Miracle-dz/UniFAR-FTUs huggingface dataset:
Text simplification for children

The goal in this paper is to automatically transform text into a simpler text, so that it is easier to understand by children. We perform syntactic simplification, i.e. the splitting of sentences, and lexical simplification, i.e. replacing difficult words with easier synonyms. We test the performance of this approach for each component separately on a per sentence basis, and globally with the automatic construction of simplified news articles and encyclopedia articles. By including information from a language model in the lexical simplification step, we obtain better results over a baseline method. The syntactic simplification shows that some phenomena are difficult to recognize by a parser, and that errors are often introduced. Although the reading difficulty goes down, it still doesn’t reach the required level for young children.
Information Geometry Near Randomness And Near Independence

Thank you for downloading information geometry near randomness and near independence. Maybe you have knowledge that, people have look numerous times for their chosen novels like this information geometry near randomness and near independence, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious bugs inside their laptop.
Solution Techniques for Classes of Biobjective and Parametric Programs

Mathematical optimization, or mathematical programming, has been studied for several decades. Researchers are constantly searching for optimization techniques which allow one to determine the ideal course of action in extremely complex situations. This line of scientific inquiry motivates the primary focus of this dissertation — nontraditional optimization problems having either multiple objective functions or parametric input. Utilizing multiple objective functions allows one to account for the fact that the decision process in many real-life problems in engineering, business, and management is often driven by several conflicting criteria such as cost, performance, reliability, safety, and productivity. Additionally, incorporating parametric input allows one to account for uncertainty in models’ data, which can arise for a number of reasons, including a changing availability of resources, estimation or measurement errors, or implementation errors caused by storing data in a fixed precision format. However, when a decision problem has either parametric input or multiple objectives, one cannot hope to find a single, satisfactory solution. Thus, in this work we develop techniques which can be used to determine sets of desirable solutions. The two main problems we consider in this work are the biobjective mixed integer linear program (BOMILP) and the multiparametric linear complementarity problem (mpLCP). BOMILPs are optimization problems in which two linear objectives are optimized over a polyhedron while restricting some of the decision variables to be integer. We present a new data structure in the form of a modified binary tree that can be used to store the solution set of BOMILP. Empirical evidence is provided showing that this structure is able to store these solution sets more efficiently than other data structures that are typically used for this purpose. We also develop a branch-and-bound (BB) procedure that can be used to compute the solution set of BOMILP. Computational experiments are conducted in order to compare the performance of the new BB
Single image super resolution of 3D MRI using local regression and intermodality priors

Clinical practice requires multiple scans with different modalities for diagnostic tasks, but each scan does not produce the image of the same resolution. Such phenomenon may influence the subsequent analysis such as registration or multimodal segmentation. Therefore, performing super-resolution (SR) on clinical images is needed. In this paper, we present a unified SR framework which takes advantages of two primary SR approaches – self-learning SR and learning-based SR. Through the self-learning SR process, we succeed in obtaining a second-order approximation of the mapping functions between low and high resolution image patches, by leveraging a local regression model and multi-scale self-similarity. Through the learning-based SR process, such patch relations are further refined by using the information from a reference HR image. Extensive experiments on open-access MRI images have validated the effectiveness of the proposed method. Compared to other advanced SR approaches, the proposed method provides more realistic HR images with sharp edges.
The Potential of Learning Analytics to Systematically Address Diverse Learning Needs and Improve Student Retention in Australian Higher Education

This paper reports on partial findings of an Australian Office for Learning and Teaching funded project entitled Learning Analytics: Assisting Universities with Student Retention. The potential of learning analytics to address diverse learning needs in a systematic and responsive manner is discussed, focusing on how the use of learning analytics can assist in developing responsive and student-centred curricula, and by extension improve student retention. Potential uses of learning analytics to address diverse learning needs and improve retention are explored, as is current use by academics. The paper first provides a literature review with a focus on the potential impact of learning analytics on student retention, and student success and engagement, before reporting on academic-level qualitative data of the project. These qualitative data for this paper are retrieved from a combination of surveys and focused interviews with academics across the Australian higher education sector. The key findings indicate that learning analytics is currently still a potential source of confusion for many academics, that institutional context is a crucial factor, and that a need exists for proactive communication about learning analytics planning and strategy by institutional leaders.
A Study on Object Search and Relationship Search from Text Archive Data

Large-scale text archive data are prevalent in many areas including informatics, computational social science and finance. However, to better explore and understand archival datasets, still many research problems remain. (1) The first problem lies in the difficulties of searching in the archives. Often searchers face the problem of the gap between the knowledge they possess and the content they desire to search due to domain differences or due to long time spans between documents contained in the archives. We call such problem a terminology gap. In such sense, it is sometimes difficult for the users to come up with a right key word to search the object in an unknown domain. (2) Besides the object search, searching for the relationships in archives is another challenging task. For example, searching for the set of evidences to explain the similarity relationship among entities. (3) In addition, the cause-and-effect relationship is another unknown relationship likely to be searched by the users who wish to discover and understand the changes reflected in text archives. For example, users may not be aware of the changes in one object causing the changes related to another object. This thesis aims at establishing methodologies for supporting object search as well as relationship search in text archive data. More specifically, we address the following three research topics: 1. Detecting Semantically Similar Terms across Different Domains We address the problem of terminology gap in object search by detecting semantically similar terms across different domains. For example, users searching for documents about music devices in 1980s which are similar to iPod, may fail to succeed since they may not know Walkman which played similar role as iPod does nowadays. We solve this problem by finding the counterpart (e.g., Walkman) of the query (e.g., iPod) that existed in the target domain (e.g., 1980s). We propose an efficient method to find counterparts by transforming the representation of terms within different vector spaces. We then enhance such global correspondence method by considering also the local context of terms (local correspondence). Through the extensive experiments conducted on the 20-years long archive, the New York Times Annotated Corpus, as well as the 200-years long archive, the Times
Understanding the dynamics of Bvit Process: a Complex adaptive Systems Approach

There has been a long-running discourse in the information systems literature around the business value of IT (BVIT). Researchers have adopted a myriad of conceptual, theoretical and analytical approaches to evaluating the tangible and intangible measures of BVIT. Little research however, has explored richer theoretical explanations of the dynamic nature of the BVIT processes in contemporary dynamic business environments. To address this gap, this research in progress seeks to explore how BVIT is created as a bottom-up emergent process. In pursuit of such understanding, this research embraces complex adaptive systems (CAS) theory to develop a bottom-up conceptual model of BVIT. The agent-based modelling (ABM) technique is introduced as an analytical tool for computationally representing and examining the CAS model of BVIT. Operationalization of the CAS model and ABM modelling will be demonstrated through a theory building exercise.
Systematic Review of Two Decades (1995 to 2014) of Research on Synchronous Online Learning

ABSTRACT Systematic reviews of literature are studies that strategically search for published research on a specific topic in order to synthesize what is known about the topic. This systematic review describes 157 articles on synchronous online learning (SOL) from thirty-four different countries on instructional setting, content areas, participant demographics, research designs, independent and dependent variables, SOL technologies, and data-collection tools.
FEN BİLGİSİ ÖĞRETMEN ADAYLARININ ARGÜMANTASYON TABANLI ÖĞRENME YAKLAŞIMINA YÖNELİK GÖRÜŞLERİ

Bu calismanin amaci fen bilgisi ogretmen adaylarinin argumantasyon tabanli ogrenme yaklasimina iliskin goruslerinin tespit edilmesidir. Bu calisma Ege Bolgesindeki bir devlet universitesinin egitim fakultesinde Fen Bilgisi ogretmenligi bolumunde ogrenim goren ucuncu sinif ogrencileri ile gerceklestirilmistir. Arastirmanin katilimci grubu 48 kisiden olusmaktadir. Katilimci grupta yer alan 48 ogrencinin 36’si kiz (% 75), 12’si erkek (% 25) ogrencilerden olusmaktadir. Katilimci grup olusturulurken olcut ornekleme yontemi kullanilmistir. Arastirmanin yurutuldugu surecte fen ogretimi laboratuvar uygulamalari 1 dersini alan fen bilgisi ogretmen adaylari calismanin katilimcilari olarak belirlenmistir. Calismada veri toplama araci olarak arastirmaci tarafindan hazirlanan acik uclu sorularin bulundugu argumantasyon tabanli ogrenme yaklasimi gorusler anketi kullanilmistir. Veri toplama araci olarak olusturulan ankette 5 adet acik uclu soru bulunmaktadir. Verilerin analizi argumantasyon tabanli yaklasimin ogretmen adaylarinda kalici ve etkili ogrenmeler olusturdugu, ogretmen adaylarinin fikirlerini rahatca ifade etmesi icin uygun ortamlarin olustugu, ogretmen adaylarini arastirma ve sorgulamaya tesvik ettigini fakat zaman sikintisi yasadiklarini ortaya koymustur.
Do Business Students Practice Smartphone Security?

Mobile phones are everywhere. According to a 2011 Pew study, 83% of American adults owned some kind of cell phone and 35% owned a smartphone [24]. Mobile technologies have the potential to transform instruction in the classroom and remotely [12]. However, along with the explosive growth of smartphones has come a rash of security problems. Previous research shows that college students lack in their personal computing security habits [26, 15, and 18]. The purpose of this study was to investigate the degree to which business students practice smartphone security. A survey of security-related practices was administered to students in business classes at a regional public university. The results of the survey show students to be lax in their smartphone security with men more willing to engage in risky behaviors than women. There were no differences in behaviors based upon maturity level or use of smartphones for financial transactions.
Age and e antigen status are associated with pre-existing tolerance mutations in Chinese patients with chronic HBV infection : a retrospective case control study

Background: The aim of this study was to investigate prevalent mutations of RT region of hepatitis B virus (HBV) genome in NA naïve Chinese patients with chronic HBV infection. Methods: A total of 217 patients with chronic HBV infection (172 with chronic hepatitis B and 45 with liver cirrhosis) were enrolled in this study. Mutations were detected by the direct sequencing of RT region after PCR amplification. Mutations and subsequent amino acid changes were analyzed for 16 well characterized NAs-resistance mutations (rtL180M, rtA181T/V/S, rtT184A/G/I/S, rtS202G/I, rtM204V/I/S, rtN236T and rtM250V/L) and 10 secondary or compensatory resistance mutations (rtV173L, rtV207I/L/G, rtS213T, rtV214A, rtQ215S, rtP237H and rtN/H238T/D). Results: Out of the 217 patients, 151 (69.6%) were male and 67 (30.4%) were female. A total of 166 patients (76.5%) were HBeAg positive. Mutations in the RT region were found in 28 patients (12.9%) including 34 mutations. Primary resistance mutations of HBV RT region were found in 8 (3.7%) cases. Of these 8 patients, 6 had rtM204I including 2 with combination of rtL180M, 1 had rtA181T and 1 had rtT184S substitution. While secondary/compensatory resistance mutations were detected in 20 (9.2%) cases. The most frequent secondary resistance mutation was rtS213T (5.0%), followed by rtV214A/E/P (2.3%) and rtV207L/M/I (1.8%). Multivariate analysis showed that age (P=0.021) and HBeAg status (P<0.001) were associated with HBV resistance mutations, while sex, ALT, AST, TBIL, HBV DNA level, genotype and liver disease stages were not statistically significant. Conclusions: Primary resistance mutations can be detected in treatment naive HBV infected patients, especially in older and HBeAg negative ones. Antivirals with high genetic barriers should be selected to avoid potential treatment failure.
Applying the Kinematic Parameters from the Bosco Jump Test to Evaluate the Athlete ’ s Preparadness and to Select Training Parameters

The aim of this study was undertaken to evaluate changes in the values of the indicators describing jumps during a 60 second Bosco test applied to female 400 m runners at the beginning of the general preparation period and how they depend on the levels of activation of anaerobic glycolysis estimated with blood lactate concentration. The experiment involved 8 female 400 m runners. Power, jump height, jump time, and the contact duration were recorded with the Optojump f. Microgate srl. device (Italy). The course of the test was also recorded with a video camera coupled with the Optojump system. On each of the subjects three points were marked: the trochanterion, the tibialis lateralis, and the mallolare fibulare. An analysis of the results of the study has demonstrated that the length of exercise has a major effect on variations in the kinematic indicator values recorded during jumps in the Bosco test. An analysis of the research findings identifies the Bosco test as a sensitive tool for measuring the anaerobic endurance of the lower extremities in athletes involved in speed-endurance disciplines. Further research should concentrate on seeking relationships between the character of the applied training means and their outcomes as revealed by the Bosco test. [Szmatlan-Gabryś U, Stanula A, Gabryś T, Ozimek M, Stanisz L. Applying the Kinematic Parameters from the Bosco Jump Test to Evaluate the Athlete’s Preparadness and to Select Training Parameters. Life Sci J 2014;11(5):383-388]. (ISSN:1097-8135). http://www.lifesciencesite. com. 52
Likelihood Ratio Policy Gradients for Reinforcement Learning

These are some notes on policy gradients for Reinforcement Learning (RL). They started life as background notes I made while I was reading ”Policy Gradient Methods for Robotics” [1]. Policy gradients are a natural choice in the robotics domain where a large change in the policy (like you might have when learning value functions) could damage the robot or its environment, and where the action and/or state spaces are continuous. Policy gradient methods are really beautiful in form and function. In these notes I’ll try to point out a few of these amazing features1 and how trying to lower the variance of the ”naive” likelihood ratio policy gradient leads to actor-critic designs [3]. The basic reinforcement learning setup is shown in Figure 1. Finally, the notation and much of the material here is taken from Pieter Abbeel and John Schulman’s excellent RL bootcamps.
Substance P and its role in viral infection

Substance P (SP) is an 11-amino acid neuropeptide of the tachykinin family that preferentially activates the neurokinin-1 receptor (NK1R). Early studies identified a role for SP and the NK1R in the digestive system, respiratory system, urogenital system, skin, nervous system, immune system, and tumors. More recently, SP and the NK1R have gained attention for their role in multiple viral infections, such as human immunodeficiency virus (HIV), HSV (herpes simplex keratitis), encephalomyocarditis virus (EMCV), respiratory syncytical virus (RSV), measles virus (MV), Epstein-Barr virus (EBV), enterovirus 71 (EV71) and so on. However, to date no human clinical assays using NK-1 receptor antagonists against viral infections have been developed, expect HIV. The use of aprepitant as antiHIV therapy has been tested in human clinical trials, although this NK-1 receptor antagonist showed no significant anti-viral activity. NK-1 receptor antagonists merit further investigation as potential therapeutic antiviral agents. In this review, we update the involvement of the SP/NK-1 receptor system in viral infections, with the aim of providing insights for future anti-viral chemotherapy studies.
Unpacking the Coworker Influence : A Moderated Mediation Model of Coworker Exchange Quality and Coworker Organizational Citizenship Behavior

This multisource field study unpacks the underlying processes linking coworker influence to employee job performance behaviors, including both task performance and organizational citizenship behavior (OCB). Drawing on a sample of 362 supervisor-focal employee-coworker triads, we developed and tested a moderated mediation model by integrating social information processing and social cognitive theories. Results generally supported the hypothesized relationships in that employee role ambiguity partially mediated the coworker exchange quality (CWX) – employee job performance relationships. Furthermore, coworker OCB fostered employee job performance behaviors directly and indirectly as a moderator to weaken the employee role ambiguity – job performance relationships. Therefore, this study highlights coworker as an important agent who can influence employee job performance behaviors. Implications of the findings are discussed.
The use of remote sensing and molecular markers as early warning indicators of the development of cyanobacterial hyperscum crust and microcystin- producing genotypes in the hypertrophic Lake Hartbeespoort, South Africa

In this study we monitor the formation of cyanobacterial hyperscum in Lake Hartbeespoort, consisting of 99% Microcystis aeruginosa cells, using satellite images. The hyperscum which formed near the reservoir wall was characterised by a distinctive white surface layer of crust exposed to photo-oxidizing due to high radiation, inflicting irreversible damage to the genetic constitution of the upper layer of Microcystis cells. Under the 3 mm thick layer of crust dark (<0.93 μmol of photons ms) anaerobic conditions (0.4 mg.l, 3% saturation) prevailed with high levels of microcystin (12,300 μg.l) in the absence of sunlight irradiation and photolysis by UV light. Real time PCR analysis indicated low levels of transcription of the mcyA, B and D genes responsible for sythesis of cyanotoxins, under these low light intensity conditions. At other sampling sites where cyanobacterial scum occurred and hyperscum was absent, only the mcyB and D genes were transcripted. The only explanation for the transcription of the mcyA gene in the hyperscum and not at the other sampling sites was possibly due to the presence of environmental stress-inducing factors e.g. low light intensity (0.93 μmol of photon m s) and pH 6.1. At sampling site 4 where no cyanobacterial scum was visible on the satellite images, low cell abundance (2.4 x 10 μg.l) and chlorophyll a (12.2 μg.l) was measured compared to sites 2 and 3 where cyanobacterial scum (chl a: 96 μg.l; 90.1 μg.l) was visible on the satellite images.
The Effects of Training Time on Serum Immunoglobulin Alterations and Cortisol Testosterone Responses in Male Athlete Students

The purpose of this study was to examine the effect of incremental continuous running as well as morning vs evening-time training on changes in serum immunoglobulins including IgA, IgG, IgM, testosterone and cortisol hormones responses. For this reason, 28 male athletic students were purposefully selected and randomly divided into the two groups; morning-time training group (N = 14, weight 68.2±9.8 kg, age 19.5± 1.6 years, training time 7: 30 AM) and evening-time training group (N=14, weight 63.8±8.4 kg, age 19.81±1.24 years, training time 16:30 PM). The participants were trained according to an incremental continuous running program with a certain heart rate for two months (16 sessions). To determine the amount of serum immunoglobulins as well as cortisol and testosterone hormones, the participants’ blood samples was taken twice, once 24 h before the first training session and once 24 h after training session. Then, a 12-minute running-walking test was used to measure the maximal oxygen consumption. The results showed there were not any significant differences between the amounts of IgA, IgM, IgG serum of both groups in pre-test and post-test (i.e., respectively, p = 0.727, P = 0.068, P=0.14). Also, there were not any significant differences between the amounts of testosterone and cortisol hormones secreted of both groups in pre-test and post-test. However, there were significant differences between the concentrations of cortisol hormone of the two groups in pre-test (P = 0.006) and post-test (P = 0.0001). More ever, the results also showed a significant difference between the pre-test of the morning-time training group and the post-test of the evening-time training group (P = 0.0001). The findings of this research indicate that cortisol hormone is influenced by the time of training, which is due to circadian rhythm.
Effect of Using Texting on Vocabulary Instruction for English Learners.

This article reports on a study that examined the effectiveness of an intervention using text messages to enhance the academic vocabulary acquisition of English language learners (ELLs). With a random control trial design, we compared students’ learning gain of target vocabulary (direct effect) and its subsequent impact on academic vocabulary learning (transfer effect) with and without the intervention treatment. The study included 108 undergraduate ELLs in a large Canadian university in Ontario. The intervention was aligned with the lesson plans of two comparable content-based courses on English for academic purposes required for the ELLs and aimed at teaching frequently used academic words embedded within the assigned course readings. The results indicated that, with the intervention, students learned significantly more target words. However, there was no difference between the treatment and control groups on academic vocabulary post-test performance measuring the transfer effect. The pedagogical implication of the findings and suggestions for future research are discussed.