Miracle-dz/UniFAR-FTUs huggingface dataset:
An Ontology-based Visual Interface for Browsing and Summarizing Conversations

In this paper we present a visual interactive interface to create focused summaries of human conversations via mapping to the concepts within an ontology. The ontology includes nodes for the conversation participants, for Dialog Act (DA) properties such as decision, action-item or subjectivity, as well as for entities mentioned in the conversation. The classifiers used to annotate conversation data with DA property and entity tags can be applied to any conversational modality including face to face meetings, emails, blogs and chats. Our interface allows the user to explore these conversations and identify informative sentences by their association with nodes of interest on the tree-structured visual representation of the ontology. The sentences thus selected by the user as potentially important components of the summary can then be used to derive a brief and focused overview of the conversation. The display interface and data parsing components in the initial prototype were all developed based on Java frameworks and toolkits.
Karyotypic analyses of the genus Neotoma (Cricetidae, rodentia).

Examination of 154 specimens representing nine species of the genus Neotoma revealed diploid numbers of 38, 52, 54 and 56. Six species had the diploid number of 52. Extensive polymorphism was found in two species, N. lepida and N. micropus. Chromosomal variation in the subgenus Neotoma was primarily in Fundamental Number and not in diploid number.
Identifying composites of famous faces: Investigating memory, language and system issues

Abstract Previous research on composite systems has cast doubt on their potential to produce a good likeness. Poor memory of the target's face and problems in translating a verbal description into a visual mental image were examined as possible reasons for this. A computerized composite system was used to construct facial images of famous individuals. Results indicated that a reasonable number of composites were identified overall. Composites produced directly by the “operators” tended to be more accurate than those produced via “describers”. In addition, composites produced via describers, but not those directly by operators, were less accurate when created from memory than when a photograph was provided. This suggests that verbal descriptions, as well as facial memory, may limit composite accuracy.
Multiple change-point audio segmentation and classification using an MDL-based Gaussian model

This study presents an approach for segmenting and classifying an audio stream based on audio type. First, a silence deletion procedure is employed to remove silence segments in the audio stream. A minimum description length (MDL)-based Gaussian model is then proposed to statistically characterize the audio features. Audio segmentation segments the audio stream into a sequence of homogeneous subsegments using the MDL-based Gaussian model. A hierarchical threshold-based classifier is then used to classify each subsegment into different audio types. Finally, a heuristic method is adopted to smooth the subsegment sequence and provide the final segmentation and classification results. Experimental results indicate that for TDT-3 news broadcast, a missed detection rate (MDR) of 0.1 and a false alarm rate (FAR) of 0.14 were achieved for audio segmentation. Given the same MDR and FAR values, segment-based audio classification achieved a better classification accuracy of 88% compared to a clip-based approach.
An Optimization Approach for QEMU

Binary translation system usually maps guest registers into host registers to accelerate the translation speed. QEMU can be treated as a typical binary translator and it uses a fixed register allocation. On most hosts, QEMU simply maps all the target registers to memory and only store a few temporary variables in host registers. However, QEMU does not consider the dependence of two or more adjacent instructions. So even a guest register's value has been loaded into the temporary variables when executing the previous instruction, the next instruction could not use the value from the temporary variable directly, which is mapped into host register. The next instruction has to reload the value from memory again. This paper presents an approach to eliminate these unnecessary operations. Tests of benchmarks from nbench show that this approach can achieve 10%~20% speed improvement.
Preparation and Characterization of Novel Bacterial Cellulose/Gelatin Scaffold for Tissue Regeneration Using Bacterial Cellulose Hydrogel

Bacterial cellulose (BC) and gelatin are well-known biomaterials. The novel bacterial cellulose/gelatin composite scaffolds were prepared using aqueous gelatin solution and bacterial cellulose excreted by Acetobacter xylinum. The prepared bacterial cellulose/gelatin scaffolds were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, mechanical test, swelling, and thermal studies. The morphology of these bacterial cellulose/gelatin scaffolds indicated that the gelatin molecules could penetrate well between the individual nanofibers of the bacterial cellulose. With the incorporation of gelatin in the bacterial cellulose, the crystallinity index tended to decrease while the thermal stability was improved. After the incorporation of gelatin in the bacterial cellulose, Young’s modulus of the composite was increased from 3.7 GPa to 3.9 GPa, while the tensile strength and strain at break point were decreased from 170 MPa (7.5%) to 114 MPa (4%), respectively. The swelling behavior test indicated that the water uptake capacity of the composite was only half of the pure bacterial cellulose. Cell adhesion studies were carried out using 3T3 fibroblast cells. The cells incubated with BC/gelatin scaffolds for 48 h were capable of forming cell adhesion and proliferation. It showed much better biocompatibility than pure bacterial cellulose. So, the prepared BC/gelatin scaffolds are bioactive and may be suitable for cell adhesion/attachment, suggesting that these scaffolds can be used for wound dressing or tissue engineering scaffolds. Therefore, these novel BC/gelatin scaffolds are useful for biomedical applications.
TGF-β-Activated Kinase 1 (TAK1) Signaling Regulates TGF-β-Induced WNT-5A Expression in Airway Smooth Muscle Cells via Sp1 and β-Catenin

WNT-5A, a key player in embryonic development and post-natal homeostasis, has been associated with a myriad of pathological conditions including malignant, fibroproliferative and inflammatory disorders. Previously, we have identified WNT-5A as a transcriptional target of TGF-β in airway smooth muscle cells and demonstrated its function as a mediator of airway remodeling. Here, we investigated the molecular mechanisms underlying TGF-β-induced WNT-5A expression. We show that TGF-β-activated kinase 1 (TAK1) is a critical mediator of WNT-5A expression as its pharmacological inhibition or siRNA-mediated silencing reduced TGF-β induction of WNT-5A. Furthermore, we show that TAK1 engages p38 and c-Jun N-terminal kinase (JNK) signaling which redundantly participates in WNT-5A induction as only simultaneous, but not individual, inhibition of p38 and JNK suppressed TGF-β-induced WNT-5A expression. Remarkably, we demonstrate a central role of β-catenin in TGF-β-induced WNT-5A expression. Regulated by TAK1, β-catenin is required for WNT-5A induction as its silencing repressed WNT-5A expression whereas a constitutively active mutant augmented basal WNT-5A abundance. Furthermore, we identify Sp1 as the transcription factor for WNT-5A and demonstrate its interaction with β-catenin. We discover that Sp1 is recruited to the WNT-5A promoter in a TGF-β-induced and TAK1-regulated manner. Collectively, our findings describe a TAK1-dependent, β-catenin- and Sp1-mediated signaling cascade activated downstream of TGF-β which regulates WNT-5A induction.
Augmenting Conversational Characters with Generated Question-Answer Pairs

We take a conversational character trained on a set of linked question-answer pairs authored by hand, and augment its training data by adding sets of question-answer pairs which are generated automatically from texts on different topics. The augmented characters can answer questions about the new topics, at the cost of some performance loss on ques- tions about the topics that the original character was trained to answer. for conversational characters which is available for down- load as part of the ICT Virtual Human Toolkit. 1 NPCEd- itor is trained on a knowledge base in the form of linked question-answer pairs, and is able to answer novel ques- tions by selecting the most appropriate response from the available answers in the knowledge base. For each new in- put question, NPCEditor computes a language model for the ideal answer using the linked training data; it then compares the language model of the ideal answer to those of all of the answers in the knowledge base, and selects the closest avail- able answer based on a similarity metric between language models. The use of language models allows NPCEditor to overcome some variation in the phrasing of questions, and retrieve appropriate responses for questions it has not seen in the training data.
Representation of Texts into String Vectors for Text Categorization

In this study, we propose a method for encoding documents into string vectors, instead of numerical vectors. A traditional approach to text categorization usually requires encoding documents into numerical vectors. The usual method of encoding documents therefore causes two main problems: huge dimensionality and sparse distribution. In this study, we modify or create machine learning-based approaches to text categorization, where string vectors are received as input vectors, instead of numerical vectors. As a result, we can improve text categorization performance by avoiding these two problems.
Environmental Regulations and Manufacturing Plant Exit : A Preliminary Analysis

(EPA), it has not been subject to the Agency's review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. We thank the EPA National Center for Environmental Economics working group for helpful comments, Jim Davis at the Boston RDC for his continued help; Wang Jin and Shital Sharma for excellent research assistance; and Diane Ferguson for editorial assistance. The opinions and conclusions expressed are those of the authors and not the U.S. Census Bureau. All papers using Census data are screened to ensure that they do not disclose confidential information.
LSB, 3D-DCT and Huffman Encoding based Steganography in Safe Message Routing and Delivery for Structured Peer-to-Peer Systems

In structured P2P systems, message deliverance can be done by identifying the peer IDs of the individual systems. The initiator has to decide the destination and can route the message through one or more hops. The message passes from one hop to another correctly by identifying the IP address and finally reaches the destination. In this paper we propose an efficient routing strategy to control the routing path and to identify the malicious nodes. We also eliminate the drawbacks of encryption by introducing steganography in message deliverance. This paper proposes a new steganographic encoding scheme which separates the colour channels of the windows bitmap images and then hides messages randomly in the LSB of one colour component of a chosen pixel where the colour components of the other two are found to be equal to the key selected. In addition to this we apply 3D-DCT based Steganography which embeds the text message in LSB of the Discrete Cosine (DC) coefficient of digital picture. Then Huffman encoding is also performed on the secret messages/images before embedding and each bit of Huffman code of secret message/image is embedded in the frequency domain by altering the LSB of each of the DCT coefficients of cover image blocks. The experimental results shows that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table. An implementation of these methods and their performance analysis has been done in this paper.
Synergic reprogramming of mammalian cells by combined exposure to mitotic Xenopus egg extracts and transcription factors

Transfer of somatic cell nuclei to enucleated eggs and ectopic expression of specific transcription factors are two different reprogramming strategies used to generate pluripotent cells from differentiated cells. However, these methods are poorly efficient, and other unknown factors might be required to increase their success rate. Here we show that Xenopus egg extracts at the metaphase stage (M phase) have a strong reprogramming activity on mouse embryonic fibroblasts (MEFs). First, they reset replication properties of MEF nuclei toward a replication profile characteristic of early development, and they erase several epigenetic marks, such as trimethylation of H3K9, H3K4, and H4K20. Second, when MEFs are reversibly permeabilized in the presence of M-phase Xenopus egg extracts, they show a transient increase in cell proliferation, form colonies, and start to express specific pluripotency markers. Finally, transient exposure of MEF nuclei to M-phase Xenopus egg extracts increases the success of nuclear transfer to enucleated mouse oocytes and strongly synergizes with the production of pluripotent stem cells by ectopic expression of transcription factors. The mitotic stage of the egg extract is crucial, because none of these effects is detected when using interphasic Xenopus egg extracts. Our data demonstrate that mitosis is essential to make mammalian somatic nuclei prone to reprogramming and that, surprisingly, the heterologous Xenopus system has features that are conserved enough to remodel mammalian nuclei.
On the asymptotic stability of the hybrid position/force control scheme for robot manipulators

Conditions are presented for the global asymptotic stability of the hybrid position/force control of robot manipulators, using Lyapunov's direct method. Although hybrid control schemes have been studied in depth, the stability problem has not been clarified completely. The authors deal with the stability of the hybrid control scheme in Cartesian coordinates of the work space, especially from the viewpoint of coupling between position and force control. Results show not only the global asymptotic stability conditions but also the physical interpretation or meaning of the stability conditions by citing an example of a two-degree-of-freedom manipulator. <<ETX>>
Compress-and-forward receiver cooperation for virtual MIMO with finite-alphabet modulation

In the downlink transmission system with a multi-antenna base station (BS) and a cluster of single-antenna mobile stations (MSs), the throughput can be greatly enhanced by exploiting the cooperating channel among MSs and forming virtual multiple input and multiple output (MIMO). With MSs close together, compress-and-forward is the most commonly used cooperation strategy. Considering the fact that in practical systems the transmit signal is usually finite-alphabet modulated symbols, e.g., quadrature amplitude modulation (QAM), the compress-and-forward cooperation is investigated correspondingly. Regarding the bit error rate (BER) performance of virtual MIMO systems, two regions are identified: the channel-noise-dominant region and the compression-noise-dominant region. In the channel-noise-dominant region, the cooperation system yields almost no loss compared to the BER lower bound. While in the compression-noise-dominant region, the system BER is limited, i.e., with an error floor. Through theoretical analysis, the minimum compression rate to guarantee that the system works in the channel-noise-dominant region is obtained. The minimum compression rate is determined mainly by three terms: the modulation alphabet size, the constellation position and the signal-to-noise ratio (SNR), whose explicit expression has also been derived.
THE NONLINEAR EFFECTS OF TEACHING AND CONSULTING ON ACADEMIC RESEARCH PRODUCTIVITY 1 April 7 , 1993

This study tests the proposition that moderate amounts of faculty time spent in the “non-research” roles of teaching and consulting are, in fact, facilitative of research productivity; and establishes values for the point at which such activities cease to have a facilitating effect. This was done by fitting continuous piecewise-linear regression models to 1980 data pertaining to a national sample of 5605 faculty. The study illustrates the effectiveness of piecewise-linear methods relative to polynomial techniques for problems of this kind and suggests that the former approach should be much more prevalent. The results indicate that up to four hours per week of consulting and up to eight hours per week of teaching are indeed facilitative of research productivity. Policy implications are discussed. The authors wish to thank Helen S. Astin of the UCLA Graduate School of Education and Higher Education Research Institute for making available the data used in this study. Support for the HERI survey was provided by the Ford Foundation. The research of this author was partially supported by ONR Grant number N00014–90–J–1714. THE NONLINEAR EFFECTS OF TEACHING AND CONSULTING ON ACADEMIC RESEARCH PRODUCTIVITY
Combining multiple kernels for efficient image classification

We investigate the problem of combining multiple feature channels for the purpose of efficient image classification. Discriminative kernel based methods, such as SVMs, have been shown to be quite effective for image classification. To use these methods with several feature channels, one needs to combine base kernels computed from them. Multiple kernel learning is an effective method for combining the base kernels. However, the cost of computing the kernel similarities of a test image with each of the support vectors for all feature channels is extremely high. We propose an alternate method, where training data instances are selected, using AdaBoost, for each of the base kernels. A composite decision function, which can be evaluated by computing kernel similarities with respect to only these chosen instances, is learnt. This method significantly reduces the number of kernel computations required during testing. Experimental results on the benchmark UCI datasets, as well as on a challenging painting dataset, are included to demonstrate the effectiveness of our method.
Focal Cerebral Ischemia Induces Active Proteases That Degrade Microvascular Matrix

Background and Purpose— Focal cerebral ischemia causes microvessel matrix degradation and generates proteases known to degrade this matrix. However, proof that the proteases generated do indeed degrade vascular matrix is lacking. Here we demonstrate that active proteases derived from ischemic tissue after middle cerebral artery occlusion (MCAO) and transferred to normal tissue can degrade vascular matrix. Methods— In an ex vivo bioassay, the effects of supernatants from ischemic and normal basal ganglia of nonhuman primates, proteases, and control buffer on the immunoreactivity of vascular matrix constituents in normal brain tissue sections were quantified. Protease families were identified with specific inhibitors. Results— Plasmin, active matrix metalloproteinase (MMP)-2, and active MMP-9 significantly reduced microvessel-associated collagen, laminin, and heparan sulfate proteoglycans (HSPG). The vascular HSPG perlecan was more sensitive than collagen or laminin in the bioassay and in the ischemic core 2 hours after MCAO. Two-hour and 7-day ischemic tissue samples significantly degraded matrix perlecan and collagen. Inhibitor studies confirmed that while active MMPs were generated, active cysteine proteases significantly degraded microvessel perlecan. The cysteine proteases cathepsins B and L were generated in the microvasculature and adjacent neurons or glial cells 2 hours after MCAO and decreased perlecan in the bioassay. Conclusions— This is the first direct evidence that active proteases are generated in ischemic cerebral tissues that are acutely responsible for vascular matrix degradation. Degradation of vascular perlecan, the most sensitive matrix component thus far identified, may be due to cathepsins B and L, generated very rapidly after MCAO.
Locality preserving clustering for image database

It is important and challenging to make the growing image repositories easy to search and browse. Image clustering is a technique that helps in several ways, including image data preprocessing, user interface designing, and search result representation. Spectral clustering method has been one of the most promising clustering methods in the last few years, because it can cluster data with complex structure, and the (near) global optimum is guaranteed. However, existing spectral clustering algorithms, like Normalized Cut, are difficult to handle data points out of training set. In this paper, we propose a clustering algorithm named Locality Preserving Clustering (LPC), which shares many of the data representation properties of nonlinear spectral method. Yet LPC provides an explicit mapping function which is defined everywhere, both on training data points and testing points. Experimental results show that LPC is more accurate than both "direct Kmeans" and "PCA + Kmeans". We also show that LPC produces in general comparable results with Normalized Cut, yet is more efficient than Normalized Cut.
MDLF-Mavg: A new speech feature with a voice print

A new feature extraction method is presented in this paper. It is modification to our previous work where we have extracted Multidimentional local features (MDLF). We name the new feature as Multi-Directional Local Feature with moving average(MDLF-Mavg). MDLF-Mavg is based on three-point linear regression and three point moving average. Linear regression is applied on horizontal (time axis) that captures phoneme onset and offset and vertical (frequency axis) which capture formant contours whereas modified moving average is applied on (45 degree) time-frequency axis and (135 degree) time-frequency axis which capture the voiceprint of speaker. The MDLF-Mavg performance is compared to other speech features in a speaker recognition system. MDLF-Mavg has shown better performance than the other features. In the case of the female only part of the database it achieved 100% recognition rate. We will show that MDLF-Mavg produce what can be looked at as a voice print for each speaker when vocalizing a certain text.