects of AEDs are needed.
The meaning of participation in school ground greening: a study from project to everyday setting

Abstract School ground greening has many acknowledged benefits for play, learning and health, but less is known about the outcomes of such projects from children’s perspectives. This study aims to investigate the process, and children’s participation, at two Swedish schools over four years of planning, planting, management and maintenance, using short interviews and observations. There was a large general interest among the children to participate in the development and maintenance of their school grounds, but different participatory and pedagogical approaches were used. The participation of children in the planning stage appears to be of specific importance for the functionality of school grounds, while long-term participation in management and maintenance can affect children’s experiences from, and perspectives on, greening areas and projects positively over time. The results point to the large impact that greening projects with continuity in participation can have on children’s activity and meaning-making.
Two Fault Tolerance Design Approaches for Hybrid CMOS / Nanodevice Digital Memories

Targeting on the future fault-prone hybrid CMOS/nanodevice digital memories, this paper presents two fault tolerance design approaches that integrally address the tolerance for defects and transient faults. The first approach is straightforward and easy to implement but suffers from a rapid drop of achievable storage capacity as defect densities and/or transient fault rates increase, while the second approach can achieve much higher storage capacity under high defect densities and/or transient fault rates at the cost of higher implementation complexity and longer memory access latency. With the use of BCH codes as ECC, we carried out simulations to demonstrate the effectiveness of the presented approaches under a wide range of defect densities and transient fault rates, while taking into account of the fault tolerance storage overhead in CMOS domain.
Subpixel mapping of hyperspectral data using high resolution color images

This article introduces a method that uses information from a high spatial resolution color image to perform subpixel mapping of a lower spatial resolution hyperspectral image. The method uses a modified majority voting approach, that makes a distinction between pure and mixed pixels, in order to combine a classification map of the hyperspectral data with a segmentation map of the color image. Experiments, conducted on two hyperspectral images, show excellent results, when compared to conventional classification of the hyperspectral data only. The developed classification scheme results in much higher accuracies and leads to large visual improvements, including well-defined class transitions and fairly homogeneous objects.
Unsupervised Continuous-Valued Word Features for Phrase-Break Prediction without a Part-of-Speech Tagger

Part of speech (POS) tags are foremost among the features conventionally used to predict intonational phrase-breaks for text to speech (TTS) conversion. The construction of such systems therefore presupposes the availability of a POS tagger for the relevant language, or of a corpus manually tagged with POS. However, such tools and resources are not available in the majority of the world’s languages, and manually labelling text with POS tags is an expensive and time-consuming process. We therefore propose the use of continuous-valued features that summarise the distributional characteristics of word types as surrogates for POS features. Importantly, such features are obtained in an unsupervised manner from an untagged text corpus. We present results on the phrase-break prediction task, where use of the features closes the gap in performance between a baseline system (using only basic punctuation-related features) and a topline system (incorporating a state-of-the-art POS tagger).
The First Alcohol Drink Triggers mTORC1-Dependent Synaptic Plasticity in Nucleus Accumbens Dopamine D1 Receptor Neurons

Early binge-like alcohol drinking may promote the development of hazardous intake. However, the enduring cellular alterations following the first experience with alcohol consumption are not fully understood. We found that the first binge-drinking alcohol session produced enduring enhancement of excitatory synaptic transmission onto dopamine D1 receptor-expressing neurons (D1+ neurons) in the nucleus accumbens (NAc) shell but not the core in mice, which required D1 receptors (D1Rs) and mechanistic target of rapamycin complex 1 (mTORC1). Furthermore, inhibition of mTORC1 activity during the first alcohol drinking session reduced alcohol consumption and preference of a subsequent drinking session. mTORC1 is critically involved in RNA-to-protein translation, and we found that the first alcohol session rapidly activated mTORC1 in NAc shell D1+ neurons and increased synaptic expression of the AMPAR subunit GluA1 and the scaffolding protein Homer. Finally, D1R stimulation alone was sufficient to activate mTORC1 in the NAc to promote mTORC1-dependent translation of the synaptic proteins GluA1 and Homer. Together, our results indicate that the first alcohol drinking session induces synaptic plasticity in NAc D1+ neurons via enhanced mTORC1-dependent translation of proteins involved in excitatory synaptic transmission that in turn drives the reinforcement learning associated with the first alcohol experience. Thus, the alcohol-dependent D1R/mTORC1-mediated increase in synaptic function in the NAc may reflect a neural imprint of alcohol's reinforcing properties, which could promote subsequent alcohol intake. SIGNIFICANCE STATEMENT Consuming alcohol for the first time is a learning event that drives further drinking. Here, we identified a mechanism that may underlie the reinforcing learning associated with the initial alcohol experience. We show that the first alcohol experience induces a persistent enhancement of excitatory synaptic transmission on NAc shell D1+ neurons, which is dependent on D1R and mTORC1. We also find that mTORC1 is necessary for the sustained alcohol consumption and preference across the initial drinking sessions. The first alcohol binge activates mTORC1 in NAc D1+ neurons and increases levels of synaptic proteins involved in glutamatergic signaling. Thus, the D1R/mTORC1-dependent plasticity following the first alcohol exposure may be a critical cellular component of reinforcement learning.
The Optimal First-Line Therapy of Helicobacter pylori Infection in Year 2012

This paper reviews the literature about first-line therapies for H. pylori infection in recent years. First-line therapies are facing a challenge because of increasing treatment failure due to elevated antibiotics resistance. Several new treatment strategies that recently emerged to overcome antibiotic resistance have been surveyed. Alternative first-line therapies include bismuth-containing quadruple therapy, sequential therapy, concomitant therapy, and hybrid therapy. Levofloxacin-based therapy shows impressive efficacy but might be employed as rescue treatment due to rapidly raising resistance. Rifabutin-based therapy is also regarded as a rescue therapy. Several factors including antibiotics resistance, patient compliance, and CYP 2C19 genotypes could influence the outcome. Clinicians should use antibiotics according to local reports. It is recommended that triple therapy should not be used in areas with high clarithromycin resistance or dual clarithromycin and metronidazole resistance.
The Performance of a Digital Interconnection Protection for Grid-Connected WECSs

This paper develops and experimentally tests the performance of a digital interconnection protection for grid-connected wind energy conversion systems (WECSs). The developed protection is constructed by two frequency frames to process voltages and currents measured at the point-of-common-coupling (PCC). The first frequency frame is set to process the d - q-axis components of the instantaneous 3φ apparent powers (sd and sq) determined at PCC. This processing of sd and sq aims to extract their high-frequency subband contents in order to detect the islanding condition. The second frequency frame is set to extract the high-frequency contents (magnitudes and phases) present in the 3φ currents flowing through PCC. These high-frequency contents provide signature information for detecting faults occurring on either side of PCC. The multiframe digital interconnection protection is implemented for performance evaluation on two different WECSs operated in grid connection. Performance results show accurate and reliable detection and identification of the islanding condition and faults occurring on either side of PCC. In addition, performance results show that the multiframe digital interconnection protection has minor sensitivity to the type, structure, ratings, and levels of power delivery to the host grid.
The Inverse Satisfiability Problem

We study the complexity of telling whether a set of bitvectors represents the set of all satisfying truth assignments of a Boolean expression of a certain type. We show that the problem is coNP-complete when the expression is required to be in conjunctive normal form with three literals per clause (3CNF). We also prove a Dichotomy Theorem analogous to the classical one by Schaefer, stating that, unless P=NP, the problem can be solved in polynomial time if and only if the clauses allowed are either all Horn, or all anti-Horn, or all 2CNF, or all equivalent to equations modulo two.
Clinical Pharmacology of Opioids for Pain

The pharmacological effects of the opioid analgesics are derived from their complex interactions with three opioid receptor types (μ, δ, and κ; morphine is an agonist at the μ opioid receptor). These receptors are found in the periphery, at presynaptic and postsynaptic sites in the spinal cord dorsal horn, and in the brain stem, thalamus, and cortex, in what constitutes the ascending pain transmission system, as well as structures that comprise a descending inhibitory system that modulates pain at the level of the spinal cord. The cellular effects of opioids include a decrease in presynaptic transmitter release, hyperpolarization of postsynaptic elements, and disinhibition. The endogenous opioid peptides are part of an endogenous pain modulatory system. A number of opioids are available for clinical use, including morphine, hydromorphone, levorphanol, oxymorphone, methadone, meperidine, oxycodone, and fentanyl, and their advantages and disadvantages for the management of pain are discussed. An understanding of the pharmacokinetic properties, as well as issues related to opioid rotation, tolerance, dependence, and addiction are essential aspects of the clinical pharmacology of opioids for pain.
Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch

We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models.
Segment polarity and DV patterning gene expression reveals segmental organization of the Drosophila brain

The insect brain is traditionally subdivided into the trito-, deuto- and protocerebrum. However, both the neuromeric status and the course of the borders between these regions are unclear. The Drosophila embryonic brain develops from the procephalic neurogenic region of the ectoderm, which gives rise to a bilaterally symmetrical array of about 100 neuronal precursor cells, called neuroblasts. Based on a detailed description of the spatiotemporal development of the entire population of embryonic brain neuroblasts, we carried out a comprehensive analysis of the expression of segment polarity genes (engrailed, wingless, hedgehog, gooseberry distal, mirror) and DV patterning genes (muscle segment homeobox, intermediate neuroblast defective, ventral nervous system defective) in the procephalic neuroectoderm and the neuroblast layer (until stage 11, when all neuroblasts are formed). The data provide new insight into the segmental organization of the procephalic neuroectodem and evolving brain. The expression patterns allow the drawing of clear demarcations between trito-, deuto- and protocerebrum at the level of identified neuroblasts. Furthermore, we provide evidence indicating that the protocerebrum (most anterior part of the brain) is composed of two neuromeres that belong to the ocular and labral segment, respectively. These protocerebral neuromeres are much more derived compared with the trito- and deutocerebrum. The labral neuromere is confined to the posterior segmental compartment. Finally, similarities in the expression of DV patterning genes between the Drosophila and vertebrate brains are discussed.
Regenerative Medicine for Neurological Diseases with the Use of Electrical Stimulation

In current clinical practice, tissue plasminogen activator (t-PA) is the gold standard drug to be administred within three hours after the onset of cerebral infarction. In the near future, it will become acceptable to administer it within 4.5 hours of onset. Even if t-PA administration cannot be utilized for cerebral infaction patients because of time window limitations, the intravascular technique using the Merci(R) retreiver and the Penumbra(R) system can be applied to some patients with cerebral infarction. Not all cerebral infarction patients can be saved by these clinical therapeutic methods. Despite surviving the acute phase of cerebral infarction as a result of these clinical therapeutic methods, some patients suffer from permanent hemipa‐ resis in the chronic phase. It is for this reason that regenerative medicine must play more important role in solving this problem.
Informal Learning Behavior Analysis Using Action Logs and Slide Features in E-Textbooks

This paper discusses learning behavior analysis using a learning management system (LMS) and an e-textbook system. We collected a large number of operation logs from e-textbooks to analyze the process of learning. In addition, we conducted a quiz to check the level of understanding. In our study, we especially focus on an analysis of the relationship between learning behavior in informal learning and its effectiveness in the corresponding quiz. We apply a machine learning and classification methodology for behavior analysis. Our experimental results demonstrate that students who undertake good informal learning achieve better scores in quizzes.
An Approach Towards Fast Gradient-based Image Segmentation

In this paper we present and investigate an approach to fast multi-label color image segmentation using convex optimization techniques. The presented model is in some ways related to the well-known Mumford-Shah model, but deviates in certain important aspects. The optimization problem has been designed with two goals in mind: The objective function should represent fundamental concepts of image segmentation, such as incorporation of weighted curve length and variation of intensity in the segmented regions, while allowing transformation into a convex concave saddle point problem that is computationally inexpensive to solve. This paper introduces such a model, the nontrivial transformation of this model into a convex-concave saddle point problem, and the numerical treatment of the problem. We evaluate our approach by applying our algorithm to various images and show that our results are competitive in terms of quality at unprecedentedly low computation times. Our algorithm allows high-quality segmentation of megapixel images in a few seconds and achieves interactive performance for low resolution images.
Unsupervised segmentation Algorithm based on fusion of multiresolution features

— This paper presents the development of an unsupervised image segmentation using the multi-resolution analysis technique. An important contribution of this work consists of combining gabor filters and wavelet. Texture analysis is done using a bank of filters and many features are computed using texture decomposition with the aim of identifying the homogenous regions in the image. The system builds Features vector for each pixel that contains information about the gray level, and other texture information. These vectors are used as inputs for the K-means clustering method, which results a segmented image whose regions are distinct from each other according to texture characteristic content. To evaluate the performance of this analyze we applied the methodology to a brodatz database and to MSG images.
Polymer-attached zanamivir inhibits synergistically both early and late stages of influenza virus infection

Covalently conjugating multiple copies of the drug zanamivir (ZA; the active ingredient in Relenza) via a flexible linker to poly-l-glutamine (PGN) enhances the anti-influenza virus activity by orders of magnitude. In this study, we investigated the mechanisms of this phenomenon. Like ZA itself, the PGN-attached drug (PGN-ZA) binds specifically to viral neuraminidase and inhibits both its enzymatic activity and the release of newly synthesized virions from infected cells. Unlike monomeric ZA, however, PGN-ZA also synergistically inhibits early stages of influenza virus infection, thus contributing to the markedly increased antiviral potency. This inhibition is not caused by a direct virucidal effect, aggregation of viruses, or inhibition of viral attachment to target cells and the subsequent endocytosis; rather, it is a result of interference with intracellular trafficking of the endocytosed viruses and the subsequent virus-endosome fusion. These findings both rationalize the great anti-influenza potency of PGN-ZA and reveal that attaching ZA to a polymeric chain confers a unique mechanism of antiviral action potentially useful for minimizing drug resistance.
Fast collision checking for intelligent vehicle motion planning

We present a method for fast collision checking that is suitable for application in motion planning for intelligent vehicles. One of the difficulties that arises in this domain is the fact that typical, car-like autonomous vehicles cannot easily be approximated by a rotationally invariant disk shape. Instead, the orientation of the vehicle must be accounted for explicitly. Our proposal is to decompose the vehicle shape into several disk shaped primitives, so that the task of collision checking can be broken down into few very simple collision tests. We also propose a highly optimised method to perform these primitive collision tests that requires a minimum of arithmetic operations. We show by experiments that our method bears significant performance benefits over conventional methods.
A lightweight defence against the Packet in Packet attack in ZigBee networks

ZigBee is a standard for low-power, low-rate wireless communication. It is modeled on the physical layer and medium access control defined in IEEE 802.15. 4. In this paper, we study an attack on modern radios called the “Packet in Packet” (PIP) attack. We replicate the attack in ZigBee devices and discuss possible defenses against the attack. We implement a solution to thwart the PIP attack in TinyOS and show through extensive experiments that the solution defends against the attack, while imposing little additional overhead.
An Information Entropy Approach for Sleep Scheduling in Densely-Deployed Sensor Networks

Wireless sensor networks are usually densely deployed, and it is quite common for sensors to gather and transmit redundant information, which results in unnecessary energy consumption. Sleep scheduling is quite helpful for reducing overall energy consumption of the network, and thus prolongs the network lifetime. In this paper, we propose an Information Entropy Approach for Sleep Scheduling (IEASS). Information entropy is exploited in the algorithm to characterize the correlation of data which is used for determining the eligibility of node sleeping. The main objective of IEASS is to achieve adaptive coverage while keeping network connectivity. From the simulation results, IEASS performs well on coverage ratio and coverage degree with much less active sensor nodes. Moreover, IEASS achieves high flexibility by adjusting the algorithm parameters.
Feasibility of Translaminar Screw Placement in Korean Population: Morphometric Analysis of Cervical Spine

Purpose To analyze the feasibility of unilateral and bilateral translaminar screw placement in Koran population, and compare the acceptance rate using previously reported data in American population. Materials and Methods The translaminar lengths, thickness, heights, and sagittal-diagonal measurements were performed. The feasibility analysis was performed using unilateral and bilateral 3.5 mm cervical screw placement on the CT scans within 0.5 mm of safety margin. We also performed radiographic analysis of the morphometric dimensions and the feasibility of unilateral and bilateral translaminar screw placement at C3-C7. Results Korean population had similar or significantly shorter translaminar lengths and thickness (lengths and thickness in C7 among males; lengths in C6-C7 and thickness in C4 among females) than American population, but had similar or significantly longer translaminar heights and sagittal-diagonal measurements (heights in C3-C7 and sagittal-diagonal measurements in C3-C6 among males; heights in C7 and sagittal-diagonal measurements in C3-C7 among females). Unilaterally, translaminar screw acceptance rates in C3-C7 were similar between Korean and American male population, but the rates in C4-C6 were significantly smaller between Korean and American female population. Bilaterally, translaminar screw acceptance rates in C3 and C5-C6 were significantly larger between Korean and American male population, but the rates in C3-C7 were similar between Korean and American female population. Conclusion The feasibility of unilateral and bilateral translaminar screw placement is different depending on different ethnics. Subaxial cervical unilateral translaminar screw placement among Korean male population and bilateral placement at C4-C7 among Korean female population are more acceptable than American population.