Miracle-dz/UniFAR-FTUs huggingface dataset:
A Flexible POS Tagger Using an Automatically Acquired Language Model

We present an algorithm that automatically learns context constraints using statistical decision trees. We then use the acquired constraints in a flexible POS tagger. The tagger is able to use information of any degree: n-grams, automatically learned context constraints, linguistically motivated manually written constraints, etc. The sources and kinds of constraints are unrestricted, and the language model can be easily extended, improving the results. The tagger has been tested and evaluated on the WSJ corpus.
Monolingual and bilingual infants' attention to talking faces: evidence from eye-tracking and Bayesian modeling

Introduction A substantial amount of research from the last two decades suggests that infants' attention to the eyes and mouth regions of talking faces could be a supporting mechanism by which they acquire their native(s) language(s). Importantly, attentional strategies seem to be sensitive to three types of constraints: the properties of the stimulus, the infants' attentional control skills (which improve with age and brain maturation) and their previous linguistic and non-linguistic knowledge. The goal of the present paper is to present a probabilistic model to simulate infants' visual attention control to talking faces as a function of their language learning environment (monolingual vs. bilingual), attention maturation (i.e., age) and their increasing knowledge concerning the task at stake (detecting and learning to anticipate information displayed in the eyes or the mouth region of the speaker). Methods To test the model, we first considered experimental eye-tracking data from monolingual and bilingual infants (aged between 12 and 18 months; in part already published) exploring a face speaking in their native language. In each of these conditions, we compared the proportion of total looking time on each of the two areas of interest (eyes vs. mouth of the speaker). Results In line with previous studies, our experimental results show a strong bias for the mouth (over the eyes) region of the speaker, regardless of age. Furthermore, monolingual and bilingual infants appear to have different developmental trajectories, which is consistent with and extends previous results observed in the first year. Comparison of model simulations with experimental data shows that the model successfully captures patterns of visuo-attentional orientation through the three parameters that effectively modulate the simulated visuo-attentional behavior. Discussion We interpret parameter values, and find that they adequately reflect evolution of strength and speed of anticipatory learning; we further discuss their descriptive and explanatory power.
Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs

Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well known that the probability of a user clicking on a result is strongly biased toward documents presented higher in the result set irrespective of relevance. We introduce a simple method to modify the presentation of search results that provably gives relevance judgments that are unaffected by presentation bias under reasonable assumptions. We validate this property of the training data in interactive real world experiments. Finally, we show that using these unbiased relevance judgments learning methods can be guaranteed to converge to an ideal ranking given sufficient data.
Research on the Efficiency of China's Listed Commercial Banks from the Perspective of Risk Management

Based on the panel data of 36 listed commercial banks in my country from 2014 to 2018, this paper takes Loan Loss Reserves (LLR) and Non-performing Loans (NPL) as undesired output, analyzes the impact of risk management factors on the efficieney of China's listed commercial banks, and provides a comprehensive A comparative study on the efficiency of four types of banks: joint-stock commercial banks, city commercial banks and rural commercial banks, and the Bootstrap method is used to analyze the factors affecting bank efficiency.
Mitigation of Nonlinear Effects on WDM QAM Signals Enabled by Optical Phase Conjugation With Efficient Bandwidth Utilization

We present nonlinear impairment mitigation of wavelength division multiplexed signals, through optical phase conjugation (OPC). We conduct our experiments on a 400-km-long installed fiber link equipped with erbium-doped fiber amplifiers, with the OPC placed close to the middle of the link. Our OPC configuration realizes efficient reuse of the signal bandwidth, avoiding the loss of half of the spectral band typical of most phase conjugating schemes. We demonstrate the operation of the system using both 16- and 64-quadrature amplitude modulation (QAM) signals and report Q-factor improvements up to 0.5 and 2.5 dB for 16- and 64-QAM, respectively.
A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos

OBJECTIVE Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. MATERIALS AND METHODS The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit. edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. CONCLUSION Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable information, as well as intuitively and conveniently preview essential content of a single or a collection of videos.
Could the Length of the Alkyl Chain Affect the Photodynamic Activity of 5,10,15,20-Tetrakis(1-alkylpyridinium-4-yl)porphyrins?

Photodynamic therapy (PDT) is a minimally invasive treatment that uses the combination of a photosensitizing agent (PS) and light to selectively target solid tumors, as well as several non-neoplastic proliferating cell diseases. After systemic administration, PSs are activated by localized irradiation with visible light; in the presence of adequate concentrations of molecular oxygen, this causes the formation of reactive oxygen species (ROS) and subsequent tissue damage. In this study, two series of tetrakis(N-alkylpyridinium-4-yl)porphyrins were synthesized, differing in the presence or absence of a zinc ion in the tetrapyrrole nucleus, as well as in the N-alkyl chain length (from one to twelve carbon atoms). The compounds were chemically characterized, and their effect on cell viability was evaluated using a panel of three tumor cell lines to determine a possible relationship between photodynamic activity and Zn presence/alkyl chain length. The types of cell death mechanisms involved in the effect of the various PSs were also evaluated. The obtained results indicate that the most effective porphyrin is the Zn-porphyrin, with a pendant made up of eight carbon atoms (Zn-C8).
Distributed Robust Multicell Coordinated Beamforming With Imperfect CSI: An ADMM Approach

Multicell coordinated beamforming (MCBF), where multiple base stations (BSs) collaborate with each other in the beamforming design for mitigating the intercell interference (ICI), has been a subject drawing great attention recently. Most MCBF designs assume perfect channel state information (CSI) of mobile stations (MSs); however CSI errors are inevitable at the BSs in practice. Assuming elliptically bounded CSI errors, this paper studies the robust MCBF design problem that minimizes the weighted sum power of BSs subject to worst-case signal-to-interference-plus-noise ratio (SINR) constraints on the MSs. Our goal is to devise a distributed optimization method to obtain the worst-case robust beamforming solutions in a decentralized fashion with only local CSI used at each BS and limited backhaul information exchange between BSs. However, the considered problem is difficult to handle even in the centralized form. We first propose an efficient approximation method for solving the nonconvex centralized problem, using semidefinite relaxation (SDR), an approximation technique based on convex optimization. Then a distributed robust MCBF algorithm is further proposed, using a distributed convex optimization technique known as alternating direction method of multipliers (ADMM). We analytically show the convergence of the proposed distributed robust MCBF algorithm to the optimal centralized solution. We also extend the worst-case robust beamforming design as well as its decentralized implementation method to a fully coordinated scenario. Simulation results are presented to examine the effectiveness of the proposed SDR method and the distributed robust MCBF algorithm.
Structural and Functional Insights into Small, Glutamine-Rich, Tetratricopeptide Repeat Protein Alpha

The small glutamine-rich, tetratricopeptide repeat-containing protein alpha (SGTA) is an emerging player in the quality control of secretory and membrane proteins mislocalized to the cytosol, with established roles in tail-anchored (TA) membrane protein biogenesis. SGTA consists of three structural domains with individual functions, an N-terminal dimerization domain that assists protein sorting pathways, a central tetratricopeptide repeat (TPR) domain that mediates interactions with heat-shock proteins, proteasomal, and hormonal receptors, and viral proteins, and a C-terminal glutamine rich region that binds hydrophobic substrates. SGTA has been linked to viral lifecycles and hormone receptor signaling, with implications in the pathogenesis of various disease states. Thus far, a range of biophysical techniques have been employed to characterize SGTA structure in some detail, and to investigate its interactions with binding partners in different biological contexts. A complete description of SGTA structure, together with further investigation into its function as a co-chaperone involved quality control, could provide us with useful insights into its role in maintaining cellular proteostasis, and broaden our understanding of mechanisms underlying associated pathologies. This review describes how some structural features of SGTA have been elucidated, and what this has uncovered about its cellular functions. A brief background on the structure and function of SGTA is given, highlighting its importance to biomedicine and related fields. The current level of knowledge and what remains to be understood about the structure and function of SGTA is summarized, discussing the potential direction of future research.
Anomalously High Cretaceous Paleobrine Temperatures: Hothouse, Hydrothermal or Solar Heating?

Elevated surface paleobrine temperatures (average 85.6 °C) are reported here from Cretaceous marine halites in the Maha Sarakham Formation, Khorat Plateau, Thailand. Fluid inclusions in primary subaqueous “chevron” and “cumulate” halites associated with potash salts contain daughter crystals of sylvite (KCl) and carnallite (MgCl2·KCl·6H2O). Petrographic textures demonstrate that these fluid inclusions were trapped from the warm brines in which the halite crystallized. Later cooling produced supersaturated conditions leading to the precipitation of sylvite and carnallite daughter crystals within fluid inclusions. Dissolution temperatures of daughter crystals in fluid inclusions from the same halite bed vary over a large range (57.9 °C to 117.2 °C), suggesting that halite grew at different temperatures within and at the bottom of the water column. Consistency of daughter crystal dissolution temperatures within fluid inclusion bands and the absence of vapor bubbles at room temperature demonstrate that fluid inclusions have not stretched or leaked. Daughter crystal dissolution temperatures are reproducible to within 0.1 °C to 10.2 °C (average of 1.8 °C), and thus faithfully document paleobrine conditions. Microcrystalline hematite incorporated within halite crystals also indicate high paleobrine temperatures. We conclude that halite crystallized from warm brines rich in K-Mg-Na-Cl; sylvite and carnallite daughter crystals were nucleated during cooling of the warm brines sometime after deposition. Hothouse, hydrothermal, and solar-heating hypotheses are compared to explain the anomalously high surface paleobrine temperatures. Solar radiation stored in shallow density stratified brines is the most plausible explanation for the observed paleobrine temperatures and the progressively higher temperatures downward through the paleobrine column. The solar-heating hypothesis may also explain high paleobrine temperatures documented from fluid inclusions in other ancient halites.
Adaptive Highlighting Of Links To Assist Surfing On The Internet

Gathering of novel information from the WWW constitutes a real challenge for artificial intelligence (AI) methods. Large search engines do not offer a satisfactory solution, their indexing cycle is long and they may offer a huge amount of documents. An AI-based assistant agent is studied here, which sorts the availabe links by their estimated value for the user. By using this link-list the best links could be highlighted in the browser, making the user's choices easier during surfing. The method makes use of (i) "experts", i.e. pre-trained text classifiers, forming the long-term memory of the system, (ii) relative values of experts and value estimation of documents based on recent choices of the user. Value estimation adapts fast and forms the short-term memory of the system. All experiments show that surfing based filtering can efficiently highlight 10%–20% of the documents in about five steps, or less.
Efficient distributed random walks with applications

We focus on the problem of performing random walks efficiently in a distributed network. Given bandwidth constraints, the goal is to minimize the number of rounds required to obtain a random walk sample. We first present a fast sublinear time distributed algorithm for performing random walks whose time complexity is sublinear in the length of the walk. Our algorithm performs a random walk of length l in Õ(√l D) rounds (with high probability) on an undirected network, where D is the diameter of the network. This improves over the previous best algorithm that ran in Õ(l2/3D1/3) rounds (Das Sarma et al., PODC 2009). We further extend our algorithms to efficiently perform k independent random walks in Õ(√kl D + k) rounds. We then show that there is a fundamental difficulty in improving the dependence on l any further by proving a lower bound of Ω(√l/log l + D) under a general model of distributed random walk algorithms. Our random walk algorithms are useful in speeding up distributed algorithms for a variety of applications that use random walks as a subroutine. We present two main applications. First, we give a fast distributed algorithm for computing a random spanning tree (RST) in an arbitrary (undirected) network which runs in Õ(√mD) rounds (with high probability; here m is the number of edges). Our second application is a fast decentralized algorithm for estimating mixing time and related parameters of the underlying network. Our algorithm is fully decentralized and can serve as a building block in the design of topologically-aware networks.
Pseudo-random Puncturing: A Technique to Lower the Error Floor of Turbo Codes

It has been observed that particular rate-1/2 partially systematic parallel concatenated convolutional codes (PCCCs) can achieve a lower error floor than that of their rate-1/3 parent codes. Nevertheless, good puncturing patterns can only be identified by means of an exhaustive search, whilst convergence towards low bit error probabilities can be problematic when the systematic output of a rate-1/2 partially systematic PCCC is heavily punctured. In this paper, we present and study a family of rate-1/2 partially systematic PCCCs, which we call pseudo-randomly punctured codes. We evaluate their bit error rate performance and we show that they always yield a lower error floor than that of their rate-1/3 parent codes. Furthermore, we compare analytic results to simulations and we demonstrate that their performance converges towards the error floor region, owning to the moderate puncturing of their systematic output. Consequently, we propose pseudo-random puncturing as a means of improving the bandwidth efficiency of a PCCC and simultaneously lowering its error floor.
The effect of translocation of microbenthic communities in a polluted lowland stream

Transloeation of eommunities from unpolluted to polluted waters and viee versa might allow the srudy of stress and reeovery of assemblages and thus provide information on its resistanee and resilienee to changes. The use of biologieal eommunities as indieators of water quality and its ehanges ean include taxonomie deseriptors (e.g. diversity index, taxa riehness, speeies indieator) and non-taxonomie measures (e.g. biomass, ehlorophyll x unit area) (HILL et al. 2000). Transloeation of mierobenthie eommunities developed on artifieial substrates has been seareely applied. IVORRA I CASTELLÀ (2000) analysed the strueture an d funetion o f biofilms developing in rivers under different degrees of meta! stress. The objeetive of this srudy was to analyse the ehanges in biofilm development in three si tes of the Don Carlos Stream, a small stream that runs aeross a built-up area of the Pampean plain. The strueture, speeifie eomposition and ehanges in biomass were tested for a mierobenthie eommunity exposed to the outflows eoming from a textile faetory and sewage. For this purpose, experiments on transloeation of the mierobenthie eommunity were earried out.
THE IMPACT OF ISLAMIC WORK ETHICS, ATTITUDE, AND HEDONIC VALUES ON THE INTENTION TO ESTABLISH SUSTAINABLE ENTREPRENEURSHIP AMONG MUSLIM STUDENTS IN JAVA

Purpose: This research examines Islamic Ethics Work, Hedonic Values, and Attitudes toward the Intention to Establish Sustainable Entrepreneurship. Design/methodology/approach: The research method used is quantitative with a conclusive research design. The primary data used is obtained through a questionnaire distributed on the internet, with the criteria of Muslim students. A total of 210 respondents were gathered. This study employs the SEM-PLS data analysis model. Findings: The results show that Islamic Ethics Work has a positive direct influence on Attitude, while Hedonic Values do not directly impact Attitude. Furthermore, the Islamic Ethics Work variable does not directly impact the Intention to Establish Sustainable Entrepreneurship. In contrast, Attitude has a positive influence, and Hedonic Values have a negative influence. Islamic Ethics Work positively influences the Intention to Establish Sustainable Entrepreneurship through Attitude. Meanwhile, Hedonic Values have little impact on the Intention to Establish Sustainable Entrepreneurship through Attitude. Research implications: The results of this study can have implications for developing entrepreneurship courses in higher education by incorporating Islamic Ethics Work to provide opportunities for students to adopt a sustainable entrepreneurship approach and reduce hedonism.
Advances in Interpretation of Geological Processes: Refinement of Multi-scale Data and Integration in Numerical Modelling

Iterative comparison of analytical results and natural observations with predictions of numerical models improves interpretation of geological processes. Further refinements derive from wide-angle comparison of results from various scales of study. In this volume, advances from field, laboratory and modelling approaches to tectonic evolution – from the lithosphere to the rock scale – are compared. Constructive use is made of apparently discrepant or non-consistent results from analytical or methodological approaches in processing field or laboratory data, P–T estimates, absolute or relative age determinations of tectonic events, tectonic unit size in crustal scale deformation, grain-scale deformation processes, various modelling approaches, and numerical techniques. Advances in geodynamic modelling critically depend on new insights into grain- and subgrain-scale deformation processes. Conversely, quantitative models help to identify which rheological laws and parameters exert the strongest control on multi-scale deformation up to lithosphere and upper mantle scale.
Unsupervised Language Acquisition: Theory and Practice

In this thesis I present various algorithms for the unsupervised machine learning of aspects of natural languages using a variety of statistical models. The scientific object of the work is to examine the validity of the so-called Argument from the Poverty of the Stimulus advanced in favour of the proposition that humans have language-specific innate knowledge. I start by examining an a priori argument based on Gold's theorem, that purports to prove that natural languages cannot be learned, and some formal issues related to the choice of statistical grammars rather than symbolic grammars. I present three novel algorithms for learning various parts of natural languages: first, an algorithm for the induction of syntactic categories from unlabelled text using distributional information, that can deal with ambiguous and rare words; secondly, a set of algorithms for learning morphological processes in a variety of languages, including languages such as Arabic with non-concatenative morphology; thirdly an algorithm for the unsupervised induction of a context-free grammar from tagged text. I carefully examine the interaction between the various components, and show how these algorithms can form the basis for a empiricist model of language acquisition. I therefore conclude that the Argument from the Poverty of the Stimulus is unsupported by the evidence.