Miracle-dz/UniFAR-FTUs huggingface dataset:
Text Style Transfer via Back Inference with Pseudo-Parallel Data

Text style transfer and text manipulation in natural language generation requires an explicit disentanglement of text style and content. However, despite the success of deep generative models in computer vision, this problem remains challenging due to the lack of parallel labeled data and also the complexity of natural language. In this project, we propose a new generative model based on Auto-encoder with a back-inference regularization. We utilize language models to guide the generators by aligning the generated distributions to those of the corresponding styles, and the encoder is forced to align the back-inferred latent representations of the pseudo-parallel examples via adversarial training. Our proposed method is able to achieve comparable results on all of the evaluation metrics, and by adding back-inference phase with pseudo-parallel data, we are able to gain further improvements in terms of BLEU scores and transfer accuracy.
Youth in the Education Sustainable Development Goal Highlights

 Out-of-school youth (SDG 4.1.5) still represent more than 10% of the population in the official age range for upper secondary education in over one-quarter of OECD and partner countries. Nonetheless, some countries have succeeded in significantly reducing the proportion of out-of-school youth. For instance, in Mexico and the Russian Federation, this proportion has decreased by at least 18 percentage points since 2005.
- 1-Multivariate Parametric Approaches for Dependently Left-truncated Data

Many statistical methods for left-truncated data rely on the independence assumption regarding the truncation variable. In many application studies, however, the dependence between a variable X of interest and its truncation variable L plays a fundamental role in modeling data structure. For truncated data, a typical interest is in estimating the marginal distributions of ) , ( X L and often in examining the degree of the dependence between X and L . To relax the independence assumption, we present a method of fitting a parametric models on ) , ( X L , which can easily incorporate the dependence structure on the truncation mechanisms. Focusing on a specific example for the bivariate normal distribution, the estimating equations and Fisher information matrix are provided. It is demonstrated that the current approach is adaptive to many important sampling designs, including a two-stage course placement system. Simulations are performed to examine finite-sample performances of the proposed method under two practical sampling designs.
Integrating current methods for the preservation of amphibian genetic resources and viable tissues to achieve best practices for species conservation

—Global amphibian declines associated with anthropogenic causes, climate change, and amphibianspecific infectious diseases (e.g., chytridiomycosis) have highlighted the importance of biobanking amphibian genetic material. Genetic resource collections were the first to centralize the long-term storage of samples for use in basic science, including disciplines such as molecular evolution, molecular genetics, phylogenetics, and systematics. Biobanks associated with conservation breeding programs put a special emphasis on the cryopreservation of viable cells. These cell lines have a broader application, including the potential for genetic rescue and use in species propagation for population enhancement, such as captive breeding and reintroduction programs. We provide an overview of the most commonly used methods for the preservation of genetic resources, identify ways to standardize collection processes across biobanks, and provide decision trees to assist researchers in maximizing the potential use of their samples for both scientific research and the practice of species conservation. We hope that the collection and deposition of tissues preserved using methods that enable eventual cell line establishment will become routine practice among researchers, particularly herpetologists working in the field. While many major museums do not yet cryopreserve reproductive cells or cell lines, they contain the infrastructure and staff to maintain these collections if protocols and procedures are adapted. Collaboration between organizations can play an important future role in the conservation of amphibians, especially biobanks associated with research institutions and those pioneering techniques used in breeding programs.
Safe use of Robotic Arms as Input Devices

The independent research centre i-Botics, founded by TNO and University of Twente, currently uses the omega.7 haptic device as a master for the telemanipulation of the KUKA LWR 4+ robotic arm as a slave device for tasks that need to be performed in a dangerous or hostile environment for human operators. To improve this state of the art, the Emika Franka Panda robotic arm is, herein, proposed as replacement for the omega.7 device. Since human operators are to physically interact with the Panda robotic arm, strict safety measures prompt for proper energy, force and power limitations to be carefully set. The novel master device needs to also fulfil the requirements of a haptic input device. Herein, a control methodology was developed and implemented such that the necessary safety and haptic prerequisites are met. The system successfully passed the four evaluation tests that addressed its haptic performance and safety. Although the slave device was used as a Gazebo simulation of the KUKA LWR 4+ robotic arm, the design is also valid and recommended for the real hardware. Robotics and Mechatronics Adrian Ion Lazar iv Safe use of robotic arms as input devices Adrian Ion Lazar University of Twente
Soumelis V. et al.: “Human Epithelial Cells Trigger Dendritic Cell Mediated Allergic Inflammation by Producing TSLP” Nature Immu

Davies J. et al.: "Affinity Improvement of Single Antibody VH Domains: Residues in All Three Hypervariable Regions Affect Anti gen Binding. ” Immunotechnology, Elsevier Science Publishers BV, NL, vol. 2, No. 3, Sep. 1996, pp. 169-179. Holt L.J. etal. "Domain Antibodies: Proteins for Therapy,” Trends in Biotechnology, Elsevier Publications, Cambridge, GB, vol. 21, No. 11, Nov. 2003, pp. 484-490. Online: “Anti-Human TSLP Antibody AF 1398. ” Internet Citation, Feb. 15, 2006, Retrieved from the Internet: URL: http://www. mdsystems.com/pdfaf1398.pdf. Online: "Monoclonal Anti-Human TSLP Antibody. ” Internet Cita tion, Aug. 6, 2005, Retrieved from the Internet: URL: http://www. mdsystems.com/pdf MAB1398.pdf. Soumelis V. et al.: “Human Epithelial Cells Trigger Dendritic Cell Mediated Allergic Inflammation by Producing TSLP” Nature Immu nology, Nature Publishing Group, GB, vol. 3. No. 7 Jul. 2002, pp. 673-680. Soumelis V. et al.: “Human Thymic Stromal Lymphopoientin: A Novel Epithelial Cell-Derived Cytokine and a Potential Key Player in the Induction of Allergic Inflammation. ” Springer Seminar in Immunopathology, Springer Verlag, DE, vol. 25, No. 3-4, Feb. 2004, pp. 325-333. Fundamental Immunology, p. 242, William E. Paul, M.D. ed., 3d ed; 1993.
Data stream mining techniques: a review

A plethora of infinite data is generated from the Internet and other information sources. Analyzing this massive data in real-time and extracting valuable knowledge using different mining applications platforms have been an area for research and industry as well. However, data stream mining has different challenges making it different from traditional data mining. Recently, many studies have addressed the concerns on massive data mining problems and proposed several techniques that produce impressive results. In this paper, we review real time clustering and classification mining techniques for data stream. We analyze the characteristics of data stream mining and discuss the challenges and research issues of data steam mining. Finally, we present some of the platforms for data stream mining.
An integrated model for determining business intelligence systems adoption and post-adoption benefits in banking sector

Business Intelligence (BI) Systems have been theorized as providing immerse benefits to organizations that adopt them. These benefits include: improved customer satisfaction improved decision-making process, provision of faster and more accurate reporting, increased revenues and increased competitive advantage. However, there are limited studies on the factors affecting adoption and actual benefits accruing to organizations adopting the system. The main aim of this study is to develop an integrated model for determining BI System’s adoption and post-adoption benefits in banking industry. The proposed model is an integration of the Diffusion of Innovations Theory (DOI), Technology-Organization-Environment (TOE) Framework, the Institutional Theory (INT), and Kaplan & Norton’s Balance Scorecard (BSC). This model is different from other studies in the context of organizational adoption of BI Systems as it integrates the determinants, and evaluation of the benefits of the technology in one study. There is also a moderator Time since adoption which is used to moderate the impact of the extent of adoption to organizational performance.
On the road – listening to data subjects’ personal mobility data privacy concerns

ABSTRACT Efficient utilisation of new mobility data-based services and promotion of acceptance of data collection from vehicles and people demand an understanding of mobility data privacy concerns, associated with increasing use of tracking technologies, diverse data usages and complex data collection environments. Understanding privacy concerns enables improved service and system development and identification of appropriate data management solutions that contribute to data subjects’ privacy protection, as well as efficient utilisation of the collected data. This study aimed to explore earlier research findings on privacy concerns evaluation and investigate their validity in mobility data collection. Explorative multimethod research was conducted in a mobility service pilot through data controller interviews, user interviews and a user survey. The study's results indicated the need to revise and complement existing privacy concerns evaluation in mobility data collection contexts. The primary findings were as follows: (1) Privacy concerns specific to the mobility data collection context exist. (2) Privacy concerns may change during the service use. (3) Users are not necessarily personally worried about their privacy although they ponder on privacy issues. (4) In contrast to traditional ‘privacy calculus’ thinking, users’ expected benefits from data disclosure may also be driven by altruistic motives.
Implementation of OFDM Modulated Digital Communication Using Software Defined Radio Unit For Radar Applications

This paper presents an analysis and synthesis of Orthogonal Frequency Division Multiplexing (OFDM) modulated signal for Radar based applications, using Benchmark’s Software Defined Radio (SDR) unit. OFDM is a trending digital modulation scheme based on multi-carriers. Experimental trials were performed using the SDR setup allowing for analysis of real time data to assess the difficulties involved, in an attempt to make it more suitable for Radar based detection of slow moving targets. This thereby aids in the implementation of small monostatic radar for micro-Doppler based detection of small UAVs, with reduced false alarm probability
Eliciting Persona Characteristics for Risk-based Decision Making

Personas are behavioural specifications of archetypical users in Human Factors Engineering and User Interaction research aimed at preventing biased views system designers may have of users. Personas are therefore nuanced representations of goals and expectations that should be addressed when designing systems. Previous work has shown how personas may be validated by grounding in qualitative models; however, more evidence is needed on the applicability for grounding models in risk decision making research. We present an approach for eliciting persona characteristics for risk-based decision making by using Observe Orient Decide Act (OODA) as a modelling baseline. The approach illustrates how modelling personas based on decision makers’ understanding of risk facilitates designing for risk and uncertainty.
Development of Corpus for Affect Analysis in Japanese

This paper presents a design of a dialogue corpus required for the research on affect analysis in Japanese. The research on analyzing and estimating emotional states of users during their interaction with robots and generally perceived cyberenvironment has been focused on developing sophisticated methods rather than gathering a relevant material for evaluation. In this paper we explain an urgent need for the change of this tendency and propose a design of a corpus meant to support research in this field. We also propose the first application of the corpus in the evaluation method proposed by us in the former research.
A Study of Learning Based Beamforming Methods for Speech Recognition

This paper presents a comparative study of three learning based beamforming methods that are specifically designed for robust speech recognition. The three methods are 1) neural network that predicts beamforming weights from generalized cross correlation (GCC) features; 2) neural network that predicts timefrequency (TF) mask which is used to estimate MVDR (minimum variance distortionless response) beamforming weights; 3) maximum likelihood estimation of beamforming weights to fit enhanced features to clean trained Gaussian mixture model. All three methods operate in frequency domain. They are evaluated on the CHiME-4 benchmarking speech recognition task and compared with traditional delay-and-sum and MVDR beamforming methods on the same speech recognition task. Discussions and future research directions are presented.
Do Trade Agreements Reduce the Volatility of Agricultural Assistance Rates ? ∗

The objective of this paper is to evaluate the extend to which trade agreements affect agricultural trade policy volatility. Using a new panel database compiled as part of the World Bank’s Agricultural Distortions research project, we estimate the effect of regionalism (proxied in various ways) on the volatility of price distortions measured by the absolute value of their first differences, averaged, for each country and year, over all agricultural goods. Using an instrumental-variable approach to correct for the endogeneity of regional trade agreements, (RTAs), we find that participation in RTAs has a significantly negative effect on agricultural trade policy volatility. We find that the WTO’s agricultural agreement also contributed to reducing agricultural trade policy volatility, in spite of the weak disciplines involved, but the effect is only weakly identified. Our results are robust to a variety of robustness checks and hold, in particular, for the Latin American sub-sample. JEL classification numbers: F10.
Screening of Chronic Kidney Disease Patients Using Gradient Boosted Trees with Grid Optimization

This work presents a development of a system which assists in chronic kidney disease screening. A gradient boosting algorithm with decision tree model is applied to generate a reliable diagnosis prediction technique. The hyperparameters in model generation process are optimally adjusted with grid search methods. Synthetic Minority Over-Sampling Technique, SMOTE, is applied to solve an imbalanced issue of the used data set. The model is used as a core prediction engine in a web-based application to facilitate a screening task on chronic kidney disease patients in Thailand. In experiments, the proposed system perfectly performs for full scores in all measurements including accuracy, precision and f-measure. The testing with the actual patient data obtains the all correct results approved by a medical expert.
Cost Analysis of the Faint and Fall Clinic : A New Model in Health-care Delivery

Aims: The Faint and Fall Clinic (FFC) at the University of Utah offers a multidisciplinary, guideline-driven approach to prompt diagnosis and treatment of patients presenting with faint or fall. We have recently shown that the standardized approach used in the FFC resulted in a higher rate of diagnosis and a decrease in the utilization of costly tests when compared with the conventional approach. The purpose of this study was to evaluate the financial performance of the FFC during its first year of operation. Methods and results: Operating margin was defined as payments less direct expenses. Contribution margin was defined as operating margin less administrative and support costs. A total of 486 patients were seen, with more than half covered by Medicare. Excluding all laboratory tests, a total of 1,790 procedures and tests were performed. The total charges and payments were $3,645,900 and $1,615,400 respectively with a reimbursement rate averaging at 44.3%. The total direct costs and administrative supports were $1,046,000 and $105,830 totaling $1,151,830. The operating and contribution margins averaged 35.2% and 28.7%, respectively. Conclusions: In conclusion, the FFC provides a novel approach to patients with faint and fall that not only improves outcome but also appears to be profitable.
Global Localization on OpenStreetMap Using 4-bit Semantic Descriptors

Localization is an essential capability of mobile vehicles such as robots or autonomous cars. Localization systems that do not rely on GNSS typically require a map of the environment to compare the local sensor readings to the map. In most cases, building such a model requires an explicit mapping phase for recording sensor data in the environment. In this paper, we investigate the problem of localizing a mobile vehicle equipped with a 3D LiDAR scanner, driving on urban roads without mapping the environment beforehand. We propose an approach that builds upon publicly available map information from OpenStreetMap and turns them into a compact map representation that can be used for Monte Carlo localization. This map requires to store only a tiny 4-bit descriptor per location and is still able to globally localize and track a vehicle. We implemented our approach and thoroughly tested it on real-world data using the KITTI datasets. The experiments presented in this paper suggest that we can estimate the vehicle pose effectively only using OpenStreetMap data.
Genetic Algorithms for Estimation of Reflectance Parameters

Most of the current appearance acquisition methods require the use of specialized equipment and/or involved capture sessions. We propose a singleimage approach based on genetic algorithms which greatly simplifies the process, and allows to estimate reflectance properties of both opaque and translucent objects. Given the underconstrained nature of an image-based approach, we leverage two well-known illumination models, Phong and the diffuse approximation, to reduce the high-dimensional parameter space. Additionally, a study was carried out to provide guidance in the election of the configuration parameters of the genetic algorithm. Universidad de Zaragoza Belen Masia Adolfo Munoz Alfonso Tolosa Oscar Anson Jorge Lopez-Moreno Jorge Jimenez Diego Gutierrez
SERVICES EXPORT AND ITS IMPLICATIONS ON ECONOMIC GROWTH IN INDIA : AN EMPIRICAL STUDY

The structural shift in India’s services export since 2003-04 may be attributed to rapid expansion in international trade and investment facilitated by an increased liberalization and the use of technology. The study aims to investigate the possible cointegration and the direction of causality between software services export and nonsoftware miscellaneous services (business, financial, communication and other miscellaneous) export and economic growth during the period 2000-01:Q1-2008-09:Q4. Granger Causality Test conducted in a Vector Error Correction Model (VECM) framework revealed unidirectional causality from software services export to economic growth. To investigate the long and short run dynamics among the variables impulse response analysis is also done.
Patterns as Structure , Process , and Community

The modern patterns movement, with its roots in the work of Christopher Alexander, has made impressive strides since the 1990s. Most of this work has focused on the creation of patterns as structures for documenting knowledge. This paper argues that two other aspects of patterns—process and community—have received less attention. However, the time is prime to increase the discussion of how the patterns community can put more emphasis on process and the creation of wider communities. The goal of this paper is to propose a manifesto for the patterns community to make better use of all three features in patterns: structure, process, and community.
Loan-To-Value Policy and Housing Loans: effects on constrained borrowers

This paper explores the effects on constrained borrowers of an LTV limit implemented on September 2013 on two segments of housing loans that constitute the bulk of housing loan originations in Brazil. LTV limits and related policies entail identification challenges, since constrained individuals are no longer directly observed after the regulation. We use comprehensive credit register information of individual housing loans augmented with a detailed, granular employment register. We focus on the average treatment effect on the treated borrowers, defined as the ones that would violate the LTV limit if allowed to do so. Partially observed treatment status is overcome by the use of an adjusted difference-in-difference method. In the housing loan segment that was subject to a sudden increase in demand due to broader eligibility rules, constrained individuals borrow housing loans with higher interest rates, shortened maturities, and, as expected, reduced loan amounts and LTV. These borrowers also purchase more affordable homes and are less likely to be in arrears 12 months in the future. In the other housing loan segment, subject to more stringent eligibility criteria, constrained borrowers also meet the LTV threshold, but the resulting contract terms stay roughly the same.
PRODUCTION AND PARTIAL PURIFICATION OF ANTIFUNGAL CHITINASE FROM Bacillus cereus VITSD 3

The current work was designed to isolate and characterize chitin degrading bacteria. Among the 55 bacterial colonies isolated from 7 different soil samples, 4 isolates were capable of degrading chitinase, among which one strain VITSD3 was found to be potent. Based on the morphological, biochemical and molecular characterization of VITSD3 the isolate was confirmed as Bacillus cereus (Genbank accession number: KC961638), designated as Bacillus cereus VITSD3. The crude enzyme had a total activity of 220 U, precipitated with 44.8 U and 22.5 U for dialysed sample. The hydrolysed product NAG (N-Acetyl Glucosamine) from chitin was analysed by high-pressure liquid chromatography (HPLC). The molecular weight of the chitinase was determined using SDS PAGE and found to be 55 kDa. The partially purified chitinase produced from Bacillus cereus VITSD3 showed antifungal activity against Aspergillus fumigatus (18 mm), Aspergillus niger (6 mm) and Aspergillus flavus (15 mm). Hence the investigation suggests a potential benefit of partially purified chitinase extracted from Bacillus cereus VITSD3 which will serve as an excellent antifungal potential with therapeutic use.
PREDICTING BACHELOR ’ S DEGREE GRADUATION CASE STUDY ON FACULTY OF SCIENCE , KMITL , THAILAND

The purpose of this study is to characterize the differences between graduate and dropout for bachelor’s program of the student in The faculty of Science KMITL, Thailand. The discriminant technique, by stepwise method, is used for analyzing data that is gathered from personal records of students. The continuous variables are checked for normality by Kolmogorov-Smirnov test and nonnormal variables are transformed by rank transformation analysis. Homogeneity of variance-covariance matrices is checked by using an approximate Box’s M test. The accuracy rate of classifications is used for measuring the validity of the model. The proposed model gives 80.3% collectly classified with 15.9% type I error and 27.3% type II error.