Impacts of Land Use Change and Summer Monsoon on Nutrients and Sediment Exports from an Agricultural Catchment

Agricultural non-point source (NPS) pollution is a major concern for water quality management in the Soyang watershed in South Korea. Nutrients (phosphorus and nitrogen), organic matter, and sediment exports in streams were estimated in an agricultural catchment (Haean catchment) for two years. The stream water samples were taken in dry and rainy seasons to evaluate the effect of monsoonal rainfall on pollutants exports. The influence of land use changes on NPS pollution was assessed by conducting a land use census and comparing the NPS characteristic exports. Total phosphorus (TP), suspended solids (SS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) increased dramatically in rainy seasons. Land uses were changed during the study period. Dry fields and rice paddies have decreased distinctively while orchard (apple, grape, and peach) and ginseng crops showed an increase within the catchment. The TP and SS loading decreased in the streams in 2010 compared to the loading in 2009 while the BOD and NO3− did not show distinct significant change. In this study, monsoonal driven rainfalls increased exports of agricultural NPS pollutants into streams. Land use change (mostly crop and paddy fields to orchards and ginseng fields) remarkably mitigated TP and SS exports into the streams

YAF2 promotes TP53-mediated genotoxic stress response via stabilization of PDCD5

AbstractProgrammed cell death 5 (PDCD5) plays a crucial role in TP53-mediated apoptosis, but the regulatory mechanism of PDCD5 itself during apoptosis remains obscure. We identified YY1-associated factor 2 (YAF2) as a novel PDCD5-interacting protein in a yeast two-hybrid screen for PDCD5-interacting proteins. We found that YY1-associated factor 2 (YAF2) binds to and increases PDCD5 stability by inhibiting the ubiquitin-dependent proteosomal degradation pathway. However, knocking-down of YAF2 diminishes the levels of PDCD5 protein but not the levels of PDCD5 mRNA. Upon genotoxic stress response, YAF2 promotes TP53 activation via association with PDCD5. Strikingly, YAF2 failed to promote TP53 activation in the deletion of PDCD5, whereas restoration of wild-type PDCD5WT efficiently reversed the ineffectiveness of YAF2 on TP53 activation. Conversely, PDCD5 efficiently overcame the knockdown effect of YAF2 on ET-induced TP53 activation. Finally, impaired apoptosis upon PDCD5 ablation was substantially rescued by restoration of PDCD5WT but not YAF2-interacting defective PDCD5E4D nor TP53-interacting defective PDCD5E16D mutant. Our findings uncovered an apoptotic signaling cascade linking YAF2, PDCD5, and TP53 during genotoxic stress responses

Кераміка «terra sigillata» з с. Зимне на Волині

Стаття присвячена публікації чотирьох керамічних посудин типу «terra sigillata», знайдених на дні р. Луги у с. Зимне Володимир-Волинського району Волинської області. Попередній аналіз цих знахідок дозволяє віднести їх до Понтійського центру виробництва такого посуду. Вірогідним шляхом потрапляння цієї колекції на Волинь була готська експансія у Північне Причорномор’я

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Cross-cultural validity and equivalency of oral health-related quality of life (OHQoL) measurement for Korean older adults

Introduction: Oral Health Impact Profile (OHIP) is a widely used psychometric instrument or scale developed in English to measure Oral Health-related Quality of Life (OHQoL), and there has been many translations of the instrument into other languages, including Korean. Purpose: My thesis examines the validity and cultural equivalence of the English and Korean versions of the scale by answering the questions: “What methods are available to validate the cultural equivalence of psychometric instruments?” and “How culturally appropriate and valid is the Korean version of the short-form of the OHIP (OHIP-14K)?" Method: Ten Korean dental experts fluent in English and Korean independently assessed the clarity, relevance, and cultural equivalence of the OHIP-14K and offered suggestions for improving the cultural sensitivity and validity of the instrument content. The item-level Content Validity Index (I-CVI) was used to measure the validity of each item from the experts’ ratings followed by the calculation of Scale-level Content Validity Index (S-CVI) as the proportion of content valid items. Additional analyses including the average deviation index (ADM) and Kappa statistics (Kfree) were performed with the clarity index (CI), relevance index (RI) and cultural equivalence index (CEI) to measure the level of agreement between the experts. Results: The experts rated the OHIP-14K as mostly clear (S-CVI= 0.93), but they were concerned about the relevance of many items to the expected domains of the instrument (S-CVI = 0.42) and about its cultural equivalence (S-CVI = 0.50) to the English version. However, there was much disagreement between the experts as measured by the RI (Kfree = 0.19 to 1.00) and CEI (ADM = 0.36 to 0.96). Conclusion: The relevance and cultural equivalence of the OHIP-14K to the original English version of the OHIP-14 are not strong. Suggestions are offered for improving the OHIP-14K, which needs further testing within the Korean populations.Dentistry, Faculty ofGraduat

Effective Evolutionary Multilabel Feature Selection under a Budget Constraint

Multilabel feature selection involves the selection of relevant features from multilabeled datasets, resulting in improved multilabel learning accuracy. Evolutionary search-based multilabel feature selection methods have proved useful for identifying a compact feature subset by successfully improving the accuracy of multilabel classification. However, conventional methods frequently violate budget constraints or result in inefficient searches due to ineffective exploration of important features. In this paper, we present an effective evolutionary search-based feature selection method for multilabel classification with a budget constraint. The proposed method employs a novel exploration operation to enhance the search capabilities of a traditional genetic search, resulting in improved multilabel classification. Empirical studies using 20 real-world datasets demonstrate that the proposed method outperforms conventional multilabel feature selection methods

Evolutionary Multilabel Feature Selection Using Promising Feature Subset Generation

Recent progress in the development of sensor devices improves information harvesting and allows complex but intelligent applications based on learning hidden relations between collected sensor data and objectives. In this scenario, multilabel feature selection can play an important role in achieving better learning accuracy when constrained with limited resources. However, existing multilabel feature selection methods are search-ineffective because generated feature subsets frequently include unimportant features. In addition, only a few feature subsets compared to the search space are considered, yielding feature subsets with low multilabel learning accuracy. In this study, we propose an effective multilabel feature selection method based on a novel feature subset generation procedure. Experimental results demonstrate that the proposed method can identify better feature subsets than conventional methods

A Short Survey and Comparison of CNN-Based Music Genre Classification Using Multiple Spectral Features

The goal of music genre classification is to identify the genre of given feature vectors representing certain characteristics of music clips. In addition, to improve the accuracy of music genre classification, considerable research has been conducted on extracting spectral features, which contain critical information for genre classification, from music clips and feeding these features into training models. In particular, recent studies argue that classification accuracy can be enhanced by employing multiple spectral features simultaneously. Consequently, fusing information from multiple spectral features is a critical consideration in designing music genre classification models. Hence, this paper provides a short survey of recent studies on music genre classification and compares the performance of the most recent CNN-based models with a newly devised model that employs a late fusion strategy for the multiple spectral features. Our empirical study of 12 public datasets, including Ballroom, ISMIR04, and GTZAN, showed that the late fusion CNN model outperforms other compared methods. Additionally, we performed an in-depth analysis to validate the effectiveness of the late fusion strategy in music genre classification