Miracle-dz/UniFAR-FTUs huggingface dataset:
Involvement of an Extracellular Protease in Algicidal Activity of the Marine Bacterium Pseudoalteromonassp. Strain A28

ABSTRACT The marine bacterium Pseudoalteromonas sp. strain A28 was able to kill the diatom Skeletonema costatum strain NIES-324. The culture supernatant of strain A28 showed potent algicidal activity when it was applied to a paper disk placed on a lawn ofS. costatum NIES-324. The condensed supernatant, which was prepared by subjecting the A28 culture supernatant to ultrafiltration with a 10,000-Mw-cutoff membrane, showed algicidal activity, suggesting that strain A28 produced extracellular substances capable of killing S. costatum cells. The condensed supernatant was then found to have protease and DNase activities. Two Pseudoalteromonas mutants lacking algicidal activity, designated NH1 and NH2, were selected afterN-methyl-N′-nitrosoguanidine mutagenesis. The culture supernatants of NH1 and NH2 showed less than 15% of the protease activity detected with the parental strain, A28. The protease was purified to homogeneity from A28 culture supernatants by using ion-exchange chromatography followed by preparative gel electrophoresis. Paper-disk assays revealed that the purified protease had potent algicidal activity. The purified protease had a molecular mass for 50 kDa, and the N-terminal amino acid sequence was determined to be Ala-Thr-Pro-Asn-Asp-Pro. The optimum pH and temperature of the protease were found to be 8.8 and 30°C, respectively, by using succinyl-Ala-Ala-Pro-Phe-p-nitroanilide as a substrate. The protease activity was strongly inhibited by phenylmethylsulfonyl fluoride, diisopropyl fluorophosphate, antipain, chymostatin, and leupeptin. No significant inhibition was detected with EDTA, EGTA, phenanthroline or tetraethylenepentamine. These results suggest thatPseudoalteromonas sp. strain A28 produced an extracellular serine protease which was responsible for the algicidal activity of this marine bacterium.
Duality theory for optimal investments under model uncertainty

Robust utility functionals arise as numerical representations of investor prefer- ences, when the investor is uncertain about the underlying probabilistic model and averse against both risk and model uncertainty. In this paper, we study the duality theory for the problem of maximizing the robust utility of the terminal wealth in a general incomplete market model. We also allow for very general sets of prior models. In particular, we do not assume that all prior models are equivalent to each other, which allows us to handle many economically meaningful robust utility functionals such as those defined by AVaR , concave distortions, or convex capacities. We also show that dropping the equivalence of prior models may lead to new eects such as the existence of arbitrage strategies under the least favorable model.
Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement

In this paper, we propose a new tag-based image retrieval framework to improve the retrieval performance of a group of related personal images captured by the same user within a short period of an event by leveraging millions of training web images and their associated rich textual descriptions. For any given query tag (e.g., “car”), the inverted file method is employed to automatically determine the relevant training web images that are associated with the query tag and the irrelevant training web images that are not associated with the query tag. Using these relevant and irrelevant web images as positive and negative training data respectively, we propose a new classification method called support vector machine (SVM) with augmented features (AFSVM) to learn an adapted classifier by leveraging the prelearned SVM classifiers of popular tags that are associated with a large number of relevant training web images. Treating the decision values of one group of test photos from AFSVM classifiers as the initial relevance scores, in the subsequent group-based refinement process, we propose to use the Laplacian regularized least squares method to further refine the relevance scores of test photos by utilizing the visual similarity of the images within the group. Based on the refined relevance scores, our proposed framework can be readily applied to tag-based image retrieval for a group of raw consumer photos without any textual descriptions or a group of Flickr photos with noisy tags. Moreover, we propose a new method to better calculate the relevance scores for Flickr photos. Extensive experiments on two datasets demonstrate the effectiveness of our framework.
Neuroendocrine Control of Growth Hormone Secretion

It is now a tenet of neuroendocrinology that the secretion of growth hormone (GH) is regulated by the central nervous system (CNS) (1). Two specific neuropeptides in the hypothalamus, GH-releasing hormone (GHRH) and somatostatin, exert dual control over GH secretion. These in turn are regulated by numerous neurotransmitters, which may act at the level of the GHRHor somatostatin-producing neurones or both. Both amine and amino acids neurotransmitters play a role in the control of GH release and, in general, they exert a dual influence, either stimulating or inhibiting hormone release. This dual effect on GH secretion results from actions of the same molecule at both GHRHand somatostatin-secreting neurones. This is best exemplified by catecholamines, where aand 0-adrenoceptors exert, respectively, stimulatory and inhibitory influences. Alternatively, the neurotransmitter may pass into the stalk blood to act at a receptor site located on the somatotroph (2). As a result of GH secretion, both GH itself and the GH-dependent insulinlike growth factors (IGFs) exert a feedback inhibitory action on GH secretion via hypothalamic and/or pituitary sites (Fig. 1). In addition to the classical neurotransmitters, a host of neuropeptides stimulate GH release, though their physiological function is unclear. In general, these compounds do not act directly at the level of the pituitary, but via the CNS, particularly with the mediation of classical neurotransmitters (1, 3). This paper focuses on certain aspects of the neuroendocrine control of GH secretion which the authors have investigated recently.
Interaction between current imbalance and magnetization in LHC cables

The quality of the magnetic field in superconducting accelerator magnets is associated with the properties of the superconducting cable. Current imbalances due to coupling currents /spl Delta/I, as large as 100 A, are induced by spatial variations of the field sweep rate and contact resistances. During injection at a constant field all magnetic field components show a decay behavior. The decay is caused by a diffusion of coupling currents into the whole magnet. This results in a redistribution of the transport current among the strands and causes a demagnetization of the superconducting cable. As soon as the field is ramped up again after the end of injection, the magnetization rapidly recovers from the decay and follows the course of the original hysteresis curve. In order to clarify the interactions between the changes in current and magnetization during injection the authors performed a number of experiments. A magnetic field with a spatially periodic pattern was applied to a superconducting wire in order to simulate the coupling behavior in a magnet. This model system was placed into a stand for magnetization measurements and the influence of different powering conditions was analyzed.
Establishing a method of vector contamination identification in database sequences

MOTIVATION The nucleotide sequence databases are invaluable tools both for the private and the academic research communities, from the retrieval of sequences to homology searching. Several issues related to data quality, such as the existence of sequencing artifacts and errors, are facing the databases. We investigated a major source of these errors, i.e. the presence of vector-contaminated sequences. RESULTS Using a panel of 180 vector polylinker sequences, we found 0.36% or 3029 vector-matching sequences in GenBank Release 95-96, with an average vector-matching length of 72 nucleotides. The number of vector-contaminated sequences has been growing with the database; however, the percent contamination has remained approximately constant at an average of 0.28% from 1982 to 1996. AVAILABILITY Access to the database of vector polylinker sequences via sequence similarity searching is available at http://seqsim.ncgr. org/vector/ CONTACT gas@molinfo.com
Social Work and Hermeneutic Phenomenology

In this article, I discuss the connections between social work practice and interpretive approaches to knowledge building, introduce and situate hermeneutic phenomenology for novice social work researchers, and explore the fit between hermeneutic phenomenology and social work. Â This paper also presents a historical, methodological, and philosophical overview of the roots of hermeneutic/interpretive phenomenology from Augustine to Sartre. Â I advocate for the congruence between an hermeneutic approach and social work research due to its focus on inquiry as application, emphasis on the situated nature of human experiences, concept of attention to the unspoken or undisclosed, idea of the hermeneutic circle as a link between individual experiences and larger structures, fusion of horizons, and inclusion of the practitioner identity in research activities.
An Ontology-Based Computational Framework for Analyzing Public Opinion Framing in News Media

The aim of this study is to develop a computational framework for analyzing the framing of news coverage for controversial public issues by comparing the coverage from ideologically distant news media sources. Because news media sources play a key role in the formation of public opinion, their coverage also plays a major role in the dynamics of the public debates. It can be hypothesized that the public interactions of political players may be treated differently in the media based on the editorial perspective of the media sources in question and the positions that the political players occupy in the political arena. However, the question arises, how can these differences be measured? Using corpus extraction techniques, SPARQL queries, and ontology engineering, this study compares the positions that key political players occupy in discourse spaces that are modeled by two ideologically distant news media sources based on the same controversial public issue.
Supervised framework for automatic recognition and retrieval of interaction: a framework for classification and retrieving videos with similar human interactions

This study presents supervised framework for automatic recognition and retrieval of interactions (SAFARRIs), a supervised learning framework to recognise interactions such as pushing, punching, and hugging, between a pair of human performers in a video shot. The primary contribution of the study is to extend the vectors of locally aggregated descriptors (VLADs) as a compact and discriminative video encoding representation, to solve the complex class partitioning problem of recognising human interaction. An initial codebook is generated from the training set of video shots, by extracting feature descriptors around the spatiotemporal interest points computed across frames. A bag of action words is generated by encoding the first-order statistics of the visual words using VLAD. Support vector machine classifiers (1 against all) are trained using these codebooks. The authors have verified SAFARRI's accuracy for classification and retrieval (query by example). SAFARRI is free from tracking or recognition of body parts and capable of identifying the region of interaction in video shots. It gives superior retrieval and classification performances over recently proposed methods, on two publicly available human interaction datasets.
Identification of gains and losses of DNA sequences in primary bladder cancer by comparative genomic hybridization

Comparative genomic hybridization (CGH) makes it possible to detect losses and gains of DNA sequences along all chromosomes in a tumor specimen based on the hybridization of differentially labeled tumor and normal DNA to normal human metaphase chromosomes. In this study, CGH analysis was applied to the identification of genomic imbalances in 26 bladder cancers in order to gain information on the genetic events underlying the development and progression of this malignancy. Losses affecting 11p, 11q, 8p, 9, 17p, 3p, and 12q were all seen in more than 20% of the tumors. The minimal common region of loss in each chromosome was identified based on the analysis of overlapping deletions in different tumors. Gains of DNA sequences were most often found at chromosomal regions distinct from the locations of currently known oncogenes. The bands involved in more than 10% of the tumors were 8q21, 13q21‐q34, 1q31, 3q24‐q26, and 1p22. In conclusion, these CGH data highlight several previously unreported genetic alterations in bladder cancer. Further detailed studies of these regions with specific molecular genetic techniques may lead to the identification of tumor suppressor genes and oncogenes that play an important role in bladder tumorigenesis.
Physical-layer encryption for enhanced cyber-physical security

Communication in wide-area measurement/control systems (WAM/CS) presents simultaneous challenges of achieving low latency, high security, and sufficient data throughputs to meet the overall quality of service requirements. High-value and timecritical information such as that indicating transient instability or attacks on the cyber-physical infrastructure must be delivered to their destination within 5-20 ms of identification [1], eliminating many of the existing commercial communications solutions that employ a traditional net-centric ISO stack-based architecture. This paper focuses on a physical-layer wireless communications technology capable of supporting real-time protection, detection, and reaction processes within the WAM/CS via physical-layer encryption. This PHY-layer encryption adapts a maximum entropy digital chaotic spread spectrum waveform originally developed for secure military communications [2] by employing the underlying spreading sequence as a private key cryptosystem, thus avoiding latencies derived from MAC-layer framing or cryptographic block algorithms. The proposed approach delivers latencies on the order of 500μs per node, allowing significant flexibility in wireless network topology. We present the proposed PHY-layer encryption system in the context of communicating an a monitored “event,” evaluate its behavior against the traditional IA objectives, and also consider its integration with related communications techniques to demonstrate its utility as a building block for enhancing cyber-physical security.
Classifier Based Text Mining for Neural Network

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms. Keywords—Back propagation, classification accuracy, text mining, time complexity.
Present and future therapies of hepatitis B: From discovery to cure

Hepatitis B virus (HBV) is a significant global pathogen, infecting more than 240 million people worldwide. While treatment for HBV has improved, HBV patients often require lifelong therapies and cure is still a challenging goal. Recent advances in technologies and pharmaceutical sciences have heralded a new horizon of innovative therapeutic approaches that are bringing us closer to the possibility of a functional cure of chronic HBV infection. In this article, we review the current state of science in HBV therapy and highlight new and exciting therapeutic strategies spurred by recent scientific advances. Some of these therapies have already entered into clinical phase, and we will likely see more of them moving along the development pipeline. Conclusion: With growing interest in developing and efforts to develop more effective therapies for HBV, the challenging goal of a cure may be well within reach in the near future. (Hepatology 2015;62:1893–1908)
Substantive and procedural aspects of international criminal law : the experience of international and national courts

Volume I: Foreword J.L. Arbour. Introduction G.K. McDonald, O. Swaak-Goldman. 1. Individual Criminal Responsibility in International Criminal Law K. Ambos. 2. The Crime ofAggression B.B. Ferencz. 3. Grave Breaches of the 1949 Geneva Convention H. Fischer. 4. Violations of the Laws or Customs of War G.H. Aldrich. 5. Genocide: A Crime Against Mankind D.D. Ntanda Nsereko. 6. Crimes Against Humanity O. Swaak-Goldman. 7. Overlapping Crimes. A. Murder/Wilful Killing G. Heine, H. Vest. B. Torture and Other Offenses Involving the Violation of the Physical or Mental Integrity of the Human Person A. Byrnes. C. Persecution O. Swaak-Goldman. D. the Context of Sexual Violence: Sexual Violence as Violations of International Humanitarian Law P. Viseur Sellers. 8. Crimes Against United Nations and Associated Personnel M. -C. Bourloyannis-Vrailas. 9. Defences Y. Dinstein. 10. National Courts and the Prosecution of War Crimes R. Wedgwood. 11. Rights of Suspects and Accused M. Wladimiroff. 12. The Protection of Victims and Witnesses C. Chinkin. 13. Pre-Trial Procedures and Practices L. Chand Vohrah. 14. Trial Procedures and Practices G.K. McDonald. 15. Appeal Procedures and Practices A.G. Karibi-Whyte. Volume II: Dedication. Introduction G.K. McDonald, O. Swaak-Goldman. Acknowledgements. Part 1: Documents. A. International. B. Regional. C. Municipal. Part 2: Cases. A. International. B. Regional. C. Municipal.
Detection of volatile compounds emitted by Pseudomonas aeruginosa using selected ion flow tube mass spectrometry

Pseudomonas aeruginosa (PA) is associated with a distinctive smell produced by a combination of volatile compounds (VCs). Selected ion flow tube mass spectrometry (SIFT‐MS) provides a novel and rapid methodology for rapid, accurate detection of trace quantities (parts per billion; ppb) of VCs in air. We studied the VCs produced by different isolates of PA cultures in vitro from patients with cystic fibrosis. Twenty‐one patients with cystic fibrosis provided sputum and cough swab samples for culture. These were used to inoculate blood agar (BA) and Pseudomonas‐selective media (PSM). These plates were incubated for 48 hr at 37°C inside sealed plastic bags. The air surrounding the samples after 48 hr (headspace) was analyzed using SIFT‐MS. PA growth was commonly associated with the production of significant quantities of VCs, notably hydrogen cyanide gas (HCN). This was detectable in the headspace of 15/22 of PA‐positive samples. In contrast, it was only seen in the headspace of 1/13 control samples (6 sterile plates and 7 plates with only mixed upper respiratory tract flora). The concentration of HCN was significantly higher above PA‐positive samples than above other bacterial growth (P < 0.01), and in our study, levels of HCN greater than 100 ppb were a sensitive (68%) and highly specific (100%) biomarker of PA. SIFT‐MS can detect a range of VCs from PA in vitro. HCN may be a specific indicator of PA infection in vivo, and offers promise as a biomarker for noninvasive detection of PA infection by breath analysis. Pediatr Pulmonol. © 2005 Wiley‐Liss, Inc.
Autoimmunity to type II collagen an experimental model of arthritis

We have found that intradermal injection of native type II collagen extracted from human, chick or rat cartilage induces an inflammatory arthritis in approximately 40% of rats of several strains whether complete Freund's adjuvant or incomplete Freund's adjuvant is used. Type I or III collagen extracted from skin, cartilage proteoglycans and alpha1(II) chains were incapable of eliciting arthritis, as was type II collagen injected without adjuvant. The disease is a chronic proliferative synovitis, resembling adjuvant arthritis in rats and rheumatoid arthritis in humans. Native type II co-lagen modified by limited pepsin digestion still produces arthritis, suggesting that type- specific determinants residing in the helical region of the molecule are responsible for the induction of disease. Since homologous type II collagen emulsified in oil without bacterial preparations regularly causes the disease, this new animal model of arthritis represents a unique example of experimentally-inducible autoimmunity to a tissue component.
Estrategias de selección de información en tareas de contestación a preguntas

Resumen El objetivo del estudio fue investigar las estrategias de selección de información de estudiantes de secundaria en una situación de lectura orientada a tareas. Treinta seis estudiantes leyeron dos textos y contestaron seis preguntas por texto, tres de las cuales habían sido manipuladas para inducir un falso emparejamiento de palabras entre el enunciado de la pregunta y localizaciones erróneas del texto. Analizamos si los estudiantes con buen y peor nivel de comprensión contestarían con éxito las preguntas y si copiarían información errónea a partir de un falso emparejamiento de palabras. Los estudiantes con buen nivel de comprensión puntuaron mejor en preguntas y aquellos con peores niveles de comprensión copiaron información más veces a partir de pistas falsas, especialmente en las preguntas más difíciles. Estos resultados sugieren que un buen nivel de comprensión facilita el uso de estrategias de selección a partir de ideas, mientras que un peor nivel de comprensión induce el uso inapropiado de estrategias de contestación basadas en el emparejamiento de palabras.
A study of relevance feedback in vector space model

A Study of Relevance Feedback in Vector Space Model by Deepthi Katta Dr. Kazem Taghva, Examination Committee Chair Professor of Computer Science University of Nevada, Las Vegas Information Retrieval is the science of searching for information or documents based on information need from a huge set of documents. It has been an active field of research since early 19 century and different models of retrieval came in to existence to cater the information need. This thesis starts with understanding some of the basic information retrieval models, followed by implementation of one of the most popular statistical retrieval model known as Vector Space Model. This model ranks the documents in the collection based on the similarity measure calculated between the query and the respective document. The user specifies the "information need" which is more commonly known as a "query" using the visual interface provided. The given query is then processed and the results are displayed to the user in a ranked order. We then focus on the Relevance feedback, a technique that modifies the user query based on the characteristics of the document