Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Structural Relaxation and Crystallization of Bulk Metallic Glasses in Powder Bed Fusion Additive Manufacturing

In recent years, bulk metallic glasses (BMGs) have attracted intensive interest not only in the science community but also in industry. Their amorphous structures give them many desirable properties, such as high yield stress (1-5 GPa) and high elastic strain limits (up to ∼2%) compared to typical crystalline metals [1]. In addition to the remarkable features of additive manufacturing, i.e. high design flexibility and near-net-shape formability, the rapid cooling rate of this technology should also be noted. The cooling rates at the solidification front can reach the order of 106 K/s in selective beam melting [2], which is very beneficial for glass forming. In spite of the fact that this rapid technology has been employed to fabricate BMGs [3], the knowledge about structural relaxation and crystallization in the process is still in demand. Structural relaxation brings the non-equilibrium glassy material back into the equilibrium undercooled liquid state, whereas crystallites are formed during crystallization, both of which will lead to a loss of the characteristic features of BMGs. Understanding these phenomena and the possibility to numerically determine processing windows is the subject of current research. Phenomenological models for structural relaxation and crystallization are coupled to the existing simulation software for powder-bed-based additive manufacturing. They are the well-known Kohlrausch-Williams-Watts (KWW) model, which has been extensively used to describe the structural relaxation [4] and the Nakamura model, which has been applied to investigate the crystallization of polymers during additive manufacturing [5]. The preliminary results will be presented. The relaxation or crystallization map depicts space-distribution and its evolution with respect to time, qualitatively.
PILOT STUDY ON THE EFFECTS OF UPPER LIMB LOSS AND PROSTHESIS USE ON LOCOMOTOR STABILITY

American Academy of Orthotists & Prosthetists 43rd Academy Annual Meeting & Scientific Symposium March 1-4, 2017 FPTH14 INTRODUCTION During steady-state walking, natural arm dynamics facilitate locomotor stability by minimizing body angular momentum through counterbalancing leg motion [1] and reducing trunk motion to constrain body center-of-mass (BCoM) excursion [2]. Consequently, persons with upper limb loss may experience reduced locomotor stability that may be dependent on prosthesis use. This pilot study investigated the effects of prosthesis use and matching inertial properties of the prosthetic limb to the sound limb on stability during walking.
2 Skeletal Anatomy in Densitometry

The bones of the skeleton can be described by four characteristics, one of which is unique to densitometry. The characterizations are important, as this often determines which skeletal site is the most desirable to measure in a given clinical situation. A skeletal site may be described as axial or appendicular, weight bearing or non-weight bearing, central or peripheral, and predominantly cortical or trabecular.
Analysis on Control Stability of STATCOM Applied on Weak Power System

Control stability when Multi-level STATCOM is applied on weak power system is discussed in this paper. In order to research the stability of weak system quantitatively, the current inner open-loop transfer function with system impedance is presented. Nyquist curve is used to demonstrate the relationship between the system impedance and the system control performance. Then a new control strategy - adding the current’s proportion-differential (PD) to the feed forward voltage, is proposed. This control strategy can eliminate the positive feedback action caused by system impedance. Finally, test result proves that the above theoretical analysis is correct.
Classification Technique of Interviewer-Bot Result using Naïve Bayes and Phrase Reinforcement Algorithms

Students with hectic college schedules tend not to have enough time repeating the course material. Meanwhile, after they graduated, to be accepted in a foreign company with a higher salary, they must be ready for the English-based interview. To meet these needs, they try to practice conversing with someone who is proficient in English. On the other hand, it is not easy to have someone who is not only proficient in English, but also understand about a job interview related topics. This paper presents the development of a machine which is able to provide practice on English-based interviews, specifically on job interviews. Interviewer machine (interviewer bot) is expected to help students practice on speaking English in particular issue of finding suitable job. The interviewer machine design uses words from a chat bot database named ALICE to mimic human intelligence that can be applied to a search engine using AIML. Naive Bayes algorithm is used to classify the interview results into three categories: POTENTIAL, TALENT and INTEREST students. Furthermore, based on the classification result, the summary is made at the end of the interview session by using phrase reinforcement algorithms. By using this bot, students are expected to practice their listening and speaking skills, also to be familiar with the questions often asked in job interviews so that they can prepare the proper answers. In addition, the bot’ users could know their potential, talent and interest in finding a job, so they could apply to the appropriate companies. Based on the validation results of 50 respondents, the accuracy degree of interviewer chat-bot (interviewer engine) response obtained 86.93%.
Aalborg Universitet An Adaptive Power Sharing Control for Management of DC Microgrids Powered by Fuel Cell and Storage System

This paper presents an adaptive powersharing methodology for management of dc microgrids powered by fuel cell (FC) and storage system (SS). In this context, the use of an adaptive k-sharing function in the control scheme is proposed to compensate the fast transients on the ac-side and manage the power sharing at steady-state regime between the FC and SS. The adaptive k-sharing is implemented with a low-pass filter transfer function for the FC and a complementary transfer function associated with the adaptive k-sharing gain for the SS. The proposed adaptive k-sharing function links the FC and the SS dynamics with the management of the dc microgrid, ensuring that the entire FC operation is performed in accordance with its operational limits. One of the main advantages of the proposed adaptive k-sharing is to reach high levels of stability and minimum disruptions on the FC terminals. To evaluate the feasibility of the proposed approach, we analyze the k-sharing behavior to determine the operational limits of the dc microgrid. Finally, to support the theoretical analysis we carried out a set of experimental results. Index Terms Fuel cells, dc/dc power converters, interconnected systems.
Linking Time Use to Implementation of Spatial Plans : What Explains the Dysfunctional Urban Landscapes in Zimbabwe ?

The paper examines the importance of time and related resources in spatial planning in order to explain how different types of plans have resulted in amorphous urban landscapes in Zimbabwe. It draws on the different perspectives, attitudes and practices of planners regarding the ‘time-spatial development gap’ [1]. There is a void in the studies that draws from similar perspectives in other African cities for enhanced spatial planning policy and practice. A study by Todes, Karam, Klug and Malaza (2010) has indicated the shortcomings of master planning and justified the adoption of new approaches to spatial planning in South Africa [23]. However, little could be seen as different from what master planning has been offering to development. To researchers, the story is just a question of semantics rather than of substance. The study came about as an investigation to decipher the reason for the so-called non-popularity of master planning in different circles of spatial and built environment field. Indeed, the gap in the nonimplementation of these important tools for spatial development has been a contentious issue of concern. This gap is sometimes widened by the existence of contrasting interests, values and priorities between planners (technocrats, trying as much as possible to be ‘professional’) and politicians (being Centre for Research on Settlements and Urbanism
The role of corporate governance on shariah non-compliant risk : Evidence from Southeast Asia

Shariah non-compliance risk is a unique feature in Islamic finance. Non-compliance with Shariah principles can lead to loss of income in the short-run and reputation risks in the short term. Since the overall governance and Shariah governance framework determines the status of Shariah compliance risk, this paper examines the relationship between the board of directors, shariah committee and shariah non-compliant risk. This paper empirically investigates, for the first time, how the structure of the board and shariah committee affects shariah non-compliance risk in Malaysia and Indonesia over the period 2010-2015. The results show that an independent board demands an additional and extensive shariah audit from a large and active shariah committee in order to certify their monitoring function as well as to protect the shariah law, resulting in higher shariah non-compliant income. We also find that a larger and active shariah committee is associated with effective monitoring, which, in turn, helps to reduce shariah non-compliant risk. Collectively, the results suggest that strong corporate governance reduces bank risk taking. The findings are of potential interest to policy makers, professionals and boards of directors, especially on issues relating to shariah noncompliance risk and the mandating of corporate governance practices.
Precious metals , Oil and the Exchange rate : Contemporaneous Spillover Effects

We investigate the concurrent interrelationship among gold, silver, platinum, palladium, crude oil and the US dollar exchange rate for the period January 1, 1999 to December 31, 2013. We employ both the conventional reduced form VAR methodology based on lead/lag dynamics and the Structural VAR (Rigobon, 2003) based on contemporaneous relationship among precious metals, crude oil and the US dollar. We obtain stark differences in our results based on the two methodologies. We contend that by not taking into consideration the contemporaneous interrelationships among assets, traditional VAR analysis leads to inaccurate outcomes and inevitably to inaccurate interpretation of causal relationships among variables.
Multicellular rosettes drive fluid-solid transition in epithelial tissues

Models for confluent biological tissues often describe the network formed by cells as a triple-junction network, similar to foams. However, higher order vertices or multicellular rosettes are prevalent in developmental and in vitro processes and have been recognized as crucial in many important aspects of morphogenesis, disease and physiology. In this work, we study the influence of rosettes on the mechanics of a confluent tissue. We find that the existence of rosettes in a tissue can greatly influence its rigidity. Using a generalized vertex model and effective medium theory we find a fluid-to-solid transition driven by rosette density and intracellular tensions. This transition exhibits several hallmarks of a second-order phase transition such as a growing correlation length and a universal critical scaling in the vicinity a critical point. Further, we elucidate the nature of rigidity transitions in dense biological tissues and other cellular structures using a generalized Maxwell constraint counting approach. This answers a long-standing puzzle of the origin of solidity in these systems.
Responsive and Self-Expressive Dialogue Generation

A neural conversation model is a promising approach to develop dialogue systems with the ability of chit-chat. It allows training a model in an end-to-end manner without complex rule design nor feature engineering. However, as a side effect, the neural model tends to generate safe but uninformative and insensitive responses like “OK” and “I don’t know. ” Such replies are called generic responses and regarded as a critical problem for user-engagement of dialogue systems. For a more engaging chit-chat experience, we propose a neural conversation model that generates responsive and self-expressive replies. Specifically, our model generates domain-aware and sentiment-rich responses. Experiments empirically confirmed that our model outperformed the sequence-to-sequence model; 68.1% of our responses were domain-aware with sentiment polarities, which was only 2.7% for responses generated by the sequence-to-sequence model.
On-Line labeled Topic Model Based on Global and Local Topic

A large number of electronic documents are labeled using human-interpretable annotations. High-efficiency text mining on such data set requires generative model that can flexibly comprehend the significant of observed labels while simultaneously uncovering topics within unlabeled documents. This paper presents a novel and generalized on-line labeled topic model based on global and local topic (GL-OLT) tracking the time evolution of topics in a sequentially organized multi-labeled corpus. GL-OLT topic model has an incrementally update principle based on time slices by an on-line fashion, and each label has not only a set of local topics, but also has several global topics. Empirical results are presented to demonstrate significant improvements accuracy of label predictive, and lower perplexity and high performance of our proposed model when compared with other models.
The drivers of brand equity in international nonprofit organizations

International nonprofit organizations are the world’s new “super brands,” their brand values are on par with major international corporations and they command unprecedented levels of trust. Yet brand building activities within these organizations appear relatively limited, perhaps because no brand equity models exist specifically for them. This study explores the drivers of brand equity for international nonprofit organizations by developing a model using a combination of a system dynamics approach and grounded theory development. This model proposes that four key variables drive brand equity in these organizations: consistency, focus, trust and partnerships, and advances eleven specific recommendations for nonprofit brand managers. These recommendations are based on the causal loop diagrams for the four key variables which offer a deeper understanding of what influences these four key variables and how they interact.
Isolation and Characterization of NBS-Encoding Disease Resistance Gene Analogs in Watermelon against Fusarium Wilt

Fusarium wilt (Fusarium oxysporum f. sp. niveum) in watermelon is one of the deadliest diseases around the globe, and availability of disease-resistant varieties is moderate. Disease management utilizing resistance genes (R-genes)/resistance gene analogs (RGAs) has proven to be a promising and successful approach. In the present study, six watermelon RGAs were isolated from wild, fusarium wilt resistant genotype IIHR-82 (Citrullus lanatus var. citroides) using degenerate primers that identify nucleotide binding site-leucine-rich repeat (NBS–LRR) regions. Multiple sequence alignment of these RGAs identified the characteristic NBS– LRR motif, and BLASTp search revealed similarity of these RGAs with other pathogenesis-related proteins. Phylogeny and motif analysis revealed genetic diversity of RGAs within those isolated from watermelon and with other plant R-genes. The watermelon RGAs isolated in this study contained both TIR–NBS–LRR (TNL) and non-TIR–NBS–LRR (CNL) classes of Rgenes. Protein secondary structure prediction of these watermelon RGAs revealed the composition of proteins, including α-helix, β-strand, disordered region and other template-related information. Watermelon RGAs identified in the present study will help in the development of RGA-based markers for resistance to fusarium wilt of watermelon.
Development of a Low Cost 3D Printer Indicated to Prototyping Objects

A indústria 4.0 vem impactando a cadeia produtiva refletindo no desenvolvimento tecnológico sustentável, sendo que o uso da impressão em 3D se encontra entre as tendências que devem criar novas oportunidades de negócios, como confecção de peças personalizadas e de difícil aquisição, entre outras. Em países como Brasil a impressora 3D comercial ainda possui elevado custo. Assim, este estudo teve por objetivo desenvolver uma impressora 3D de baixo custo, aplicando o método RepRap de auto replicação, testar, calibrar e imprimir peça para comparar com uma impressora comercial similar certificada. Realizou-se a montagem de uma impressora similar ao modelo Prusa i3 com o firmware Marlin utilizado para controle de seus componentes e software Repetier para sua configuração e controle. Como resultado foi desenvolvida a impressora 3D configurada e calibrada realizando-se a comparação de qualidade imprimindo uma peça na impressora 3D de baixo custo e em impressora comercial certificada. Também foram fabricadas peças como tela protetora e suporte para filamento, visando a melhoria do projeto. Com esta pesquisa foi possível concluir que é possível desenvolver uma impressora 3D RepRap de baixo custo se comparada à impressora comercial certificada com características idênticas quanto a precisão na qualidade final da impressão.
Adaptive ground segmentation method for real-time mobile robot control

For an autonomous mobile robot operating in an unknown environment, distinguishing obstacles from the traversable ground region is an essential step in determining whether the robot can traverse the area. Ground segmentation thus plays a critical role in autonomous mobile robot navigation in challenging environments, especially in real time. In this article, a ground segmentation method is proposed that combines three techniques: gradient threshold, adaptive break point detection, and mean height evaluation. Based on three-dimensional (3D) point clouds obtained from a Velodyne HDL-32E sensor, and by exploiting the structure of a two-dimensional reference image, the 3D data are represented as a graph data structures. This process serves as both a preprocessing step and a visualization of very large data sets, mobile-generated data for segmentation, and building maps of the area. Various types of 3D data—such as ground regions near the sensor center, uneven regions, and sparse regions—need to be represented and segmented. For the ground regions, we apply the gradient threshold technique for segmentation. We address the uneven regions using adaptive break points. Finally, for the sparse region, we segment the ground by using a mean height evaluation.
The valuation of ecosystem services and assets for SEEA ecosystem accounting

The aim of this background paper is to provide a context for a national accounting-based approach to the valuation of ecosystem services and assets. In doing so, it is hoped that this material can support an informed discussion on how the variety of approaches to environmental valuation that have been developed may be best applied for the implementation of the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) framework.
Modeling and simulation of nanowire based field-effect biosensors

3 The biofunctionalized boundary layer 6 3.1 The site-dissociation model . 7 3.2 Screening and biomolecules . 8 3.2. 1 The Metropolis-Monte-Carlo method . 9 3.2. 2 The Poisson-Boltzmann equation . 11 3.2. 3 PROPKA . 12 3.3 Summary . 13
The RWTH Aachen University Machine Translation Systems for WMT 2019

This paper describes the neural machine translation systems developed at the RWTH Aachen University for the German-English, Chinese-English and Kazakh-English news translation tasks of the Fourth Conference on Machine Translation (WMT19). For all tasks, the final submitted system is based on the Transformer architecture. We focus on improving data filtering and fine-tuning as well as systematically evaluating interesting approaches like unigram language model segmentation and transfer learning. For the De-En task, none of the tested methods gave a significant improvement over last years winning system and we end up with the same performance, resulting in 39.6% BLEU on newstest2019. In the Zh-En task, we show 1.3% BLEU improvement over our last year’s submission, which we mostly attribute to the splitting of long sentences during translation. We further report results on the Kazakh-English task where we gain improvements of 11.1% BLEU over our baseline system. On the same task we present a recent transfer learning approach, which uses half of the free parameters of our submission system and performs on par with it.
Effect of an Educational Session on Antibiotic Prescription among Primary Healthcare Physicians : An Interventional Study

Antimicrobial resistance is an increasing public health problem due to inappropriate antimicrobial use. Do educational interventions affect primary healthcare physicians’ antibiotic prescription practice? In this pre-post quasi-experimental interventional study, 43 primary care center Saudi Arabian physicians answered a self-administered questionnaire; institutional antibiotic guidelines and expert opinions were unanimous on factors affecting participants’ antibiotic regimen. Moreover, 82% were unaffected by patient/parent antibiotic demands. Differences in antimicrobial resistance knowledge and perception and current antimicrobial use were not significant. A significant post-intervention improvement existed in the practical knowledge of proper antimicrobial selection. All participants exhibited basic knowledge of antimicrobial use and the emerging resistance. The practical knowledge improvement through one educational session indicates the need for such programs to minimize antimicrobial resistance.
A review on aging or degradation of polymer optical fibers ( POFs ) : polymer chemistry and mathematical approach

We review the chemistry of POFs degradation or aging which has been done so far to understand the transmission loss in climatically stressed fibers. Mathematical models developed so far for light propagation and influence of aging process have also been reviewed. Introduction Short haul optical data communication through polymer optical fibers (POFs) has got much importance over silica optical fibers because of two main reasons; they are low cost of production and have high mechanical properties. But still these fibers have a main disadvantage of high transmission loss (or attenuation) due to absorption and scattering [1, 2, 3]. Since a decade investigations have been made to reduce intrinsic loss in POFs successfully by replacing H atoms in the core polymer molecules by halogen atoms (F, Cl and Br), deuterium atoms(d), blending core polymer with dopants (halogen containing compounds) and by using co-polymerization technique [4,5,6,7]. But main disadvantages of these techniques are hazardous nature of monomers and high cost of production. However, PMMA based POFs are widely being used in optical signal processing and many other optical applications under different environmental stress factors [8]. Some investigations have shown that degradation of macromolecules proceed via different fashions, formation of new fragments and change in their molecular network structure, when they are exposed to environmental stress factors for long time [9, 31]. Thus, in POFs transmission loss arises with different reasons. In this article, we report a general review on three degradation processes namely high temperature, humidity, and mechanical degradation. Existing mathematical models of light propagation and possible ways of incorporating aging parameters are also reviewed. Loss factors in POF Loss factors in a typical commercially available POF can be shown as below [9].