Miracle-dz/UniFAR-FTUs huggingface dataset:
Normal Lytic Granule Secretion by Cytotoxic T Lymphocytes Deficient in BLOC‐1, ‐2 and ‐3 and Myosins Va, VIIa and XV

Melanocytes and cells of the immune system share an unusual secretory mechanism which uses the lysosome as a regulated secretory organelle. Recently, a number of the proteins required for these ‘secretory lysosomes’ to undergo exocytosis have been identified. These include Rab27a, Lyst, Rab geranyl geranyl transferase and the adapter protein complex AP‐3. Patients lacking any of these proteins are characterized by the rare combination of albinism and immunodeficiency, revealing roles for these proteins in both melanocyte and immune cell secretion. In order to ask how far the link between albinism and immunodeficiency extends we have examined cytotoxic T‐lymphocyte (CTL) secretion from two BLOC‐3‐deficient patients and seven different mouse models of Hermansky–Pudlak syndrome, all of which display defects in pigmentation and platelet function. We find that CTL function is normal in HPS patients and pale‐ear mice deficient in BLOC‐3, pallid, muted and sandy mice deficient in BLOC‐1, ruby‐eye mice deficient in BLOC‐2 and buff mice deficient in Vps33a. Similarly, the unconventional myosins, Va, VIIa and XV, which can act as effectors for Rab27a in some cell types, are not required in CTL. These results reveal differences in the protein machinery required for biogenesis and/or secretion of lysosome‐related organelles in CTL and melanocytes.
Acute effects of passive stretching vs vibration on the neuromuscular function of the plantar flexors

This study examined the acute effects of passive stretching (PS) vs prolonged vibration (VIB) on voluntary peak torque (PT), percent voluntary activation (%VA), peak twitch torque (PTT), passive range of motion (PROM), musculotendinous stiffness (MTS), and surface electromyographic (EMG) and mechanomyographic (MMG) amplitude of the medial gastrocnemius (MG) and soleus (SOL) muscles during isometric maximal voluntary contractions (MVCs) of the plantar flexors. Fifteen healthy men performed the isometric MVCs and PROM assessments before and after 20 min of PS, VIB, and a control (CON) conditions. There were 10% and 5% decreases in voluntary PT, non‐significant 3% and 2% decreases in %VA, 9–23% decreases in EMG amplitude of the MG and SOL after the PS and VIB, respectively, with no changes after the CON. PROM increased by 19% and MTS decreased by 38% after the PS, but neither changed after the VIB or CON conditions. Both PS and VIB elicited similar neural deficits (i.e., γ loop impairment) that may have been responsible for the strength losses. However, mechanical factors related to PROM and MTS cannot be ruled out as contributors to the stretching‐induced force deficit.
Improved End-to-End Speech Recognition Using Adaptive Per-Dimensional Learning Rate Methods

The introduction of deep neural networks (DNNs) leads to a significant improvement of the automatic speech recognition (ASR) performance. However, the whole ASR system remains sophisticated due to the dependent on the hidden Markov model (HMM). Recently, a new endto-end ASR framework, which utilizes recurrent neural networks (RNNs) to directly model context-independent targets with connectionist temporal classification (CTC) objective function, is proposed and achieves comparable results with the hybrid HMM/DNN system. In this paper, we investigate per-dimensional learning rate methods, ADAGRAD and ADADELTA included, to improve the recognition of the end-to-end system, based on the fact that the blank symbol used in CTC technique dominates the output and these methods give frequent features small learning rates. Experiment results show that more than 4% relative reduction of word error rate (WER) as well as 5% absolute improvement of label accuracy on the training set are achieved when using ADADELTA, and fewer epochs of training are needed. key words: connectionist temporal classification, adaptive perdimensional learning rate method, end-to-end ASR
Observations on Pervasive Information Systems Design

This paper seeks to lay out a number of observations on Pervasive information systems design that have been made during the Chawton House project, an augmented field trip for school children. After laying out the Chawton House case study, the information infrastructure is described and arising issues are examined concerning design for persistence, empowerment of non technical users, and re-use.
Hypoxia Inhibits Osteogenesis in Human Mesenchymal Stem Cells through Direct Regulation of RUNX2 by TWIST

Background Bone loss induced by hypoxia is associated with various pathophysiological conditions, however, little is known about the effects of hypoxia and related signaling pathways on osteoblast differentiation and bone formation. Because bone marrow-derived mesenchymal stem cells (MSCs) survive under hypoxic conditions and readily differentiate into osteoblasts by standard induction protocols, they are a good in vitro model to study the effects of hypoxia on osteoblast differentiation. Methodology/Principle Findings Using human MSCs, we discovered TWIST, a downstream target of HIF-1α, was induced under hypoxia and acted as a transcription repressor of RUNX2 through binding to the E-box located on the promoter of type 1 RUNX2. Suppression of type 1 RUNX2 by TWIST under hypoxia further inhibited the expression of BMP2, type 2 RUNX2 and downstream targets of RUNX2 in MSCs. Conclusions/Significance Our findings point to the important role of hypoxia-mediated signalling in osteogenic differentiation in MSCs through direct regulation of RUNX2 by TWIST, and provide a method for modifying MSC osteogenesis upon application of these cells in fracture healing and bone reconstruction.
An Efficient Algorithm to Find All Small-Size Stopping Sets of Low-Density Parity-Check Matrices

In this work, we introduce an efficient algorithm to find all stopping sets, of size less than some threshold, of a fixed low-density parity-check (LDPC) matrix. The solution is inspired by the algorithm proposed by Rosnes and Ytrehus in 2005 to find an exhaustive list of all small-size turbo stopping sets in a turbo code. The efficiency of the proposed algorithm is demonstrated by several numerical examples. For instance, we have applied the algorithm to the well-known (3, 5)-regular (155, 64) Tanner code and found all stopping sets of size at most 18 in about 1 min on a standard desktop computer. Also, we have verified that the minimum stopping set size of the (4896, 2474) Ramanujan-Margulis code is indeed 24, and that the corresponding multiplicity is exactly 204. Furthermore, we have applied the algorithm to the IEEE 802.16e LDPC codes and determined the minimum stopping set size and the corresponding multiplicity exactly for these codes. Finally, as an application, we present a greedy algorithm to find a small number of redundant parity checks to add to the original parity-check matrix in order to remove all stopping sets in the corresponding Tanner graph of size less than the minimum distance. An extensive case study of the (155, 64) Tanner code illustrates the usefulness of the algorithm, and we present a 110 times 155 redundant parity-check matrix for this code with no stopping sets of size less than the minimum distance. Simulation results of iterative decoding on the binary erasure channel show performance improvements for low-to-medium erasure probabilities when this redundant parity-check matrix is used for decoding.
A 10Gbps/channel On-Chip Signaling Circuit with an Impedance-Unmatched CML Driver in 90nm CMOS Technology

An on-chip signaling system consists of a CML driver, a differential transmission-line and a CML receiver is fabricated. We developed an impedance-unmatched driver for power reduction. The impedance-unmatched driver reduces the tail current of the CML buffer by tuning the load resistance. The designed circuit achieves 3mm, 10Gbps/channel on-chip signal transmission and the impedance-unmatched driver saves the energy per bit by 21% compared with a conventional impedance-matched driver.
A general limit theorem for recursive algorithms and combinatorial structures

Limit laws are proven by the contraction method for random vectors of a recursive nature as they arise as parameters of combinatorial structures such as random trees or recursive algorithms, where we use the Zolotarev metric. In comparison to previous applications of this method, a general transfer theorem is derived which allows us to establish a limit law on the basis of the recursive structure and the asymptotics of the first and second moments of the sequence. In particular, a general asymptotic normality result is obtained by this theorem which typically cannot be handled by the more common 2 metrics. As applications we derive quite automatically many asymptotic limit results ranging from the size of tries or m-ary search trees and path lengths in digital structures to mergesort and parameters of random recursive trees, which were previously shown by different methods one by one. We also obtain a related local density approximation result as well as a global approximation result. For the proofs of these results we establish that a smoothed density distance as well as a smoothed total variation distance can be estimated from above by the Zolotarev metric, which is the main tool in this article.
Low-power control architecture for embedded processors

This paper presents a low-power design strategy to implement the control architecture of embedded processors. Instead of using power demanding memories to store instruction words, we exploit the way instructions are coded, and substitute for the memory array with a specialized reconfigurable combinational circuit, with lower power requirements. The paper also presents the implementation of the technique in an FPGA-based microcontroller.
Knockdown of GRP78 Promotes Apoptosis in Pancreatic Acinar Cells and Attenuates the Severity of Cerulein and LPS Induced Pancreatic Inflammation

Acute pancreatitis (AP) is a potentially lethal disease characterized by inflammation and parenchymal cell death; also, the severity of AP correlates directly with necrosis and inversely with apoptosis. However, mechanisms of regulating cell death in AP remain unclear. The endoplasmic reticulum (ER) chaperone protein GRP78 has anti-apoptotic properties, in addition to modulating ER stress responses. This study used RNA interference (RNAi) approach to investigate the potential role of GRP78 in regulating apoptosis during AP. In vitro models of AP were successfully developed by treating AR42J cells with cerulein or cerulein plus lipoplysaccharide (LPS). There was more pancreatic inflammation and less apoptosis with the cerulein plus LPS treatment. Furthermore, knockdown of GRP78 expression markedly promoted apoptosis and reduced necrosis in pancreatic acinar cells. This was accomplished by enhancing the activation of caspases and inhibiting the activity of X-linked inhibitor of apoptosis protein (XIAP), as well as a receptor interacting protein kinase-1(RIPK1), which is a key mediator of necrosis. This attenuated the severity of pancreatic inflammation, especially after cerulein plus LPS treatment. In conclusion, these findings indicate that GRP78 plays an anti-apoptotic role in regulating the cell death response during AP. Therefore, GRP78 is a potential therapeutic target for AP.
Development of a solid state thyratron replacement for the LCLS klystron modulator

This paper discusses the development of a solid state replacement for the L-4888 thyratron, which is presently used in the eighty-three high-power klystron modulators of SLAC's Linac Coherent Light Source (LCLS). The motivations are to improve modulator performance, increase availability and decrease operational costs. The solid state switch is based on an array of SGTO thyristors. The challenging dI/dt (10 kA/μs), peak power (150 MW), and average power (100 kW) requirements of this application differentiate this work from prior solid state thyratron replacement efforts. Herein, are described the application (including system specifications), the present development status (demonstrated performance and reliability), as well as future development plans.
Topoisomerase I levels in the NCI-60 cancer cell line panel determined by validated ELISA and microarray analysis and correlation with indenoisoquinoline sensitivity

Topoisomerase I (Top1) is a proven target for cancer therapeutics, and the level of Top1 in tumors has been used as a biomarker for chemotherapeutic efficacy. In this study, we report the development and validation of a two-site enzyme chemiluminescent immunoassay for Top1, which we used to measure Top1 levels in the NCI-60 cancer cell line panel. Top1 levels ranged from 0.9 to 9.8 ng/mL/μg protein extract in these cell lines. Levels varied both within and between cancer types but were generally highest in colon cancer and leukemia cell lines and lowest in central nervous system and renal cancer cell lines. Top1 mRNA levels in the NCI-60 cell lines were also measured by microarray; mRNA values generally showed a good correlation with protein levels (Pearson correlation = 0.8). When these expression levels were compared with the activity of the indenoisoquinoline class of Top1 inhibitors across the NCI-60 cell panel, low levels of Top1 were associated with increased resistance to these drugs. The results of our studies indicate that our Top1 assay can be used to quantify Top1 levels in untreated cells as well as cells treated with Top1 inhibitors and that the assay has the potential to be adapted for use in predicting clinical response to Top1-active antineoplastic agents. [Mol Cancer Ther 2009;8(7):1878–84]
Meat and heme iron intake and esophageal adenocarcinoma in the European Prospective Investigation into Cancer and Nutrition study

Although recent studies suggest that high intakes of meat and heme iron are risk factors for several types of cancer, studies in relation to esophageal adenocarcinoma (EAC) are scarce. Previous results in the European Prospective Investigation into Cancer and Nutrition (EPIC) based on a relatively small number of cases suggested a positive association between processed meat and EAC. In this study, we investigate the association between intake of different types of meats and heme iron intake and EAC risk in a larger number of cases from EPIC. The study included 481,419 individuals and 137 incident cases of EAC that occurred during an average of 11 years of follow‐up. Dietary intake of meat (unprocessed/processed red and white meat) was assessed by validated center‐specific questionnaires. Heme iron was calculated as a type‐specific percentage of the total iron content in meat. After adjusting for relevant confounders, we observed a statistically significant positive association of EAC risk with heme iron and processed meat intake, with HR: 1.67, 95% CI: 1.05–2.68 and HR: 2.27, 95% CI:1.33–3.89, respectively, for comparison of the highest vs. lowest tertile of intake. Our results suggest a potential association between higher intakes of processed meat and heme iron and risk of EAC.
Towards Visual Strategy: An Architectural Framework for Roadmapping

Roadmapping concepts and techniques have been widely adopted (and adapted), at product, technology, company, sector and policy levels, since its first application in the late 1970s to support integrated product-technology planning. The roadmapping approach is flexible and scalable, and can be customized to suit many different strategic and innovation contexts. However, this demands careful planning and design, including consideration of roadmap structure, process and participation. This paper explores the issues of how to design and architect roadmaps and roadmapping processes, which is crucial if the approach is to provide a framework for supporting effective dialogue and communication within and between organizations. The structure of the roadmap, and the process for developing and maintaining the roadmap, should be designed to serve the purpose for which the activity is intended to satisfy, providing a 'common language and structure' for both development and deployment of strategy.
A Study on Linking Wikipedia Categories to Wordnet Synsets using Text Similarity

This paper studies the application of text similarity methods to disambiguate ambiguous links between WordNet nouns and Wikipedia categories. The methods range from word overlap between glosses, random projections, WordNetbased similarity, and a full-fledged textual entailment system. Both unsupervised and supervised combinations have been tried. The goldstandard with disambiguated links is publicly available. The results range from 64.7% for the first sense heuristic, 68% for an unsupervised combination, and up to 77.74% for a supervised combination.
Long-Distance Axial Trapping with Focused Annular Laser Beams

Focusing an annular laser beam can improve the axial trapping efficiency due to the reduction of the scattering force, which enables the use of a lower numerical aperture (NA) objective lens with a long working distance to trap particles in deeper aqueous medium. In this paper, we present an axicon-to-axicon scheme for producing parallel annular beams with the advantages of higher efficiency compared with the obstructed beam approach. The validity of the scheme is verified by the observation of a stable trapping of silica microspheres with relatively low NA microscope objective lenses (NA = 0.6 and 0.45), and the axial trapping depth of 5 mm is demonstrated in experiment.
A False Alarm Reduction Method for a Gas Sensor Based Electronic Nose

Electronic noses (E-Noses) are becoming popular for food and fruit quality assessment due to their robustness and repeated usability without fatigue, unlike human experts. An E-Nose equipped with classification algorithms and having open ended classification boundaries such as the k-nearest neighbor (k-NN), support vector machine (SVM), and multilayer perceptron neural network (MLPNN), are found to suffer from false classification errors of irrelevant odor data. To reduce false classification and misclassification errors, and to improve correct rejection performance; algorithms with a hyperspheric boundary, such as a radial basis function neural network (RBFNN) and generalized regression neural network (GRNN) with a Gaussian activation function in the hidden layer should be used. The simulation results presented in this paper show that GRNN has more correct classification efficiency and false alarm reduction capability compared to RBFNN. As the design of a GRNN and RBFNN is complex and expensive due to large numbers of neuron requirements, a simple hyperspheric classification method based on minimum, maximum, and mean (MMM) values of each class of the training dataset was presented. The MMM algorithm was simple and found to be fast and efficient in correctly classifying data of training classes, and correctly rejecting data of extraneous odors, and thereby reduced false alarms.
Class.3.0 : a Probabilistic Classiier Using Decomposable Models

Class.3. 0 is a probabilistic classiier designed for use with decomposable models. It classiies held out test instances based on parameter estimates made from training data. This document is a tutorial introduction to the classiier. Class.3. 0 is written in Perl and is freely available from the author.
Using Zero Anaphora Resolution to Improve Text Categorization

In Chinese, anaphors are frequently omitted, termed zero anaphor (ZA), from text due to their prominence. Thus the information carried by ZAs in text can not be used to contribute the calculation of text categorization. In this paper, we employ a ZA resolution method to recover the omissions of anaphors in text. Then the resulting text is used as the input of a text categorization system. The experiment result shows that ZA resolution method enhances the accuracy of text categorization from 79% to 84%.
A Method for Multi-Linear TV Channels Streaming based on Non-uniform Tiled Structure

In this paper, we propose a cost-effective way to encode and transmit multi-linear TV channels on IPTV service as one video stream. To overcome the disadvantages of the existing Multiple Program Transport Stream (MPTS) method that requires high terminal specifications and the Cloud Video UI method that incurs high costs, several linear channels are made into tiles using High Efficiency Video Coding (HEVC) standard technology, then merged into one stream and transmitted. Through this approach, it is expected that IPTV customers will be able to greatly solve the difficulty of finding the desired channels and programs as several channels, grouped by genre, are displayed on one screen at the same time. In addition, this method efficiently improves the picture quality when multi-channels in a screen are non-equivalent size. Non-uniform tiled structure is introduced by modifying the HEVC PPS Syntax and Slice Header value for each tile. Experimental results show that the proposed tiled structure can improve the PNSR picture quality compared to the existing uniform tiled structure.
A Classifier for Schema Types Generated by Web Data Extraction Systems

Generating Web site schema is a core step for value-added services on the web such as comparative shopping and information integration systems. Several approaches have been developed to detect this schema. For a real web site, due to the complexity of the site schema, post process of this schema such as labeling the schema types, comparing among different schema types and generating an extractor to extract instances of a schema type is a challenge. In this paper, a new tree structured called schema-type semantic model is proposed as a classifier for a schema type. Given some instances of a schema type, HTML tags contents, DOM trees structural information and visual information of these instances are exploited for the classifier construction. Using multivariate normal distribution, the classifier can be used to compare between two different schema types; i.e., the classifier can be used for schema mapping which is a core step of information integration. Also, the suggested classifier can be used to detect and extract instances of a schema type; i.e., it can be used as an extractor for web data extraction systems. Furthermore, the classifier can be used to improve the performance of the schema generated by web data extraction systems; i.e., the classifier can be used to get, as much as possible, a perfect schema. The experiments show an encourage result with the schemas of the test web sites (a data set of 40 web sites). General Terms Information Extraction, Schema-Type Classifier
WASPBENCH: a lexicographer's workbench incorporating state-of-the-art word sense disambiguation

Human Language Technologies (HLT) need dictionaries, to tell them what words mean and how they behave. People making dictionaries (lexicographers) need HLT, to help them identify how words behave so they can make better dictionaries. Thus a potential for synergy exists across the range of lexical data - in the construction of headword lists, for spelling correction, phonetics, morphology and syntax, but nowhere more than for semantics, and in particular the vexed question of how a word's meaning should be analysed into distinct senses. HLT needs all the help it can get from dictionaries, because it is a very hard problem to identify which meaning of a word applies. Lexicographers need all the help they can get because the analysis of meaning is the second hardest part of their job (Kilgarriff, 1998), it occupies a large share of their working hours, and it is one where, currently, they have very little to go on beyond intuition and other dictionaries.