Miracle-dz/UniFAR-FTUs huggingface dataset:
Tris{2-methoxy-6-[(4-methylphenyl)iminiomethyl]phenolato-κ2 O,O′}tris(thiocyanato-κN)praseodymium(III) monohydrate

The asymmetric unit of title compound, [Pr(NCS)3(C15H15NO2)3]·H2O, consists of three Schiff base 2-methoxy-6-[(4-methylphenyl)iminomethyl]phenol (HL) ligands, three independent thiocyanate anions and an uncoordinated water molecule. The PrIII ion is nine-coordinated. The thiocyanate anions coordinate to the PrIII ion via the N atoms and the three HL ligands chelate the PrIII ion via the phenoxy and methoxy O atoms. The protonated imine N atoms are involved in intramolecular hydrogen bonds with the phenolate groups.
LMI-based robust admissible control for uncertain singular delta operator systems

This paper investigates the problem of state feedback robust admissible control for singular delta operator systems with norm-bounded coefficient matrix uncertainties. A necessary and sufficient condition is derived to ensure the admissibility of the closed-loop singular delta operator system for all allowable uncertainties. Then, by specifying the structure of some matrix variables, the existence condition and explicit expression of a robust admissible controller are obtained in terms of strict linear matrix inequalities. Moreover, from the relation between singular discrete systems and singular delta operator systems, the corresponding results are also presented for uncertain singular discrete systems. Finally, some numerical examples are provided to demonstrate the effectiveness of the results in this paper.
Regulation of pho Regulon Gene Expression by the Carbon Control Protein A, CcpA, in Bacillus subtilis

Bacterial regulons involved in carbon, nitrogen and phosphorus metabolism must interact for purposes of coordination, but the mechanisms involved are not understood. We here report that the carbon control pro-tein-A (CcpA) of Bacillus subtilis, primarily concerned with carbon metabolism, influences expression of various phosphorus (pho) regulon genes including the two alkaline phosphatase structural genes, phoA and phoB. The directions and magnitudes of the effects of glucose and the loss of CcpA on these two genes depend on growth conditions, but they always correlate inversely. Absolute expression levels of phoA and phoB depend on a rich nitrogen source, and gene activation by a fermentable substrate such as glucose depends on the presence of a respiratory substrate such as succinate. We show that these CcpA-dependent glucose effects can be explained by the effects of glucose and CcpA acting on the phoPR operon. Although a good CcpA-binding site (CRE) is found in the control region of the phoPR operon, direct regulation of phoPR gene expression by CcpA via this CRE could not account for the effects of glucose and CcpA on phoA and phoB gene expression. We conclude that CcpA exerts indirect control over the pho regulon by a mechanism that involves CcpA and PhoRP but does not involve the phoPR operon CRE.
Machine learning for query formulation in question answering

Abstract Research on question answering dates back to the 1960s but has more recently been revisited as part of TREC's evaluation campaigns, where question answering is addressed as a subarea of information retrieval that focuses on specific answers to a user's information need. Whereas document retrieval systems aim to return the documents that are most relevant to a user's query, question answering systems aim to return actual answers to a users question. Despite this difference, question answering systems rely on information retrieval components to identify documents that contain an answer to a user's question. The computationally more expensive answer extraction methods are then applied only to this subset of documents that are likely to contain an answer. As information retrieval methods are used to filter the documents in the collection, the performance of this component is critical as documents that are not retrieved are not analyzed by the answer extraction component. The formulation of queries that are used for retrieving those documents has a strong impact on the effectiveness of the retrieval component. In this paper, we focus on predicting the importance of terms from the original question. We use model tree machine learning techniques in order to assign weights to query terms according to their usefulness for identifying documents that contain an answer. Term weights are learned by inspecting a large number of query formulation variations and their respective accuracy in identifying documents containing an answer. Several linguistic features are used for building the models, including part-of-speech tags, degree of connectivity in the dependency parse tree of the question, and ontological information. All of these features are extracted automatically by using several natural language processing tools. Incorporating the learned weights into a state-of-the-art retrieval system results in statistically significant improvements in identifying answer-bearing documents.
Passive sonar harmonic detection using feature extraction and clustering analysis

A current key problem in the development of passive sonar is the classification of data into its different noise sources. This paper focuses on solving the problem using feature extraction and clustering techniques. The methods described in this paper have been developed for data collected from a single sensor omni-directional passive sonar, with the input data being the extracted frequency tracks from a time-frequency lofagram. A single noise source will exhibit a number of frequency tracks within a lofagram, collectively these tracks form a harmonic set. The problem of harmonic detection is to associate the different components of each of the harmonic sets, or noise sources. Each of the frequency tracks within a harmonic set have a strong physical relationship defining their behaviour and properties. In solving the harmonic detection problem this physical relationship is exploited to associate frequency tracks with similar characteristics. In the solution to this problem each of the frequency tracks present have several key features measured. This allows the characteristics of each of the frequency tracks to be described in a small number of key, directly comparable, parameters. In this paper a small selection of features that may be used in the analysis of the frequency tracks are described. These features are then measured for a number of different data sets. With these sets of parameterised features it is possible to associate harmonically related frequency tracks by implementing clustering analysis, since the strong physical relationship of the features mean that related tracks will be clustered. In applying clustering, decisions need to be made into how many clusters there are in the data. The approach used in this paper uses hierarchical clustering. Hierarchical clustering begins by placing each data point into its own cluster. Two clusters are then merged based on a clustering criterion. At each step two clusters are joined until all the data is held within a single cluster. The progression of the cluster can be shown in a tree diagram, or dendrogram, which is then used to find the optimal level based on the ratio of the distribution of data within a cluster and the separation between different clusters.
Effet of Chlordecone on Rat Brain Parts Cnos Activity Livels in Vivo

In view of the neurotoxic effects induced by chlordecone an attempt is made to study the in vivo effect of this organic insecticide on rat brain based nitric oxide synthase (NOS) activity. Rats cerebellum, hypothalamus, midbrain, straiatum, hippocampus, cerebral cortex and medulla oblongate receiving sub-lethal and lethal doses of chlordecone showed decreased levels of their constitutive NOS activity and the changes were found to be statistically significant (p<0.001) over the control. Since cNOS activity in dependent on calcium / calmodulin, interaction of chlordecone with Ca²⁺/ CaM mediated events might be the reason for inhibition of cNOS activity of various brain parts of rats.
Feature Selection, Association Rules Network and Theory Building

As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be used to build a network of features, which we refer to as an association rules network, to extract features from large data sets. Association rules network can play a fundamental role in theory building - which is a task common to all data sciences- statistics, machine learning and data mining. The process of carrying out research is undergoing a dramatic shift in the twenty rst century. The cause of the shift is due to the preponderance of data available in all almost all research disciplines. From anthropology to zoology, manufacturing to surveillance, all domains are witnessing an explosion of data. The availability of massive and cheap data has opened up the possibility of carrying out data-driven research and data mining is the discipline which provides tools and techniques for carrying out this endeavour. However much of these vast repositories of data generated are observational as opposed to experimental. Observational data is undirected and is often collected without any specic task in mind. For example, web servers generate a log of client activity. The web log can then be used for a myriad of tasks ranging from tracking search engine spiders to personalization of web sites. Experimental data, on the other hand, is directed and is generated to test a specic
Regulation of apical membrane Na 1 / H 1 exchangers NHE 2 and NHE 3 in intestinal epithelial cell line C 2 / bbe

McSwine, Rebecca L. , Mark W. Musch, Crescence Bookstein, Yue Xie, Mrinalini Rao, and Eugene B. Chang. Regulation of apical membrane Na1/H1 exchangers NHE2 and NHE3 in intestinal epithelial cell line C2/bbe. Am. J. Physiol. 275 (Cell Physiol. 44): C693–C701, 1998. —We examined the regulation of the Na1/H1 exchangers (NHEs) NHE2 and NHE3 by expressing them in human intestinal C2/bbe cells, which spontaneously differentiate and have little basal apical NHE activity. Unidirectional apical membrane 22Na1 influxes were measured in NHE2-transfected (C2N2) and NHE3-transfected (C2N3) cells under basal and stimulated conditions, and their activities were distinguished as the HOE-642-sensitive and -insensitive components of 5-(N,N-dimethyl)amiloride-inhibitable flux. Both C2N2 and C2N3 cells exhibited increased apical membrane NHE activity under non-acid-loaded conditions compared with nontransfected control cells. NHE2 was inhibited by 8-(4-chlorophenylthio)adenosine 38,58-cyclic monophosphate and thapsigargin, was stimulated by serum, and was unaffected by cGMPand protein kinase C-dependent pathways. In contrast, NHE3 was inhibited by all regulatory pathways examined. Under acid-loaded conditions (which increase apical Na1 influx), NHE2 and NHE3 exhibited similar patterns of regulation, suggesting that the second messenger effects observed were not secondary to effects on cell pH. Thus, in contrast to their expression in nonepithelial cells, NHE2 and NHE3 expressed in an epithelial cell line behave similarly to endogenously expressed intestinal apical membrane NHEs. We conclude that physiological regulation and function of epitheliumspecific NHEs are dependent on tissue-specific factors and/or conditional requirements.
Females’ Labor Force Participation and Job Opportunities in the Middle East

The Middle Eastern economy suffers from high unemployment, especially among youth. Despite the fact that women comprise over 50 percent of college students in some countries, the unemployment rate among females has been much higher than their male counterparts. Using the available data, this study will compare the socio-economic factors underlying female unemployment in Iran, Egypt and Turkey. The result shows that growth rate per capita income reduces labor force participation (LFP) of women in Iran and Turkey while it has an opposite effect in Egypt. An increase in age dependency ratio decreases LFP of Iranian women but inversely affects LFP of women in Turkey. In Iran’s case, the increase in government spending on development projects has led to an increase in the unemployment rate for women.
Subspace Clustering with Distance-density Function and Entropy in High-dimensional Data

Subspace clustering is an extension of traditional clustering that enables finding clusters in subspaces within a data set, which means subspace clustering is more suitable for detecting clusters in high-dimensional data sets. However, most subspace clustering methods usually require many complicated parameter settings, which are almost troublesome to determine, and therefore there are many limitations in applying these subspace clustering methods. In our previous work, we developed a subspace clustering method Automatic Subspace Clustering with Distance-Density function (ASCDD), which computes the density distribution directly in highdimensional data sets by using just one parameter. In order to facilitate choosing the parameter in ASCDD we analyze the relation of neighborhood objects and investigate a new way of determining the range of the parameter in this article. Furthermore, we will introduce here a new method by applying entropy in detecting potential subspaces in ASCDD, which evidently reduces the complexity of detecting relevant subspaces.
A high performance blind adaptive filtering algorithm

Recently a dithered signed-error constant modulus algorithm (DSE-CMA) has been proposed for the purpose of low complexity implementation of constant modulus algorithm (CMA), which is widely used for blind adaptive filtering due to its LMS-like desirable robustness properties. Despite the fact that this algorithm has robustness properties closely resembling those of CMA, it is very slow in convergence. In this work, we present a simple modification of DSE-CMA using a variable step size that results in faster convergence while preserves the low computational complexity and robustness properties of the DSE-CMA algorithm.
‘You think your writing belongs to you?’: Intertextuality in Contemporary Jewish Post-Holocaust Literature

This article examines a sub-category of recent Jewish post-Holocaust fiction that engages with the absent memory of the persecution its authors did not personally witness through the medium of intertextuality, but with intertextual recourse not to testimonial writing but to literature only unwittingly or retrospectively shadowed by the Holocaust. It will be proposed that this practice of intertextuality constitutes a response to the post-Holocaust Jewish author’s ‘anxiety of influence’ that, in the wake of the first generation’s experience of atrocity, their own life story and literature will always appear derivative. With reference to works by four such post-Holocaust authors, Jonathan Safran Foer’s Tree of Codes (2010), Maxim Biller’s Im Kopf von Bruno Schulz (2013), Helen Maryles Shankman’s In the Land of Armadillos (2016), and Nicole Krauss’s The History of Love (2005) and Forest Dark (2017), all of which engage intertextually with Franz Kafka and Bruno Schulz, it will be suggested that these authors are looking to return to a Kristevan practice of intertextuality after the predominantly citational recourse to antecedent material that has often characterized post-Holocaust literature. In the process, they also succeed in troubling recently popular conceptualizations of ‘postmemory’ literature as the ‘belated’ and ‘evacuated’ recipient of encrypted traumatic content inherited from the first generation that it must now seek either to preserve or to work through vicariously.
Protection of microgrids with a high penetration of inverter-coupled energy sources

Microgrids with a high penetration of inverterconnected DER provide a high level of flexibility and control over the exchanged active and reactive power as well as local voltage magnitude. This paper discusses the protection of these microgrids, focussing on islanded operation. First a current limitation method for the inverters is discussed, which is necessary to avoid inverter disconnection during faults. Then a method to determine the type of fault is described. Finally a new protection strategy is presented, operating without the need for communication.
Yeast gene YRR1, which is required for resistance to 4‐nitroquinoline N‐oxide, mediates transcriptional activation of the multidrug resistance transporter gene SNQ2

We have cloned and characterized a Saccharomyces cerevisiae gene YRR1 that is important for resistance to the mutagen 4‐nitroquinoline N‐oxide (4‐NQO). The wild‐type YRR1 gene encodes a protein that contains a Zn(II)2Cys6‐type zinc‐finger motif. Disruption of the YRR1 gene leads to hypersensitivity to 4‐NQO. A dominant mutation (YRR1‐1 ) that confers strong resistance to 4‐NQO has been identified. Epistasis analysis demonstrated that 4‐NQO resistances mediated by the YRR1 and YRR1‐1 alleles require the presence of the SNQ2 gene that encodes a multidrug resistance ATP binding cassette superfamily protein responsible for 4‐NQO export. Northern blot analysis of SNQ2 mRNA levels indicated that Yrr1p is involved in basal and drug‐induced transcriptional activation of SNQ2, whereas Pdr1p/Pdr3p transcription factors are mainly involved in basal SNQ2 expression. In the YRR1‐1 mutant, the level of SNQ2 mRNA is constitutively elevated. These results establish that Yrr1p is important for 4‐NQO resistance by mediating transcriptional activation of the SNQ2 gene in response to the stress imposed by 4‐NQO. The gain‐of‐function mutation of Yrr1‐1p was attributable to the duplication of a 12‐amino‐acid sequence generated near the carboxy terminus.
Accelerating Mutual Information Analysis based Power Analysis Attacks Using GPU

Side Channel Attacks are a popular modern cryptanalysis technique used by adversaries in embedded devices to break the security key. In these types of attacks, the attackers are keen on identifying the weaknesses of the physical implementation of the cryptosystem and utilize such vulnerabilities to extract the key. Power Analysis Attack is a form of Side Channel Attack in which, the adversary exploits power consumed by a cryptographic device during encryption to obtain the key. Mutual Information Analysis (MIA) is a concept introduced in information theory that measures the dependence between two random variables. In MIA based Power Analysis Attack, mutual information between two random variables is taken as the side channel distinguisher. Here, the two variables are physical leakages of the device and the power model based on key estimates. Since this method has more advantages to attackers compared to other methods, it is vital for cryptanalysts to find better countermeasures against this. But, due to the lack of efficient implementations it is hard for cryptanalysts to do that kind of research. In this paper, we present a methodology to accelerate MIA based Power Analysis Attacks using a GPU (Graphical Processor Unit) like NVIDIA Compute Unified Device Architecture (CUDA). Our proposed method promises to better utilize the capabilities of NVIDIA CUDA and obtain a speedup of more than 100 times compared to its sequential version.
PHENOLIC CONTENT DISTRIBUTION AND ANTIOXIDANT ACTIVITIES OF TERMINALIA SERICEA BURCH

Background: Terminalia sericea has been used traditionally for the treatment of diseases associated with oxidative stress. This study was aimed at determining the distribution of phenols in the leaves, stem bark and root bark of Terminalia sericea and their antioxidant activity. Materials and methods: Hot and cold water, methanol/acetone extracts were evaluated for their total phenolic content (TPC), flavone/flavonol content (FFC), flavonone/dihydroflavone content (FDFC), hydroxycinnamic acid derivative content (HCAC) and tannin content (TC). DPPH (2,2-diphenyl-1-picrylhydrazyl) free radicals and reducing power assays were used to assess the antioxidant activity. Results: The leaves had the highest average TPC (440) expressed in milligram Gallic Acid Equivalent (mgCAE) /gram of the extract. The leaves also had the highest average TC (7.14) expressed in milligram Quercetin Equivalent (mgQE) /gram of the extract. The stem had the highest average FDFC (19.23 mgQE/g) while the root had the highest average FFC (74.76 mgQE/g) and HCAC (214.57) expressed in milligram Caffeic Acid Equivalent mgCAE/ gram of the extract. The stem exhibited the highest average DPPH free radical scavenging (9.85 µg/mL) and reducing power (6.01 µg/mL) activities. Water was a better extracting solvent for TPC and FDFC while methanol/acetone was a better extracting solvent for FFC and HCAC. The correlation between TC and reducing power activity (r=0.668) at P < 0.05 suggests that tannins were responsible for the antioxidant activity. Conclusion: This study has shown that the distribution of phenolics differs in the organs of T. sericea, and could affect the quality of medicinal products sold.
A time-series analysis of altered histone H3 acetylation and gene expression during the course of MMAIII-induced malignant transformation of urinary bladder cells

Our previous studies have shown that chronic exposure to low doses of monomethylarsonous acid (MMAIII) causes global histone acetylation dysregulation in urothelial cells (UROtsa cells) during the course of malignant transformation. To reveal the relationship between altered histone acetylation patterns and aberrant gene expression, more specifically, the carcinogenic relevance of these alterations, we performed a time-course analysis of the binding patterns of histone 3 lysine 18 acetylation (H3K18ac) across the genome and generated global gene-expression profiles from this UROtsa cell malignant transformation model. We showed that H3K18ac, one of the most significantly upregulated histone acetylation sites following MMAIII exposure, was enriched at gene promoter-specific regions across the genome and that MMAIII-induced upregulation of H3K18ac led to an altered binding pattern in a large number of genes that was most significant during the critical window for MMAIII-induced UROtsa cells' malignant transformation. Some genes identified as having a differential binding pattern with H3K18ac, acted as upstream regulators of critical gene networks with known functions in tumor development and progression. The altered H3K18ac binding patterns not only led to changes in expression of these directly affected upstream regulators but also resulted in gene-expression changes in their regulated networks. Collectively, our data suggest that MMAIII-induced alteration of histone acetylation patterns in UROtsa cells led to a time- and malignant stage-dependent aberrant gene-expression pattern, and that some gene regulatory networks were altered in accordance with their roles in carcinogenesis, probably contributing to MMAIII-induced urothelial cell malignant transformation and carcinogenesis.
Supervision and interaction

This paper presents the design and the implementation of a new tour-guide robot and reports on the first results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot basic navigational abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that serve to refine our design choices and to enhance the robot efficiency and acceptability