Human papillomavirus 16/18 and nasopharyngeal carcinoma

Sixteen cases of nasopharyngeal carcinoma (eight anaplastic and eight well differentiated squamous types) were examined for the presence of human papillomavirus types 16 and 18 genomes using the polymerase chain reaction on paraffin wax embedded biopsy specimens. Although nasopharyngeal carcinoma, particularly the anaplastic type, is strongly associated with Epstein-Barr virus, other factors may be involved in its pathogenesis. No DNA of either human papillomavirus subtype was detected. It is concluded, therefore, that these two 'high risk' types of human papillomavirus are not implicated in the pathogenesis of nasopharyngeal carcinoma. The number of cases in this series was small, however, and further studies are warranted using fresh biopsy material and including other viral subtypes.published_or_final_versio

The brattleboro rat displays a natural deficit in social discrimination that is restored by clozapine and a neurotensin analog.

Cognitive deficits in schizophrenia are a major source of dysfunction for which more effective treatments are needed. The vasopressin-deficient Brattleboro (BRAT) rat has been shown to have several natural schizophrenia-like deficits, including impairments in prepulse inhibition and memory. We investigated BRAT rats and their parental strain, Long-Evans (LE) rats, in a social discrimination paradigm, which is an ethologically relevant animal test of cognitive deficits of schizophrenia based upon the natural preference of animals to investigate conspecifics. We also investigated the effects of the atypical antipsychotic, clozapine, and the putative antipsychotic, PD149163, a brain-penetrating neurotensin-1 agonist, on social discrimination in these rats. Adult rats were administered saline or one of the three doses of clozapine (0.1, 1.0, or 10 mg/kg) or PD149163 (0.1, 0.3, or 1.0 mg/kg), subcutaneously. Following drug administration, adult rats were exposed to a juvenile rat for a 4-min learning period. Animals were then housed individually for 30 min and then simultaneously exposed to the juvenile presented previously and a new juvenile for 4 min. Saline-treated LE rats, but not BRAT rats, exhibited intact social discrimination as evidenced by greater time spent exploring the new juvenile. The highest dose of clozapine and the two highest doses of PD149163 restored social discrimination in BRAT rats. These results provide further support for the utility of the BRAT rat as a genetic animal model relevant to schizophrenia and drug discovery. The potential of neurotensin agonists as putative treatments for cognitive deficits of schizophrenia was also supported

Polaronic effect in the x-ray absorption spectra of La1-x Ca x MnO3 manganites.

X-ray absorption spectroscopy (XAS) is performed to study changes in the electronic structures of colossal magnetoresistance (CMR) and charged ordered (CO) La1-x Ca x MnO3 manganites with respect to temperature. The pre-edge features in O and Mn K-edge XAS spectra, which are highly sensitive to the local distortion of MnO6 octahedral, exhibit contrasting temperature dependence between CMR and CO samples. The seemingly counter-intuitive XAS temperature dependence can be reconciled in the context of polarons. These results help identify the most relevant orbital states associated with polarons and highlight the crucial role played by polarons in understanding the electronic structures of manganites

Enhancing resilience by reducing critical load loss via an emergent trading framework considering possible resources isolation under typhoon

Leveraging distributed resources to enhance distribution network (DN) resilience is an effective measure in response to natural disasters. However, the willingness and economy of distributed resources are typically ignored. To address this issue, this paper proposes an emergent trading framework that uses parking lots (PLs) as resources to provide power support to critical loads (CLs) in a blackout due to typhoons. In this trading framework, an evolutionary Stackelberg game-based trading model is established to consider maximizing all stakeholders' economic benefits, considering possible resources isolation under typical fault scenarios caused by typhoons, and a benefit allocation mechanism is proposed for all stakeholders to motivate all stakeholders to participate in the trading. This framework allows that critical loads could reduce their load loss, parking lots could receive adequate compensation to stimulate them to participate in the trading, and distribution utility could ensure its economic benefits. Furthermore, an iterative evolutionary-Stackelberg solution set-up is applied to obtain the equilibria of the proposed framework. Simulation results on the modified IEEE 69-bus test system and IEEE 123-bus test system reveal the validity of the proposed method

Adaptive subspace sampling for class imbalance processing

© 2016 IEEE. This paper presents a novel oversampling technique that addresses highly imbalanced data distribution. At present, the imbalanced data that have anomalous class distribution and underrepresented data are difficult to deal with through a variety of conventional machine learning technologies. In order to balance class distributions, an adaptive subspace self-organizing map (ASSOM) that combines the local mapping scheme and globally competitive rule is proposed to artificially generate synthetic samples focusing on minority class samples. The ASSOM is conformed with feature-invariant characteristics, including translation, scaling and rotation, and it retains the independence of basis vectors in each module. Specifically, basis vectors generated via each ASSOM module can avoid generating repeated representative features that offer nothing but heavy computational load. Several experimental results demonstrate that the proposed ASSOM method with supervised learning manner is superior to other existing oversampling techniques

Fuzzy decision-making fuser (FDMF) for integrating human-machine autonomous (HMA) systems with adaptive evidence sources

© 2017 Liu, Pal, Marathe, Wang and Lin. A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems

Exploring the "energy-saving personality traits" in the office and household situation: An empirical study

Behavior-driven energy conservation has been a promising strategy for reducing building energy consumption as well as carbon emissions. With the intention of revealing the impacts of an individual’s personality basis on energy conservation behavioral attitudes and intentions in households and offices, the present study proposes and conducts an experiment in Xi’an, China with two groups for the investigation of such attitudes towards household energy-saving behavior (HESB) and office energy-saving behavior (OESB), respectively. The research adopts structural equation modeling for experiment data analysis. The analysis results suggest that the two personality traits, Agreeableness and Neuroticism, are significantly related to both HESB and OESB attitudes. Especially, agreeable people tend to present stronger energy-saving attitudes, while individuals with higher Neuroticism are less likely to do so. The results indicate that the impacts of these two traits on energy-saving attitude are found to be less influenced by different environment settings. Further, the results find that Extraversion positively influences energy-saving attitude in the office environment, while Openness only significantly works in the household environment. It is hoped that the findings of the present study can provide informative references to energy-saving intervention design as well as further studies on the spillover of pro-environmental behaviors.</jats:p

Fuzzy Integral with Particle Swarm Optimization for a Motor-Imagery-Based Brain-Computer Interface

© 2016 IEEE. A brain-computer interface (BCI) system using electroencephalography signals provides a convenient means of communication between the human brain and a computer. Motor imagery (MI), in which motor actions are mentally rehearsed without engaging in actual physical execution, has been widely used as a major BCI approach. One robust algorithm that can successfully cope with the individual differences in MI-related rhythmic patterns is to create diverse ensemble classifiers using the subband common spatial pattern (SBCSP) method. To aggregate outputs of ensemble members, this study uses fuzzy integral with particle swarm optimization (PSO), which can regulate subject-specific parameters for the assignment of optimal confidence levels for classifiers. The proposed system combining SBCSP, fuzzy integral, and PSO exhibits robust performance for offline single-trial classification of MI and real-time control of a robotic arm using MI. This paper represents the first attempt to utilize fuzzy fusion technique to attack the individual differences problem of MI applications in real-world noisy environments. The results of this study demonstrate the practical feasibility of implementing the proposed method for real-world applications

FDG-PET assessment of the locus coeruleus in Alzheimer’s disease

Sensitive and reliable in vivo imaging of the locus coeruleus (LC) is important to develop and evaluate its potential as a biomarker in neurodegenerative diseases such as Alzheimer’s disease (AD). It is not known whether AD-related alterations in LC integrity can be detected using 18F-labelled fluoro-2-deoxyglucose (FDG) positron emission tomography (PET). Mean FDG-PET images from AD patients (N ​= ​193) and controls (N ​= ​256) from the ADNI database were co-registered to a study-wise anatomical template. Regional LC median standardized uptake value ratio (SUVR) values were obtained using four previously published LC masks and normalized to values from pons and cerebellar vermis reference regions. To support the validity of our methods, other regions previously reported to be most and least affected metabolically in AD were also compared to controls. The LC did not show between-group differences in FDG-PET signal, whereas the mammillary bodies did, despite these regions having comparable volumes and SUVR ranges. Brain regions previously reported to be most and least affected metabolically in AD compared to controls showed medium-to-large and small effect sizes for SUVR differences respectively. The results do not support the current application of LC FDG-PET signal as an in vivo biomarker for AD. Methodological and demographic factors potentially contributing to these findings are discussed. Future research may investigate age-related differences in LC FDG-PET signal and higher resolution images to fully explore its biomarker potential

Identification of the major chemical constituents and their metabolites in rat plasma and various organs after oral administration of effective Erxian Decoction (EXD) fraction by liquid chromatography-mass spectrometry

A simple and specific LC-DAD-ESI-MS/MS method has been developed and applied for the primary investigation of the chemical constituents absorbed or metabolized in vivo, after the rat oral administration of Erxian Decoction (EXD), a Chinese medicine prescription for menopausal syndromes. Through the online ESI-MS n analysis, a total of 35 compounds have been identified or tentatively characterized from the seven tested samples, and 13 of them were unambiguously identified through a direct comparison of the retention time, UV spectra and MS n fragmentation patterns with the authentic ones. The results showed that 21 compounds were detected from rat plasma, 20 compounds were detected from rat kidneys and adrenal glands, 19 compounds were detected from rat ovaries, 12 compounds were found in rat intestines, nine compounds were identified from rat livers and nine compounds were detected from rat brains at certain time points after oral administration of the eff ective EXD fraction. Copyright © 2009 John Wiley & Sons, Ltd.postprin