Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormalities in visual processing lead to hypersociability and evaluation of trust Shore

Accurate assessment of trustworthiness is fundamental to successful and adaptive social behavior. Initially, people assess trustworthiness from facial appearance alone. These assessments then inform critical approach or avoid decisions. Individuals with Williams syndrome (WS) exhibit a heightened social drive, especially toward strangers. This study investigated the temporal dynamics of facial trustworthiness evaluation in neurotypic adults (TD) and individuals with WS.We examinedwhether differences in neural activity during trustworthiness evaluation may explain increased approach motivation in WS compared to TD individuals. Event-related potentials were recorded while participants appraised faces previously rated as trustworthy or untrustworthy. TD participants showed increased sensitivity to untrustworthy faces within the first 65–90 ms, indexed by the negative-going rise of the P1 onset (oP1). The amplitude of the oP1 difference to untrustworthy minus trustworthy faces was correlated with lower approachability scores. In contrast, participants with WS showed increased N170 amplitudes to trustworthy faces. The N170 difference to low–high-trust faces was correlated with low approachability in TD and high approachability in WS. The findings suggest that hypersociability associated with WS may arise from abnormalities in the timing and organization of early visual brain activity during trustworthiness evaluation. More generally, the study provides support for the hypothesis that impairments in low-level perceptual processes can have a cascading effect on social cognition.
An optimum energy consumption hybrid algorithm for xln strategic design in wsns

In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15. 4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.
Induction and Inhibition Studies of Hypoxia and Oxidative Stress in Immortalized Keratinocytes Using traditional microplate detection and automated digital widefield fluorescence microscopy

This application note demonstrates a multiplexed assay that can monitor the induction of hypoxia and oxidative stress phenotypes using fluorogenic probes. Data readout can be achieved using whole-well fluorescence intensities measured using either monochromators or spectral filters for rapid measurements depicting relative phenotype changes. Absolute ratios of effected cells for each phenotype can also be obtained through cellular analysis using automated digital widefield fluorescence microscopy. The ability of a library of antioxidants to inhibit hypoxia was then assessed in a separate assay. The library was screened rapidly using whole-well intensities. A hit picking feature in the instrument software was activated to image only those wells meeting the predetermined criteria. Imaging then provided qualitative and quantitative assessments of the extent of hypoxia phenotype inhibition. Excessive inhibition relative to controls was found to be caused by compound toxicity using a luminescent cell viability assay. All cell-based assays were performed using the Agilent BioTek Cytation 3 cell imaging multimode reader.
Advances in detecting object classes and their semantic parts

Object classes are central to computer vision and have been the focus of substantial research in the last fifteen years. This thesis addresses the tasks of localizing entire objects in images (object class detection) and localizing their semantic parts (part detection). We present four contributions, two for each task. The first two improve existing object class detection techniques by using context and calibration. The other two contributions explore semantic part detection in weakly-supervised settings. First, the thesis presents a technique for predicting properties of objects in an image based on its global appearance only. We demonstrate the method by predicting three properties: aspect of appearance, location in the image and class membership. Overall, the technique makes multi-component object detectors faster and improves their performance. The second contribution is a method for calibrating the popular Ensemble of ExemplarSVM object detector. Unlike the standard approach, which calibrates each ExemplarSVM independently, our technique optimizes their joint performance as an ensemble. We devise an efficient optimization algorithm to find the global optimal solution of the calibration problem. This leads to better object detection performance compared to using independent calibration. The third innovation is a technique to train part-based model of object classes using data sourced from the web. We learn rich models incrementally. Our models encompass the appearance of parts and their spatial arrangement on the object, specific to each viewpoint. Importantly, it does not require any part location annotation, which is one of the main limits to training many part detectors. Finally, the last contribution is a study on whether semantic object parts emerge in Convolutional Neural Networks trained for higher-level tasks, such as image classification. While previous efforts studied this matter by visual inspection only, we perform an extensive quantitative analysis based on ground-truth part location annotations. This provides a more conclusive answer to the question.
Land-use Changes Alter Energy and Water Balances on an African BrachiariaPasture Replacing a Native Savanna in the Orinoco llanos

The seasonal changes in the energy balance after the substitution of a herbaceous savanna by a Brachiaria field located in the Orinoco lowlands were assessed over an entire year using the eddy covariance technique. Simultaneously, an herbaceous savanna was monitored as a control. This work provides evidence that the vegetation replacement lead to different patterns of energy and water balance. The seasonal trends of the latent heat flux (λE) to available energy (Ra) ratio tended to decrease as senescence increased due to seasonal influence of air humidity mole fraction deficit and soil water content on leaf area index (LAI) and surface conductance (gs). Therefore, the partitioning of the available energy depended on both climatological (i.e., solar radiation, volumetric soil water content and air humidity mole fraction deficit) and biological variables (i.e., conductance behavior and LAI) which were stress-induced. For the wet season, the seasonally averaged daily λE in the Brachiaria field (i.e., 0.8 ± 0.1 mm d-1) was 1.3-fold higher than that in the herbaceous savanna (i.e., 0.6 ± 0.1 mm d-1) (Mann-Whitney U-test). For the dry season, the value was 2.7 ± 0.6 and 2.2 ± 0.4 mm d-1, respectively, these means values were not significantly different. In the Brachiaria and herbaceous savanna stands, the annual evapotranspiration was 731 and 594 mm year-1, respectively, and the annual ratio of evapotranspiration to precipitation was 0.52 to 0.42 respectively. In Brachiaria field, the deep drainage was relatively lower (43% of total precipitation) than that in the herbaceous savanna stand (53%) leaving a similar amount of water to increase soil storage. The current shift in land cover decrease deep drainage and increased λE by water uptake from a pasture with high belowground phytomass and LAI.
Credit Growth in Central and Eastern Europe : Trend , Cycle or Boom ?

Credit to the private sector has been growing very rapidly in a number of Central and Eastern European countries in recent years. The main question is whether this dynamics is an equilibrium convergence process or may rather pose stability risks. Using panel econometric techniques, this paper attempts to identify the equilibrium credit/GDP levels of the new EU countries, disentangling the observed growth into an equilibrium trend and an excess (boom) component. In the paper the pooled mean group estimator was used for its flexibility and efficiency. Using instrumental variable technique we tested whether long run endogeneity affects the consistency. The estimations show that large part of the credit growth in new member states can be explained by the catching-up process, and, in general, credit/GDP ratios are below the levels consistent with macroeconomic fundamentals. However, in some countries credit growth is significantly faster than what would be justified along the equilibrium path. The study finds that credit growth in Latvia and Estonia can be considered as potentially the most risky, beyond any plausible adjustment rate. JEL classification: E44
Inverse Reinforcement Learning for Autonomous Ground Navigation Using Aerial and Satellite Observation Data

Inverse reinforcement learning (IRL) is a supervised learning paradigm where a learner observes expert demonstrations to learn a hidden cost function in order to mimic the expert’s behavior. Eliminating the need of elaborate feature engineering, deep IRL approaches have been gaining interests in various problem domains including robot navigation. With the advent of low-cost drones and satellite services increasing the availability of 2D and 3D data over large area, there has been growing interest in end-to-end autonomous navigation systems which uses aerial and satellite information where prior knowledge of the environment is often outdated or no longer valid. In this paper, we propose a Conditional Multimodal Deep Inverse Reinforcement Learning approach that uses a deep neural network to learn sophisticated features for generating cost maps for multiple driving behaviors in the global planning context while utilizing both 2D and 3D data to accomplish such a task.
Trend analysis of rainfall and frequency of rainy days over Coimbatore

Rainfall is very crucial for the economic development, disaster management, hydrological planning for the country. In the context of climate change, it is pertinent to ascertain whether the characteristic of Indian rainfall is also changing. Using daily rainfall data for the period of 1907-2012 analysis were carried out, to find out the change in rainfall and frequency of rainfall intensity. Results indicated that the annual rainfall is not dependable. Contribution of NEM to the total rainfall is 50.3 percent which was followed by SWM (26.3%). Contribution of NEM during every 30 years of periods was constantly increasing and the increasing trend was statistically significant at 95% confidence level. Total number of rainy days (very light, light, moderate, rather heavy, heavy, very heavy rainy days) during the study period was 80.2 days, in which the frequency of very light rainy days (35.0 days) was highest followed by light (20.7 days) and moderate rainy days (20.8 days). Trend analysis was done for all categories of rainfall to find out the presence of increasing or decreasing trend. Total number of rainy days slightly gets decreasing in all the seasons except NEM where the rainy days are increasing but the changes were not statistically significant. The results showed that there is no change in long term of monthly, seasonal, annual rainfall and frequency of rainy days. Hence, it can be concluded that there is no climate change observed over Coimbatore.
Essential Oil Components as Potential Means to Control Penicillium digitatum Pers . ( Sacc . ) and Other Postharvest Pathogens of Citrus Fruit

The studies were conducted on 37 compounds present in citrus essential oils, to test their activity against Penicillium digitatum Pers. (Sacc.) by three in vitro assays: agar diffusion, amended growth medium (“poisoned food”) and vapor assay. The aliphatic alcohols 1nonanol, 1-decanol and especially 1-octanol exhibited the highest activities against P. digitatum, as assayed by all the methods used. The terpenoid compounds perillalcohol, perillaldehyde, citral, terpineol, carveol and citronellol, as well as the aromatic compound cinnamaldehyde, which is not a component of citrus oil but was used as a reference material, exhibited high activity against P. digitatum. The hydrocarbons d-limonene and myrcene, and the esters octyl acetate, decyl acetate, geranyl acetate, neryl acetate and linalyl acetate did not inhibit this fungus. 1-Octanol, perillaldehyde, citral, perillalcohol and terpineol were fungicidal, whereas 1-decanol, 1-nonanol, carveol and citronellol were only fungistatic. 1-Octanol, 1-decanol, perillaldehyde and citral also showed antifungal activity against Alternaria citri Ell. et Pierce and Penicillium italicum Wehmer. In addition 1-octanol and perillaldehyde were active against Geotrichum candidum Link. The selected promising compounds 1-octanol and citral were further tested in vivo on P. digitatum-inoculated lemons as active ingredients of microbiocidal formulations. Application of formulations comprising 1-octanol and citral either separately or together inhibited decay of P. digitatum-inoculated lemons for three weeks after inoculation without visible phytotoxic damage or perceivable offodor, although total control was not achieved. The results obtained demonstrated the potential of essential oil components as postharvest citrus fungicides. _____________________________________________________________________________________________________________
Brussel Plasticity of adult human pancreatic duct cells by neurogenin 3-mediated reprogramming

Aims/Hypothesis: Duct cells isolated from adult human pancreas can be reprogrammed to express islet beta cell genes by adenoviral transduction of the developmental transcription factor neurogenin3 (Ngn3). In this study we aimed to fully characterize the extent of this reprogramming and intended to improve it. Methods: The extent of the Ngn3-mediated duct-to-endocrine cell reprogramming was measured employing genome wide mRNA profiling. By modulation of the Delta-Notch signaling or addition of pancreatic endocrine transcription factors Myt1, MafA and Pdx1 we intended to improve the reprogramming. Results: Ngn3 stimulates duct cells to express a focused set of genes that are characteristic for islet endocrine cells and/or neural tissues. This neuro-endocrine shift however, is incomplete with less than 10% of full duct-to-endocrine reprogramming achieved. Transduction of exogenous Ngn3 activates endogenous Ngn3 suggesting auto-activation of this gene. Furthermore, pancreatic endocrine reprogramming of human duct cells can be moderately enhanced by inhibition of Delta-Notch signaling as well as by co-expressing the transcription factor Myt1, but not MafA and Pdx1. Conclusions/Interpretation: The results provide further insight into the plasticity of adult human duct cells and suggest measurable routes to enhance Ngn3-mediated in vitro reprogramming protocols for regenerative beta cell therapy in diabetes. Citation: Swales N, Martens GA, Bonné S, Heremans Y, Borup R, et al. (2012) Plasticity of Adult Human Pancreatic Duct Cells by Neurogenin3-Mediated Reprogramming. PLoS ONE 7(5): e37055. doi:10.1371/journal.pone. 0037055 Editor: Patrick Callaerts, VIB & Katholieke Universiteit Leuven, Belgium Received July 20, 2011; Accepted April 16, 2012; Published May 14, 2012 Copyright: 2012 Swales et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Financial support was from the VUB Research Council (HH), the Research Foundation – Flanders (FWO; http://www.fwo.be/) (HH, SB), the European Union Sixth Framework Program (http://ec.europa.eu/research/fp6/index_en.cfm; LSHB-CT-2005-512145) (ZL, DP and HH) and the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT; http://www.iwt.be) (NS and HH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: harry.heimberg@vub.ac. be . These authors contributed equally to this work.
INDUCTION OF DEFENSE ENZYMES IN FLOURESCENT PSEUDOMONADS AGAISNT WILT COPMLEX PATHOGENS OF MEDICINAL PLANTS

Wilt complex of Coleus (Coleus forskohlii (Wild) Briq. ) and Ashwagandha (Withania somnifera L. Dunal) are caused by a multitude pathogens either alone or in combination and distributed, wherever coleus and ashwagandha cultivation are persuade intensively. The major pathogens involved in wilt disease are species of Fusarium and a bacterium Ralstonia solanacearum (Smith) and root-knot caused by Meloidogyne incognita (Kofoid and White) Chitwood. All the pathogens are known to form complexes with nematodes, aggravating the disease. Nematodes alone are also potential pathogens of coleus and ashwagandha. The non availability of efficient appliances and pesticides (fungicide, bactericide and nematicide) and lack multiple disease resistant varieties also aggravated the problem. Therefore, a need for alternative methods of control of wilt complex and soil borne pathogens has become vital. Hence an attempt was made to manage these different groups of soil-borne pathogens using plant growth promoting rhizobacteria (PGPR), which induce resistance to wide range of pathogens (Liu et al., 1995). Fluorescent pseudomonads suppress the pathogens by various modes of actions namely competition for nutrients and space, antibiosis, siderophore, lytic enzymes, production of hydrogen cyanide and degradation of toxins, production of plant growth promoting substances (Sharma et al., 2014 a & b) and also induces systemic resistance (ISR) by enhancement of plant defense enzymes. Fluorescent pseudomonads activate ISR in plants against fungal, bacterial, viral diseases (Maurhofer et al., 1998), insects (Zehnder et al., 1997) and nematode pests (Sikora, 1988). Currently, attempts to protect plants from pathogens attack through PGPR have gained worldwide attention since; it is an ecofriendly and sustainable approach of plant disease management.
EVALUATION OF AN ELECTRONIC MEDICAL RECORD SYSTEM : ZONGULDAK KARAELMAS UNIVERSITY HOSPITAL SURVEY

This study investigated the electronic medical record system (EMR) of Zonguldak Karaelmas University Hospital which is in use for the last six years. The recommendations for the development of EMR and more efficient use of the system are principle goal of this study. The purposes of this study include promoting the implementation of EMR by introducing the advantages and disadvantages from the user’s point of view. While the successful applications of EMR systems are evident in western word, the implementation of EMR to a hospital information system is a new topic in Turkey. Some applications are mainly in the form of converting the paper-based medical record systems to the fully automated electronic record systems. Our study is a pioneering attempt to analyze the users’ opinion for a fully integrated EMR system in a Turkish academic hospital. The suggestions such as restricting the access, improving the hardware, integrating to the internet are made for the improvement of the system in future.
COMBINING ABILITY IN SNAKE GOURD ( TRICHOSANTHES CUCUMERINA L . )

Snake gourd (Trichosanthes cucumerina L.) belongs to the family Cucurbitaceae and it’s an important summer vegetable but it can be grown throughout the year except extreme winter. It is important as a good sources of minerals, fiber and nutrients to make the food wholesome and healthy (Ahmed et al., 2004). It is also one of the important vegetables which fetches more yield per unit area but the average yield of the crop is low. In addition it has got tremendous export potential because of its excellent keeping quality and shelf life. There are a number of cultivars with wide range of variability in size, shape and color of fruits available in this country. A large number of local lines are cultivated in the country but there is no recommended cultivar so far. There is no serious attempts have been made to upgrade the productivity of snake gourd. For developing superior varieties, it is necessary to improve the yield and its components in snake gourd. Yield is a complex character and is associated with some yield contributing characters, which are simple inherited (Rao et al., 2004). This can be achieved through effective utilization of germplasm resources and integration of genomic tools to impart efficiency and pace of breeding processes (Banga, 2012). Combining ability analysis has greater importance in crop improvement to identification of best combiners and utilize them in hybridization programme to produce superior hybrids, either to exploit for heterosis or to combine favourable genes (Meena et al., 2015). This technique was developed by Kempthorne in 1957. In addition, the information on nature of gene action will be helpful to develop efficient crop improvement programme. General combining ability is due to additive and additive × additive gene action and is fixable in nature while specific combining ability is due to non-additive gene action which may be due to dominance or epistasis or both and is non-fixable. The presence of non-additive genetic variance is the primary justification for initiating the hybrid breeding programme (Pali and Mehta, 2014). Keeping these points in view, the present investigation was undertaken to determine general combining ability and specific combining ability in snake gourd.
Development of synthesis method of magnetic nanoparticles modified by oleic acid and chitosan as a candidate for drug delivery agent

In this study, magnetic nanoparticles (MNPs) coated with a combination of oleic acid and chitosan were synthesized by ex situ and in situ coprecipitation methods. Morphology and particle size, crystal structure and crystallite size, chemical structure, and magnetic saturation were characterized by scanning electron microscope (SEM), X-ray diffraction (XRD), Fourrier transform infrared, and vibrating sample magnetometer (VSM), respectively. SEM images showed that better spherical morphology is obtained by ex situ co-precipitation method. The XRD pattern identified that nanoparticles containing Fe3O4 and γ-Fe2O3. The particles and crystallite size of the nanoparticles tended to decrease with increasing oleic acid to the optimum composition. Further functionalization through the chitosan addition (crosslinked by Tripolyphosphate/sulfate) is contributed to the hydrophilicity properties of nanoparticles. Through VSM analysis, MNPs-oleic acid-chitosan showed superparamagnetic behavior with magnetic saturation reaching 32.63 emu/g. There was a linear correlation between magnetic saturation and Fe3O4 content of nanoparticles. Drug loading and drug release were carried out by using Doxorubicin. These nanoparticles showed a high drug loading efficiency with lower chitosan composition. Loading efficiency of Doxorubicin is related to the conjugation with carboxylic groups and hydrophobic sites from oleic acid and MNPs.