Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishment of Perineural Invasion Models and Analysis of Gene Expression Revealed an Invariant Chain (CD74) as a Possible Molecule Involved in Perineural Invasion in Pancreatic Cancer

Purpose: Perineural invasion causes frequent local recurrence even after resection and a poor prognosis for pancreatic cancer. We established perineural invasion models and analyzed the molecular mechanism of perineural invasion in pancreatic cancer. Experimental Design: Seven pancreatic cancer cell lines with or without human peripheral nerves were s.c. implanted in nonobese diabetes/severe combined immunodeficient mice. We compared expression profiles among high and low perineural invasion cell lines by using an oligonucleotide microarray. We examined up-regulation of the invariant chain (CD74) in high perineural invasion cell lines in mRNA and protein levels and surgical cases immunohistochemically. Results: Four of seven pancreatic cancer cell lines (CaPan1, CaPan2, CFPAC, and MPanc96) showed perineural invasion to s.c. transplanted human peripheral nerves. Moreover, CaPan1 and CaPan2 (high perineural invasion group) also resulted in a high frequency of perineural invasion to mouse s.c. peripheral nerves, whereas three pancreatic cancer cell lines HPAFII, AsPC1, and Panc1 (low perineural invasion group) did not show perineural invasion to either human or mouse nerves. We identified 37 up-regulated genes and 12 down-regulated genes in the high perineural invasion group compared with the low perineural invasion group. Among them, CD74 was up-regulated in the high perineural invasion group in mRNA and protein levels. Furthermore, immunohistochemical expression of CD74 in clinical cases revealed its significant overexpression in pancreatic cancer with perineural invasion (P < 0.008). Conclusions: This is the first report of perineural invasion models using human pancreatic cancer cell lines. In combination with gene expression profiling, it was indicated that CD74 could be a candidate molecule involved in perineural invasion. These models provide new approaches for study of perineural invasion in pancreatic cancer.
Inconsistent Ontology Handling by Translating Description Logics into Defeasible Logic Programming

The Semantic Web is a future vision of the web where stored information has exact meaning, thus enabling computers to understand and reason on the basis of such information. Assigning semantics to web resources is addressed by means of ontology definitions which are meant to be written in an ontology description language such as OWL-DL that is based on so-called Description Logics (DL). Although ontology definitions expressed in DL can be processed with existing DL reasoners, such DL reasoners are incapable of dealing with inconsistent ontology definitions. Previous research has determined that a subset of DL can be eectively translated into an equivalent subset of logic programming. We propose a method for dealing with inconsistent ontology definitions in the Semantic Web. Our proposal involves mapping DL ontologies into DeLP programs. That is, given an OWL-DL ontologyOOwl, an equivalent DL ontologyODL can be obtained. ProvidedODL satisfies certain restrictions, it can be translated into a DeLP program ODeLP. Therefore, given a query Q w.r. t. OOwl, a dialectical process will be performed to determine if Q is warranted w.r. t.ODeLP.
Bridge Floating-Point Fused Multiply-Add Design

A new floating-point fused multiply-add (FMA) design for the execution of (A times B) + C as a single instruction is presented. The bridge fused multiply-add unit is a design intended to add FMA functionality to existing floating-point coprocessor units by including specialized hardware that reuses floating-point adder and floating-point multiplier components. The bridge unit adds this functionality without requiring an overhaul of coprocessor control units and without degrading the performance or parallel execution of addition and multiplication single instructions. To evaluate the performance, area, and power costs of adding a bridge FMA unit to common floating-point execution blocks, several circuits including a double-precision floating-point adder, floating-point multiplier, classic FMA, and a bridge FMA unit have been designed and implemented with AMD 65-nm silicon-on-insulator technology to provide a realistic and fair analysis of the presented FMA hardware tradeoffs.
Macho: A failure model-oriented adaptive cache architecture to enable near-threshold voltage scaling

Recent interest in CMOS voltage scaling has produced a class of cache architectures which tolerate parametric SRAM failures at low voltage by substituting faulty words of one cache line with healthy words of another line. These caches rely on the fault maps (which grow reciprocally with smaller word sizes) for fault identification. Therefore, the benefits of cache voltage scaling must be rigorously investigated against the cost of their fault map overheads, especially in large caches. This paper reviews the word substitution caches and develops their parametric failure model. Our developed model leads to a non-intrusive and reconfigurable cache (Macho) which can be locally optimized (based on local fault density) by two graph-based algorithms. Specifically, our adaptive matching algorithm increases effective cache capacity by dynamically concentrating healthy cache blocks into active cache sets. Macho enables voltage scaling down to 400mV by tolerating high SRAM-failure rates (≥ 1%) and achieves better energy reduction (44%) than other substitution caches with similar area overheads.
Acquisition and Maintenance of Visual-Visual and Visual-Olfactory Equivalence Classes

Cross-modal equivalence formation has been of interest to behavior analysts recently because of its potential benefits over typical visual based learning. The present experiment was conducted to examine this possibility with the acquisition and maintenance of visual-olfactory classes of stimuli as compared to visual-visual classes of stimuli. Four college students completed the training and testing of visual-visual and visual-olfactory sets of stimuli including three maintenance probes followed by training and testing for merging of the classes. Results demonstrated a slight advantage in acquisition and maintenance for the visual-olfactory set of stimuli. Implications for these findings in applied settings and directions for future research are suggested.
Evaluation of mobile emissions contributions to Mexico City's emissions inventory using on-road and cross-road emission measurements and ambient data

Mobile emissions represent a significant fraction of the total anthropogenic emissions burden in the Mexico City Metropolitan Area (MCMA) and, therefore, it is cru- cial to use top-down techniques informed by on-road exhaust measurements to evaluate and improve traditional bottom-up official emissions inventory (EI) for the city. We present the measurements of on-road fleet-average emission factors ob- tained using the Aerodyne mobile laboratory in the MCMA in March 2006 as part of the MILAGRO/MCMA-2006 field campaign. A comparison of our on-road emission measure- ments with those obtained in 2003 using essentially the same measurement techniques and analysis methods indicates that, in the three year span, NO emission factors remain within the measured variability ranges whereas emission factors of aldehydes and aromatics species were reduced for all sam- pled driving conditions. We use a top-down fuel-based approach to evaluate the mobile emissions from the gasoline fleet estimated in the bottom-up official 2006 MCMA mobile sources. Within the range of measurement uncertainties, we found probable slight overpredictions of mean EI estimates on the order of 20-28% for CO and 14-20% for NO. However, we identify a probable EI discrepancy of VOC mobile emissions between 1.4 and 1.9; although estimated benzene and toluene mobile emissions in the inventory seem to be well within the uncer- tainties of the corresponding emissions estimates. Aldehydes mobile emissions in the inventory, however, seem to be un-
Bias in Variance Components Due to Nonresponse in Twin Studies

Abstract Incomplete data on trait values may bias estimates of genetic and environmental variance components obtained from twin analyses. If the nonresponse mechanism is ‘ignorable’ then methods such as full information maximum likelihood estimation will produce consistent variance component estimates. If, however, nonresponse is ‘nonignorable’, then the situation is more complicated. We demonstrate that a within-pair correlation of nonresponse, possibly different for monozygotic (MZ) and dizygotic (DZ) twins, may well be compatible with ‘ignorability’. By means of Monte Carlo simulation, we assess the potential bias in variance component estimates for different types of nonresponse mechanisms. The simulation results guide the interpretation of analyses of data on perceptual speed from the Swedish Adoption/Twin Study of Aging. The results suggest that the dramatic decrease in genetic influences on perceptual speed observed after 13 years of follow-up is not attributable solely to dropout from the study, and thus support the hypothesis that genetic influences on some cognitive abilities decrease with age in late life.
Cotranslational secretion of diphtheria toxin and alkaline phosphatase in vitro: involvement of membrane protein(s)

Crude messenger ribonucleic acid fractions isolated from Corynebacterium diphtheriae and Escherichia coli were translated in an E. coli in vitro protein-synthesizing system and yielded precursors of the secreted proteins diphtheria toxin and alkaline phosphatase, respectively. Addition of inverted E. coli inner membrane vesicles to the system during the initial stages of translation resulted in the intravesicular segregation of mature diphtheria toxin and alkaline phosphatase. Outer membrane vesicles or inner membrane vesicles whose cytoplasmic surfaces had been treated with pronase could not mediate transmembrane transfer of diphtheria toxin or alkaline phosphatase. However, inner membrane vesicles isolated from E. coli spheroplasts which had been treated with pronase and inner membrane vesicles complexed with ribosomes during pronase treatment were functional in transmembrane transfer. At temperatures below the phase transition of E. coli membranes, no intravesicular segregation of alkaline phosphatase or diphtheria toxin was observed. The precursor forms of each protein accumulated free from the vesicles. These results suggest that an inner membrane protein, exposed on the cytoplasmic surface, plays an integral role in secretion.
Foreign Language Proficiency of At-Risk and Not-At-Risk Learners Over 2 Years of Foreign Language Instruction

In this follow-up study, students at risk for problems with learning a foreign language who were taught using a multisensory, structured language approach to Spanish made significant gains over 2 years on three native language phonological/orthographic measures and a foreign language aptitude test. Despite gains, at-risk students did not “catch up” with not-at-risk students on these measures. Qualitative between-group differences were noted on foreign language proficiency measures.
Identification of secretory proteins based on similarity of amino acid sequences

Functioning as an “address tag” that directs nascent proteins to their proper sub-cellular localizations, signal peptides have become a crucial tool in finding new drugs or reprogramming cells for gene therapy. In the past twenty years, many algorithms have been proposed for predicting signal peptides. In spite of pioneering algorithms based on “scaled window” or “benchmark window”, similarity as another method for identification signal peptides is studied in details. By defining the similarity between every two sequences, we take the entire sequence effect into consideration, which is the important problem in modeling the whole amino acid sequence, and avoid the effect of variable-length problem. The normalized similarity represented the similarity among the overall sample is coincide with meaning of neighbours. So K-NN is adopted for classification. Then secretory proteins are identified based on similarity, similarity feature and SSLDA based reduced similarity features. And the prediction result for benchmark dataset is promising. The proposed similarity can also be used for other protein sequence analysis.
Graph Prediction with Random Trees

In online transductive graph prediction a learner is initially given an undirected graph G = (V,E) with unknown binary labelsy = (y1, . . . , yn) ∈ {−1,+1}n assigned to the vertices V = {1, . , n}. At time t = 1 an arbitrary vertexi1 ∈ V is selected and the learner must predict its label yi1 ∈ {−1,+1}. Then yi1 is revealed and a new vertex i2 6= i1 of V is selected. This process goes on for t = 1, 2, . , n until all vertices ofG have been selected. The learner’s goal is to minimize the number of prediction mistakes.
Non-destructive measurement of residual stresses in welded aluminium 2024 airframe alloy

Welding is being considered as a potential alternative metal joining technique to mechanical fastening, not only to save cost on existing aircraft versions but also to face the challenges in the aerospace industry of the next generation mass air transportation. However, before change of a fabrication process, the residual stress generation due to welding needs accounting for in structural integrity calculations of safety critical components subjected to fatigue loading spectra. The present work is focused on determination of the full 3D residual stress distribution, and its subsequent evolution due to machining, in fusion welded airframe aluminium alloy 2024-T351. Within the overall program two fusion welding processes - Metal Inert Gas (MIG) and Variable Polarity Plasma Arc (VPPA) were studied. A combination of diffraction techniques - neutron, synchrotron X-ray, and laboratory X-ray - were used in the course of the project. The recent advances in neutron and synchrotron X-ray diffraction techniques were utilised to obtain a very detailed three dimensional picture of residual stress distribution with high spatial accuracy. The measurement requirements and the size specificity of different samples determine the appropriate diffraction technique. Material characterisation of grain size distribution and crystallographic texture was performed and used as a vital input to the diffraction experiments. In this dissertation an integrated approach was adopted whereby stress magnitude and distribution in an as-welded sample was determined and then stress evolution and redistribution was compared before and after machining. Two welding processes were studied and compared. The residual stress in fatigue samples used to monitor short crack generation and growth (up to 1 mm) were measured for surface stress distribution and its evolution following testing. Fatigue samples for long crack (over 1 mm) growth were also studied. The effects of welding structural assemblies will not be manifested in coupon samples, and therefore, a structural wing skin and stringer assembly was also measured for residual stress generation. The weld residual stress generation is found to be higher in a MIG weld than in a VPPA weld. A distinct profile and magnitude of stress distribution is observed in both the welds studied. A systematic stress evolution is observed in the fatigue geometry samples for short and long crack growth monitoring. The magnitude of stress reduction due to machining and cutting of fatigue specimens, however, is different for the different weld processes. The wing skin stringer assembly measured also shows a different magnitude and stress distribution pattern. However, the basic footprint of stress distribution was observed to be same in the different weld processes and the samples studied.
A combined Fuzzy and Naïve Bayesian strategy can be used to assign event codes to injury narratives

Background Bayesian methods show promise for classifying injury narratives from large administrative datasets into cause groups. This study examined a combined approach where two Bayesian models (Fuzzy and Naïve) were used to either classify a narrative or select it for manual review. Methods Injury narratives were extracted from claims filed with a worker's compensation insurance provider between January 2002 and December 2004. Narratives were separated into a training set (n=11,000) and prediction set (n=3,000). Expert coders assigned two-digit Bureau of Labor Statistics Occupational Injury and Illness Classification event codes to each narrative. Fuzzy and Naïve Bayesian models were developed using manually classified cases in the training set. Two semi-automatic machine coding strategies were evaluated. The first strategy assigned cases for manual review if the Fuzzy and Naïve models disagreed on the classification. The second strategy selected additional cases for manual review from the Agree dataset using prediction strength to reach a level of 50% computer coding and 50% manual coding. Results When agreement alone was used as the filtering strategy, the majority were coded by the computer (n=1,928, 64%) leaving 36% for manual review. The overall combined (human plus computer) sensitivity was 0.90 and positive predictive value (PPV) was >0.90 for 11 of 18 2-digit event categories. Implementing the 2nd strategy improved results with an overall sensitivity of 0.95 and PPV >0.90 for 17 of 18 categories. Conclusions A combined Naïve-Fuzzy Bayesian approach can classify some narratives with high accuracy and identify others most beneficial for manual review, reducing the burden on human coders.
Ground target tracking with variable structure IMM estimator

In this paper we present the design of a Variable Structure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obtained from an airborne sensor. The targets are moving along a highway, with varying obscuration due to changing terrain conditions. In addition, the roads can branch, merge or cross-the scenario represents target convoys along a realistic road network with junctions, changing terrains, etc. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography, The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variable structure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, significantly improving performance and reducing computational load. Data association is handled using an assignment algorithm. The estimator is designed to handle a very large number of ground targets simultaneously. A simulated scenario consisting of over one hundred targets is used to illustrate the selection of design parameters and the operation of the tracker. Performance measures are presented to contrast the benefits of the VS-IMM estimator over the Kalman filter and the standard IMM estimator, The VS-IMM estimator is then combined with multidimensional assignment to gain "time-depth. " The additional benefit of using higher dimensional assignment algorithms for data association is also evaluated.
Long-run Negotiations withDynamic Accumulation

TMany negotiations are characterised by dynamic accumulation: current agreements affect future bargaining possibilities. We study such situations by using repeated bargaining games in which two parties can decide how much to invest and how to share the residual surplus for their own consumption. We show that there is a unique (stationary) Markov Perfect Equilibrium characterised by immediate agreement. Moreover, in equilibrium a relatively more patient party invests more than his opponent. However, being more patient can make a player worse off. In addition, we derive the conditions under which we obtain an efficient investment path. Our results are robust to different bargaining procedures, different rates of time preference and elasticities of substitution.
An Assessment of Nonmonotone Linesearch Techniques for Unconstrained Optimization

The purpose of this paper is to discuss the potential of nonmonotone techniques for enforcing convergence of unconstrained minimization algorithms from starting points distant from the solution. Linesearch-based algorithms are considered for both small and large problems, and extensive numerical experiments show that this potential is sometimes considerable. A new variant is introduced in order to limit some of the identified drawbacks of the existing techniques. This variant is again numerically tested and appears to be competitive. Finally, the impact of preconditioning on the considered methods is examined.
Magnetic Resonance Imaging versus Bone Scan for Assessment of Vascularization of the Hydroxyapatite Orbital Implant

Summary We prospectively studied 10 patients who were status postenucleation and primary placement of the hydroxyapatite orbital implant. Both the technetium-99m bone scan and gadolinium-enhanced magnetic resonance images (MRI) were obtained on the same day at variable time points in the postoperative period in order to assess the degree of vascularization. Up to 78% of the bone scans were interpreted as being completely vascularized, while only 10% of the corresponding MRI scans were consistent with complete vascularization. Cost analysis showed that MRI was a cost-effective imaging modality. We conclude that contrast-enhanced MRI provides a more accurate assessment of vascularization of the hydroxyapatite orbital implant when compared to bone scan.
A Unified Transmission Strategy for TDD/FDD Massive MIMO Systems With Spatial Basis Expansion Model

This paper proposes a unified transmission strategy for multiuser time division duplex (TDD)/frequency division duplex (FDD) massive multiple-input–multiple-output (MIMO) systems, including uplink (UL)/downlink (DL) channel estimation and user scheduling for data transmission. With the aid of antenna array theory and array signal processing, we build a spatial basis expansion model (SBEM) to represent the UL/DL channels with far fewer parameter dimensions. Hence, both the UL and DL channel estimations of multiusers can be carried out with a small amount of training resource, which significantly reduces the training overhead and feedback cost. Meanwhile, the pilot contamination problem in the UL training is immediately relieved by exploiting the spatial information of users. To enhance the spectral efficiency, we also design a greedy user scheduling scheme during the data transmission period. Compared with existing low-rank models, the newly proposed SBEM offers an alternative for channel acquisition without the need for channel statistics and can be applied to both TDD and FDD systems. Various numerical results are provided to corroborate the proposed studies.
Bayesian Semi-Supervised Chinese Word Segmentation for Statistical Machine Translation

Words in Chinese text are not naturally separated by delimiters, which poses a challenge to standard machine translation (MT) systems. In MT, the widely used approach is to apply a Chinese word segmenter trained from manually annotated data, using a fixed lexicon. Such word segmentation is not necessarily optimal for translation. We propose a Bayesian semi-supervised Chinese word segmentation model which uses both monolingual and bilingual information to derive a segmentation suitable for MT. Experiments show that our method improves a state-of-the-art MT system in a small and a large data environment.