Miracle-dz/UniFAR-FTUs huggingface dataset:
Multicasting at the host interface level in wormhole networks

We address the problem of providing transparent, reliable, and efficient network-level multicasting in wormhole LANs. We describe some alternatives for achieving deadlock-free multicasting using fast buffer reservation techniques at the host interface level. Tradeoffs involving complexity and performance of various solutions are discussed, and are illustrated using simulation results. Our results show that in most cases the straightforward approach of sending multiple unicast copies of the multicast message at the originator host turns out to be the most simple and effective approach.
The background modeling for the video sequences using Radial Basis Function neural network

This paper an adapted background subtraction system based on Radial Basis Function neural network is given. In the suggested system for each background pixel a two-state machine is considered in which the RBF1 neural network is used for crossing between different states of the machine. In suggested system is flexible to light changes and very few movements of background object and the presence of new object in the background and other challenges mentioned in the field of estimate the background. The test are down on image group of Wallflower data set, the obtained result confirm the efficiency of the suggested solution.
Beyond Liberal and Conservative: Advancing the Study of Judicial Behavior with a Cultural Theory of Political Values

A significant undiscussed problem with the leading conceptualization of ideologically based judicial behavior, Jeffrey Segal and Harold Spaeth’s attitudinal model, is its lack of theory. This problem leads to circular reasoning, ad hoc coding adjustments, and inaccurate characterizations and explanations of case outcomes, judicial votes and ideologies, and trends in judicial behavior. A values-based theory of ideology, such as the cultural theory pioneered by Mary Douglas, Michael Thompson, Aaron Wildavsky, and others, can help remedy this problem. Applying this cultural theory to First Amendment cases, we find that political cultures valuing equality, order, and liberty provide a more accurate account of judicial decisions than labeling them liberal or conservative.
Fundamental frequency Gabor filters for object recognition

Gabor filters are a widely used feature extraction method in image analysis. In this study, a method is presented that utilises Gabor filters for extracting fundamental frequencies of objects. The fundamental frequencies represent the shape of an object and can be used to classify objects with dissimilar spatial dimensions. Theoretical results are verified by experiments with real images of electronic components. Experiments indicate that the fundamental frequency Gabor filters are a robust tool for rotation and translation invariant object recognition.
Low-quality License Plate Character Recognition Based on CNN

In this paper, we analyze the importance and the difficulties to recognize car plate characters from low-quality monitoring videos. A solution is proposed to achieve the character recognition by classifying character images based on convolutional neural network. We analyze the degradation of car plate character in practical surveillance videos, and then model and generated simulated dataset. We also train simulated datasets in a convolutional neural network, and applied the trained network to recognize license plate characters in the actual surveillance videos. The experimental results show that this method works well to recognize these car plate characters. The proposed method can help identify some of the license plate characters that human eye can't identify.
Immunohistochemistry Successfully Uncovers Intratumoral Heterogeneity and Widespread Co-Losses of Chromatin Regulators in Clear Cell Renal Cell Carcinoma

Recent studies have shown that intratumoral heterogeneity (ITH) is prevalent in clear cell renal cell carcinoma (ccRCC), based on DNA sequencing and chromosome aberration analysis of multiple regions from the same tumor. VHL mutations were found to be universal throughout individual tumors when it occurred (ubiquitous), while the mutations in other tumor suppressor genes tended to be detected only in parts of the tumors (subclonal). ITH has been studied mostly by DNA sequencing in limited numbers of samples, either by whole genome sequencing or by targeted sequencing. It is not known whether immunohistochemistry (IHC) can be used as a tool to study ITH. To address this question, we examined the protein expression of PBRM1, and PBRM1-related proteins such as ARID1A, SETD2, BRG1, and BRM. Altogether, 160 ccRCC (40 per stage) were used to generate a tissue microarray (TMA), with four foci from each tumor included. Loss of expression was defined as 0–5% of tumor cells with positive nuclear staining in an individual focus. We found that 49/160 (31%), 81/160 (51%), 23/160 (14%), 24/160 (15%), and 61/160 (38%) of ccRCC showed loss of expression of PBRM1, ARID1A, SETD2, BRG1, and BRM, respectively, and that IHC could successfully detect a high prevalence of ITH. Phylogenetic trees were constructed that reflected the ITH. Striking co-losses among proteins were also observed. For instance, ARID1A loss almost always accompanied PBRM1 loss, whereas BRM loss accompanied loss of BRG1, PBRM1 or ARID1A. SETD2 loss frequently occurred with loss of one or more of the other four proteins. Finally, in order to learn the impact of combined losses, we compared the tumor growth after cells acquired losses of ARID1A, PBRM1, or both in a xenograft model. The results suggest that ARID1A loss has a greater tumor-promoting effect than PBRM1 loss, indicating that xenograft analysis is a useful tool to investigate how these losses impact on tumor behavior, either alone or in combination.
Fingerprint reference point detection based on local ridge orientation patterns of fingerprints

This paper introduces an approach to detect reference points for fingerprint images from their local ridge orientation maps. This approach classifies detected singular points into several core and delta point pairs. The validation procedure contains two stages in which the first stage is to remove false pairs of core and delta points and the second stage is to do some post processing of these unpaired singular points. Furthermore, this approach could be extended for reference point detection of arch and partial fingerprint images. The experiments of singular point detection part are conducted on FVC 2002 database 1 and 2. The result shows the average correct rate of singular point detection is 94.05% on the above databases.
Aggregate suppression for enterprise search engines

Many enterprise websites provide search engines to facilitate customer access to their underlying documents or data. With the web interface of such a search engine, a customer can specify one or a few keywords that he/she is interested in; and the search engine returns a list of documents/tuples matching the user-specified keywords, sorted by an often-proprietary scoring function. It was traditionally believed that, because of its highly-restrictive interface (i.e., keyword search only, no SQL-style queries), such a search engine serves its purpose of answering individual keyword-search queries without disclosing big-picture aggregates over the data which, as we shall show in the paper, may incur significant privacy concerns to the enterprise. Nonetheless, recent work on sampling and aggregate estimation over a search engine's corpus through its keyword-search interface transcends this traditional belief. In this paper, we consider a novel problem of suppressing sensitive aggregates for enterprise search engines while maintaining the quality of answers provided to individual keyword-search queries. We demonstrate the effectiveness and efficiency of our novel techniques through theoretical analysis and extensive experimental studies.
A Histopathological Image Feature Representation Method Based on Deep Learning

Automated annotation and grading for histopathological image plays an important role in CAD systems. It provides valuable information and support for medical diagnosis. Currently, computer-aid analysis of histopathological images mainly relies on some well-designed digital features, which requires abundant human efforts and experiences in problem domain. Learning a good feature representation from data can have positive effects on constructing the target model. We propose a novel method for histopathological image feature representation based on deep learning. The method extracts high level representation of raw pixels of a local region through a network model with several hidden layers, which can learn potential features automatically. The proposed method is evaluated on a real data set from a large local hospital with comparison to two current state-of-the-art methods. The result is promising indicating that it achieves significant improvement of the model performance. Moreover, our study suggests that features learned through deep models can achieve better performance than human designed features.
MYC and EGR1 synergize to trigger tumor cell death by controlling NOXA and BIM transcription upon treatment with the proteasome inhibitor bortezomib

The c-MYC (MYC afterward) oncogene is well known for driving numerous oncogenic programs. However, MYC can also induce apoptosis and this function of MYC warrants further clarification. We report here that a clinically relevant proteasome inhibitor significantly increases MYC protein levels and that endogenous MYC is necessary for the induction of apoptosis. This kind of MYC-induced cell death is mediated by enhanced expression of the pro-apoptotic BCL2 family members NOXA and BIM. Quantitative promoter-scanning chromatin immunoprecipitations (qChIP) further revealed binding of MYC to the promoters of NOXA and BIM upon proteasome inhibition, correlating with increased transcription. Both promoters are further characterized by the presence of tri-methylated lysine 4 of histone H3, marking active chromatin. We provide evidence that in our apoptosis models cell death occurs independently of p53 or ARF. Furthermore, we demonstrate that recruitment of MYC to the NOXA as well as to the BIM gene promoters depends on MYC's interaction with the zinc finger transcription factor EGR1 and an EGR1-binding site in both promoters. Our study uncovers a novel molecular mechanism by showing that the functional cooperation of MYC with EGR1 is required for bortezomib-induced cell death. This observation may be important for novel therapeutic strategies engaging the inherent pro-death function of MYC.
A third-order continuous-time sigma-delta modulator for Bluetooth

This paper presents the design of a third-order continuous-time (CT) single-bit active-RC sigma-delta (ΣΔ) modulator for Bluetooth application. Through the use of the architecture, cascade of resonators with distributed feedback (CRFB), the signal bandwidth can be improved without increasing the order of the modulator. All integrators are implemented by active-RC type to have better linearity. Furthermore, in order to reduce the effect of the clock jitter, the feedback digital-to-analog converter (DAC) shape is realized by non-return-to-zero (NRZ). The modulator is designed in a standard digital 0. 18µm CMOS process with a chip area of 1.32×1.23 mm2. The measurement results show that the modulator achieves 56.8dB SNDR and 60dB dynamic range over 1MHz signal bandwidth, consuming 22.2mW at 1.8V supply.
Screening and genetic analysis of resistance to peanut stunt virus in soybean: identification of the putative Rpsv1 resistance gene

The peanut stunt virus (PSV) causes yield losses in soybean and reduced seed quality due to seed mottling. The objectives of this study were to determine the phenotypic reactions of soybean germplasms to inoculation with two PSV isolates (PSV-K, PSV-T), the inheritance of PSV resistance in soybean cultivars, and the locus of the PSV resistance gene. We investigated the PSV resistance of 132 soybean cultivars to both PSV isolates; of these, 73 cultivars exhibited resistance to both PSV isolates. Three resistant cultivars (Harosoy, Tsurunotamago 1 and Hyuga) were crossed with the susceptible cultivar Enrei. The crosses were evaluated in the F1, F2 and F2:3 generations for their reactions to inoculation with the two PSV isolates. In an allelism test, we crossed Harosoy and Tsurunotamago 1 with the resistant cultivar Hyuga. The results revealed that PSV resistance in these cultivars is controlled by a single dominant gene at the same locus. We have proposed Rpsv1, as the name of the resistance gene in Hyuga. We also constructed a linkage map using recombinant inbred lines between Hyuga × Enrei using 176 SSR markers. We mapped Rpsv1 near the Satt435 locus on soybean chromosome 7.
The Role of the Subjective Importance of Smoking (SIMS) in Cessation and Abstinence.

Introduction Each year about two thirds of U.S. smokers make a quit attempt. Yet, less than 5% remain abstinent three months post-quit date. One factor that may affect abstinence is negative feelings about the self-associated with being a smoker (disequilibrium), particularly if smoking is important to the sense of self and one is trying to quit. Aims We evaluated a multivariate structural equation model proposing that smoking's subjective importance to a smoker would influence carbon monoxide verified smoking abstinence at 24 weeks (post-quit date). Further, we assessed whether the relation would be moderated by the smoker's experience of disequilibrium. Methods Participants were 440 regular smokers taking part in a clinical trial assessing the effectiveness of different durations of nicotine replacement therapy use. Participants completed the subjective importance of smoking survey at baseline and were assessed for carbon monoxide verified seven-day point prevalence abstinence at 24 weeks. Results Using exploratory structural equation modelling, the subjective importance of smoking was associated with point prevalence abstinence at 24 weeks, but only for smokers with high disequilibrium. Conclusions The results of this study suggest that experiencing negative feelings about being a smoker could motivate smokers to remain abstinent, despite the importance of smoking to the smoker's sense of self.
Cross-Reference Maximum Likelihood Estimatesfor Positron Emission

Maximum likelihood estimate (MLE) is a widely-used approach for PET image reconstruction. However, it has been shown that reconstructing emission tomography based on MLE without regularization would result in noise and edge artifacts. In the attempt to regularize the maximum likelihood estimate , in this paper, we propose a new and eecient method to incorporate the correlated but possibly incomplete structure information which may be derived from expertise, PET systems or other imaging modalities. A mean estimate smoothing the MLE locally within each region of interest is derived according to the boundaries provided by the structure information. Since the boundaries may not be correct, a penalized MLE using the mean estimate is sought. The resulting reconstruction is called a cross-reference maximum likelihood estimate (CRMLE). The CRMLE can be obtained through a modiied EM algorithm, which is computation and storage eecient. By borrowing the strength from the correct portion of boundary information, the CRMLE is able to extract the useful information to improve reconstruction for diierent kinds of incomplete and incorrect boundaries in Monte Carlo studies. The proposed CRMLE algorithm not only reduces the estimation errors, but also preserves the correct boundaries. The penalty parameters can be selected through human interactions or automatically data-driven methods, such as the generalized cross validation method.
Light Curve and Spectral Models for the Hypernova SN 1998bw Associated with GRB 980425

A refined model for the unusual Type Ic supernova 1998bw, discovered as the optical counterpart to GRB 980425, is presented, and synthetic light curves and spectra are compared with the observations. The first 30 days of the light curve and the broad-line features of the spectra can be reproduced with the hydrodynamic model of the explosion of a 14 M☉ C + O star, the core of a star with initial mass 40 M☉, assuming that the explosion was very energetic (kinetic energy EK = 5 × 1052 ergs) and that 0.4 M☉ of 56Ni were synthesized. At late times, however, the observed light-curve tail declines more slowly than this energetic model and is in better agreement with a less energetic (EK = 7 × 1051 ergs) one. This shift to a less energetic model may imply that the inner part of the ejecta has higher density and lower velocities than the model with EK = 5 × 1052 ergs, so that γ-rays deposit more efficiently. An aspherical explosion can produce such a structure of the ejecta. We also study detailed nucleosynthesis calculations for hyperenergetic supernova explosions and compare the yields with those of normal supernovae.
Handling uncertainty for video event recognition

This paper presents a cognitive vision approach for video event recognition able of handling the uncertainty of the recognition process. The recognition task is complex because of image noise, of segmentation and classification issues. In this work, we extend the event recognition algorithm (crisp algorithm) proposed in [1] by proposing a geometric method which handles the uncertainty of the recognition process. This method consists in computing the precision of the 3D information of the mobile objects evolving in the scene for each frame of the video sequence. We use the computed information to calculate the probability of the event. The proposed method is tested with videos of everyday activities of elderly people. Events of interest have been modeled with the help of medical experts (i.e. gerontologists). The experimental results show that the proposed approach improves significantly the process of recognition and can characterize the likelihood of the recognized events. (6 pages)
Instrogram: Probabilistic Representation of Instrument Existence for Polyphonic Music

This paper presents a new technique for recognizing musical instruments in polyphonic music. Since conventional musical instrument recognition in polyphonic music is performed notewise, i.e., for each note, accurate estimation of the onset time and fundamental frequency (F0) of each note is required. However, these estimations are generally not easy in polyphonic music, and thus estimation errors severely deteriorated the recognition performance. Without these estimations, our technique calculates the temporal trajectory of instrument existence probabilities for every possible F0. The instrument existence probability is defined as the product of a nonspecific instrument existence probability calculated using the PreFEst and a conditional instrument existence probability calculated using hidden Markov models. The instrument existence probability is visualized as a spectrogram-like graphical representation called the instrogram and is applied to MPEG-7 annotation and instrumentation-similaritybased music information retrieval. Experimental results from both synthesized music and real performance recordings have shown that instrograms achieved MPEG-7 annotation (instrument identification) with a precision rate of 87.5% for synthesized music and 69.4% for real performances on average and that the instrumentation similarity measure reflected the actual instrumentation better than an MFCC-based measure.
Exploring Experienced Teachers’ Constructions of Culturally and Linguistically Diverse Students in an Online Class

This article examines online discussions during a teacher education class for experienced teachers seeking licensure in teaching English learners. It seeks to understand experienced teachers’ constructions of culturally and linguistically diverse (CLD) students. Using discourse analysis to emphasize talk as situated and action-oriented, the article indicates how belief claims expressed during experienced teachers’ online discussions construct specific versions of what it means to be a CLD student. Findings further suggest that participants managed their authority to speak about students’ needs in patterned ways. These findings have implications for teaching and learning, particularly for the preparation of experienced teachers.
Coupled Positive and Negative Feedbacks Produce Diverse Gene Expression Patterns in Colonies

ABSTRACT Formation of patterns is a common feature in the development of multicellular organism as well as of microbial communities. To investigate the formation of gene expression patterns in colonies, we build a mathematical model of two-dimensional colony growth, where cells carry a coupled positive-and-negative-feedback circuit. We demonstrate that the model can produce sectored, target (concentric), uniform, and scattered expression patterns of regulators, depending on gene expression dynamics and nutrient diffusion. We reconstructed the same regulatory structure in Escherichia coli cells and found gene expression patterns on the surface of colonies similar to the ones produced by the computer simulations. By comparing computer simulations and experimental results, we observed that very simple rules of gene expression can yield a spectrum of well-defined patterns in a growing colony. Our results suggest that variations of the protein content among cells lead to a high level of heterogeneity in colonies. IMPORTANCE Formation of patterns is a common feature in the development of microbial communities. In this work, we show that a simple genetic circuit composed of a positive-feedback loop and a negative-feedback loop can produce diverse expression patterns in colonies. We obtained similar sets of gene expression patterns in the simulations and in the experiments. Because the combination of positive feedback and negative feedback is common in intracellular molecular networks, our results suggest that the protein content of cells is highly diversified in colonies. Formation of patterns is a common feature in the development of microbial communities. In this work, we show that a simple genetic circuit composed of a positive-feedback loop and a negative-feedback loop can produce diverse expression patterns in colonies. We obtained similar sets of gene expression patterns in the simulations and in the experiments. Because the combination of positive feedback and negative feedback is common in intracellular molecular networks, our results suggest that the protein content of cells is highly diversified in colonies.
Using MP statements to explain voting behaviour in the German Bundestag

Why do members of parliament (MPs) vote against the party line? Recent explanations of party unity focus on MPs cross-pressured between the demands of competing principals such as their party and local constituencies. This article tests key claims of the Competing Principals Theory on the level of individual deputies. It relies on public statements in which MPs explain their voting behaviour. This new data source allows more direct insights into MPs’ decision-making calculus than roll-call data. The article develops a theoretical model for the usage of such statements and the position MPs take vis-à-vis the party line. Empirically, it studies Explanations of Votes on all roll-call votes in the 16th German Bundestag (2005–2009) statistically controlling for sample selection. The analyses show among others things that district MPs take more critical stances, party leaders dissent less and government MPs are more likely to voice reservations without defecting in voting.