Miracle-dz/UniFAR-FTUs huggingface dataset:
Antimicrobial Activity and Phytochemicals Screening of Jojoba (Simmondsia chinensis) Root Extracts and Latex

: Abstract─ Plants are rich sources of bioactive compounds. In this study the photochemical screening of hexane, ethanolic and aqueous extracts of roots and latex of jojoba (Simmondsia chinensis) plant revealed the presence of saponins, tannins, alkaloids, steroids and glycosides. Ethanolic extract was found to be richer in these metabolites than hexane, aqueous extracts and latex. The extracts and latex displayed effective antimicrobial activity against Salmonella typhimurium, Bacillus cereus, Clostridium perfringens, Staphylococcus aureus, Escherichia coli, Candida albicans and Aspergillus flavus. The increase in volume of the extracts and latex caused more activity, as shown by zones of inhibition. Candida albicans growth was inhibited only by hexane extract. Jojoba latex was not effective against Candida albicans at 0.1 and 0.5 ml extracts concentration but showed 5mm zone of inhibition at (1.0 ml). Lower volume (0.1ml) of latex encouraged Aspergillus flavus growth, while at (1.00 ml) reduced its mycelial growth. Thus, jojoba root extracts and latex can be of potential natural antimicrobial agents.
Automatic discretization of actions and states in Monte-Carlo tree search

While Monte Carlo Tree Search (MCTS) represented a revolution in game related AI research, it is currently unfit for tasks that deal with continuous actions and (often as a consequence) game-states. Recent applications of MCTS to quasi continuous games such as no-limit Poker variants have circumvented this problem by discretizing the action or the statespace. We present Tree Learning Search (TLS) as an alternative to a priori discretization. TLS employs ideas from data stream mining to combine incremental tree induction with MCTS to construct game-state-dependent discretizations that allow MCTS to focus its sampling spread more efficiently on regions of the search space with promising returns. We evaluate TLS on global function optimization problems to illustrate its potential and show results from an early implementation on a full scale no-limit Texas Hold’em Poker bot.
MolMovDB: analysis and visualization of conformational change and structural flexibility

The Database of Macromolecular Movements (http://MolMovDB.org) is a collection of data and software pertaining to flexibility in protein and RNA structures. The database is organized into two parts. Firstly, a collection of 'morphs' of solved structures representing different states of a molecule provides quantitative data for flexibility and a number of graphical representations. Secondly, a classification of known motions according to type of conformational change (e.g. 'hinged domain' or 'allosteric') incorporates textual annotation and information from the literature relating to the motion, linking together many of the morphs. A variety of subsets of the morphs are being developed for use in statistical analyses. In particular, for each subset it is possible to derive distributions of various motional quantities (e.g. maximum rotation) that can be used to place a specific motion in context as being typical or atypical for a given population. Over the past year, the database has been greatly expanded and enhanced to incorporate new structures and to improve the quality of data. The 'morph server', which enables users of the database to add new morphs either from their own research or the PDB, has also been enhanced to handle nucleic acid structures and multi-chain complexes.
Intraoperative Monitoring of an Aspect of Executive Functions: Administration of the Stroop Test in 9 Adult Patients During Awake Surgery for Resection of Frontal Glioma

BACKGROUND: Awake brain surgery allows extensive intraoperative monitoring of not only motor and sensory functions and language but also executive functions. OBJECTIVE: To administer the Stroop test intraoperatively to avoid dramatic side effects such as akinetic mutism and to monitor executive functions in an attempt to optimize the benefit/risk balance of surgery. METHODS: A series of 9 adult patients with frontal glioma were operated on for gross tumor resection under local anesthesia. All procedures involved the anterior cingulate cortex (ACC). RESULTS: Three types of response to the Stroop test were observed: 3 patients had a Stroop effect only for stimulation of the contralateral ACC; 3 patients had a Stroop effect for stimulation of the ipsilateral ACC; and 3 patients had no Stroop effect. Preoperative and postoperative neuropsychological and surgical results are presented and discussed. Stimulation sites eliciting a Stroop effect are compared with published image-based data, and insight provided by these surgical data regarding ACC function and plasticity is discussed. No operative complication related to intraoperative administration of the Stroop test was observed. CONCLUSION: Administration of the Stroop test during resection of gliomas involving the ACC in adult patients is an option for intraoperative monitoring of executive functions during awake surgery. Globally, these results suggest functional compensation, mediated by plasticity mechanisms, by contralateral homologous regions of the ACC in adult patients with frontal glioma. ABBREVIATIONS: ACC, anterior cingulate cortex SE, Stroop effect
Adaptive processing of thin structures to augment segmentation of dual-channel structural MRI of the human brain

This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.
Using local texture maps of brain MR images to detect Mild Cognitive Impairment

Early detection of Alzheimer's disease is expected to aid in the development and monitoring of more effective treatments. Classification methods have been proposed to distinguish Alzheimer's patients from normal controls using Magnetic Resonance Images. However, their performance drops when classifying patients at a prodromal stage, such as in Mild Cognitive Impairment. Most often, the features used in these classification tasks are related to structural measures such as volume, shape and tissue density. However, microstructural changes have been shown to arise even earlier than these larger-scale alterations. Taking this into account, we propose the use of local statistical texture maps that make no assumptions regarding the location of the affected brain regions. Each voxel contains texture information from its local neighborhood and is used as a feature in the classification of normal controls and Mild Cognitive Impairment patients. The proposed approach obtained an accuracy of 87% (sensitivity 85%, specificity 95%) with Support Vector Machines, outperforming the 63% achieved by the local gray matter density feature.
Detecting autism, emotions and social signals using adaboost

In the area of speech technology, tasks that involve the extraction of non-lingustic information have been receiving more attention recently. The Computational Paralinguistics Challenge (ComParE 2013) sought to develop techniques to efficiently detect a number of paralinguistic events, including the detection of non-linguistic events (laughter and fillers) in speech recordings as well as categorizing whole (albeit short) recordings by speaker emotion, conflict or the presence of development disorders (autism). We treated these sub-challenges as general classification tasks and applied the general-purpose machine learning meta-algorithm, AdaBoost.MH, and its recently proposed variant, AdaBoost.MH. BA, to them. The results show that these new algorithms convincingly outperform baseline SVM scores.
Assessing pathogenicity of Gallibacterium anatis in a natural infection model: the respiratory and reproductive tracts of chickens are targets for bacterial colonization

Two separate bird trials were performed to establish a reliable route of infection for Gallibacterium anatis in chickens, comparing intranasal (i.n.) and intravenous (i.v.) applications. Additionally, three mutually divergent isolates from three geographical locations, as shown by MALDI-TOF-MS and partial rpoB gene sequence analysis, were compared. In the first trial, birds were infected with one of the selected isolates by the i.v. or i.n. route. Subsequently, birds were killed 3, 12 and 24 h post infection following i.v. infection while at 3, 7 and 10 days post infection (dpi) in the case of i.n. infection along with birds of the control group. As a result, i.n. infection showed prominent and consistent bacterial tissue distribution in different organs persisting until 10 dpi, which was a striking contrast to the i.v. infection route. Likewise, histopathology revealed mild to severe tracheal lesions following i.n. infection. The second trial was set up to confirm both the achieved results and the robustness of i.n. infection but with an extended observation period, until 28 dpi In agreement with the preceding trial, identical results for bacteriological and histopathological examinations were obtained with persistency of bacteria until 28 dpi Comparing the three different isolates from Mexico, China and Austria, the Mexican isolate showed a somewhat higher pathogenicity than the other strains. Consequently, pathogenesis of G. anatis strains was studied in chickens elucidating i.n. infection as the most reliable route characterized by a long-lasting bacteraemia, targeting the respiratory and reproductive tract.
Design of frequency shift acceleration control for anti-islanding of an inverter-based DG

The paper proposes frequency shift acceleration control (FSAC) for anti-islanding of an inverter-based distributed generator. The key concept is to disturb an islanded system frequency by controlling reactive current output in d-q frame, and accelerate the resulting frequency shift using an acceleration gain. Design method of the acceleration gain is proposed using analytical approaches, based on small-signal stability and step input response. Simulation and experimental results are presented.
A sex-specific role for androgens in angiogenesis

Mounting evidence suggests that in men, serum levels of testosterone are negatively correlated to cardiovascular and all-cause mortality. We studied the role of androgens in angiogenesis, a process critical in cardiovascular repair/regeneration, in males and females. Androgen exposure augmented key angiogenic events in vitro. Strikingly, this occurred in male but not female endothelial cells (ECs). Androgen receptor (AR) antagonism or gene knockdown abrogated these effects in male ECs. Overexpression of AR in female ECs conferred androgen sensitivity with respect to angiogenesis. In vivo, castration dramatically reduced neovascularization of Matrigel plugs. Androgen treatment fully reversed this effect in male mice but had no effect in female mice. Furthermore, orchidectomy impaired blood-flow recovery from hindlimb ischemia, a finding rescued by androgen treatment. Our findings suggest that endogenous androgens modulate angiogenesis in a sex-dependent manner, with implications for the role of androgen replacement in men.
Analysis of interleukin 6 receptor and gp130 expressions and proliferative capability of human CD34+ cells

We recently demonstrated that stimulation of gp130 by a combination of soluble interleukin 6 receptor (sIL-6R) and IL-6 but not IL-6 alone significantly stimulates the ex vivo expansion of primitive hematopoietic progenitors and the generation of erythroid cells from human CD34+ cells in the presence of stem cell factor (SCF). Here, we show that gp130 is found low positively on most CD34+ cells, whereas IL- 6R is expressed on only 30-50% of these cells. Although most of the colonies generated from FACS-sorted CD34+IL-6R+ cells were granulocyte/macrophage (GM) colonies, CD34+IL-6R- cells gave rise to various types of colonies, including erythroid bursts, GM, megakaryocytes, and mixed colonies in methylcellulose culture with a combination of IL-6, sIL-6R, and SCF. Similar results were obtained in culture supplemented with a combination of IL-3, IL-6, SCF, granulocyte colony-stimulating factor, erythropoietin, and thrombopoietin. A limiting dilution analysis of long-term culture-initiating cells (LTC- IC) showed that the CD34+IL-6R- cells contained a larger number of LTC- IC than did the CD34+IL-6R+ cells. In a serum-free suspension of CD34+IL-6R- cells, the addition of sIL-6R to the combination of IL-6 and SCF dramatically increased the total and multipotential progenitors, whereas CD34+IL-6R+ cells failed to do so under the same conditions. These results indicate that most of the erythroid, megakaryocytic, and primitive human hematopoietic progenitors are included in the IL-6R- populations, and the activation of gp130 on these progenitors can be achieved by a complex of IL-6-sIL-6R, but not by IL-6 alone. The present culture system using IL-6, sIL-6R, and SCF may provide a novel approach for ex vivo expansion of human primitive hematopoietic progenitors.
Change Detection Using High Resolution Remote Sensing Images Based on Active Learning and Markov Random Fields

Change detection has been widely used in remote sensing, such as for disaster assessment and urban expansion detection. Although it is convenient to use unsupervised methods to detect changes from multi-temporal images, the results could be further improved. In supervised methods, heavy data labelling tasks are needed, and the sample annotation process with real categories is tedious and costly. To relieve the burden of labelling and to obtain satisfactory results, we propose an interactive change detection framework based on active learning and Markov random field (MRF). More specifically, a limited number of representative objects are found in an unsupervised way at the beginning. Then, the very limited samples are labelled as “change” or “no change” to train a simple binary classification model, i.e., a Gaussian process model. By using this model, we then select and label the most informative samples by “the easiest” sample selection strategy to update the former weak classification model until the detection results do not change notably. Finally, the maximum a posteriori (MAP) change detection is efficiently computed via the min-cut-based integer optimization algorithm. The time consuming and laborious manual labelling process can be reduced substantially, and a desirable detection result can be obtained. The experiments on several WorldView-2 images demonstrate the effectiveness of the proposed method.
Acceptability ratings by humans and automatic gesture recognition for variations in sign productions

In this study we compare human and machine acceptability judgments for extreme variations in sign productions. We gathered acceptability judgments of 26 signers and scores of three different automatic gesture recognition (AGR) algorithms that could potentially be used for automatic acceptability judgments, in which case the correlation between human ratings and AGR scores may serve as an dasiaacceptability performancepsila measure. We found high human-human correlations, high AGR-AGR correlations, but low human-AGR correlations. Furthermore, in a comparison between acceptability and classification performance of the different AGR methods, classification performance was found to be an unreliable predictor of acceptability performance.
Political Language and Metaphor: Interpreting and Changing the World edited by Terrell Carver and Jernej Pikalo

List of illustrations x Notes on contributors xii Acknowledgements xvi Editors' introduction 1 (12) Terrell Carver Jernej Pikalo PART I Science 13 (42) The ways of stargazing: Newtonian metaphoricity in American foreign policy 15 (13) Dimitrios E. Akrivoulis Slippery slopes in political discourse 28 (13) Dag Stenvoll Mechanical metaphors in politics 41 (14) Jernej Pikalo PART II Structures 55 (48) Metaphors of social order 57 (12) Erik Ringmar Metaphors of solidarity 69 (14) Iseult Honohan Exploring the metaphorical (de-)construction of legitimacy: a comparison of legitimation discourses in American and British newspapers 83 (20)
Characterization and modeling of zero bias rf-detection diodes based on triple barrier resonant tunneling structures

InP-based resonant tunneling diodes with symmetrical I/V-characteristics have shown their excellent high frequency performance for THz signal generation. For signal detection we present a device with an additional third barrier to create an unsymmetrical I/V-characteristic. Sensitivity measurements are performed and further improvements by scaling of the active device area are discussed. To allow SPICE based circuit simulation an approach for a large signal model is presented.
Quitting smoking: The importance of non-smoker identity in predicting smoking behaviour and responses to a smoking ban

Objective: We examined how ‘smoker’ and ‘non-smoker’ self- and group-identities and socio-economic status (SES) may predict smoking behaviour and responses to antismoking measures (i.e. the Dutch smoking ban in hospitality venues). We validated a measure of responses to the smoking ban. Design: Longitudinal online survey study with one-year follow-up (N = 623 at T1 in 2011; N = 188 at T2 in 2012) among daily smokers. Main outcome measures: Intention to quit, quit attempts and ‘rejecting’, ‘victimizing’, ‘socially conscious smoking’ and ‘active quitting’ responses to the smoking ban. Results: Non-smoker identities are more important than smoker identities in predicting intention to quit, quit attempts and responses to the smoking ban, even when controlling for other important predictors such as nicotine dependence. Smokers with stronger non-smoker identities had stronger intentions to quit, were more likely to attempt to quit between measurements, and showed less negative and more positive responses to the smoking ban. The association between non-smoker self-identity and intention to quit was stronger among smokers with lower than higher SES. Conclusion: Antismoking measures might be more effective if they would focus also on the identity of smokers, and help smokers to increase identification with non-smoking and non-smokers.
Diffusion in Social Networks and Market Stability

In this paper we propose a model of the evolution of a market with linear utilities in the presence of both local and global social interactions. In the scenario considered, there is a market consisting of buyers and divisible goods. In consecutive time periods, the decision of a buyer is affected by the consumption plan of his neighbors and by a global signal, the distribution of actions of all agents. Moreover, we assume that the market prices and the allocation of the goods are stabilized by the law of supply and demand. We simulate the model, along with a market equilibria algorithm, and we investigate the long time behavior of the system. Specifically, we analyze the distribution of the prices and the market share of the products, when the configuration of the network is Erdos-Renyi and Scale-free graph. The experimental results show that the long time behavior of the system is not always static. The long time states depict a periodic pattern and are sensitive to a) the initial agents' beliefs, b) the weights that each agent assigns to the local and the global factor respectively and c)the degree distribution of the nodes in the network.
On Modeling Network with Multiple Feedback Loops using Fluid-Flow Approximation

In this paper, we propose a novel analytic approach for a closed-loop network with multiple feedback loops by extending the analytic model proposed in [1]. Specifically, we model building blocks of a network (i.e., the congestion control mechanism of TCP, propagation delay of a transmission link, and the buffer of a router) by independent continuous-time systems. By interconnecting these systems, we obtain the model for the entire closed-loop network. We also obtain a block diagram for each continuous-time system using the CAD tool for control engineering. We then perform several preliminary performance evaluations of a closed-loop network using numerical simulations. Moreover, we validate the effectiveness of our analytic approach by comparing our analytic results with simulation results.