Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Dynamic Relationship Capabilities on B 2 B Lolyalty MÁRTON VILMÁNYI

The management of inter-organisational collaboration is still a key issue even in today’s networked economy. This is particularly the case when the success of an organisation not only depends on its internal efficiency and productivity, but rather on the success of those network(s) within which the organisation operates. This study is aimed at finding out how the embedded patterns of reconfiguration in relationship behaviour influence the success of collaboration between organisations. The success of relationships can be illustrated on several dimensions. In the different models, these dimensions appear in various correlations, but there are only a few models where the role of dynamic relationship capabilities are examined in the view of the quality of the relationship and there are even fewer theoretical approaches that examine the coherence between dynamic relationship capabilities and interorganisational loyalty. In the approach of this study, dynamic relationship capability refers to a process during which organisations are able and willing to demonstrate permanent flexible behaviour and reconfigure their actions and behaviour in order to meet the expectations of their partners. Reconfiguration propensity that appears on the various levels of dynamic relationship capabilities also represents a continued development of relationship capabilities. DYNAMIC RELATIONSHIP CAPABILITIES
Stuttgart Deep Reinforcement Learning in Dialog Systems

This thesis explores advanced deep reinforcement learning methods for learning dialog policies. While many recent contributions in the area of reinforcement learning focus on learning how to play Atari games, this thesis applies them in a real-world scenario. When talking to a dialog system, the dialog policy is the component which chooses the response based on the history of the interaction between user and system. Nowadays, dialog policies may be learned automatically by training a reinforcement learning agent with a user simulator. In this thesis, a baseline method for dialog policy learning is implemented and extended by various state-of-the art deep reinforcement learning methods. An ablation study discusses the significance of each extension, highlighting beneficial and harmful addidtions. Each extended agent is shown to perform better than the baseline method with all agents outperforming policies from an existing benchmark. Two agents even prove to be on par with handcrafted dialog policies. Along with the quantitative evaluation, qualitative results are provided in the form of chats between a user and a trained agent.
Evaluation of the therapeutic effect of Nigella sativa crude oil and its blend with omega-3 fatty acid-rich oils in a modified hepatorenal syndrome model in rats

In the present study, the hepato and reno-protective effect of Nigella sativa crude oil and its binary blend with omega-3 fatty acid-rich oils (fish and flaxseed oils) was studied in a modified hepatorenal syndrome model (MHRS) in rats. MHRS was induced through feeding a high fructose diet followed by an intraperitoneal injection of galactosamine hydrochloride. Nigella oil and its different blends were given as a daily oral dose to MHRS rats. Two control groups of MHRS and normal healthy rats were run. Different biochemical and nutritional parameters were assessed. The induction of MHRS produced liver and kidney dysfunction, and elevated oxidative stress, an inflammatory biomarker, endothelin 1, and plasma cholesterol. Reduced plasma high density lipoprotein cholesterol, albumin and Ca and elevated urinary N-acetyl-β-D-Glucosaminidase and liver fats were noticed. The administration of Nigella crude oil that originally had 0.2% total omega-3 fatty acids or its blend with fish oil (17.9% omega-3) or flaxseed oil (42.1% omega-3) significantly improved all biochemical parameters of MHRS. There was no significant difference in the biochemical parameters among the different oil treated groups regardless of the omega-3 fatty acid content. This may point out to the potential profound effect of the volatile oil fraction of Nigella crude oil which may compensates for its low omega-3 content.
End-to-End Conversation Modeling : Moving beyond Chitchat DSTC 7 Task 2 Description ( v 1 . 0 )

Recent work [1, 2, 3, 4, 5, etc.] has shown that conversational models can be trained in a completely end-to-end and data-driven fashion, without any hand-coding. However, such prior work has been mostly applied to chitchat, as this is the salient trait of the social media data (e.g., Twitter [1]) utilized to train these systems. To effectively move beyond chitchat, fully data-driven models would need grounding in the real world and access to external knowledge (textual or structured), in order to produce system responses that are both substantive and “useful”. Figure 1 illustrates this desideratum: while an ideal response would directly include entities relevant to the current conversation, most state-of-the-art neural conversation models produce responses that are
Human Resource Development and Competence on Employee Performance through Application of Human Resource Accounting at PT .

HR is one of the resources that cannot be released from the management of a business. This study aims to analyze the influence of (1) human resource (HR) development on the application of human resource accounting (HRA); (2) HR competencies on the application of HRA; (3) HR development on employee performance; (4) HR competencies on employee performance; (5) the application of HRA on employee performance; (6) the HR development through the application of HRA has an effect on employee performance; (7) HR competencies through the application of HRA has an influence on effect performance. To achieve these objectives, the method of data collection was done through observation, questionnaires, and interviews. Analysis of the data used were validity and reliability test, descriptive analysis, analysis of the measurement model (outer model), analysis of the structure model (inner model), and hypothesis testing. The results of the analysis show that the HR development has had a positive and significant influence on the application of HRA. HR competence has had a positive and significant influence on the application of HRA. The HR development has a positive and significant influence on employee performance. HR competence can improve employee performance and have a significant influence on employee performance. The application of HRA has a positive and significant influence on employee performance. The mediation test results that show that the application of HRA has not been able to mediate the influence of HR development on the performance of employees, but the development of human resources can only influence employee performance. The test results mediate the influence of competencies with employee performance through the application of HRA. Wherein the mediation test in this study shows that the application of HRA cannot mediate the influence of competency on employee performance.
Real-time Detailed Video Analysis of Fruit Flies

contour area Feature(s) • Type: classifier • Input: the contours of two flies • Output: whether the contours are ordered as male-female or female-male • Data augmented by reversing the ordering of examples • Feature(s): areas and aspect ratios of both contours • Model: • feature standardization, followed by • logistic regression • Results: • 0.7% test error • (1.4% without aspect ratio features) • 0.7 ms runtime
The most direct way to monitor PCR amplification for quantification and mutation detection

The polymerase chain reaction (PCR) is perhaps the most powerful modern tool available for today's molecular biologist. Its extraordinary sensitivity allows for the detection of only a few molecules of DNA. The sensitivity of PCR is often complimented by the specificity of hybridization techniques such as Southern blotting or oligonucleotide hybridization. Amplification and hybridization techniques are usually performed separately. However, with the recent development of LightCyclerTM technology, PCR amplification and hybridization probe detection occur simultaneously in homogeneous solution. That is, both amplification and hybridization analysis can proceed in the same reaction. Because the LightCycler Instrument uses rapid cycling techniques (12), the entire process is finished in 15–30 min.
Compressed Suffix Arrays for Massive Data Sirén , Jouni 2009-0615 T 05 : 12 : 47

We present a fast space-efficient algorithm for constructing compressed suffix arrays (CSA). The algorithm requires O(n log n) time in the worst case, and only O(n) bits of extra space in addition to the CSA. As the basic step, we describe an algorithm for merging two CSAs. We show that the construction algorithm can be parallelized in a symmetric multiprocessor system, and discuss the possibility of a distributed implementation. We also describe a parallel implementation of the algorithm, capable of indexing several gigabytes per hour.
Chapter 3 Nonclassical States of Light and Mechanics

This chapter reports on theoretical protocols for generating nonclassical states of light and mechanics. Nonclassical states are understood as squeezed states, entangled states or states with negative Wigner function, and the nonclassicality can refer either to light, to mechanics, or to both, light and mechanics. In all protocols nonclassicality arises from a strong optomechanical coupling. Some protocols rely in addition on homodyne detection or photon counting of light. K. Hammerer (B) Institute for Theoretical Physics, Institute for Gravitational Physics (Albert-Einstein-Institute), Leibniz University Hannover, Hanover, Germany e-mail: klemens.hammerer@itp.uni-hannover.de C. Genes University of Innsbruck, Innsbruck, Austria e-mail: claudiu.genes@uibk.ac. at D. Vitali · P. Tombesi University of Camerino, Camerino, Italy e-mail: david.vitali@unicam.it P. Tombesi e-mail: paolo.tombesi@unicam.it G. Milburn University of Queensland, Brisbane, Australia e-mail: milburn@physics.uq. edu.au C. Simon University of Calgary, Calgary, Canada e-mail: csimo@ucalgary.ca D. Bouwmeester Huygens-Kamerlingh Onnes Laboratory, Leiden University, Leiden, The Netherlands Department of Physics, University of California Santa Barbara, Santa Barbara, USA e-mail: bouwmeester@physics.ucsb. edu M. Aspelmeyer et al. (eds.), Cavity Optomechanics, Quantum Science and Technology, 25 DOI: 10.1007/978-3-642-55312-7_3, © Springer-Verlag Berlin Heidelberg 2014 26 K. Hammerer et al.
A Survey of Word Reordering Model in Statistical Machine Translation

Machine translation is the process of translating one natural language in to another natural language by computers. In statistical machine translation word reordering is a big challenge between distant language pair. It is important factor for its quality and efficiency. Word reordering is major challenge For Indian languages who have big structural difference like English and Hindi language. This paper present description about statistical machine translation, reordering model and reordering types. Keywords—Machine translation,Statictical machine translation,word reordering, parser. __________________________________________________*****_________________________________________________
Analysis of Aggregate Trips Across Paratransit Providers

This paper estimates the demand for transportation systems that are used primarily by disabled individuals. These systems are known as paratransit systems, and have experienced large increases in number and average size over the past 15 years. We Þrst use a national database and standard time series techniques to model aggregate demand. We then use a unique data set of administrative records from a paratransit system in central Virginia to estimate standard and nonstandard count models of individual demand. We conclude that most of the demand growth is from new passengers, but that predicting the growth of new passengers is very difficult. Our results also highlight the importance of incorporating autocorrelation and possible sample attrition into standard count models. ∗We would like to thank the JAUNT Board of Directors for providing us with access to the data, Debbie Taylor from JAUNT for collecting it and helping us to understand it, Helen Poore, Betty Bollendorf, and Betty Saunders from CTS for collecting and helping us to understand the CTS data, and David Givens for excellent research assistance. Steven Stern was a member of the JAUNT Board of Directors at the time that much of the work for this paper was performed. The views expressed in this paper are the authors and not those of the JAUNT Board of Directors, the Federal Reserve Bank of New York, or the Federal Reserve System. All errors are the fault of the authors. Corresponding Author: Steven Stern, Department of Economics, Rouss Hall, University of Virginia, Charlottesville, VA 22903; Email: sns5r@virignia.edu; Phone: (804) 924-6754; FAX: (804) 982-2904.
LABOUR MARKET RESPONSES TO TRADE & TRADE STRUCTURE : A PANEL STUDY OF THE MALAYSIAN MANUFACTURING

Intra-industry trade (IIT) has become an important component of Malaysia’s international trade in manufactured goods. This study reveals that besides trade flows per se, the structure of trade, particularly IIT, is also of importance to the Malaysian manufacturing labour market. The empirical findings on the contemporaneous effects of intra-industry trade on aggregate employment are found to be positive and significant. More importantly, the long run impact of intra-industry trade is greater than the corresponding short run effect. On average, there is more impact of intra-industry trade on the quantity side of the labour market (that is employment) than on the wage side. In total, there is supportive evidence that foreign trade, particularly intra-industry, has stimulated employment growth of the manufacturing sector. Evelyn Devadason Department of Applied Economics Faculty of Economics & Administration University of Malaya 50603 Kuala Lumpur Malaysia. Tel: 603-79673726 Fax: 603-79567252 Email: evelyns@um.edu. my * The study forms part of the author’s ongoing research for the Doctoral dissertation at the University of Malaya.
Beyond Hypothesis-Testing : using Approximate Bayesian Computation for comparing multiple models of cultural transmission in Neolithic Europe

The current renaissance of computer simulation in archaeology is showcasing a wide array of successful applications where archaeological theory-building is formalised, and existing methods are evaluated and refined through “tactical” simulations (Lake 2010). However, hypothesis-testing continues to suffer the difficult task of comparing simulation outputs against empirically observed archaeological data. The mathematical rigour used in statistical science is hardly applied in many cases, and simulation models are often evaluated exclusively in visual and qualitative terms. Moreover, the ultimate objective is often not the rejection of a null model, but to evaluate the goodness-of-fit of a purposely designed archaeological model. Whilst this approach has undoubtedly yielded a useful basis for further theory-building through the assessment of mismatches between the artificial and archaeological data, it does not question whether alternative models that can equally, or even better, explain the observed pattern that exists. Such a multi-model approach is beginning to be used in the evaluation of competing statistical models in anthropology and archaeology through the epistemological framework of information-criteria (e.g. Beheim and Bell 2011, Eve and Crema 2014). Similar approaches in agent-based simulation are however still uncommon (but see Piou et al 2009).
E-therapy : case studies, guiding principles, and the clinical potential of the Internet

Here, a leading provider of online mental health information, Dr. Robert Hsiung, has gathered a group of distinguished contributors to discuss clinical, ethical, and legal issues pertaining to e-therapy. Full of case studies and examples of active programs that deliver mental health information and therapy via new media, E-Therapy offers first-hand accounts of the potential and risks of recent trends in 'distance therapy' and 'telepsychiatry. ' Chapters include * The Internet 'Expert': Ronald Pies * An E-Patient's Story: Martha Ainsworth * Chat Room Therapy: Gary S. Stofle * Using E-mail to Support Outpatient Treatment: Joel Yager * Community Telepsychiatry: Sara F. Gibson * An Online Self-Help Group Hosted by a Mental Health Professional: Robert C Hsiung * Principles of Professional Ethics: Robert C Hsiung * Legal Ethics in On-line Mental Health: Nicholas P. Terry
Enhancement of Dissolution Rate of Gliclazide by Liquisolid Technique

The purpose of the present research was to investigate the in vitro dissolution properties of poorly water soluble gliclazide by utilizing liquisolid technique. Avicel PH 102 and Neusilin were employed as carrier material; Aerosil 200 as coating material and crosspovidone as disintegrant respectively for preparing liquisolid compacts. Liquisolid compacts were prepared and evaluated for their tabletting properties. The tabletting properties of the liquisolid compacts were within the acceptable limits and drug release rates of all prepared LS compacts were distinctly higher as compared to directly compressed tablets, and marketed tablets. The results showed that liquisolid compacts demonstrated significantly higher drug release rates than those of conventionally prepared directly compressible tablets. This was due to an increase in wetting properties and surface of drug available for dissolution. From this study it concludes that the LS technique is an effective approach to enhance the dissolution rate of gliclazide.
Reference Values for Spirometry for Healthy Sri Lankan Adults : Age between 20 To 65 Years

DOI: 10.21276/sjams.2018. 6.9. 38 Abstract:Spirometry is the most important method of investigation in respiratory medicine. When conducting Spirometry, South Indians’ references were mostly used as prediction values for Sri Lankans. There can be some misinterpretations of lung function test results when using Indian references for Sri Lankan individuals. Hence, objectives of this study were to develop separate prediction equations, and investigate reference values for Spirometry for healthy Sri Lankan adults’ of age between 20 to 65 years and compare these values with reference values which obtained using South Indian references of Sri Lankan individuals. Healthy nonsmoking individuals were selected as the study sample and the sample size was 1021 subjects including 520 (50.9%) males and 501(49.1%) females. Data collection was categorized to 20-25, 2635, 36-45, 46-55, 56-65 years of age groups to make the data collection more reliable. Prediction equations for Forced Vital Capacity (FVC), Force Expiratory volume within first second (FEV1), FEV1/FVC%, Peak Expiratory Flow Rate (PEFR) were derived using each individuals’ age, standing height, weight and BMI for both male and females separately and Lower Limits of Normal (LLN) were calculated to clarify the level of diagnosing of a disease condition. GAMLSS model with Box-Cox-Cole-Green (BCCG) family distribution was selected as the best fitted model to derive prediction equations and prediction values were generated using those equations. When compare these prediction values, FVC, FEV1 and PEFR values were overestimated while FEV1/FVC% was underestimated by reference values which obtained using South Indian references of Sri Lankan individuals for both males and females and there is significant difference between reference values which obtained using South Indian references and Sri Lankan references of Sri Lankan individuals at 5% significant level. Hence, this study is concluded that separate reference values can be used for Sri Lankan individuals when conducting Spirometry instead of using South Indian references.
A Neural Forth Abstract Machine

Recently, a renewed interest in neural models of computation has sparked a surge of invention in neural architectures that can learn to perform algorithms akin to traditional computers, using primitives such as memory access and stack manipulation (Graves et al., 2014; Joulin & Mikolov, 2015; Kaiser & Sutskever, 2016; Kurach et al., 2016; Reed & de Freitas, 2016). These architectures can be trained from data through standard gradient descent methods, enabling machines to learn complex algorithmic behavior. However, for many tasks training data is scarce. In these cases the programmer may know the rough structure of the program, or how to implement sub-routines that are likely necessary to solve the task. In these scenarios, the question remains how to best exploit this type of knowledge when learning algorithms.
Distribution and dynamics of bacterioplankton production in a polymictic tropical lake ( Lago Xolotl án , Nicaragua )

From 1988 to 1993 we assessed the variability of bacterioplankton production and biomass in Lake Xolotlán (L. Managua), Nicaragua via [ 3H]thymidine incorporation into DNA and cell counting. Bacterial production ranged from 3 to 8μg C l−1 h−1, and since production was equal throughout the water column, areal production was high (≈ 600–1200 mg C m−2 d−1). Bacterial abundance in Lake Managua was extremely high, 7–30 × 1 9 cells l−1. Thus, specific rates of bacterial production were low. There was a strong correlation between production and number and the specific rate of bacterial production was constant. Comparable measurements of production via [3H]leucine incorporation into proteins indicated that bacteria were experiencing ‘balanced growth’. We conclude that bacterioplankton in Lake Xolotlán had reached its carrying capacity and a significant correlation between bacterial production and concentration of phaeophytin implied that dead or dying algae was the limiting substrate for bacterioplankton. The majority of bacterial number and most of bacterial production (up to 75%) were associated with particles in the> 3-μm fraction, probably lysing algal cells to which bacterioplankton were ‘attached’. Grazing on bacterioplankton must be low and bacteria should be a ‘sink’ for organic matter in Lake Xolotlán.
ancing the Perfo ance of Wireless Sensor Networks with MIMO Communications

Wireless sensor networks are an enabling technology for many future surveillance-oriented applications. Before a practical wireless sensor network is realized, however, significant challenges must be overcome. Chief among the obstacles to netted sensors is providing low power, robust communications between sensor nodes. Multiple lnput, Multiple Output (MIMO) communication promises performance enhancements over conventional single input, single output (SISO) technology for the same radiated power If leveraged in a sensor network, MIMO may be able to provide significant network performance improvements in power consumption, latency, and network robustness. This paper investigates the benefit of MIMO implementations in multihop wireless sensor networks in terms of the mean path length. We find that MIMO provides improvement to wireless sensor networks, particularly those that have low to midrange node densities.