Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Methylation Methods in Multi-Context Organisms

DNA methylation is an epigenetic modification that has the ability to alter gene expression without any change in the DNA sequence. DNA methylation occurs when a methyl chemical group attaches to cytosine bases on the DNA sequence. In mammals, DNA methylation primarily occurs at CG sites, when a cytosine is followed by a guanine in the DNA sequence. In plants, DNA methylation can also occur in other cytosine sequences, such as when a cytosine is not followed directly by a guanine. Many of the statistical methods that have been developed to estimate methylation levels and test differential methylation in whole-genome bisulfite sequencing studies incorporate the observed correlation between methylation levels of neighboring cytosine sites. However, most of these methods have been applied to human studies, where only CG sites are investigated. In this study, we focus on plant studies and show that the correlation between methylation levels at neighboring sites depends on the DNA sequence immediately following the cytosine. We investigate the importance of accounting for these differences in the correlation structure by comparing the performance of three existing methods (MethylSig, MAGI, and MD) in plants.
The Potential Misinterpretation Problem of Residual Based Models Due to Industry Misclassification

Accounting researchers frequently employ industry-specific residual based models to draw inferences. Examples include discretionary accruals in Jones (1991) and modified Jones model (1995), and accruals quality in Francis et al. (2005). This paper illustrates that the interpretation of the residual terms is potentially subject to the problem that arises from industry misclassification. In an industry-specific crosssectional regression, the assumed homogeneity within the same industry is problematic because the industry classification system is noisy, and thus large magnitude residuals are potentially caused by misclassified observations. Moreover, the misclassification may not happen randomly. If firms with certain characteristics are more likely to be misclassified, directional biases rather than pure noise may emerge. In firm-specific time-series settings, the implied stationarity over time for the same firm is also questionable. Firms face external shocks and/or internal changes. The big magnitude residuals could capture those “shock” or “change” years. Given that researchers often investigate whether there exists earnings management around special events, such as M&A or equity issuance, it would be necessary to distinguish between whether abnormal accruals around the event is due to earnings management or simply non-stationarity.
Squalestatin-induced production of taxol and baccatin in cell suspension culture of yew (Taxus baccata L.)

Various elicitors have already been reported to enhance the production of taxol and related taxanes. In this study, effects of a fungal metabolite, squalestatin, on production of taxol and baccatin III were studied. Expressions of 4 key involved genes, ts, dbat, bapt, and dbtnbt, in suspension cultures of Taxus baccata were also detected using qPCR. Results showed that application of squalestatin significantly increased taxol and baccatin III yields. Increased expressions of the genes were in accordance with measures of taxol and baccatin accumulations in cells and medium. Production of H2O2 has significant positive correlations with both gene expression and taxanes, indicating that the increase in H2O2 might be involved in the upregulation of the taxane production in yew under squalestatin treatment. Our results suggest that H2O2 is a key signaling component in the stimulation of taxane production in T. baccata cells induced by squalestatin.
Genetic, morphological and spatial characterization of two populations of Mabea fistulifera Mart. (Euphorbiaceae), in different successional stages

Two popu lations of Mabea fistulifera (Euphorbiaceae) located a t Rio Doce State Park (Minas Gerais, Brazil) in places characterized as in d ifferent successional stages, were investigated through genetic and ecological traits. Twenty randomly chosen individuals from each population had its genetic data assessed by 43 RAPD markers and were also evaluated through five morphologic traits and its spatial distribution. Both Shannon’s index and AMOVA reveled that most of the genetic v ariation was found between individuals within p opulations and about 9% of variation was located between populations. Moreover, populations differed genetically, but presented similar values of genetic diversity. Morphologic data showed d ifferences between populations. Significant correlations among matrix of genetic, geographic and morphologic distances were obtained considering both populations, and spatially closer individuals were more similar genetically, characterizing genetic substructured populations.
EU preferences for agri-food products from developing countries- winning and losing due to the EU GSP reform 2013

This paper looks into the general system of preferences of the European Union (EU) (henceforth referred to as the EU GSP system). In order to account for new EU trade agreements and emerging economies, the EU GSP system was reformed according to Regulation (EU) No 987/2012). The new EU GSP system was set into force in 1st January 2014. Focusing on agri-food products, we identify respective products and countries affected by the reform as well as analyse the changes of preferences. In addition to a brief review of the literature, we outline the main provisions of the new EU GSP system. In our analysis, we apply detailed tariff data for 2013. The number of tariff lines and trade under the EU GSP system indicate the effects, and the AVE tariffs of those countries and products that are no longer eligible for GSP reveals if countries really lose out.
INFLUENCE OF ORGANISATIONAL STRUCTURE ON IMPLEMENTATION OF ELECTRONIC PROJECT MONITORING INFORMATION SYSTEM IN PUBLIC TERTIARY INSTITUTIONS IN KENYA

ABSTRACT The purpose of this article is to explore the influence of organisational structure on implementation of electronic project monitoring information system (e-ProMIS) in public tertiary institutions. It is based on literature review and filed research by employing crosssectional survey research design. Questionnaire was used to collect data from 30 tertiary institutions and a sample size of 162 members of staff selected through stratified random sampling technique. Null hypothesis was tested using regression analysis at 0.05 confidence interval. The results indicate that all the three types of structure: formalization; complexity; and centralization were statistically significant with coefficients (.=0.238, t=3.167, p=0.002<0.05), (.=0.204, t=2.777, p=0.006<0.05) and (.=0.317, t=4.574, p=0.000<0.05) respectively. Specifically one unit change in implementation of e-ProMIS was associated with 23.8% changes in formalization structure, 20.4% changes in complexity structure and 31.7% change in centralization structure. The overall F statistics was (3,158) = 23.760 at level of significance p = 0.000<0.05 suggesting that there was a statistically significant relationship between organisational structure and implementation of electronic project monitoring information system in public tertiary institutions in Kenya. These study findings imply that for successful implementation of e-ProMIS and other e-government systems, organisational structure is imperative. In this era of digital systems public and private institutions that intend to implement ICT based technologies should ensure that their organisations adopted the right structure that is well aligned to supporting e-government systems.
Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks

Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks by Siddharthan Rajasekaran Master’s in Robotics Engineering Worcester Polytechnic Institute This thesis focuses on two key problems in reinforcement learning: How to design reward functions to obtain intended behaviors in autonomous systems using the learning-based control? Given complex mission specification, how to shape the reward function to achieve fast convergence and reduce sample complexity while learning the optimal policy? To answer these questions, the first part of this thesis investigates inverse reinforcement learning (IRL) method with a purpose of learning a reward function from expert demonstrations. However, existing algorithms often assume that the expert demonstrations are generated by the same reward function. Such an assumption may be invalid as one may need to aggregate data from multiple experts to obtain a sufficient set of demonstrations. In the first and the major part of the thesis, we develop a novel method, called Nonparametric Behavior Clustering IRL. This algorithm allows one to simultaneously cluster behaviors while learning their reward functions from demonstrations that are generated from more than one expert/behavior. Our approach is built upon the expectation-maximization formulation and non-parametric clustering in the IRL setting. We apply the algorithm to learn, from driving demonstrations, multiple driver behaviors (e.g., aggressive vs. evasive driving behaviors). In the second task, we study whether reinforcement learning can be used to generate complex behaviors specified in formal logic Linear Temporal Logic (LTL). Such LTL tasks may specify temporally extended goals, safety, surveillance, and reactive behaviors in a dynamic environment. We introduce reward shaping under LTL constraints to improve the rate of convergence in learning the optimal and probably correct policies. Our approach exploits the relation between reward shaping and actor-critic methods for speeding up the convergence and, as a consequence, reducing training samples. We integrate compositional reasoning in formal methods with actor-critic reinforcement learning algorithms to initialize a heuristic value function for reward shaping. This initialization can direct the agent towards efficient planning subject to more complex behavior specifications in LTL. The investigation takes the initial step to integrate machine learning with formal methods and contributes to building highly autonomous and self-adaptive robots under complex missions.
Phylogenetic position of Jaoa, a green algal genus endemic to China

Jaoa prasina, a freshwater green alga endemic to China, was collected from a stream in Hubei province, China. Unialgal cultivation, morphological observation, and phylogenetic analyses of small subunit ribosomal DNA and RuBisCO large subunit sequences were performed. When cultured on agar medium, the alga was irregularly filamentous, similar to marine species of Acrochaete. Aplanospores were observed on solid medium. A vesicular‐like thallus without rhizoids developed in liquid medium, similar to specimen development in natural habitats. Molecular phylogenetic analyses revealed that Jaoa was closely related to the marine genera Acrochaete Pringsheim and Ulvella Crouan & Crouan. The results suggested the genus Jaoa is a member of the family Ulvellaceae (Ulvophyceae), which contains mostly marine algae. The family name Jaoaceae should be abandoned. We speculate that Jaoa may have evolved from a marine Ulvellaceae ancestor.
Ecological and Chemotypic Analysis for Improved Growth and Management of Naturally Occurring Black Cohosh ( Actaea racemosa L.) Populations in Western Maryland

Black cohosh (Actaea racemosa L.) is a perennial herb native to deciduous woodlands in eastern North America with an extensive history of traditional use, most commonly for rheumatoid arthritis and female reproductive issues. Modern clinical research has maintained this herb’s relevance into the 21st century with a majority of authentic black cohosh raw material still harvested from naturally occurring populations in Appalachian woodlands for use in botanical supplements. Increased use and interest in black cohosh have led to increased wild harvesting, reports of adulteration, and stress on this important natural resource. In an effort to study this significant medicinal plant as part of an ecosystem, and to understand factors that would contribute to the more effective growth and maintenance of black cohosh, key chemical, physiological, and ecological aspects of two occurring populations in western Maryland were surveyed. Rhizomes were harvested from six populations of naturally occurring black cohosh in two state forests located in the Allegheny Plateau and Ridge and Valley physiogeographic provinces of Maryland. The concentrations of five medicinal compounds found in black cohosh extracts, actein, 23-epi-26-deoxyactein, cafeic acid, ferulicacid, and N-methylserotonin, were compared with plant reproductive status as well as accompanying overstory and under story species, soil moisture, and soil pH at each site. Compound levels showed a complex dependence on physiography but were independent of reproductive state. The findings provide clues to guide efforts at effective growth and management of wild populations of black cohosh and other threatened medicinal plants.
SCHOOL OF BUSINESS, ECONOMICS AND LAW AT UNIVERSITY OF GOTHENBURG GRADUATE SCHOOL MASTER OF SCIENCE IN FINANCE

This paper examines the performance of the original one-factor Cox, Ingersoll & Ross model during a contemporary dataset using an OLS procedure. The model is fundamental for many financial models used for investment decisions, it is therefore important to validate its performance during current market conditions characterized by low interest rates. The study is performed on a dataset of US Treasury Notes traded during the period 2005/01/01 2016/12/31 and contains 663 unique bonds. In accordance with previous studies, it is concluded that the estimated parameters are unstable and that the model performs worse during periods when short term interest rates are close to zero. Consequently, the assumption of positive interest rates might be too strong.
Dynamic Strategy Selection in Collaborative Spatial Tasks

ABSTRACT When speakers coordinate with one another, they have available a range of alternatives for conceptualizing and describing spatial relationships. To understand the features of successful communication in collaborative spatial tasks, it is important to identify factors that shape speakers’ linguistic choices and evaluate them in relation to task success. In this article we examine how description strategies—in particular, references to global versus local conceptualizations of spatial relationships—change over time, how the use of these strategies is related to both contextual cues and the partner’s feedback, and finally how these factors affect communicative success in terms of efficiency and accuracy in the task. In the dialogue task we used, Directors described from memory a spatial layout with intrinsic properties to a Matcher who reconstructed it based on those descriptions. We found that global description strategies and feedback from the Matcher that contributed to grounding (such as recaps) predicted better task performance, whereas local description strategies and queries from the Matcher predicted poorer performance. Importantly, the strategy adopted by pairs early in the dialogue predicted their ultimate accuracy in reconstructing the layout. This work underscores that to unpack the complex factors that contribute to successful communication, it is important to consider not only the linguistic strategies that speakers use, but also how these unfold over time and are shaped by interactive processes, such as those reflected by the partner’s feedback.
THE DEVELOPMENT AND IMPLEMENTATION OF BIOLOGY TEACHING KITS USING SELF REGULATED LEARNING (SRL) STRATEGIES

Abstract: This study was aimed to develop Biology teaching kits using Self Regulated Learning (SRL)-based strategy in senior high schools that have been validated and tested. The study was carried out by using the development strategy of Borg and Gall. The subjects were the tenth grade students of SMA Negeri 1 Sentolo in the academic year of 2014/2015. The data for the validation process and the implementation of the teaching kits were collected through questionnaires and observations. The data of the validator assessment were analyzed using the categorization formula and Borich formula. The data on the try-out were analyzed using the paired sample test. The findings were in the form of teaching kits product for Bryophyta materials for the tenth grade students. The teaching kits had been validated theoretically by experts and teachers, the lesson plans had been validated and simulated, and the teaching kits and research instruments had been tried out in a small scale and implemented in the field. Keywords: teaching kits, Self Regulated Learning (SRL) strategies PENGEMBANGAN DAN IMPLEMENTASI PERANGKAT PEMBELAJARAN BIOLOGI DENGAN STRATEGI SELF REGULATED LEARNING (SRL) Abstrak: Tujuan penelitian pengembangan ini adalah dihasilkannya perangkat pembelajaran biologi berbasis Self Regulated Learningdi SMA yang telah tervalidasi dan teruji. Metode penelitian menggunakan strategi pengembangan Borg dan Gall. Subjek penelitian perangkat pembelajaran adalah siswa kelas X SMAN 1 Sentolo. Teknik pengumpulan data dalam proses validasi dan implementasi perangkat pembelajaran menggunakan angket dan observasi. Data penilaian validator dianalisis dengan rumus kategorisasi, sedang persamaan validator terhadap lembar validasi menggunakan rumus Borich. Data hasil uji coba dianalisis dengan paired sample test. Hasil penelitian berupa produk perangkat pembelajaran pada materi tumbuhan lumut di kelas X SMA. Perangkat pembelajaran tersebut telah divalidasi secara teoretis yang dilakukan oleh ahli dan guru, rencana pelaksanaan pembelajaran tertentu telah diuji secara terbatas keterbacaan dan disimulasikan, perangkat pembelajaran dan instrumen penelitian telah diuji coba terbatas dan lebih luas. Kata kunci: perangkat pembelajaran, strategi self regulated learning
Transportation Informatics: An Image Analysis System for Managing Transportation Facilities – Phase II

One of the most important tasks in maintaining transportation facilities such as highways and streets is the evaluation of the existing condition. Visual evaluation by human inspectors is subjective in nature, therefore has issues of consistency and the speed and frequency of evaluation is limited due to the manual process. Automated evaluation using modern digital image processing and pattern recognition techniques can increase the efficiency and accuracy and decrease the costs of condition evaluation. Several automated condition evaluation systems have been developed, but these systems commonly require special devices such as strobe light, laser beams, etc, which increase the cost and limit the system to certain applications. In this study, a low cost automatic pavement distress evaluation approach is presented. This method can provide real-time pavement distress detection as well as evaluation results based on color images captured from a camera installed on a survey vehicle. The entire process consists of two main parts: pavement surface extraction followed by pavement distress detection and classification. In the first part, a novel color segmentation method based on a feed forward neural network is employed to separate the road surface from the background. In the second part, a segmentation technique based on probabilistic relaxation is used to separate distress areas from the road surface. The geometrical parameters obtained from the detected distresses are then fed to a neural network based pavement distress classifier in which the defects are classified into different types. Simulation results are given to show that the scheme presented in this report is both effective and reliable on a variety of pavement images.
SEXUAL DYSFUNCTION RELATIONSHIP WITH PSYCHIATRIC DISORDERS IN WOMEN

فده : هـعجارم یـناور تیعـضو و یـسنج درـکلمع للاتخا نیب طابترا نییعت رضاح شهوژپ فده کـینیلک هـب ناگدـننک تسا هدوب یکشزپناور . شور : دروم عون زا یسررب نیا م دهاش ی دشاب . ار دروـم هورگ 165 هـعجارم ییاپرـس ناراـمیب زا رـفن کـینیلک هـب هدـننک صیخشت یاراد هک دنداد لیکشت یکشزپناور ،بارطضا ،یگدرسفا یاه یضرم سرت ش و یرگشاخرپ ، ک تیا یاه دندوب ینامسج ) للاتخا ره زا 33 رفن ( . دهاش هورگ 33 ادن کشزپناور هب هعجارم هقباس چیه هک یناسک زا رفن تش دن فرـصم یبـصع یاهوراد و یمن دندرک و تاقلام و ناهارمه نایم زا دندش باختنا نارامیب ناگدننک . هب و یفداصتریغ شور هب دارفا نیا وص هنومن تر یرـیگ دندش باختنا سرتسد رد . هداد یروآدرگ یارب شسرپ و هبحاصم شور اه دش هدرب راک هب همان . لماـش یسررب نیا شجنس رازبا شسرپ کی ن یگژیو هما تیعمج یاه شسرپ ،یتخانش ملاع تسرهف و یسنج درکلمع للاتخا همان ت یاه 90 تسا هدوب یلاؤس . هتفای اه : هورگ رد یسنج درکلمع للاتخا عیزوت نیب هک داد ناشن هدمآ تسد هب جیاتن یـنعم تواـفت دهاـش و دروـم یاه راد دراد دوجو . مه نینچ توافت نیا هورگ و هدرسفا نارامیب نیب ،دهاش دهاـش هورـگ و یرگـشاخرپ راچد نارامیب و ناراـمیب اـب تیاکش ینامسج یاه دش هدید دهاش هورگ و زین و للاتخا رد دهاش و دروم هورگ ود نیب هک دش هداد ناشن یاه مساگرا و لیم ینعم توافت دراد دوجو راد . هجیتن : للاتخا هعجارم رد یسنج یاه هاگنامرد هب ناگدننک شزپناور یاه تسا یداع تیعمج زا رتشیب یک .
Human Resources Management Practices And Learning Organizational Culture – A New Perspective

While focusing on developing new ways to increase business competition, we’ve conducted a qualitative research among HR managers in big Romanian companies, with the purpose of establishing the developmental status of organisational culture as well as new tendencies which have appeared in human resource management. The results point to a need to update the roles of the HR departments and to establish a coherent organisational culture learning process based on metacognition which should lead to an increase in employee motivation as well as personal and professional growth. Based on the research conclusions, we created an organisational model which could capitalize on the relationship between the Human Resources Management HRM and the Organizational Culture OC with the aim of improving results of each individual company.
Transcultural study on quality of life in patients diagnosed of schizophrenia from Mexico and Spain

The aim of this paper was to evaluate the differences between two samples of schizophrenic patients from two different cultural contexts. Matched by age and gender, each 40-subject sample includes patients with differential diagnosis of schizophrenia. One sample was taken from the Barcelona Hospital network (Spain) and the other one from the Hospital Civil Universitario of Guadalajara (Mexico). Several demographic and clinical variables were evaluated and the Health Related Quality of Life Scale (HRQLS) was conducted on all the subjects. The HRQLS was adapted to Spanish (Rodriguez, et al., 1995). The results confirmed the factor structure studied and they showed no special differences in the total score of the HRQLS. However, an important effect was found when analyzing the results separately for the three factors: Interpersonal Relationship (IR1), Instrumental Resources (IR2) and Intrapsychic Foundation (IF), or in the items of the Intrapsychic Foundations factor. Given these differences, it is considered that these scales can be used to carry out an exhaustive profile analysis in order to organize a personalized treatment, in comparison to the total score of the HRQLS.
A Local Radial Basis Function Method for High-Dimensional American Option Pricing Problems

In this work, we apply the local Wendland radial basis function (RBF) for solving the time-dependent multi dimensional option pricing nonlinear PDEs. Firstly, cross derivative terms of the PDE are removed with a change of spatial variables based in LDLT factorization of the di_usion matrix. Then, it is discussed that the valuation of a multi-asset option up to 4D can be computed using a modified shape parameter algorithm. In fact, several experiments containing of three and four assets are worked out showing that the results of the presented method are in good agreement with the literature and could be much more accurate once the shape parameter is chosen carefully.