Miracle-dz/UniFAR-FTUs huggingface dataset:
Studies on nucleoli and cytoplasmic fibrillar bodies of human hepatocellular carcinomas.

The ultrastructure of neoplastic cells of hepatocellular carcinomas in 3 untreated male patients of similar ages was studied and compared with liver cells of 2 persons with normal histology of the liver. As in rapidly growing experimental hepatomas and the Walker tumor of rats, nucleoli in a rapidly growing human hepatocellular carcinoma were characterized by a decrease of the relative percentages of total nucleolar areas containing fibrillar components when compared with slowly growing tumors or normal liver. The nucleolus-associated chromatin of the rapidly growing human hepatocellular carcinoma contained some “giant” microspherules with diameters up to 1400 A. The cytoplasm of these hepatocellular carcinoma cells contained fibrillar inclusion bodies and another type of fibrillar body.
Neural Network Approaches to Image Compression

This paper presents a tutorial overview of neural networks as signal processing tools for image compression. They are well suited to the problem of image compression due to their massively parallel and distributed architecture. Their characteristics are analogous to some of the features of our own visual system, which allow us to process visual information with much ease. For example, multilayer perceptrons can be used as nonlinear predictors in differential pulse-code modulation (DPCM). Such predictors have been shown to increase the predictive gain relative to a linear predictor. Another active area of research is in the application of Hebbian learning to the extraction of principal components, which are the basis vectors for the optimal linear Karhunen-Loève transform (KLT). These learning algorithms are iterative, have some computational advantages over standard eigendecomposition techniques, and can be made to adapt to changes in the input signal. Yet another model, the self-organizing feature map (SOFM), has been used with a great deal of success in the design of codebooks for vector quantization (VQ). The resulting codebooks are less sensitive to initial conditions than the standard LBG algorithm, and the topological ordering of the entries can be exploited to further increase coding efficiency and reduce computational complexity.
Development of Laguerre Neural-Network-Based Intelligent Sensors for Wireless Sensor Networks

The node of a wireless sensor network (WSN), which contains a sensor module with one or more physical sensors, may be exposed to widely varying environmental conditions, e.g., temperature, pressure, humidity, etc. Most of the sensor response characteristics are nonlinear, and in addition to that, other environmental parameters influence the sensor output nonlinearly. Therefore, to obtain accurate information from the sensors, it is important to linearize the sensor response and compensate for the undesirable environmental influences. In this paper, we present an intelligent technique using a novel computationally efficient Laguerre neural network (LaNN) to compensate for the inherent sensor nonlinearity and the environmental influences. Using the example of a capacitive pressure sensor, we have shown through extensive computer simulations that the proposed LaNN-based sensor can provide highly linearized output, such that the maximum full-scale error remains within ± 1.0% over a wide temperature range from -50 °C to 200 °C for three different types of nonlinear dependences. We have carried out its performance comparison with a multilayer-perceptron-based sensor model. We have also proposed a reduced-complexity run-time implementation scheme for the LaNN-based sensor model, which can save about 50% of the hardware and reduce the execution time by four times, thus making it suitable for the energy-constrained WSN applications.
Students' Perceived Support from Teachers: Impacts on Academic Achievement, Interest in Schoolwork, Attendance, and Self-Esteem.

U.S. junior high school students in grades 7 and 8 (N.226) responded to survey items on their self-esteem and interest in schoolwork, their personal expectancy of completing high school, and perceived support from their teachers, parents, and peers for this expectancy. Their grade point average (GPA) and attendance data were obtained from school records. Structural equation models found that each of the four factors (Personal, Teacher, Parent, and Peer) had noteworthy positive impacts on self-esteem, interest in schoolwork, and GPA. The Personal and Teacher factors also had negative impacts on absence from school. However, when all four predictors and four outcome measures were considered in the same model, for all four outcomes, the strongest paths were from the Teacher factor, stronger than the paths from the Personal factor or from the significant others. These results show the importance of teacher support at the critical stage of early high school. Teacher educators should equip teachers in training and in service to provide students with favorable feedback on academic expectancy. An appendix lists study variables with their alpha reliability estimates. (Contains 2 tables and 37 references.) (Author/SLD) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
The Answer is at your Fingertips: Improving Passage Retrieval for Web Question Answering with Search Behavior Data

Passage retrieval is a crucial first step of automatic Question Answering (QA). While existing passage retrieval algorithms are effective at selecting document passages most similar to the question, or those that contain the expected answer types, they do not take into account which parts of the document the searchers actually found useful. We propose, to the best of our knowledge, the first successful attempt to incorporate searcher examination data into passage retrieval for question answering. Specifically, we exploit detailed examination data, such as mouse cursor movements and scrolling, to infer the parts of the document the searcher found interesting, and then incorporate this signal into passage retrieval for QA. Our extensive experiments and analysis demonstrate that our method significantly improves passage retrieval, compared to using textual features alone. As an additional contribution, we make available to the research community the code and the search behavior data used in this study, with the hope of encouraging further research in this area.
Efficient path planning in changing environments

This paper addresses the problem of path planning in environments in which some of the obstacles can change their positions. It uses the popular PRM method for navigating a robot through an environment. One of the key features of PRM is that it moves the major part of the calculations involved in the path planning process to the preprocessing phase. After that, paths can be extracted very quickly (in a query phase) usually without any noticeable delay. While very successful in many applications, doing most of the work in a preprocessing phase restricts the environment to be static i.e. obstacles are not allowed to change their configurations after the preprocessing phase. In this paper we describe and evaluate an algorithm based on PRM that does allow obstacles to change their configuration after preprocessing while still allowing for a quick query phase.
Fetching Strategy in the Startup Stage of p2p Live Streaming

A protocol named Threshold Bipolar (TB) is proposed as a fetching strategy at the startup stage of p2p live streaming systems. In this protocol, chunks are fetched consecutively from buffer head at the beginning. After the buffer is filled into a threshold, chunks at the buffer tail will be fetched first while keeping the contiguously filled part in the buffer above the threshold even when the buffer is drained at a playback rate. High download rate, small startup latency and natural strategy handover can be reached at the same time by this protocol. Important parameters in this protocol are identified. The buffer progress under this protocol is then expressed as piecewise lines specified by those parameters. Startup traces of peers measured from PPLive are studied to show the real performance of TB protocol in a real system. A simple design model of TB protocol is proposed to reveal important considerations in a practical design.
Determining of Crystalline Silica in Respirable Dust Samples by Infrared Spectrophotometry in the Presence of Interferences

Determining of Crystalline Silica in Respirable Dust Samples by Infrared Spectrophotometry in the Presence of Interferences: Jun Ojima. National Institute of Industrial Health—Infrared Spectrophotometry (IR) is now widely used to determine crystalline silica in industrial dust samples. Though the IR method has many advantages when dealing with respirable dust samples, some serious analytical errors are often caused by interference minerals contamination. These minerals have a characteristic absorption band corresponding in position to the analytical peak for crystalline silica. In this paper, six typical interference minerals (Kaolinite, Mullite, Muscovite, Pyrophyllite, Montmorillonite and Amorphous silica) were pre‐size controlled to respirable range and their infrared spectra were measured by means of an FT‐IR with the well known potassium bromide tablet technique. The effects of these interference minerals on the Japanese OEL or the administrative control level for respirable dust which depend on the silica content were calculated and expressed in figures. The measured absorption coefficients of the interference minerals and quartz were 1.36–6.98 Abs/mg and 24.46 Abs/mg, respectively. The absorption band height ratios of each interference minerals were also measured. Then the efficiency and applicability of two spectrum correction methods for the interference minerals, absorbance ratio method and difference spectrum method were examined by using artificially mixed samples (standard interference mineral + standard quartz). By comparing the quantifying results for the mixture samples, it was revealed that the interfered spectra were almost corrected successfully when using the difference spectrum method, whereas correction by the absorbance ratio method resulted in apparent negative errors. Furthermore, the difference spectrum method was proven to be superior to the absorbance ratio method in applicability.
Exploit the tripartite network of social tagging for web clustering

In this poster, we investigate how to enhance web clustering by leveraging the tripartite network of social tagging systems. We propose a clustering method, called "Tripartite Clustering", which cluster the three types of nodes (resources, users and tags) simultaneously based on the links in the social tagging network. The proposed method is experimented on a real-world social tagging dataset sampled from del.icio. us. We also compare the proposed clustering approach with K-means. All the clustering results are evaluated against a human-maintained web directory. The experimental results show that Tripartite Clustering significantly outperforms the content-based K-means approach and achieves performance close to that of social annotation-based K-means whereas generating much more useful information.
MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data

Most existing statistical methods developed for calling single nucleotide polymorphisms (SNPs) using next-generation sequencing (NGS) data are based on Bayesian frameworks, and there does not exist any SNP caller that produces p-values for calling SNPs in a frequentist framework. To fill in this gap, we develop a new method MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs with NGS data. MAFsnp is based on an estimated likelihood ratio test (eLRT) statistic. In practical situation, the involved parameter is very close to the boundary of the parametric space, so the standard large sample property is not suitable to evaluate the finite-sample distribution of the eLRT statistic. Observing that the distribution of the test statistic is a mixture of zero and a continuous part, we propose to model the test statistic with a novel two-parameter mixture distribution. Once the parameters in the mixture distribution are estimated, p-values can be easily calculated for detecting SNPs, and the multiple-testing corrected p-values can be used to control false discovery rate (FDR) at any pre-specified level. With simulated data, MAFsnp is shown to have much better control of FDR than the existing SNP callers. Through the application to two real datasets, MAFsnp is also shown to outperform the existing SNP callers in terms of calling accuracy. An R package “MAFsnp” implementing the new SNP caller is freely available at http://homepage.fudan. edu.cn/zhangh/softwares/.
Novel Proteins, Putative Membrane Transporters, and an Integrated Metabolic Network Are Revealed by Quantitative Proteomic Analysis of Arabidopsis Cell Culture Peroxisomes1[W][OA]

Peroxisomes play key roles in energy metabolism, cell signaling, and plant development. A better understanding of these important functions will be achieved with a more complete definition of the peroxisome proteome. The isolation of peroxisomes and their separation from mitochondria and other major membrane systems have been significant challenges in the Arabidopsis (Arabidopsis thaliana) model system. In this study, we present new data on the Arabidopsis peroxisome proteome obtained using two new technical advances that have not previously been applied to studies of plant peroxisomes. First, we followed density gradient centrifugation with free-flow electrophoresis to improve the separation of peroxisomes from mitochondria. Second, we used quantitative proteomics to identify proteins enriched in the peroxisome fractions relative to mitochondrial fractions. We provide evidence for peroxisomal localization of 89 proteins, 36 of which have not previously been identified in other analyses of Arabidopsis peroxisomes. Chimeric green fluorescent protein constructs of 35 proteins have been used to confirm their localization in peroxisomes or to identify endoplasmic reticulum contaminants. The distribution of many of these peroxisomal proteins between soluble, membrane-associated, and integral membrane locations has also been determined. This core peroxisomal proteome from nonphotosynthetic cultured cells contains a proportion of proteins that cannot be predicted to be peroxisomal due to the lack of recognizable peroxisomal targeting sequence 1 (PTS1) or PTS2 signals. Proteins identified are likely to be components in peroxisome biogenesis, β-oxidation for fatty acid degradation and hormone biosynthesis, photorespiration, and metabolite transport. A considerable number of the proteins found in peroxisomes have no known function, and potential roles of these proteins in peroxisomal metabolism are discussed. This is aided by a metabolic network analysis that reveals a tight integration of functions and highlights specific metabolite nodes that most probably represent entry and exit metabolites that could require transport across the peroxisomal membrane.
Balanced-to-single-ended filtering power dividers

Balanced-to-single-ended filtering power dividers have been used widely in modern communication systems due to their ability of easy connection with balanced and single-ended components simultaneously as well as differential-mode power division, common-mode suppression and filtering function, which is similar to balanced-to-balanced filtering power dividers. The conventional single-ended filtering power divider needs additional baluns to configure the balanced-to-balanced and balanced-to-single-ended filtering power divider, which results in large circuit size. Compared with balanced-to-balanced designs, few balanced-to-single-ended designs are reported. In this paper, two types of balanced-to-single-ended filtering power dividers are proposed and performances of them are compared.
Correlation of primary tumor prostate-specific membrane antigen expression with disease recurrence in prostate cancer.

PURPOSE The restricted expression of the surface glycoprotein prostrate-specific membrane antigen (PSMA) to normal prostate tissue, primary and metastatic prostate cancer (PCa), and the neovasculature of various nonprostatic epithelial malignancies has enabled targeting strategies for PCa treatment using anti-PSMA antibodies. EXPERIMENTAL DESIGN Using prostatectomy specimens, immunohistochemical staining for PSMA (7E11 antibody) was performed on formalin-fixed paraffin-embedded sections of 136 cases of PCa. Cytoplasmic immunoreactivity was scored for intensity and distribution, and results were correlated with tumor grade, pathological stage, DNA ploidy status (Feulgen spectroscopy), and disease recurrence. PSMA mRNA expression in selected primary tumors and metastatic lesions was also detected using in situ hybridization and autoradiography. RESULTS Generally, PCa cells expressed relatively increased levels of PSMA as compared with benign elements. Among the PCa cases, increased (high) PSMA expression correlated with tumor grade (P = 0.030), pathological stage (P = 0.029), aneuploidy (P = 0.010), and biochemical recurrence (P = 0.001). The mean serum prostate-specific antigen level of 18.28 ng/ml at the time of diagnosis for the PSMA-overexpressing tumors was significantly greater than the mean serum prostate-specific antigen of 9.10 ng/ml for the non-PMSA-overexpressing group (P = 0.006). On multivariate analysis, pathological stage (P = 0.018) and PSMA expression (P = 0.002) were independent predictors of biochemical recurrence. PSMA protein overexpression in high-grade primary PCa tumors and metastatic lesions also correlated with increased PSMA mRNA expression levels using in situ hybridization and autoradiography. CONCLUSIONS This study demonstrates for the first time that overexpression of PSMA in primary PCa correlates with other adverse traditional prognostic factors and independently predicts disease outcome.
Neuronal Oscillations in Cortical Networks

Clocks tick, bridges and skyscrapers vibrate, neuronal networks oscillate. Are neuronal oscillations an inevitable by-product, similar to bridge vibrations, or an essential part of the brain's design? Mammalian cortical neurons form behavior-dependent oscillating networks of various sizes, which span five orders of magnitude in frequency. These oscillations are phylogenetically preserved, suggesting that they are functionally relevant. Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
Dynamic Remodeling of Dendritic Arbors in GABAergic Interneurons of Adult Visual Cortex

Despite decades of evidence for functional plasticity in the adult brain, the role of structural plasticity in its manifestation remains unclear. To examine the extent of neuronal remodeling that occurs in the brain on a day-to-day basis, we used a multiphoton-based microscopy system for chronic in vivo imaging and reconstruction of entire neurons in the superficial layers of the rodent cerebral cortex. Here we show the first unambiguous evidence (to our knowledge) of dendrite growth and remodeling in adult neurons. Over a period of months, neurons could be seen extending and retracting existing branches, and in rare cases adding new branch tips. Neurons exhibiting dynamic arbor rearrangements were GABA-positive non-pyramidal interneurons, while pyramidal cells remained stable. These results are consistent with the idea that dendritic structural remodeling is a substrate for adult plasticity and they suggest that circuit rearrangement in the adult cortex is restricted by cell type–specific rules.
Adding ternary complex roles to ALCRP(D)

The goal of this paper is to introduce the description logic ALCRP(D). This logic is based on the DL ALCRP(D) extended by a ternary role-forming predicate operator and by inverse roles. In order to be able to define a compositional semantics for ALCRP(D), which supports n-ary relations, we introduce a DLR-style syntax. For simplicity and from the viewpoint of the applicability in practice, only ternary relations will be discussed. The paper discusses syntactic restrictions on concepts and roles to ensure decidability of the language.
An exploration of the prevalence of hypermobility and joint hypermobility syndrome in Omani women attending a hospital physiotherapy service.

BACKGROUND AND OBJECTIVES Joint hypermobility syndrome (JHS) is an inherited disorder of connective tissue. It presents as a condition in which there are neuromusculoskeletal signs and symptoms, including pain, without the inflammatory component of a joint disease such as rheumatoid arthritis. Re-attendance in rheumatology clinics, re-injury and prolonged rehabilitation are also features of JHS. The primary aims of this study were to establish the prevalence of hypermobility and JHS in those attending physiotherapy clinics with neuromusculoskeletal disorders in Oman. METHODS A cross-sectional case control study design was used. The participant population included Omani women, aged 18-50 years, attending physiotherapy services for musculoskeletal complaints. The comparison population comprised women of a similar age and ethnic origin who were staff at the hospital. The primary outcome measures were the Beighton Score and the Brighton Criteria. RESULTS A total of 184 subjects were recruited into the study. These consisted of 94 in the participant group and 90 in the comparison group. Hypermobility was recorded in 51% of the participant group and 30% of the comparison group. The number of participants with JHS was 55%, while 21% of the comparison group exhibited features of the JHS phenotype without pain. A significant number of participants with JHS were re-attending for treatment compared with those without JHS. CONCLUSIONS This study confirms a high prevalence of JHS among subjects with musculoskeletal signs and symptoms and that re-attendance for physiotherapy treatment is more frequent in subjects with JHS than in those without.
Anchored fusion for image restoration

Recently, a series of advances were made for image restoration tasks such as image denoising and single image super-resolution. It is particularly remarkable that methods employing different formulations and assumptions achieve comparable top performances. Moreover, the top methods operate at their best on some particular image contents and poorer on other. No method is the best on all the image contents. The methods are complementary in both formulation and performance. We propose a locally adaptive fusion of results of such methods towards an improved restoration result. We work patch-wise and partition the patch space such that per each partition to train anchored regressors from the fused methods' output patches to the fusion target result. At test our anchored fusion method applies efficiently the anchored regressors corresponding to the input patches to be fused. Whilst having a low time complexity, we achieve significant improvements over the fused state-of-the-art methods on standard test images for both image denoising and super-resolution tasks (e.g. 0.1 – 0.5dB PSNR).