Miracle-dz/UniFAR-FTUs huggingface dataset:
CPSC 290 Research Proposal: Multi-lingual Word Embeddings in Natural Language Processing

One of the key lessons from the recent development in Natural Language Processing (NLP) is that vectorization of words, i.e. word embedding, plays an important role in various tasks. First, word embedding has benefited an approach to semantics called distributional semantics. Distributional semantics takes an inspiration from linguistics and philosophy that “you shall know a word by the company it keeps”, believing that the meaning of a word can be represented by the contexts it takes. This means that the primary task of distributional semantics comes down to compressing high dimensional information of raw contexts into lower dimension while keeping semantically sensible structures and discarding noises. Although there are many kinds of technique for such compression, including the singular value decomposition, neural networks have proven powerful. The neural network based word vectorization, Word2Vec, developed by Mikolov at Google appears to preserve a linguistically sensible linear structure [1]. For instance, it turns out that the closest vector to the vector obtained by a simple vector operation −−→ king −−−→ man+−−−−→ woman is −−−→ queen. Such results encourage us to see word embedding as a good representation of semantics. Moreover, pre-trained word embeddings are often used as an initialization point for many tasks such as Machine Translation and Part-of-Speech Tagging.
Use of Interpersonal Deception Theory in Counter Social Engineering

Social engineering attacks exploit human vulnerabilities rather than computer vulnerabilities. Ranging from straightforward spam emails to sophisticated context-aware social engineering, social engineering has demonstrated rich varieties. Surprisingly, even the simplest type of attacks are able to fool numerous innocent people. The more sophisticated ones are even more “successful” in achieving their malicious purposes. In order to mitigate and combat these attacks, we need better automated counter social engineering algorithms and tools. In this position paper, we propose a reinforcement learning framework that incorporates interpersonal deception theory to fight against social engineering attacks on social media sites.
The effects on riding performance using active vs passive recovery during a simulated motocross race

Aleix Ollé Casanovas. 2017. The effects on riding performance using active vs passive recovery during a simulated motocross race. University of Jyväskylä. 53p. The aim of the present study was to examine the effect of active and passive recovery methods in order to improve physical performance between motocross races. Exercise induced muscle damage post motocross racing was assessed as well. Participants performed 2 races of 30 minutes with one hour break in between. During the break they performed either active or passive recovery protocols. Specific motocross performance outcomes and athlete’s physical conditions were measured during, and before and after every motocross race. Lap times (LT) and heart rate (HR) were recorded during racing, and strength and power tests such as handgrip strength (HS), upper back pull (UBP), counter movement jump (CMJ) and medicine ball throw (BT) were performed pre and post racing. Metabolic demands and reaction time were evaluated pre and post race as well via blood lactate (BL) concentration, and a visual stimulus reaction time test (RT). Creatine kinase (CK) and strength test were assessed 24h after exercise bout. No significant differences (p>0.8) in laptimes, and in force and power production (CMJ p>0.1; UBP p>0.5; HS p>0.2; BT p>0.8) were found, after using active or passive recovery in between races. A significant drop in HS was found when comparing pre and post race values (HS p<0.0001). RT was not affected by any of the recovery protocols but it tended to improve at every trial. 24 h post racing, baseline strength values were not recovered, and CK values were above resting levels. The results of this study do not support the use of active recovery in between races when it comes to restoration of performance values. Motocross racing seem to cause some degree of exercise-induced muscle damage.
Mortality trends and risk of dying from breast cancer in the 32 states and 7 socioeconomic regions of Mexico, 2002-2011

Objective. To determine mortality trends from breast cancer in Mexico nationwide, by state, by socioeconomic region, and to establish an association between education, state of residence, and socioeconomic region with mortality from breast cancer in 2002–2011. Methods. Records of mortality associated with breast cancer were obtained. Rates of mortality nationwide, by state, and by socioeconomic region were calculated. The strength of association between states where women resided, socioeconomic regions, and education with mortality from breast cancer was determined. Results. Women who completed elementary school had a higher risk of dying from breast cancer than people with more education [relative risk (RR) 2.58, 95% confidence interval (CI) 2.49–2.67]. Mexico City had the strongest association with dying from breast cancer as state and as socioeconomic region 7 [Mexico City: RR 3.47, CI95% 2.7-4.46 (2002) and RR 3.33, CI95% 2.66-4.15 (2011) and region 7: RR 3.72, CI 95%: 3.15-4.38 (2002) and RR 2.87, CI 95%: 2.51-3.28 (2011)]. Conclusions. In Mexico, the raw mortality rates per 100 000 women who died from breast cancer increased. Mortality was higher in women who had elementary school than in those with more education. The strongest association was in Mexico City as state and as region 7.
BSDE with random terminal time under enlarged filtration and financial applications

Markets with asymmetrical information have been already studied, generally in a wealth optimization point of view. We study here a hedging problem for a financial agent possessing an additional information on the market. We extend the results given for hedging strategies under a fixed terminal time to the case of a random terminal time. In particular, we provide tools to understand the behavior of American option pricing by an insider. To achieve this aim, we prove the existence and uniqueness of solution of BSDE with random terminal time under enlarged filtration.
Characterization and toxicity of Bacillus thuringiensis serovar chanpaisis ( H 46 ) : A serovar from Thailand

A new strain of Bacillus thuringiensis serovar chanpaisis was isolated from soil samples in Thailand. It was classified and characterized in terms of the crystal proteins, carbohydrates fermentation patterns, cry gene content, and its toxicological properties against the species of Lepidoptera, Coleoptera, and Deptera. This strain was identified as Bacillus thuringiensis according to morphological and biochemical characteristics. The strain produced bipyramidal crystal proteins consisting of major bands at about 130 kDa, 85kDa, 64kDa, 50kDa, and 20 kDa. A PCR analysis of the cry genes revealed that only cry32 genes could be detected and localized on chromosomal DNA and plasmid DNA of the organism. The bioassay showed that B. thuringiensis serovar chanpaisis had no larvicidal activity against any species of the Lepidoptera or Coleoptera but exhibited mortality level against Aedes aegypti and Culex quinquefasciatus with LC50 values of 1.48×10 spores mL and 1.00×10 spores mL, respectively.
Development Process : An Action Grammars Perspective

Practitioners adapt development methodologies to suit loc al needs, for example, by combining agile and traditional elements. To support this, we need a deeper underst anding of the underlying mechanisms behind the various software development approaches, with the aim of fin ding a perspective that is common to all. In the field of IT, it has been suggested that a change in perspective from ‘technology and people’ to ‘action’ might help address the disconnect between artifactand people-c entric approaches. In this position paper, we explore this idea for software development by considering a ch ange in viewpoint frommethodologyto patterns of action. Actions are the core functions that are the building blocks for oftware development and are defined in a lexicon. Possible relationships between actions are depicted in a grammarand processes are modelled as action grammars . We represent some common development methodologies as act ion grammars and discuss insights gained. Our contributions are the exploration of a novel way of viewing the software process, some insights gained and the exposure of issues with popular term inology.
13 A DIAGNOSTIC STUDY OF EPISODIC MIXING MODELS OF SHALLOW CUMULUS CLOUDS

Shallow cumulus clouds play a fundamental role in the vertical redistribution of energy and moisture in the lower troposphere. While their influence is well established, there are currently a wide range of approaches to represent the ensemble effect of these clouds in largescale models. This breadth of approach is understandable given lack of consensus as to the mechanism by which turbulent clouds mix with their surroundings [see, e.g. Blyth, 1993; Siebesma, 1998; Emanuel, 1994]. Episodic mixing and buoyancy sorting (EMBS) models are motivated by observations of cloud structure that suggest undilute subcloud air (USCA) is present at well above cloud base. Episodic mixing idealizes a cloud as a core updraft of (USCA), part of which mixes with environmental air at each vertical level. The mixing is envisioned as occurring in eddies that create a spectrum of mixtures ranging from pure subcloud air to pure ambient air. Buoyancy-sorting assumes that the generated individual mixtures are primarily driven by their own buoyancy against the environment and are eventually detrained from their individual neutral buoyancy level (NBL). While EMBS models can make a claim for a physically more realistic representation of cloud mixing, they obviously represent a highly idealized picture of cloud environment mixing, and require the specification of three pieces of information for which there are few observational constraints: 1) the rate at which USCA is shed by the undiluted thermal (which we will refer to as the undilute eroding rate, or UER); 2) the mass distribution of cloud mixtures following a mixing event; and 3) a detrainment criterion to specify the vertical level of detrained cloud parcels. In this study we investigate the capability of the EMBS model in representation of nonprecipitatingcumulus clouds. In particular, we retrieve the UER, which constitutes a major assumption in all EMBS models [Emanuel and Zivkovic-Rothman, 1999] (EZ99) based on the observed large-scale forcing and equilibrium state of a trade cumulus atmosphere, given a fixed mixtures mass distribution and a detrainment criterion. In Section 2 we introduce the EMBS model and the diagnostic approach. In Section 3, we present a case study and its results. In Section 4 we discuss the results and its implication to the parameterization of cumulus ensemble.
Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model

Recent work on variational autoencoders (VAEs) has enabled the development of generative topic models using neural networks. Topic models based on latent Dirichlet allocation (LDA) successfully use the Dirichlet distribution as a prior for the topic and word distributions to enforce sparseness. However, there is a trade-oﬀ between sparsity and smoothness in Dirichlet distributions. Sparsity is important for a low reconstruction error during training of the autoencoder, whereas smoothness enables generalization and leads to a better log-likelihood of the test data. Both of these properties are encoded in the Dirichlet parameter vector. By rewriting this parameter vector into a product of a sparse binary vector and a smoothness vector, we decouple the two properties, leading to a model that features both a competitive topic coherence and a high log-likelihood. Eﬃcient training is enabled using rejection sampling variational inference for the reparameterization of the Dirichlet distribution. Our experiments show that our method is competitive with other recent VAE topic models.
Get Me Out: A History of Childbirth from the Garden of Eden to the Sperm Bank

Get Me Out: A History of Childbirth From the Garden of Eden to the Sperm Bank By Randi Hunter Epstein (New York: W.W. Norton & Co., 2010) (302 pages, $24.95 cloth) Get Me Out: A History of Childbirth From the Garden of Eden to the Sperm Bank is an overview of childbirth and its intersection with social trends and technology from antiquity to modern day. Journalist and physician Randi Hunter Epstein addresses various obstetrical topics in an accessible style that will appeal to diverse readers. Epstein explains that human interest in pregnancy and birth is not new, and neither are human attempts to improve maternal and neonatal outcomes. Epstein's purpose in this volume is to explore the end results of intersections between medicine and society. One trend that Epstein documents, but does not comment on, is that maternity care practices are driven only partly by the practitioners; rather, childbearing women pushed for various advances. Physicians may have introduced forceps into obstetrics, but they found a willing market among women seeking safe deliveries. Twilight sleep, diethylstilbestrol (DES), cesarean sections, and natural childbirth-each of these was actively chosen by women, and when their choice was not available, they sought care elsewhere-sometimes going to Europe, other times lobbying locally. Trends turned even within a generation; mothers who insisted on twilight sleep and medicated childbirth had daughters who were adherents of the Lamaze method. Both of those sets of mothers used similar techniques to get the services they wanted, sometimes in spite of the prevailing medical advice. Arranged somewhat chronologically, Epstein's 14 chapters cover various topics that are connected to obstetrics. Epstein examines topics that are unique to this volume such as sperm banking, ultrasound, cesarean sections, and egg freezing, as well as others that have been covered extensively by other authors in book-length manuscripts (the introduction of forceps, the natural childbirth movement, maternal mortality, and the development of hospital-based maternity care). Epstein's writing style combined with the interesting details she unearths (among them: Caesar could not have been delivered by a cesarean section, and sperm donors are generally attractive) make this quite an entertaining and readable book. Epstein covers a very long period, from antiquity to modern day practice. The "ick factor" of some ancient obstetric treatments is high, but Epstein humanizes practitioners and practices that were intended to improve obstetric care and outcomes. She also includes stories from the darker side of obstetrics including Marion Sims' experiments on enslaved Black women and the Chamberlen family's commercially driven protection of their forceps secret. …
Comparison of Two Value-Modeling Methods: e3 value and SEAM

In the last few decades, several value-modeling methods have emerged in requirements engineering for IS research. We compare two value-modeling methods, e3 value and SEAM. We illustrate their use with an example of the exchange of the Intellectual Property Rights (IPR) on music. In the process, we propose a comparison framework. The results of our study show that e3 value and SEAM are similar value-modeling techniques: both model services in networked systems and focus on value exchanges. They differ, however, in the way value is conceptualized: the market viability of the service system in e3 value versus the subjective value and lack of market profitability analysis in SEAM. e3 value shows how value flows from one actor to another, whereas SEAM shows the relative importance of different value propositions and how they are constructed by the service network. These results can be used by modelers to select a value-modeling method for their purposes by proposing explicit selection criteria. The comparison framework, which is in its early stages of development, can be used to compare other modeling methods.
Expression Pattern and Transcriptional Control of SoxB 1 in Embryos of the Ascidian Halocynthia roretzi

The Sox family is a large group of transcription factors that are characterized by the presence of a DNA-binding HMG domain. We isolated HrSoxB1 , an ascidian homolog of the Sox gene that belongs to the B1 subclass of the Sox family, from Halocynthia roretzi . Expression was initiated as early as the 8-cell stage. During cleavage stages, HrSoxB1 was expressed in three quarters of embryonic blastomeres but not in posterior-vegetal (B-line) blastomeres. Misexpression of mRNAs of HrPEM but not of macho-1 , whose maternal mRNAs are localized to the posterior-vegetal cytoplasm of eggs and early embryos, repressed the anterior-vegetal expression of HrSoxB1 . This result suggests that the zygotic expression of HrSoxB1 is controlled by the localized maternal mRNA. When HrSoxB1 was overexpressed in early embryos, ectopic expression of HrBra , a gene for a transcription factor expressed in notochord blastomeres, occurred in the most posterior blastomeres (B7.5), although these blastomeres did not eventually differentiate into notochord but developed into muscle, as they do in normal embryogenesis. In later embryogenesis, HrSoxB1 was specifically expressed in neural plate cells. However, overexpression of HrSoxB1 did not affect the expression of a neural plate marker gene, HrETR-1 .
SPATIAL REFRACTIVE INDEX MODULATION OF THE RETINA ASSESSED BY HYPERSPECTRAL QUANTITATIVE PHASE MICROSCOPY

The refractive index (RI) of the retina and its dispersion are essential parameters in ophthalmologic imaging. On one hand, the RI determines the light propagation inside the tissue towards the photoreceptors. On the other hand, its spatial distribution reflects tissue structures by biophysical properties such as density or birefringence. In this context, knowledge about wavelength dependency is crucial in high-resolution imaging, e.g., for dispersion compensation in optical coherence tomography (OCT). However, the spatial RI distribution in retinal tissue is difficult to access. We explored the capabilities of quantitative phase microscopy (QPM) for RI determination of murine retina using digital holographic microscopy (DHM) [1]. Multispectral QPM was achieved by coupling light from a tunable supercontinuum laser into a Michelson interferometer-based DHM configuration in which one of the mirrors was slightly tilted to generate digital off-axis holograms [2]. Unstained cryostat sections from mouse retina were prepared on glass carriers, embedded in phosphate buffered saline and covered with a cover slip. Digital holograms of the samples were recorded at different wavelengths in the near infrared spectral range that is highly relevant for OCT. Coherence induced noise was reduced by averaging phase maps that were acquired at different light wavelengths [3]. The tissue refractive indices that were obtained from the reconstructed quantitative DHM phase images are in well agreement with previously reported values for living cells and dissected tissues. Moreover, the detected spatial refractive index distributions correlate with results from complementary conducted OCT investigations. In summary, multispectral DHM is a promising tool for label-free characterization of optical retina properties.
Optimizing the Design and Cost for Crowdsourced Conversational Utterances

As more industries adopt chatbot technology, there is a growing demand for crowdsourcing utterances for training dialogue systems. Yet, it is well-known that crowdsourcing has a high rate of noisy and low-quality data. While techniques such as "golden answers" help with filtering noise for certain kinds of data collections, these techniques are difficult to use with utterance collection, due to its open-ended nature, resulting in large amounts of data that must be discarded. Thus, obtaining high quality utterance data often requires careful design and multiple iterations of the crowdsourcing task, which can lead to increase in cost of the crowdsourcing task. In this paper, we consider several variations of commonly-used workflows for utterance collection in a crowdsourcing platform and their effect on the utterance quality. In addition, we propose a strategy to adaptively terminate the data collection process based on utterance coverage and evaluate its effect on the performance of the downstream model. Finally, we examine the cost considerations for crowdsourced tasks and provide suggestions for future utterance collection procedures.
A New Approach to the Ezafe Phrase in Persian

This paper investigates the Ezafe Phrase (EzP), a functional phrasal category specific to Persian. The EzP is headed by a morpheme which may be phonetically realized as e/ye or null Ø. This morpheme regulates the occurrence of more than one complement in DPs/NPs and APs. The analysis follows the Minimalist framework of Chomsky (1995, 2000, 2001) and adopts Kayne’s (1994) Linear Correspondence Axiom (LCA) which examines the relation of hierarchical structure and linear order based on the antisymmetry of syntax. Presenting a comprehensive analysis of this construction, the paper concludes that this functional category follows the general Spec-Head-Complement configuration proposed by the LCA.
Chapter 2 Web multiform data structuring for warehousing

In a data warehousing process, the data preparation phase is crucial. Mastering this phase allows multidimensional analysis or the use of data mining algorithms, as well as substantial gains in terms of time and performance when performing such analyses. Furthermore, a data warehouse can require external data. The web is a prevalent data source in this context, though the data broadcasted on this medium are very heterogeneous. In this chapter, we propose a modeling process for integrating all these diverse, heterogeneous data into a unified format. Furthermore, the very schema definition provides first-rate metadata in our data warehousing context. At the conceptual level, a complex object is represented in UML as a superclass of any useful data source (databases, plain or tagged texts, images, sounds, video clips, etc.). Our logical model is an XML schema that can be described with a DTD or the XML-Schema language. Eventually, we have designed a Java prototype that transforms our multiform input data into XML documents representing our physical model. Then, the XML documents we obtain are mapped into a relational database. We view this database as an ODS (Operational Data Storage), whose data will have to be re-modeled in a multidimensional way to allow their storage in a warehouse and, later, their analysis.
Investigation of the semantic priming effect with the N 400 using symbolic pictures in text

In face-to-face communication, a large portion of communicative devices rely on the visual modality of bodily behaviors which include facial expression and hand gestures. However through the use of digitally mediated communication which is becoming increasingly prevalent with advances in technology, people are evolving their way to communicate. Texts become shorter and the use of emojis are changing. Facial emojis are symbols for human faces that have become increasingly popular with communicative devices. The original and still most frequent use of emojis is to provide a comment to the text which they follow. However, the latest trend is also to use emojis in the middle of sentences replacing words or adding information to the text. Through the use of EEG and the N400 ERP component, this study investigates which objects emojis refer to via an internet survey and a EEG semantic priming test in which moving emojis in sentences are paired with congruous and incongruous probes. The results of both the survey and the EEG test indicate that there is no preference for particular positions of the emojis and that some of the unusual emojis were ambiguous and did not add to comprehension.