Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-label learning with millions of labels: recommending advertiser bid phrases for web pages

Recommending phrases from web pages for advertisers to bid on against search engine queries is an important research problem with direct commercial impact. Most approaches have found it infeasible to determine the relevance of all possible queries to a given ad landing page and have focussed on making recommendations from a small set of phrases extracted (and expanded) from the page using NLP and ranking based techniques. In this paper, we eschew this paradigm, and demonstrate that it is possible to efficiently predict the relevant subset of queries from a large set of monetizable ones by posing the problem as a multi-label learning task with each query being represented by a separate label. We develop Multi-label Random Forests to tackle problems with millions of labels. Our proposed classifier has prediction costs that are logarithmic in the number of labels and can make predictions in a few milliseconds using 10 Gb of RAM. We demonstrate that it is possible to generate training data for our classifier automatically from click logs without any human annotation or intervention. We train our classifier on tens of millions of labels, features and training points in less than two days on a thousand node cluster. We develop a sparse semi-supervised multi-label learning formulation to deal with training set biases and noisy labels harvested automatically from the click logs. This formulation is used to infer a belief in the state of each label for each training ad and the random forest classifier is extended to train on these beliefs rather than the given labels. Experiments reveal significant gains over ranking and NLP based techniques on a large test set of 5 million ads using multiple metrics.
Demodulation of Amplitude Modulated Noise: A Mathematical Evaluation of a Demodulator for Pathological Tremor EMG's

A mathematical description is given of amplitude modulated noise, simulating EMG signals of pathological tremors, and its demodulation into a tremor signal by means of a fuli wave rectifier. In this description these signals are considered in the frequency domain in the form of power spectra. The mathematically derived formulas are compared with the results of an experimental setup using a demodulator designed for use in clinical practice. The purpose of the experiments was to determine the signal-to-noise ratio of the tremor signal with respect to the demodulation noise, the latter being an inevitable consequence of demodulating the amplitude modulated carrying noise. The theoretically derived data are in acceptable agreement with the experimental results obtained in this way. As a result of the theoretical approach to the amplitude modulated noise, the signal-to-noise ratio of the demodulated signal is proportional to the bandwidth of the carrying noise of the amplitude modulation, and, for small modulation depths, is proportional to the square of the modulation depth.
Nonlinear Quantum Dynamics in Superconducting NISQ Processors

A recently proposed variational quantum algorithm has expanded the horizon of variational quantum computing to nonlinear physics and fluid dynamics. In this work, we employ this algorithm to find the ground state of the nonlinear Schr\"{o}dinger equation with a quadratic potential and implement it on the cloud superconducting quantum processors. We analyze the expressivity of real-amplitude ansatz to capture the ground state of the nonlinear system across various interaction regimes characterized by varying strengths of nonlinearity. Our investigation reveals that although quantum hardware noise impairs the evaluation of the energy cost function, small instances of the problem consistently converge to the ground state. We implement a variety of problem instances on IBM Q devices and report analogous discrepancies in the energy cost function evaluation attributable to quantum hardware noise. The latter are absent in the state fidelity estimation. Our comprehensive analysis offers valuable insights into the practical implementation and advancement of the variational algorithms for nonlinear quantum dynamics.
Targeting of mTOR catalytic site inhibits multiple steps of the HIV-1 lifecycle and suppresses HIV-1 viremia in humanized mice

Significance Most HIV antiretrovirals target viral proteins. Unfortunately, HIV mutates under drug pressure, which can lead to drug resistance. Targeting cellular proteins that HIV necessitates in its lifecycle may help overcome HIV drug resistance because cellular proteins have lower mutations rates than do HIV proteins. Mammalian target of rapamycin (mTOR) is a cellular kinase that forms two complexes (mTORC-1 and -2), regulating protein translation and transduction signaling. We demonstrate that dual targeting of mTORC-1/2 with the catalytic inhibitor INK128 blocks HIV by interfering with entry and with transcription (basal and induced). Importantly, INK128 suppressed HIV in a preclinical animal model, suggesting that mTORC-1/2 catalytic inhibitors may help control HIV in patients, particularly in those with drug-resistant HIV. HIV necessitates host factors for successful completion of its life cycle. Mammalian target of rapamycin (mTOR) is a conserved serine/threonine kinase that forms two complexes, mTORC1 and mTORC2. Rapamycin is an allosteric inhibitor of mTOR that selectively inhibits mTORC1. Rapamycin interferes with viral entry of CCR5 (R5)-tropic HIV and with basal transcription of the HIV LTR, potently inhibiting replication of R5 HIV but not CXCR4 (X4)-tropic HIV in primary cells. The recently developed ATP-competitive mTOR kinase inhibitors (TOR-KIs) inhibit both mTORC1 and mTORC2. Using INK128 as a prototype TOR-KI, we demonstrate potent inhibition of both R5 and X4 HIV in primary lymphocytes (EC50 < 50 nM), in the absence of toxicity. INK128 inhibited R5 HIV entry by reducing CCR5 levels. INK128 also inhibited both basal and induced transcription of HIV genes, consistent with inhibition of mTORC2, whose activity is critical for phosphorylation of PKC isoforms and, in turn, induction of NF-κB. INK128 enhanced the antiviral potency of the CCR5 antagonist maraviroc, and had favorable antiviral interactions with HIV inhibitors of reverse transcriptase, integrase and protease. In humanized mice, INK128 decreased plasma HIV RNA by >2 log10 units and partially restored CD4/CD8 cell ratios. Targeting of cellular mTOR with INK128 (and perhaps others TOR-KIs) provides a potential strategy to inhibit HIV, especially in patients with drug resistant HIV strains.
Towards an Entity-based Recognition of Textual Entailment

This paper describes the experiments developed and the results obtained in the participation of UNED in the Fourth Recognising Textual Entailment (RTE) Challenge. This year we decided to change the scope of our work with the aim of beginning to develop a system that performs a deeper analysis than the techniques used in the last editions. This participation has been the first step in the development of our new system.
Ieee Computer Graphics and Applications the Language of Comics Generating Comics from 3d Interactive Computer Graphics

S toryboards and scripts use comic-like frames to narrate stories. Such displays can also summarize the main events in a film, video, or virtual world interaction creating a more succinct representation of the original graphics. 1 Our goal is to create a sequence of comic-like images summarizing the main events in a virtual world environment and present them in a coherent, concise, and visually pleasing manner. The transformation from dynamic graphics to static nonpho-torealistic images reduces the complexity of both the temporal and the spatial domains. Hence, the challenge is twofold: ■ In the temporal domain, we want to automatically detect and choose the most important or most interesting (as specified by the viewer) events in the interaction. ■ In the spatial domain, we want to depict these events with one or more images that will convey their meaning faithfully. This includes choosing the points in time to portray the event, selecting camera parameters to create descriptive images, choosing a rendering style, and arranging the image layout. Traditionally in comics, selecting or producing image and text that communicate the right message is the artist's job. Indeed, we're still far from an artist's capability and expressiveness. However, our system can extract a sequence of important events from a continuous temporal story line and convert the events into a graphical representation automatically. Our automatic end-to-end system transforms interactions in 3D graphics into a succinct representation depicted by comics. The system is based on principles of comic theory and can produce different comic sequences on the basis of user-provided semantic parameters, such as viewpoint and level-of-details using the same reduction principle in both the temporal and the spatial domains. Figure 1 (on the next page) gives an overview of our system. The system starts with a log of events based on player interactions inside a 3D virtual world and progresses through several steps to generate a series of comic strips highlighting important events from the log. Comics have the reputation of being somewhat childish , with images that are often deliberately simplified and nonphotorealistic. Still, comics can invoke strong emotional reactions, create identification, and effectively convey a story in an appealing manner. In fact, symbolism and abstraction in comics can promote identification because symbolic figures can represent anyone or anywhere, whereas realistic images resemble specific people or places. A primary principle of comics is the translation of time into space. Comic frames are …
Evaluating persuasion-enhancing techniques from a resource-matching perspective

This article examines how two ad execution characteristics intended to heighten persuasion can influence the resources required to process an ad under high and low motivation conditions. These ad execution characteristics include (1) whether the ad copy is narrative or factual and (2) whether the ad layout either physically integrates or separates the ad picture and ad claims. Results reveal that under low motivation, persuasion is unaffected by these two execution characteristics but instead is affected by heuristic aspects of the ad photo. Under high motivations whether persuasion is heightened or undermined appears to depend on the extent to which the ad execution characteristics render the resources needed to process the ad equal to, in excess of, or inadequate compared with those that motivated viewers have available for processing the ad. Copyright 1997 by the University of Chicago.
Cross-saturation effects on position estimation using BEMF methods in PMAC machines

Under load and in the presence of saturation in particular, PMAC machines exhibit the magnetic axis shift from the rotor position, which in turn causes an error in a control algorithm that uses conventional rotor position estimation. This error is particularly pronounced in the shaft-sensorless position estimation based on the back EMF measurements since most conventional algorithms completely ignore the existence of the cross-saturation i.e. cross-coupling inductance Lqd is assumed to be zero. The described error is a function of operating point and local saturation levels so it is intuative to conclude that it will also be impacted by various machine parameters such as; rotor geometry, winding configuration and so on. In this paper we conduct a comparative study to show the influence of the various PMAC machine topologies on the magnitude of the described error, while utilizing an existing back EMF based position sensorless controller. The impact of the error on the machine performance is also examined. Four major types of PMAC machines are considered; surface and interior permanent magnet machines with concentrated and distributed winding configurations. First, we will use a non-linear mode to analytically characterize this error for an arbitrary PMAC machine and use the FEA to characterize the error for the specific IPM and SPM machines with distributed and concentrated winding topologies. Finally, degradation in the torque-speed capability and efficiency over the entire operating range of the machines due to the error will be also presented.
Critical Role for Heat Shock Protein 20 (HSP20) in Migration of Malarial Sporozoites*

Background: Small heat shock proteins have been associated with microfilament regulation. Results: Ablation of HSP20 impairs the speed, directionality, and adhesion of Plasmodium sporozoites. Conclusion: HSP20 is a key factor for locomotion and infection of the malaria parasite. Significance: This study is the first genetic evidence for a role of a small heat shock protein in cellular motility. Plasmodium sporozoites, single cell eukaryotic pathogens, use their own actin/myosin-based motor machinery for life cycle progression, which includes forward locomotion, penetration of cellular barriers, and invasion of target cells. To display fast gliding motility, the parasite uses a high turnover of actin polymerization and adhesion sites. Paradoxically, only a few classic actin regulatory proteins appear to be encoded in the Plasmodium genome. Small heat shock proteins have been associated with cytoskeleton modulation in various biological processes. In this study, we identify HSP20 as a novel player in Plasmodium motility and provide molecular genetics evidence for a critical role of a small heat shock protein in cell traction and motility. We demonstrate that HSP20 ablation profoundly affects sporozoite-substrate adhesion, which translates into aberrant speed and directionality in vitro. Loss of HSP20 function impairs migration in the host, an important sporozoite trait required to find a blood vessel and reach the liver after being deposited in the skin by the mosquito. Our study also shows that fast locomotion of sporozoites is crucial during natural malaria transmission.
Newell and Simon's Logic Theorist: Historical Background and Impact on Cognitive Modeling

Fifty years ago, Newell and Simon (1956) invented a “thinking machine” called the Logic Theorist. The Logic Theorist was a computer program that could prove theorems in symbolic logic from Whitehead and Russell's Principia Mathematica. This was perhaps the first working program that simulated some aspects of peoples' ability to solve complex problems. The Logic Theorist and other cognitive simulations developed by Newell and Simon in the late 1950s had a large impact on the newly developing field of information-processing (or cognitive) psychology. Many of the novel ideas about mental representation and problem solving instantiated in the Logic Theorist are still a central part of the theory of cognitive psychology, and are still used in modeling the complex tasks studied in human factors psychology. This paper presents some of the theoretical precursors of the Logic Theorist, describes the principles and implementation of the program, and discusses its immediate and long-term impacts.
Probing the putative 7 nAChR/NMDAR complex in human and murine cortex and hippocampus: Different degrees of complex formation in healthy and Alzheimer brain tissue

α 7 nicotinic acetylcholine receptors (nAChRs) and N -methyl-D-aspartate receptors (NMDARs) are key mediators of central cholinergic and glutamatergic neurotransmission, respectively. In addition to numerous well-established functional interactions between α 7 nAChRs and NMDARs, the two receptors have been proposed to form a multimeric complex, and in the present study we have investigated this putative α 7 nAChR/NMDAR assembly in human and murine brain tissues. By α -bungarotoxin (BGT) affinity purification, α 7 and NMDAR subunits were co-purified from human and murine cortical and hippocampal homogenates, substantiating the notion that the receptors are parts of a multimeric complex in the human and rodent brain. Interestingly, the ratios between GluN1 and α 7 levels in BGT pull-downs from cortical homogenates from Alzheimer’s disease (AD) brains were significantly lower than those in pull-downs from non-AD controls, indicating a reduced degree of α 7 nAChR/NMDAR complex formation in the diseased tissue. A similar difference in GluN1/ α 7 ratios was observed between pull-downs
SELDI‐TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma

Proteomic profiling of serum is an emerging technique to identify new biomarkers indicative of disease severity and progression. The objective of our study was to assess the use of surface‐enhanced laser desorption/ionization time‐of‐flight mass spectrometry (SELDI‐TOF MS) to identify multiple serum protein biomarkers for detection of liver disease progression to hepatocellular carcinoma (HCC). A cohort of 170 serum samples obtained from subjects in the United States with no liver disease (n = 39), liver diseases not associated with cirrhosis (n = 36), cirrhosis (n = 38), or HCC (n = 57) were applied to metal affinity protein chips for protein profiling by SELDI‐TOF MS. Across the four test groups, 38 differentially expressed proteins were used to generate multiple decision classification trees to distinguish the known disease states. Analysis of a subset of samples with only hepatitis C virus (HCV)‐related disease was emphasized. The serum protein profiles of control patients were readily distinguished from each HCV‐associated disease state. Two‐way comparisons of chronic hepatitis C, HCV cirrhosis, or HCV‐HCC versus healthy had a sensitivity/specificity range of 74% to 95%. For distinguishing chronic HCV from HCV‐HCC, a sensitivity of 61% and a specificity of 76% were obtained. However, when the values of known serum markers α fetoprotein, des‐gamma carboxyprothrombin, and GP73 were combined with the SELDI peak values, the sensitivity and specifity improved to 75% and 92%, respectively. In conclusion, SELDI‐TOF MS serum profiling is able to distinguish HCC from liver disease before cirrhosis as well as cirrhosis, especially in patients with HCV infection compared with other etiologies. (HEPATOLOGY 2005;41:634–642.)
Discrepancy between inner and overt speech: Implications for post-stroke aphasia and normal language processing

Background: Patients with aphasia often complain that there is a poor correlation between the words they think (inner speech) and the words they say (overt speech). Aims: This study tried to characterise the relation between inner speech and overt speech in post-stroke aphasia. Methods & Procedures: We tested language abilities, speech apraxia, and performance on inner speech tasks, including homophone and rhyme judgements, of 27 patients with chronic post-stroke aphasia. Outcomes & Results: The patients with aphasia were distributed across the entire spectrum of abilities related to both inner and overt speech. For most patients, performance levels of inner and overt speech were similar. However, some patients had relatively better-preserved inner speech with a marked deficit in overt speech, while in others the opposite pattern was observed. Conclusions: The results are discussed within the framework of current models of language, and their implications for language therapy and aphasia diagnosis are outlined.
A Bio-Inspired Method for the Constrained Shortest Path Problem

The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method.
Photodynamic Effect of Hypericin on the Conformation and Catalytic Activity of Hemoglobin

Hypericin, extracted from H. perforatum, can induce the generation of reactive oxygen species by visible light irradiation, which may consequently induce the conformational change of hemoglobin. We have not only employed UV-vis spectroscopy to observe the changes of UV-vis spectra of the protein, which reveals the conformational changes of the protein, but also employed electrochemical method to obtain its enhanced peroxidase activity. The photodynamic effect of hypericin on the conformation and catalytic activity of the protein has also been proven to be strongly dependent on the irradiation time, the hypericin concentration and the presence of oxygen. This work is beneficial not only to the fabrication of more sensitive hydrogen peroxide biosensor, but also to the guidance of the usage of this medicinal herb molecule, since the conformational change of the protein and the enhanced peroxidase can be easily obtained only by visible light irradiation on hypericin, the process of which is so common to happen.
Greedy algorithms for on-line set-covering and related problems

We study the following on-line model for set-covering: elements of a ground set of size n arrive one-by-one and with any such element ci, arrives also the name of some set Si0 containing ci and covering the most of the uncovered ground set-elements (obviously, these elements have not been yet revealed). For this model we analyze a simple greedy algorithm consisting of taking Si0 into the cover, only if ci is not already covered. We prove that the competitive ratio of this algorithm is √n and that it is asymptotically optimal for the model dealt, since no on-line algorithm can do better than √n/2. We next show that this model can also be used for solving minimum dominating set with competitive ratio bounded above by the square root of the size of the input graph. We finally deal with the maximum budget saving problem. Here, an initial budget is allotted that is destined to cover the cost of an algorithm for solving set-covering. The objective is to maximize the savings on the initial budget. We show that when this budget is at least equal to √n times the size of the optimal (off-line) solution of the instance under consideration, then the natural greedy off-line algorithm is asymptotically optimal.
On the relationship between morphological and phonological awareness: Effects of training in kindergarten and in first-grade reading

This study examined the relationship between phonological and morphological awareness in kindergarten, and their respective influence on learning to read in first grade, through an experimental training design with three groups of children. One experimental group received phonological awareness training while the other received morphological awareness training. The control group did not receive any training. Both training sessions were efficient since the largest pre- and post-test improvements were observed in the trained domains. Reciprocal influence analysis indicated that morphological awareness improved phonological sensitivity, but not the explicit manipulation of phonemes. In addition, phonological awareness training helped children to segment morphemes, but not to derive complex words. Thus, while some processes are shared by both metalinguistic domains, each domain appears to have its own specificity and may develop independently, at least partly. Even though morphological awareness training was found to be efficient at the kindergarten level, no clear impact on reading was found at the first-grade level, while phonological training displayed a clear positive effect on reading.