Miracle-dz/UniFAR-FTUs huggingface dataset:
Lower bounds on threshold and related circuits via communication complexity

Using communication complexity concepts and techniques, we derive linear (/spl Omega/(n)) and almost-linear (/spl Omega/(n/logn)) lower bounds on the size of circuits implementing certain functions. Our approach utilizes only basic features of the gates used, hence the bounds hold for general families of gates of which the symmetric and threshold gates are special cases. Each of the bounds derived is shown to be tight for some functions and some applications to threshold circuit complexity are indicated. The results generalize and in some cases strengthen recent results. >
Annotating and Learning Compound Noun Semantics

There is little consensus on a standard experimental design for the compound interpretation task. This paper introduces well-motivated general desiderata for semantic annotation schemes, and describes such a scheme for in-context compound annotation accompanied by detailed publicly available guidelines. Classification experiments on an open-text dataset compare favourably with previously reported results and provide a solid baseline for future research.
A Distributed Model For Multiple-Viewpoint Melodic Prediction

The analysis of sequences is important for extracting information from music owing to its fundamentally temporal nature. In this paper, we present a distributed model based on the Restricted Boltzmann Machine (RBM) for melodic sequences. The model is similar to a previous successful neural network model for natural language [2]. It is first trained to predict the next pitch in a given pitch sequence, and then extended to also make use of information in sequences of note-durations in monophonic melodies on the same task. In doing so, we also propose an efficient way of representing this additional information that takes advantage of the RBM’s structure. In our evaluation, this RBM-based prediction model performs slightly better than previously evaluated n-gram models in most cases. Results on a corpus of chorale and folk melodies showed that it is able to make use of information present in longer contexts more effectively than n-gram models, while scaling linearly in the number of free parameters required.
The effect of customer perceived value on relationship quality between illustrator and fans to recommendation on facebook

In recent years, along with the prevalence of social networking sites, the illustrators of Wretch have accordingly transferred to new community platform. These illustrator's fan pages have become popular through viral marketing. Many companies have spotted enormous business opportunities and then worked with illustrators to boost sales by combining illustrators and commercial products. By utilizing a research model of relationship quality, online word-of-mouth, purchase intention and perceived value, the purpose of study is to explore whether fans would purchase the product endorsed by their favorite illustrators or other peripheral products. The finding show that relationship quality is positively related to online word-of-mouth and had an indirect effect on purchase intention. Online word-of-mouth and purchase intention are positively correlated. In addition, perceived value is positively related to relationship quality, online word-of-mouth, and purchase intention. The main contribution of this research is in proposing a new research model and also discovering the importance of customer perceived value to the hedonic value of products.
Decoding Sentiment from Distributed Representations of Sentences

Distributed representations of sentences have been developed recently to represent their meaning as real-valued vectors. However, it is not clear how much information such representations retain about the polarity of sentences. To study this question, we decode sentiment from unsupervised sentence representations learned with different architectures (sensitive to the order of words, the order of sentences, or none) in 9 typologically diverse languages. Sentiment results from the (recursive) composition of lexical items and grammatical strategies such as negation and concession. The results are manifold: we show that there is no ‘one-size-fits-all’ representation architecture outperforming the others across the board. Rather, the top-ranking architectures depend on the language at hand. Moreover, we find that in several cases the additive composition model based on skip-gram word vectors may surpass supervised state-of-art architectures such as bi-directional LSTMs. Finally, we provide a possible explanation of the observed variation based on the type of negative constructions in each language.
The influence of life‐history strategy on genetic differentiation and lineage divergence in darters (Percidae: Etheostomatinae)

Recent studies determined that darters with specialized breeding strategies can exhibit deep lineage divergence over fine geographic scales without apparent physical barriers to gene flow. However, the extent to which intrinsic characteristics interact with extrinsic factors to influence population divergence and lineage diversification in darters is not well understood. This study employed comparative phylogeographic and population genetic methods to investigate the influence of life history on gene flow, dispersal ability, and lineage divergence in two sympatric sister darters with differing breeding strategies. Our results revealed highly disparate phylogeographic histories, patterns of genetic structure, and dispersal abilities between the two species suggesting that life history may contribute to lineage diversification in darters, especially by limiting dispersal among large river courses. Both species also showed striking differences in demographic history, indicating that extrinsic factors differentially affected each species during the Pleistocene. Collectively, our results indicate that intrinsic and extrinsic factors have influenced levels of gene flow among populations within both species examined. However, we suggest that life‐history strategy may play a more important role in lineage diversification in darters than previously appreciated, a finding that has potentially important implications for understanding diversification of the rich North American freshwater fish fauna.
Acute Myeloid Leukemia With RBM15-MKL1 Presenting as Severe Hepatic Failure

Creative Commons Non Commercial CC-BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits noncommercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Brief Report
Curcumin Conjugated with PLGA Potentiates Sustainability, Anti-Proliferative Activity and Apoptosis in Human Colon Carcinoma Cells

Curcumin, an ingredient of turmeric, exhibits a variety of biological activities such as anti-inflammatory, anti-atherosclerotic, anti-proliferative, anti-oxidant, anti-cancer and anti-metastatic. It is a highly pleiotropic molecule that inhibits cell proliferation and induces apoptosis in cancer cells. Despite its imperative biological activities, chemical instability, photo-instability and poor bioavailability limits its utilization as an effective therapeutic agent. Therefore, enhancing the bioavailability of curcumin may improve its therapeutic index for clinical setting. In the present study, we have conjugated curcumin with a biodegradable polymer Poly (D, L-lactic-co-glycolic acid) and evaluated its apoptotic potential in human colon carcinoma cells (HCT 116). The results show that curcumin-PLGA conjugate efficiently inhibits cell proliferation and cell survival in human colon carcinoma cells as compared to native curcumin. Additionally, curcumin conjugated with PLGA shows improved cellular uptake and exhibits controlled release at physiological pH as compared to native curcumin. The curcumin-PLGA conjugate efficiently activates the cascade of caspases and promotes intrinsic apoptotic signaling. Thus, the results suggest that conjugation potentiates the sustainability, anti-proliferative and apoptotic activity of curcumin. This approach could be a promising strategy to improve the therapeutic index of cancer therapy.
Exploiting Expressed Sequence Tag Databases for the Development and Characterization of Gene‐Derived Simple Sequence Repeat Markers in the Opium Poppy (Papaver somniferum L.) for Forensic Applications

Abstract: Simple sequence repeat (SSR) markers in the opium poppy (Papaver somniferum L.) were identified from an expressed sequence tag (EST) database comprised of 20,340 sequences. In total, 2780 SSR‐containing sequences were identified. The most frequent microsatellite had an AT/TA motif (37%). Twenty‐two opium poppy EST‐SSR markers were presently developed and polymorphisms of six markers (psom 2, 4, 12, 13, 17, and 22) were utilized in 135 individuals under narcotic control investigation. An average of three alleles per locus (range: 2–5 alleles) with a mean heterozygosity of 0.167 was detected. Six loci identified 29 unique profiles in 135 individuals. The EST‐SSR markers exhibited small degrees of genetic differentiation (fixation index = 0.727, p < 0.001). Other variable markers will be needed to facilitate the forensic identification of the opium poppy for future cases. To determine the potential for cross‐species amplification, six markers were tested in five Papaver genera species and two Eschscholzia genera. The psom 4 and psom 17 primer pair was transferable. This is the first study to report SSR markers of the opium poppy.
ℓP minimization for sparse vector reconstruction

In this paper we present a new technique for minimizing a class of nonconvex functions for solving the problem of under-determined systems of linear equations. The proposed technique is based on locally replacing the nonconvex objective function by a convex objective function. The main property of the utilized convex function is that it is minimized at a point that reduces the original concave function. The resulting algorithm is iterative and outperforms some previous algorithms that have been applied to the same problem.
Update on optimal use of omalizumab in management of asthma

Omalizumab is a humanized monoclonal anti-IgE antibody recently approved for the treatment of severe allergic asthma. This drug inhibits allergic responses by binding to serum IgE, thus preventing interaction with cellular IgE receptors. Omalizumab is also capable of downregulating the expression of high affinity IgE receptors on inflammatory cells, as well as the numbers of eosinophils in both blood and induced sputum. The clinical effects of omalizumab include improvements in respiratory symptoms and quality of life, paralleled by a reduction of asthma exacerbations, emergency room visits, and use of systemic corticosteroids and rescue bronchodilators. Omalizumab is relatively well-tolerated, and only rarely induces anaphylactic reactions. Therefore, this drug represents a valid option as add-on therapy for patients with severe persistent allergic asthma inadequately controlled by high doses of standard inhaled treatments.
A Survey of Security Challenges in Cognitive Radio Networks: Solutions and Future Research Directions

In this survey, we present a comprehensive list of major known security threats within a cognitive radio network (CRN) framework. We classify attack techniques based on the type of attacker, namely exogenous (external) attackers, intruding malicious nodes and greedy cognitive radios (CRs). We further discuss threats related to infrastructure-based CRNs as well as infrastructure-less networks. Besides the short-term effects of attacks over CRN performance, we also discuss the often ignored longer term behavioral changes that are enforced by such attacks via the learning capability of CRN. After elaborating on various attack strategies, we discuss potential solutions to combat those attacks. An overview of robust CR communications is also presented. We finally elaborate on future research directions pertinent to CRN security. We hope this survey paper can provide the insight and the roadmap for future research efforts in the emerging field of CRN security.
Deep Convolutional Networks on the Pitch Spiral For Music Instrument Recognition

Musical performance combines a wide range of pitches, nuances, and expressive techniques. Audio-based classification of musical instruments thus requires to build signal representations that are invariant to such transformations. This article investigates the construction of learned convolutional architectures for instrument recognition, given a limited amount of annotated training data. In this context, we benchmark three different weight sharing strategies for deep convolutional networks in the time-frequency domain: temporal kernels; time-frequency kernels; and a linear combination of time-frequency kernels which are one octave apart, akin to a Shepard pitch spiral. We provide an acoustical interpretation of these strategies within the source-filter framework of quasi-harmonic sounds with a fixed spectral envelope, which are archetypal of musical notes. The best classification accuracy is obtained by hybridizing all three convolutional layers into a single deep learning architecture.
Vascular lesions induced by renal nerve ablation as assessed by optical coherence tomography: pre- and post-procedural comparison with the Simplicity® catheter system and the EnligHTN™ multi-electrode renal denervation catheter

Aims Catheter-based renal nerve ablation (RNA) using radiofrequency energy is a novel treatment for drug-resistant essential hypertension. However, the local endothelial and vascular injury induced by RNA has not been characterized, although this importantly determines the long-term safety of the procedure. Optical coherence tomography (OCT) enables in vivo visualization of morphologic features with a high resolution of 10–15 µm. The objective of this study was to assess the morphological features of the endothelial and vascular injury induced by RNA using OCT. Methods and results In a prospective observational study, 32 renal arteries of patients with treatment-resistant hypertension underwent OCT before and after RNA. All pre- and post-procedural OCT pullbacks were evaluated regarding vascular changes such as vasospasm, oedema (notches), dissection, and thrombus formation. Thirty-two renal arteries were evaluated, in which automatic pullbacks were obtained before and after RNA. Vasospasm was observed more often after RNA then before the procedure (0 vs. 42%, P < 0.001). A significant decrease in mean renal artery diameter after RNA was documented both with the EnligHTN™ (4.69 ± 0.73 vs. 4.21 ± 0.87 mm; P < 0.001) and with the Simplicity® catheter (5.04 ± 0.66 vs. 4.57 ± 0.88 mm; P < 0.001). Endothelial-intimal oedema was noted in 96% of cases after RNA. The presence of thrombus formations was significantly higher after the RNA then before ablation (67 vs. 18%, P < 0.001). There was one evidence of arterial dissection after RNA with the Simplicity® catheter, while endothelial and intimal disruptions were noted in two patients with the EnligHTN™ catheter. Conclusion Here we show that diffuse renal artery constriction and local tissue damage at the ablation site with oedema and thrombus formation occur after RNA and that OCT visualizes vascular lesions not apparent on angiography. This suggests that dual antiplatelet therapy may be required during RNA.
COFFIN: A Computational Framework for Linear SVMs

In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering state-of-the-art results. Using the kernel trick, they work on several domains and even enable heterogeneous data fusion by concatenating feature spaces or multiple kernel learning. Unfortunately, they are not suited for truly large-scale applications since they suffer from the curse of supporting vectors, i.e., the speed of applying SVMs decays linearly with the number of support vectors. In this paper we develop COFFIN — a new training strategy for linear SVMs that effectively allows the use of on demand computed kernel feature spaces and virtual examples in the primal. With linear training and prediction effort this framework leverages SVM applications to truly large-scale problems: As an example, we train SVMs for human splice site recognition involving 50 million examples and sophisticated string kernels. Additionally, we learn an SVM based gender detector on 5 million examples on low-tech hardware and achieve beyond the state-of-the-art accuracies on both tasks. Source code, data sets and scripts are freely available from http://sonnenburgs.de/soeren/coffin.
Liquid‐based cytology improves productivity in cervical cytology screening

Objectives: The ThinPrep® test was introduced into our institution on a phased basis over 3 years between January 2002 and December 2004. This study set out to assess its effect on productivity (as measured by output of cases per medical scientist per day) during the changeover period. Numbers of high and low‐grade lesions and of unsatisfactory slides were also monitored.
Immunolocalization of Scaffoldin, a Trichohyalin‐Like Protein, in the Epidermis of the Chicken Embryo

Recent comparative genomic studies have identified a chicken gene that codes for a trichohyalin‐like protein rich in arginine and glutamic acid termed scaffoldin. Immunocytochemistry and immunoelectron microscopy show that this protein is predominantly localized in periderm granules, subcellular structures present in the periderm of the embryonic epidermis of chick scales, beak, claw, and in the sheath of developing and regenerating feathers. This suggests that scaffoldin contributes to the formation of periderm granules and to the soft cornification of the embryonic epidermis before the definitive epidermis is formed. Scaffoldin is absent from the definitive and adult epidermis generated underneath the periderm in scales and in inter‐follicular regions. Scaffoldin mixes with corneous beta‐proteins (beta‐keratins) synthesized in keratinocytes of the transitional layers formed beneath the periderm in the subunguis of the developing claws. Immunoreactivity for scaffoldin is absent in keratinocytes that accumulate corneous beta‐proteins such as those of scales, claws, and barbule‐barb cells of feathers. Corneous beta‐proteins represent the prevalent type of proteins present in adult epidermis of claws, scales, and feathers. These observations indicate that scaffoldin is a protein of transitional epidermal cells of the avian integument and might represent an important component of periderm granules. Anat Rec, 298:479–487, 2015. © 2014 Wiley Periodicals, Inc.
Favourite movie stars, their tobacco use in contemporary movies, and its association with adolescent smoking

OBJECTIVE To assess the relation between adolescents' favourite movie stars, the portrayal of tobacco use by those stars in contemporary motion pictures, and adolescent smoking. DESIGN AND SETTING 632 students (sixth to 12th grade, ages 10–19 years) from five rural New England public schools completed a voluntary, self administered survey in October 1996. The survey assessed tobacco use, other variables associated with adolescent smoking, and favourite movie star. In addition, tobacco use by 43 selected movie stars was measured in films between 1994 and 1996. OUTCOME MEASURES Students were categorised into an ordinal five point index (tobacco status) based on their smoking behaviour and their smoking susceptibility: non-susceptible never smokers, susceptible never smokers, non-current experimenters, current experimenters, and smokers. We determined the adjusted cumulative odds of having advanced smoking status based on the amount of on-screen tobacco use by their favourite film star. RESULTS Of the 43 stars, 65% used tobacco at least once, and 42% portrayed smoking as an essential character trait in one or more films. Stars who smoked more than twice in a film were considered smokers. For adolescents whose favourite stars smoked in only one film, the odds of being higher on the smoking index was 0.78 (95% confidence interval (CI) 0.53 to 1.15). For adolescents whose favourite stars smoked in two films, the odds of being higher on the smoking index was 1.5 (95% CI 1.01 to 2.32). For adolescents whose favourite stars smoked in three or more films (Leonardo DiCaprio, Sharon Stone, John Travolta), the odds of being higher on the smoking index was 3.1 (95% CI 1.34 to 7.12). Among never smokers (n = 281), those who chose stars who were smokers in three or more films were much more likely to have favourable attitudes toward smoking (adjusted odds ratio 16.2, 95% CI 2.3 to 112). CONCLUSIONS Adolescents who choose movie stars who use tobacco on-screen are significantly more likely to have an advanced smoking status and more favourable attitudes toward smoking than adolescents who choose non-smoking stars. This finding supports the proposition that the portrayal of tobacco use in contemporary motion pictures, particularly by stars who are admired by adolescents, contributes to adolescent smoking.
A Systems-Level Approach for Investigating Pseudomonas aeruginosa Biofilm Formation

Prevention of the initiation of biofilm formation is the most important step for combating biofilm-associated pathogens, as the ability of pathogens to resist antibiotics is enhanced 10 to 1000 times once biofilms are formed. Genes essential to bacterial growth in the planktonic state are potential targets to treat biofilm-associated pathogens. However, the biofilm formation capability of strains with mutations in these essential genes must be evaluated, since the pathogen might form a biofilm before it is eliminated. In order to address this issue, this work proposes a systems-level approach to quantifying the biofilm formation capability of mutants to determine target genes that are essential for bacterial metabolism in the planktonic state but do not induce biofilm formation in their mutants. The changes of fluxes through the reactions associated with the genes positively related to biofilm formation are used as soft sensors in the flux balance analysis to quantify the trend of biofilm formation upon the mutation of an essential gene. The essential genes whose mutants are predicted not to induce biofilm formation are regarded as gene targets. The proposed approach was applied to identify target genes to treat Pseudomonas aeruginosa infections. It is interesting to find that most essential gene mutants exhibit high potential to induce the biofilm formation while most non-essential gene mutants do not. Critically, we identified four essential genes, lysC, cysH, adk, and galU, that constitute gene targets to treat P. aeruginosa. They have been suggested by existing experimental data as potential drug targets for their crucial role in the survival or virulence of P. aeruginosa. It is also interesting to find that P. aeruginosa tends to survive the essential-gene mutation treatment by mainly enhancing fluxes through 8 metabolic reactions that regulate acetate metabolism, arginine metabolism, and glutamate metabolism.