Miracle-dz/UniFAR-FTUs huggingface dataset:
VSoLSCSum: Building a Vietnamese Sentence-Comment Dataset for Social Context Summarization

This paper presents VSoLSCSum, a Vietnamese linked sentence-comment dataset, which was manually created to treat the lack of standard corpora for social context summarization in Vietnamese. The dataset was collected through the keywords of 141 Web documents in 12 special events, which were mentioned on Vietnamese Web pages. Social users were asked to involve in creating standard summaries and the label of each sentence or comment. The inter-agreement calculated by Cohen’s Kappa among raters after validating is 0.685. To illustrate the potential use of our dataset, a learning to rank method was trained by using a set of local and social features. Experimental results indicate that the summary model trained on our dataset outperforms state-of-the-art baselines in both ROUGE-1 and ROUGE-2 in social context summarization.
Factor analysis of a model of stock market returns using simulation-based estimation techniques

A dynamic latent factor model of stock market returns is estimated using simulation-based techniques. Stock market volatility is decomposed into common and idiosyncratic components, and volatility decompositions are compared between stable and turmoil periods to test for possible shift-contagion in equity markets during Asian financial crisis. Five core Asian emerging stock markets are analyzed—Thailand, Indonesia, Korea, Malaysia and the Philippines. Results identify the existence of shift-contagion during the crisis and indicate that the Thai market was a trigger for contagious shock transmission. ; Monte Carlo experiments are conducted to compare simulation method of moments and indirect inference estimation techniques. Consistent with the literature such experiments find that, in the presence of autocorrelation and time-varying volatility, indirect inference is a better method of conducting variance decomposition analysis for stock market returns than the conventional method of moments.
Cooperative signaling by alpha 5 beta 1 and alpha 4 beta 1 integrins regulates metalloproteinase gene expression in fibroblasts adhering to fibronectin

Rabbit synovial fibroblasts (RSF) express basal levels of the metalloproteinases (MMP) collagenase, stromelysin-1 and 92-kD gelatinase when plated on intact fibronectin (FN), but elevated levels when plated on either the central RGD-containing cell-binding region of FN (120FN) or antibody against the alpha 5 beta 1 integrin, suggesting that domains outside 120FN may suppress the induction of MMP (Werb, Z., P. M. Tremble, O. Behrendtsen, E. Crowley, and C.H. Damsky. 1989. J. Cell Biol. 109:877-889). We therefore attempted to reconstitute the basal signaling of intact FN by plating RSF on 120FN together with domains of FN outside this region. Large COOH-terminal fragments containing both the heparin-binding and HICS domains suppressed MMP when combined with 120FN. To map the active sequences, peptides from this region and larger fragments that did, or did not, include the CS-1 portion of IIICS were tested. Only CS-1 peptide, or larger fragments containing CS-1, suppressed MMP expression induced by 120FN. In contrast, peptide V from the heparin-binding region, shown previously to stimulate focal contact formation, further enhanced MMP expression by RSF when present on the substrate with 120FN. RSF expressed alpha 4 beta 1 integrin, the receptor for CS-1, and the anti-alpha 4 mAb blocked the ability of CS-1 to suppress MMP induction by 120FN. These results show that signals modulating MMP expression and focal contact assembly are regulated independently, and that cooperative signaling by alpha 5 beta 1 and alpha 4 beta 1 integrins plays a dominant role in regulating expression of these extracellular matrix-remodeling genes in response to FN. This work demonstrates directly the modular way in which information in the extracellular matrix is detected and processed by cell surface receptors.
Fostering a Culture for Innovativeness in the Forest Products Industry

The complete model included Innovativeness as the strategic orientation of the firm, firm size, industry, and business strategy (See Figure 2). For a complete description of all the variables measured in this study the reader is referred to an earlier research brief. Results The anticipated relationships were supported by our analyses. Business strategy was not found to impact the relationship between Innovativeness and Performance (Figure 2). Secondary manufacturers are better able to convert innovativeness into performance.
Analysis of the Accuracy and Robustness of the Leap Motion Controller

The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2 mm has been obtained for static setups and of 1.2 mm for dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction.
A NON-PARAMETRIC METHOD FOR INCURRED BUT NOT REPORTED CLAIM RESERVE ESTIMATION

The number and cost of claims that will arise from each policy of an insurance company’s portfolio are unknown. In fact, there is a high degree of uncertainty on how much will ultimately be the cost of claims, not only during the period of inception but also after the contract termination, since there might be future, not yet reported, losses associated with past claims. Therefore, in practice, insurance companies have to protect themselves against the possibility of this ultimate cost by creating an additional reserve known as the incurred but not reported (IBNR) reserve. This work introduces new non-parametric models to IBNR estimation based on kernel methods; namely, support vector regression and Gaussian process regression. These are used to learn certain types of nonlinear structures present in claims data using the residuals produced by a benchmark IBNR estimation model, Mack’s chain ladder. The proposed models are then compared to Mack’s model using real data examples. Our results show that the three new proposed models are competitive when compared to Mack’s benchmark model: they may produce the closest predictions of IBNR and also more accurate estimates, given that the variance for the reserve estimation, obtained through the bootstrap technique, is usually smaller than the one given by Mack’s model.
On a hierarchy of Boolean functions hard to compute in constant depth

Any attempt to find connections between mathematical properties and complexity has a strong relevance to the field of Complexity Theory. This is due to the lack of mathematical techniques to prove lower bounds for general models of computation. \par This work represents a step in this direction: we define a combinatorial property that makes Boolean functions ''\emphhard'' to compute in constant depth and show how the harmonic analysis on the hypercube can be applied to derive new lower bounds on the size complexity of previously unclassified Boolean functions.
Arbitrage-free estimation of the risk-neutral density from the implied volatility smile

All methods for estimating the risk-neutral density from the volatility smile boil down to the completion of the implied volatility function by interpolating between available strike prices and extrapolating outside their range. In this paper we focus on the extrapolation and develop a new method, which is, under weak constraints, consistent with the absence of arbitrage. The method does not depend on a particular interpolation scheme and is therefore universally applicable. The implementation involves only straightforward numerical procedures. In an empirical study we apply the method to options on the German stock index DAX. The method turns out to be robust, accurate, and fast. Compared with the methods of Shimko (1993) and Bliss and Panigirtzoglou (2002), it tends to be superior.
Human-like brain hemispheric dominance in birdsong learning

Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca’s area in the frontal lobe and Wernicke’s area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke’s area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.
Information Revelation and Strategic Delay in a Model of Investment

The authors characterize the symmetric equilibria of an investment game with a pure informational externality. When the period length is very short, the game ends very quickly; with positive probability, an informational cascade (herding) causes an investment collapse. As the period length increases, the possibility of herding disappears. As the number of players increases, the rate of investment and the information flow are eventually independent of the number of players; adding more players simply increases the number who delay. In the limit, a period of low investment is followed by either an investment surge or a collapse. Copyright 1994 by The Econometric Society.
Functional Connectivity of Ventral and Dorsal Visual Streams in Posterior Cortical Atrophy.

BACKGROUND Posterior cortical atrophy (PCA) induces progressive dysfunction of ventral and dorsal visual networks. Little is known, however, about corresponding changes in functional connectivity (FC). OBJECTIVES To investigate FC changes in the visual networks, their relationship with cortical atrophy, and the association with Alzheimer's disease (AD) pathology. METHODS Ten PCA patients and 28 age-matched controls participated in the study. Using resting state fMRI, we measured FC in ventral and dorsal cortical visual networks, defined on the basis of a priori knowledge of long-range white matter connections. To assess the relationships with AD, we determined AD biomarkers in cerebrospinal fluid and FC in the default mode network (DMN), which is vulnerable to AD pathology. Voxel-based morphometry analysis assessed the pattern of grey matter (GM) atrophy. RESULTS PCA patients showed GM atrophy in bilateral occipital and inferior parietal regions. PCA patients had lower FC levels in a ventral network than controls, but higher FC in inferior components of the dorsal network. In particular, the increased connectivity correlated with greater GM atrophy in occipital regions. All PCA patients had positive cerebrospinal fluid biomarkers for AD; however, FC in global DMN did not differ from controls. CONCLUSIONS FC in PCA reflects brain structure in a non-univocal way. Hyperconnectivity of dorsal networks may indicate aberrant communication in response to posterior brain atrophy or processes of neural resilience during the initial stage of brain dysfunction. The lack of difference from controls in global DMN FC highlights the atypical nature of PCA with respect to typical AD.
Working Memory Capacity Dissociates Lexical and Sentential Context Effects

Semantically associated and unassociated word pairs were embedded in normal meaningful sentences and in sentences that were semantically anomalous throughout The influence of lexical context was isolated via comparison of responses to the second words of the associated and unassociated pairs The influence of sentence-level context was isolated by comparing responses to the same words in the two sentence types Subjects of high, medium and low working memory capacity (as evaluated by the reading span test) showed modulations of event-related brain potentials in response to lexical context In contrast, only the high- and medium-capacity groups were responsive to purely sentence-level semantic context The results demonstrate that sentential context influences the processing of words in intermediate sentence positions at normal reading speeds but that the on-line utilization of this context is more demanding of working memory than single-word contexts
Land and the politics of belonging in West Africa

Recognizing that land rights are ambiguous, negotiable and politically embedded, these case studies explore the long-term processes and recent changes in contemporary rural West Africa affecting the conversion of control over land into social and political capital and vice versa. They point to the colonial origins of what came to be viewed as 'customary' tenure and to the legal pluralism characterizing pre-colonial tenure arrangements. Furthermore, they show the spiritual and ritual importance of land that can be converted into political power and economic prerogatives, a dimension neglected by much of the recent literature. Analyses cover forest and savannah, state and segmentary societies, facilitating comparison and insights across the Anglo-Francophone divide.
Inhibition of hepatitis B virus expression and replication by RNA interference

RNA interference (RNAi) is the process of sequence‐specific gene silencing, initiated by double‐stranded RNA (dsRNA) that is homologous in sequence to the target gene. Because it has been shown that RNAi can be accomplished in cultured mammalian cells by introducing small interfering RNAs (siRNAs), much effort has been invested in exploiting this phenomenon for experimental and therapeutic means. In this study, we present a series of experiments showing a significant reduction in hepatitis B virus (HBV) transcripts and proteins in cell culture, as well as in the viral replicative forms, induced by siRNA‐producing vectors. The antiviral effect is sequence‐specific and does not depend on active viral replication. In conclusion, our data suggest that RNAi may provide a powerful therapeutic tool, acting both on replication‐competent and on replication‐incompetent HBV. (Hepatology 2003;37:764‐770.)
Cb1 Modulation of Temporally Distinct Synaptic Facilitation among Local Circuit Interneurons 1 Mediated by N-type Calcium Channels in Ca1 2 Running Title: Modulation of Signal Transmission via Cb1 Receptors 3 4

26 One of the critical factors in determining network behaviour of neurons is the influence of local circuit 27 connections among interneurons. The short-term synaptic plasticity and the subtype of presynaptic 28 calcium channels used at local circuit connections of inhibitory interneurons in CA1 were investigated 29 using dual whole-cell recordings combined with biocytin and double immunofluorescence labelling in 30 acute slices of P18-21 day old rat stratum radiatum (SR) and lacunosum moleculare (SLM). Two forms 31 of temporally distinct synaptic facilitation were observed among interneuron connections involving 32 presynaptic cholecystokinin (CCK)-positive cells in SR; frequency-dependent facilitation (FDF) and a 33 delayed onset of release (45-80ms) with subsequent facilitation (DORF). Inhibition at both these 34 synapses was under tonic cannabinoid-type 1 (CB1) receptor activity. DORF synapses did not display 35 conventional release-dependent properties, however, blocking CB1 receptors with antagonist, AM-251 36 (10 μM), altered the synaptic transmission to frequency dependent depression with a fast onset of 37 release (2-4ms). Presynaptic CCK-negative interneurons in SLM elicited IPSPs insensitive to CB1 38 receptor pharmacology displayed frequency dependent depression. Release of GABA at facilitating 39 synapses was solely mediated via N-type presynaptic calcium channels, while depressing synapses 40 utilized P/Q-type channels. These data reveal two distinct models of neurotransmitter release patterns 41 among interneuron circuits that correlate with the subtype of presynaptic calcium channel. These data 42 suggest that endocannabinoids act via CB1 receptors to selectively modulate N-type calcium channels 43 to alter signal transmission.
Reallocation and Allocation of Virtual Machines in Cloud Computing

Cloud computing has given the new face to the distributed field. Two main issues are discussed in this paper, (I) the process of finding the efficient virtual machine by using the concept of load balancing algorithm. (II) Reallocation of the Virtual Machines i.e. migration of the Virtual Machines when cloud provider is not available with the required Virtual Machines. We have discussed about the different load balancing algorithms which are used for deciding the efficient Virtual Machine for the allocation to the client on demand. While in the second issue is concern we have discuss about different modules available for the migration of Virtual Machines from one source machine to the other target machine. At last discussion about the different simulators available for the cloud are carried out in this paper.
A Study on Prognosis of Brain Tumors Using Fuzzy Logic and Genetic Algorithm Based Techniques

In present study attempt has been taken to determine the degree of malignancy of brain tumors using artificial intelligence. The suspicious regions in brain as suggested by the radiologists have been segmented using fuzzy c-means clustering technique. Fourier descriptors are utilized for precise extraction of boundary features of the tumor region. As Fourier Descriptors introduce a large number of feature vectors that may invite the problem of over learning and chance of misclassifications, the proposed diagnosis system efficiently search the significant boundary features by genetic algorithm and feed them to the adaptive neuro-fuzzy based classifier. In addition to shape based features, textural compositions are also incorporated to achieve high level of accuracy in diagnosis of tumors. The study involves 100 brain images and has shown 86% correct classification rate.
Transformations in Africa : essays on Africa's later past

Static image - dynamic reality, Graham Connah African hunter-gatherers - history and the politics of ethnicity, Richard B. Lee, Robert K. Hitchcock the ecology of food production in West Africa, Joanna Casey before the Empire of Ghana - pastoralism and the origins of cultural complexity in the Sahel, K.C. MacDonald African urbanism - scale, mobility and transformation, Roland Fletcher climate and history in West Africa, George E. Brooks iron in Africa - metal from nowhere, James Woodhouse pre-colonial trading systems of the East African interior, Henry Muturo city states of the East African coast and their maritime contacts, George Abungu the Europeans in West Africa - culture contact, continuity and change, Christopher R. DeCorse.
Complements or Substitutes? Private Codes, State Regulation and the Enforcement of Labour Standards in Global Supply Chains

Recent research on regulation and governance suggests that a mixture of public and private interventions is necessary to improve working conditions and environmental standards within global supply chains. Yet less attention has been directed to how these different forms of regulation interact in practice. The form of these interactions is investigated through a contextualized comparison of suppliers producing for Hewlett-Packard, one of the world’s leading global electronics firms. Using a unique dataset describing Hewlett-Packard’s supplier audits over time, coupled with qualitative fieldwork at a matched pair of suppliers in Mexico and the Czech Republic, this study shows how private and public regulation can interact in different ways — sometimes as complements; other times as substitutes — depending upon both the national contexts and the specific issues being addressed. Results from our analysis show that private interventions do not exist within a vacuum, but rather these efforts to enforce labour and environmental standards are affected by state and non-governmental actors.
Mining Frequent Itemsets Using Re-Usable Data Structure

Several algorithms have been introduced for mining frequent itemsets. The recent datasettransformation approach suffers either from the possible increasing in the number of structures that could be produced through the execution of the algorithm or from the problem of the processing time in either projecting or decomposing the datasets. Moreover, the constructed structure cannot be re-used in ad-hoc mining queries or in other mining processes. In this paper, the ItemSet Tree (IST) structure is used in effectively counting the itemsets' support to overcome the above limitations. To speedup the support counting process, a proposal for using a Guidance Information Bits and tree size reduction is presented. The TDF algorithm will be proposed to find all the frequent itemsets. TDF explores the frequent itemsets search space in depth-first to generate candidates from the search space and count their support in the IST. Several experiments have been conducted to study the performance of the TDF algorithm.
Serine Proteinase Inhibitor 3 and Murinoglobulin I Are Potent Inhibitors of Neuropsin in Adult Mouse Brain*

Extracellular serine protease neuropsin (NP) is expressed in the forebrain limbic area of adult brain and is implicated in synaptic plasticity. We screened for endogenous NP inhibitors with recombinant NP (r-NP) from extracts of the hippocampus and the cerebral cortex in adult mouse brain. Two SDS-stable complexes were detected, and after their purification, peptide sequences were determined by amino acid sequencing and mass spectrometry, revealing that target molecules were serine proteinase inhibitor-3 (SPI3) and murinoglobulin I (MUG I). The addition of the recombinant SPI3 to r-NP resulted in an SDS-stable complex, and the complex formation followed bimolecular kinetics with an association rate constant of 3.4 ± 0.22 × 106 m − 1s− 1, showing that SPI3 was a slow, tight binding inhibitor of NP. In situ hybridization histochemistry showed that SPI3 mRNA was expressed in pyramidal neurons in the hippocampal CA1–CA3 subfields, as was NP mRNA. Alternatively, the addition of purified plasma MUG I to r-NP resulted in an SDS-stable complex, and MUG I inhibited degradation of fibronectin by r-NP to 24% at a r-NP/MUG I molar ratio of 1:2. Immunofluorescence histochemistry showed that MUG I localized in the hippocampal neurons. These findings indicate that SPI3 and MUG I serve to inactivate NP and control the level of NP in adult brain, respectively.