Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Adaptive Mesh Simplification Method Using Vertex Clustering with Topology-and-Detail Preserving

A new adaptive mesh simplification method based on vertex clustering is presented in this paper, which can preserve the model topology and subtle geometric features better than traditional vertex-clustering methods. Guided by the normal vectors corresponding to all vertices, the proposed method adopts a binary tree structure to split the bounding box of the inputting model adaptively. This subdivision does not stop unless all triangles in the cells are considered to be flat enough or the cell is small enough. Then the representative vertex for each cell is calculated according to the quadric error metric. Experimental results have demonstrated that the presented method is fast and can guarantee displayable results with good quality. In addition, it also addresses the problem of view-dependent simplification.
The transition to adulthood from care as a struggle for recognition

This article explores young people's experiences in the transition to adulthood from child welfare services and how Honneth's theory of recognition can be useful as an analytical tool to help us understand these experiences. The underpinning empirical research consisted of interviews and focus groups with 43 adolescents who had been in contact with Norwegian child welfare services. Three themes emerged as particularly important: having good relationships to caring adults, being listened to and able to influence their own lives, and receiving support and encouragement. The research shows how young people's difficulties in leaving care can be understood as experiences of misrecognition and points to some ways in which these can be overcome.
Microstructure Effects on Daily Return Volatility in Financial Markets

We simulate a series of daily returns from intraday price movements initiated by microstructure elements. Signiﬁcant evidence is found that daily returns and daily return volatility exhibit ﬁrst order autocorrelation, but trading volume and daily return volatility are not correlated, while intraday volatility is. We also consider GARCH eﬀects in daily return series and show that estimates using daily returns are biased from the inﬂuence of the level of prices. Using daily price changes instead, we ﬁnd evidence of a signiﬁcant GARCH component. These results suggest that microstructure elements have a considerable inﬂuence on the return generating process.
Hypoxia transcriptionally induces macrophage‐inflammatory protein‐3α/CCL‐20 in primary human mononuclear phagocytes through nuclear factor (NF)‐κB

Hypoxia, a condition of low oxygen tension, occurring in many pathological processes, modifies the mononuclear phagocyte transcriptional profile. Here, we demonstrate hypoxic up‐regulation of the CCL20 chemokine in primary human monocytes (Mn) and macrophages. mRNA induction was paralleled by protein secretion and dependent on gene transcription activation. Functional studies of the CCL20 promoter using a series of 5′‐deleted and mutated reporter constructs demonstrated the requirement for the NF‐κB‐binding site located at position –92/–82 for gene transactivation by hypoxia, as 1) transcription was abrogated by a 3‐bp mutation of the NF‐κB motif; 2) three copies of the wild‐type NF‐κB‐binding site conferred hypoxia responsiveness to a minimal heterologous promoter; and 3) hypoxia increased specific NF‐κB binding to this sequence. Furthermore, we provide evidence of the specific role of a single NF‐κB family member, p50, in mediating CCL20 gene transcription in hypoxic Mn. p50 homodimers were the only detectable NF‐κB complexes binding the cognate κB site on the CCL20 promoter upon hypoxia exposure, and NF‐κBp50 knockdown by lentiviral‐mediated short hairpin RNA interference resulted in complete binding inhibition. NF‐κBp50 overexpression in transient cotransfection studies promoted CCL20 gene transactivation, which was abrogated by mutation of the –92/–82 κB site. Moreover, nuclear expression of the other NF‐κB family members was inhibited in hypoxic Mn. In conclusion, this study characterizes a previously unrecognized role for hypoxia as a transcriptional inducer of CCL20 in human mononuclear phagocytes and highlights the importance of the NF‐κB pathway in mediating this response, with potential implications for inflammatory disease and cancer pathogenesis.
Signal Transduction and the Control of Gene Expression

More than 2000 transcription factors are encoded in the human genome. Such proteins have often been classified according to common structural elements. But because transcription factors evolved in the service of biologic function, we propose an alternative grouping of eukaryotic transcription factors on the basis of characteristics that describe their roles within cellular regulatory circuits.
1 Pricing Freight Rate Options

In this paper we set up the theoretical framework for the valuation of the Asian-style options traded in the freight derivatives market. Assuming lognormal spot freight dynamics, we show that Forward Freight Agreements (FFA) are also lognormal prior to the settlement period, but that this lognormality subsequently breaks down. We suggest approximate dynamics in the settlement period for the FFA that leads to closed-form option pricing formulas for Asian call and put options written on the spot freight rate indices in the Black (1976) framework. In a Monte Carlo experiment we show that our formula gives very accurate prices, in particular for forward-starting freight options.
Translation Selection by Combining Multiple Measures for Sense Disambiguation and Word Selection

Translation selection is a process to select, from a set of target language words corresponding to a source language word, the most appropriate one that conveys the correct sense of a source word and makes the target language sentence more natural. In this paper, we propose a hybrid method for translation selection that exploits a bilingual dictionary and a target language corpus. Based on the 'word-to-sense and sense-to-word' relationship between a source word and its translations, our method selects translation through two levels: sense disambiguation of a source word and selection of a target word. For translation selection, we introduce three measures: sense preference and sense probability for sense disambiguation, and word probability for word selection. The first one is based on knowledge from a bilingual dictionary, and the others are calculated using statistics from a target language corpus. We evaluated our method and results showed that our method selects more appropriate target words with knowledge extracted from easily obtainable resources.
Sustained In Vivo Inhibition of Protein Domains Using Single-Chain Fv Recombinant Antibodies and Its Application to Dissect RGMa Activity on Axonal Outgrowth

Antibodies are powerful tools for delineating the specific function of protein domains, yet several limitations restrict their in vivo applicability. Here we present a new method to obtain sustained in vivo inhibition of specific protein domains using recombinant antibodies. We show that long term in vivo expression of single-chain Fv (scFv) fragments in the developing CNS can be achieved through retroviral transduction. Moreover, specific scFvs generated against the N- and C-terminal domains of the repulsive guidance molecule, RGMa, prevent proper axon targeting in the visual system. This work reveals a previously unappreciated role for the RGMa N-terminal domain in axon guidance, and provides a novel, broadly applicable and rapid procedure to functionally antagonize any protein domain in vivo.
Benefits of lifestyle modification in the pharmacologic treatment of obesity: a randomized trial.

BACKGROUND Weight loss medications are recommended as an adjunct to diet and exercise modification but seem to be prescribed as a monotherapy by many physicians. This practice is likely to be associated with suboptimal weight loss. METHODS This 1-year, randomized trial compared the effects of sibutramine hydrochloride used alone (ie, the drug-alone group) to sibutramine plus group lifestyle modification, prescribed with either a 5021- to 6276-kJ/d diet (1200-1500-kcal/d diet) (ie, the drug-plus-lifestyle group) or, for the first 4 months, a 4184-kJ/d diet (1000-kcal/d diet (ie, drug-plus-lifestyle with a portion-controlled diet [the combined treatment] group). Participants were 53 women with a mean (+/-SD) age of 47.2 +/- 9.8 years and weight of 101.3 +/- 9.7 kg. At baseline, they reported the number of pounds they expected to lose at the end of treatment. RESULTS At month 12, patients treated with the drug alone lost (mean +/- SD) 4.1% +/- 6.3% of their initial body weight compared with significantly (P<.05) larger losses in the drug-plus-lifestyle group of 10.8% +/- 10.3% and the combined treatment group of 16.5% +/- 8.0%. Women in the 2 lifestyle groups achieved a significantly (P<.05) greater percentage of their expected weight loss than those in the drug-alone group and were significantly more satisfied with the medication and with changes in weight, health, appearance, and self-esteem (P<.05 for all). Significant reductions were observed at 12 months in triglyceride and low-density lipoprotein cholesterol levels but systolic and diastolic blood pressure both increased significantly (P<.05 for all). CONCLUSION The addition of group lifestyle modification to the pharmacologic management of obesity significantly improved weight loss and patients' satisfaction with treatment outcome.
Electronic Reprint Applied Crystallography Polycapillary Optic–source Combinations for Protein Crystallography Applied Crystallography Polycapillary Optic±source Combinations for Protein Crystallography

Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or its storage in electronic databases or the like is not permitted without prior permission in writing from the IUCr. The work in this paper is a systematic study of the application of collimating and slightly focusing polycapillary optics to the X-ray crystallographic structure determination of egg-white lysozyme using two different sources: a standard rotating anode source and a low-power table-top microfocusing source. For the rotating anode source, a series of measurements comparing duplicate data sets obtained from the same individual crystal are summarized. Intensity and data quality are discussed for measurements with a pinhole collimator, a collimating polycapillary optic and a focusing polycapillary optic. The collected data were analyzed using conventional analysis software; limitations of the use of conventional analysis software for focused beams are discussed. Two data sets were collected using the low-power source and collimating optics, and three data sets using a lower-power source and focusing optics with three different limiting apertures.
Career Persistence Model for Female Engineers in the Indonesian Context

Extant studies about female engineers have suggested their career persistency in the engineering career is influenced by the workplace, which is characterized by male dominated culture making them feel marginalized. In Indonesia, similar studies for reference are limited. This paper is based on an exploratory quantitative study using a questionnaire developed based on the Career Persistence Model. This paper is based on an empirical exploratory quantitative study by adopting Buse’s et al. Career Persistence Model (2013). The intention is to contribute to the literature in the context of Indonesia. It explores the Indonesian cultural dimensions and investigates their relationship to the roles of women in family, society and the workplace, and how women manage to navigate barriers to avoid taking alternative career paths. Contrary to extant studies, findings show women feel equally treated to men in the workplace, however some work demands may hinder. The strong acknowledgement of one’s roles in this collective society outdoes the opinions that the Islamic jurisprudence ( fiqh ) has marginalized empowerment of women, resulting in gender-based injustices and discrimination. Future studies should look into social supports at the workplace in an attempt to retain and increase the share of women in the engineering career in Indonesia. DOI : https://doi.org/10.21632/irjbs.10. 1.23-38 Keywords: female engineer, career persistence, socio-cultural influence, social harmony
Associative processes between behavioral symbols and a large scale language model

This paper describes an novel approach towards linguistic processing for robots through integration of a motion language model and a natural language model. The motion language model works for association of words from motion symbols. The natural language model is one used for a morphological analysis, which has been developed in natural language community. The natural language model is optimized using a enormous amount of words. So this model is scalable architecture. The motion language model and the natural language model can be integrated since both models are represented graphically. The integration of the motion language model and the natural language model allows robots not only to interpret motion patterns as sentences but also to generate motions from sentences. This paper demonstrates the validity of our proposed framework even in the case that large-scale word corpus is needed processing through experiments of interpreting motion patterns as sentences and generating motion patterns from sentences.
An improved particle swarm optimization algorithm for winner determination in multi-attribute combinatorial reverse auction

An electronic reverse auction system with one buyer and multiple suppliers is considered in this paper. The buyer procures multi-items from potential suppliers with unconstrained capacity and the suppliers bid competitively on combinations of items in the system. As an important decision problem from the buyer's perspective, a winner determination problem (WDP) of multi-items single-unit combinatorial reverse auction with multi-attributes of each item is described and a bi-objective programming model that minimizes the total procurement cost and maximizes the total score of the winning suppliers based on multi-attributes of each item is established. According to the characteristics of the model, an equivalent single-objective programming model is obtained. However, as the problem is NP-hard, an improved particle swarm optimization (IPSO) algorithm embedded with the quantum-inspired evolutionary and the asynchronous time-varying learning strategies is proposed. Also, a heuristic search algorithm is applied to repair the infeasible solutions in the process of IPSO. Experimental results show the effectiveness of the improved algorithm.
AKSIO - Active knowledge management in the petroleum industry

The AKSIO project is developing a process-enabled knowledge management system to support operations of offshore oilfields. The system will provide timely and contextual knowledge for work processes. Experiences will be processed and annotated by experts and linked to various resources and specialist knowledge networks. AKSIO will allow discovery of experiences through the support of a domain ontology. Core functionality of the AKSIO system is provided by careful application of Semantic Web technology, including ontology-based annotation and contextual ontology driven retrieval of content.
Modeling critical sections in Amdahl's law and its implications for multicore design

This paper presents a fundamental law for parallel performance: it shows that parallel performance is not only limited by sequential code (as suggested by Amdahl's law) but is also fundamentally limited by synchronization through critical sections. Extending Amdahl's software model to include critical sections, we derive the surprising result that the impact of critical sections on parallel performance can be modeled as a completely sequential part and a completely parallel part. The sequential part is determined by the probability for entering a critical section and the contention probability (i.e., multiple threads wanting to enter the same critical section). This fundamental result reveals at least three important insights for multicore design. (i) Asymmetric multicore processors deliver less performance benefits relative to symmetric processors than suggested by Amdahl's law, and in some cases even worse performance. (ii) Amdahl's law suggests many tiny cores for optimum performance in asymmetric processors, however, we find that fewer but larger small cores can yield substantially better performance. (iii) Executing critical sections on the big core can yield substantial speedups, however, performance is sensitive to the accuracy of the critical section contention predictor.
A learning analytics tool with hybrid graphical and textual interpretation generation

The introduction and use of on-line learning resources has improved students learning process in several aspects. But at the same time, it also introduced more complexity and made more difficult to teachers how to analyze learning evolution and improvement of students. In this paper, we propose a first approach how to visualize and analyze student interaction with on-line learning systems and Virtual Learning Environments (VLE). We present a piece of software that collects information on the interaction of the students with the Moodle VLE and that it displays to teachers in a more analytical way. The interaction data is displayed to support teacher interpretation from a learning point of view, with the inclusion of automatically generated textual explanations about the analysis of such data.
Non-interleaving Operational Semantics for Geographically Replicated Databases

For scalable distributed database systems, weak consistency models are essential. Distributed databases, such as Google Spanner, scale to millions of nodes that replicate data across datacentres possibly located on different continents. At this scale, it is infeasible to maintain serialisability, which assumes that a global total order over committed transactions can be established. Instead, weaker consistency models, such as eventual consistency, causal consistency, sequential consistency and external consistency, are assumed. The problem is that operational models, such as labelled transition systems, tend to assume an interleaving semantics, which serialises transactions. To address this limitation, we provide an operational model that allows a weaker notion of consistency for a geographically distributed database inspired by Spanner. We reduce the timing guarantees provided by Spanner's TrueTime protocol to causal dependencies that are specified in a formal calculus.
Jointly Modeling WSD and SRL with Markov Logic

Semantic role labeling (SRL) and word sense disambiguation (WSD) are two fundamental tasks in natural language processing to find a sentence-level semantic representation. To date, they have mostly been modeled in isolation. However, this approach neglects logical constraints between them. We therefore exploit some pipeline systems which verify the automatic all word sense disambiguation could help the semantic role labeling and vice versa. We further propose a Markov logic model that jointly labels semantic roles and disambiguates all word senses. By evaluating our model on the OntoNotes 3.0 data, we show that this joint approach leads to a higher performance for word sense disambiguation and semantic role labeling than those pipeline approaches.
Title Pattern of neural responses to verbal fluency shows diagnosticspecificity for schizophrenia and bipolar disorder

Background: Impairments in executive function and language processing are characteristic of both schizophrenia and bipolar disorder. Their functional neuroanatomy demonstrate features that are shared as well as specific to each disorder. Determining the distinct pattern of neural responses in schizophrenia and bipolar disorder may provide biomarkers for their diagnoses. Methods: 104 participants underwent functional magnetic resonance imaging (fMRI) scans while performing a phonological verbal fluency task. Subjects were 32 patients with schizophrenia in remission, 32 patients with bipolar disorder in an euthymic state, and 40 healthy volunteers. Neural responses to verbal fluency were examined in each group, and the diagnostic potential of the pattern of the neural responses was assessed with machine learning analysis. Results: During the verbal fluency task, both patient groups showed increased activation in the anterior cingulate, left dorsolateral prefrontal cortex and right putamen as compared to healthy controls, as well as reduced deactivation of precuneus and posterior cingulate. The magnitude of activation was greatest in patients with schizophrenia, followed by patients with bipolar disorder and then healthy individuals. Additional recruitment in the right inferior frontal and right dorsolateral prefrontal cortices was observed in schizophrenia relative to both bipolar disorder and healthy subjects. The pattern of neural responses correctly identified individual patients with schizophrenia with an accuracy of 92%, and those with bipolar disorder with an accuracy of 79% in which misclassification was typically of bipolar subjects as healthy controls. Conclusions: In summary, both schizophrenia and bipolar disorder are associated with altered function in prefrontal, striatal and default mode networks, but the magnitude of this dysfunction is particularly marked in schizophrenia. The pattern of response to verbal fluency is highly diagnostic for schizophrenia and distinct from bipolar disorder. Pattern classification of functional MRI measurements of language processing is a potential diagnostic marker of schizophrenia.
A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers

The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wavelet transformation at different levels of granularity to obtain size reduction. In subsequent phases, five features (based on statistical measurements maximum value, minimum value, arithmetic mean, standard deviation, median value) are obtained by using the feature vectors, and are presented as the input dimension to the complex-valued neural networks. The evaluation of the proposed method is conducted using the k-fold cross-validation methodology, reporting on classification accuracy, sensitivity, and specificity. The proposed method is tested using a benchmark EEG dataset, and high accuracy rates were obtained. The stated results show that the proposed method can be used to design an accurate classification system for epilepsy diagnosis.