Miracle-dz/UniFAR-FTUs huggingface dataset:
Error-Workspace Analysis of Plane Mechanisms

In this paper the unconstrained motion (Error workspace) of some planar systems with joint clearance is analyzed. For the analysis, the joints are assumed to be revolute or translational. We also assume that all joint clearances are known. The kinematic image space is used to provide a geometric environment for the analysis of Error workspace. In this paper the Error workspace of a four-bar linkage, of a slidercrank mechanism and of two multiple-loop mechanisms are studied. Furthermore, mechanisms which have folding positions due to joint clearance are studied, too.
Effect of combination explant difference leaf part and concentration of active charcoal on callus initiation mangrove (Rhizophora Apiculata BI) by in-vitro

Rhizophora Apiculata BI is one of the mangroves that has many benefits, but to cultivate naturally takes a long time. The alternative to such problems is culture cultivation in vitro. One stage of in vitro culture is through callus formation. Initiation of callus in mangrove plants is inhibited because explant release phenol compound that causes browning. Thus, it takes explant and charcoal active in a medium that can support growth explant. The purpose of this research is to study the effect of the combination of leaf explant and different activated charcoal concentration on callus initiation, to analyze the color and texture of callus produced, and to study the effect of the combination of leaf explant and different concentration of activated charcoal on the growth of explant. The basal medium used was Murashige and Skoog (MS) formula with the addition of NAA 1 mg/L and BAP 0.3 mg/L, and activated charcoal at concentration 4, 12, 20 g/L as the medium treatments. A different section of explant between base and tip of leaves combined with active charcoal were grown in MS medium. Each treatment was conducted three replications. The results showed that the combination of explant section, i.e. base of the leaf as well as activated charcoal with a concentration of 12 g / L could induce callus formation. The color and texture of callus were brownish yellow and compact. The best growth (0.1685 g) of callus was obtained at the leaf tip section combined with 4 g / L activated charcoal.
Liquid-crystal tunable filter spectral imaging for discrimination between normal and neoplastic tissues in the brain

To complement a project toward the development of real-time optical biopsy for brain tissue discrimination and surgical resection guidance, the optical properties of various brain tissues were measured in vitro and correlated to features within clinical diffuse reflectance tissue spectra measured in vivo. Reflectance and transmission spectra of in vitro brain tissue samples were measured with a single-integrating-sphere spectrometer for wavelengths 400 to 1300 nm and converted to absorption and reduced scattering spectra using an inverse adding-doubling technique. Optical property spectra were classified as deriving from white matter, gray matter, or glioma tissue according to histopathologic diagnosis and mean absorption and reduced scattering spectra were calculated for the three tissue categories. Absolute reduced scattering and absorption values and their relative differences between histopathological groups agreed with previously reported results with the exception that absorption coefficients were often overestimated, most likely due to biologic variability or unaccounted light loss during reflectance/transmission measurement. Absorption spectra for the three tissue classes were dominated by hemoglobin absorption below 600 nm and water absorption above 900 nm and generally determined the shape of corresponding clinical diffuse reflectance spectra. Reduced scattering spectral shapes followed the power curve predicted by the Rayleigh limit of Mie scattering theory. While tissue absorption governed the shape of clinical diffuse reflectance spectra, reduced scattering determined their relative emission intensities between the three tissue categories. Introduction Diffuse reflectance spectroscopy is directly related to tissue absorption and scattering [1]. Because optical property differences between tissue types directly affect tissue diffuse reflectance, optical property spectra have the capability to explain feature disparities in diffuse reflectance spectra observed between normal and neoplastic tissues. The most obvious change within a diffuse reflectance spectrum during the progression from normal to neoplastic
Physicochemical properties and antioxidant activities of white dragon fruit peel pectin extracted with conventional and ultrasound-assisted extraction

Abstract The objective of this study was to investigate the optimal condition for extracting dragon fruit peel (DFP) pectin with the best physicochemical properties and high antioxidant activity by using conventional extraction (CE) and ultrasound-assisted extraction (UAE). DFP was extracted using CE and UAE method at 45, 60 and 75°C for 30 and 60 min. In this study, UAE significantly improved antioxidant activity of the extracted DFP pectin when comparing to CE. DFP extracted with UAE at 45°C for 30 min had the highest antioxidant activity (51.58 ± 0.30 by DPPH, 39.81 ± 1.43 mgGAE/100 g by ABTS) (p < 0.05). Moreover, UAE also increased the production yield of sample at 45°C for 30 min (9.38 ± 0.50%) (p < 0.05) which was higher than the treatments with CE. The chemical properties of DFP pectin including equivalent weight, degree of esterification, methoxyl content and total anhydroronic acid revealed that DFP pectin could be categorized as low-methoxyl pectin. Present study demonstrated that DFP pectin was an ideal alternative source of pectin with high antioxidant activity compared with commercial citrus pectin. The optimal condition for extraction of pectin by UAE was at 45°C for 30 min which could be established as a potential method to extract pectin from DFP for industrial scale.
Integrating ‘weighted views’ to quantitative 3D visibility analysis as a predictive tool for perception of space

The ability to predict the human perception of space in dense urban environments would have a vast impact on planning and design processes. Many analytical models, methods and tools have been developed to describe and predict human perception and behaviour in the urban environment, and academic papers have addressed the issue of the view in urban environments as a significant variant influencing perception and quality of life. In the present paper, we introduce the integration of weighted views (the relative impact of a view on a viewer) in a 3D Line of Sight visibility analysis as a predictive tool for perceptions of space focusing on ‘perceived density’. The integration of subjective qualitative information with objective measurements of the volume of visible space may bring evaluations closer to human perceptions of space. The research background consists of state-of-the-art visibility analysis and research concerned with the impact of the view on perceptions of space. An experiment in a visualization laboratory explored the relative impact of various views on the ‘perceived density’ and ‘visual privacy’ of 100 participants. The relative weight of each view presented to the subjects was based on the statistical results of the experiment. The weights were integrated into the 3D Line of Sight visibility analysis and the model is applied in a case study. The integrated 3D Line of Sight visibility analysis currently runs with off-the-shelf software available to all practicing architects and planners. It is expected that in the near future, the tool developed in this work will become an important aid to all practitioners, the method becoming a valuable evaluation tool in planning and design processes. Considering design alternatives, it may become a stepping stone for design principles and regulations.
Elastic Net Sparse Coding-based Space Object Recognition

The traditional bag-of-features(BoF) model for object recognition assumes each local feature point is related to only one visual word.Besides,sparse coding with l1-norm constraint generally selects only one feature without concern for which one is selected.A novel bag-of-features model based on elastic net sparse coding is presented in this paper.The model uses scale invariant feature transform(SIFT) feature descriptors to construct a feature dictionary,and then applies an elastic net regression model to the solution of sparse-coefficient vectors.Finally the sparse-coefficient vectors in each object image are pooled for classification.Compared with the conventional BoF model and the BoF model based on l1-norm sparse coding,our model achieves better recognition performance and is more robust to the variation of viewpoints.Experiments on the space object image database demonstrate the effectiveness of the proposed model.
CLIL in an English as a lingua franca (ELF) classroom: on explaining terms and expressions interactively

Based on a longitudinal study of an international educational programme in English as the participants’ lingua franca, this chapter argues for ‘integrative explaining’ as a new construct that offers direct access to analysing content and language integrated learning at the micro-level. A detailed discoursepragmatic analysis of twelve lessons spread over two years in this tertiary classroom community of practice has revealed distinct patterns of explaining subject-specific versus general terms and expressions. The results offer new and revealing insights into, firstly, the community-specific discursive ‘principle of joint forces’ and, secondly, the different activation of subject- vs. language expertise in discursively integrating new concepts into already shared knowledge.
Design of graphene oxide by a one‐pot synthetic route for catalytic conversion of furfural alcohol to ethyl levulinate

BACKGROUND: Graphene oxide (GO) has abundant oxygen‐containing functionalities such as hydroxyl groups and carboxyl groups with distinct acidities. This feature makes GO a potential solid acid catalyst for the acid‐catalyzed reactions such as the production of ethyl levulinate (EL), a platform chemical, from the acid‐treatment of furfuryl alcohol (FA). The structure and functionalities of GO are closely related to its catalytic performance, and thus it is necessary to establish the relationship between the chemical structure and the catalytic properties of GO. To achieve this aim, in this work, the GO catalysts were designed by a facile one‐pot synthetic route with no subsequent modification. By controlling the parameters of oxidation process in preparation, multiple functional groups were immobilized onto graphitic substrate, significantly impacting the catalytic activity of GO in the conversion of FA to EL in an ethanol (EtOH) medium. RESULTS: The results showed that, the oxidation process significantly influenced the distribution of oxygen‐containing functionalities on the surface of GO. The amount of the oxygen‐containing functionalities can be adjusted by the oxidation parameters such as oxidizing agent equivalent, reaction time and temperature, while the organosulfate can only be remained at a moderate oxidation temperature. The existence of the synergistic effect between the oxygen‐containing functionalities and the organosulfate functionalities promoted the catalytic activity of GO for the acid‐catalyzed conversion of FA to EL. CONCLUSIONS: This work provides a new strategy of design and development of functional graphene‐based catalysts for the acid‐catalyzed reactions, and lays foundation of the practicability of GO in biomass conversion. © 2019 Society of Chemical Industry
Application of artificial neural networks to tide forecasting

In ocean environment,accurate tide forecasting is a kind of significant work for constructions and human activities.Artificial neural networks(ANN) model is presented for forecasting the tidal-level using limited field data of one site or multi-sites.Based on the characteristics of tide time series,a new conception-the periodicity analysis on tide data is proposed and applied to the testing of the performance of ANN model.The numerical results indicate that this method is efficient to solve the time lag problem existing in previous ANN models.Based on the pertinence of tidal-level data among different tidal gauge stations,a new tide forecasting method-site to site is developed,and the numerical results agree well with field data.
Visual-syntactic text formatting

A new process, visual-syntactic text formatting (VSTF), transforms block-shaped text into cascading patterns that help readers identify grammatical structure. The new method integrates converging evidence from educational, visual, and cognitive research, and is made feasible through computer-executed algorithms and electronic displays. Among college readers, the VSTF method instantly increased reading comprehension and efficiency of reading online text, while reducing eyestrain. Among high school students, who read with the format over an entire academic year, the VSTF method increased both academic achievement and long-term reading proficiency by more than a full standard deviation over randomized controls
Communication with choices

This thesis introduces the Multi-Domain Communication Model (MDCM) and the Flexible Stack Architecture (FSA) to add choices back into communication. Although human communication is an interactive process with an abundance of choices, flexibility and adaptability are somehow lost in communication systems and their protocol stacks. MDCM defines a communication model that supports choices, and a set of guidelines to make them. There are two levels of such choices. The first level chooses the mechanisms and algorithms for selection and resolution. The second level chooses the next layer protocol, the next hop gateway, and the corresponding source and destination identities from resolution results. FSA implements the communication model defined by MDCM and provides a flexible infrastructure to facilitate choice of mechanisms and algorithms. MDCM augments conventional protocol layering to integrate next layer selection, forwarding, and resolution into a simple, recursive model. It defines what a communication layer does and how one protocol layer relates to another through next layer selection and identity resolution. This thesis further explores selection guidelines based on the semantic requirements of transmission characteristics and endpoint identities. MDCM is also applied to the current Internet stack model, and this analysis suggests several extensions to improve the existing architecture. FSA defines a node infrastructure to realize the approach of MDCM. FSA extends the existing protocol stack architecture to enable per-protocol next-layer selection and allows protocols and resolution mechanisms to be dynamically plugged in and selected during runtime. This flexibility allows FSA to support experiments with new protocols and mechanisms, to instantiate new network architectures, and to enable advanced features such as backtracking and session binding. An FSA prototype with pluggable IPv6 protocol modules is also implemented. The UDP benchmark measurement of the prototype shows no detectable performance impact. MDCM and FSA achieve architectural flexibility within a well-defined structure and result in an open, extensible infrastructure for communication protocol stacks. They form a foundation to accommodate complex policy and multiplicity in communication formats and media, providing the choices that communication systems have lacked.
Representation learning for unsupervised speech processing

Automatic speech recognition for our most widely used languages has recently seen substantial improvements, driven by improved training procedures for deep artificial neural networks, cost-effective availability of computational power at large scale, and, crucially, availability of large quantities of labelled training data. This success cannot be transferred to low and zero resource languages where the requisite transcriptions are unavailable. Unsupervised speech processing promises better methods for dealing with underresourced languages. Here we investigate unsupervised neural network based models for learning frameand sequencelevel representations with the goal of improving zero-resource speech processing. Good representations eliminate differences in accent, gender, channel characteristics, and other factors to model subword or whole-term units for withinand acrossspeaker speech unit discrimination. We present two contributions focussing on unsupervised learning of frame-level representations: (1) an improved version of the correspondence autoencoder applied to the INTERSPEECH 2015 Zero Resource Challenge, and (2) a proposed model for learning representations that explicitly optimize speech unit discrimination. We also present two contributions focussing on efficiency and scalability of unsupervised speech processing: (1) a proposed model and pilot experiments for learning a linear-time approximation of the quadratic-time dynamic time warping algorithm, and (2) a series of model proposals for learning fixed size representations of variable length speech segments enabling efficient vector space similarity measures.
C-reactive protein and lipid profile among depot- medroxyprogesterone acetate injections users

Objective: To study the effect of depot-medroxyprogesterone acetate (DMPA) injections on Creactive protein (CRP) and lipid profile and to find the predictors (body weight, body mass index (BMI), blood pressure (BP) and lipid profile) that significantly predict the risk of cardiovascular disease (CVD) among DMPA injections users. Method: A prospective cohort study was performed during the period from March 2009 to March 2010 included thirty apparently healthy married women, their age ranged between 20-35 years, who were attending Al-Batool and Al-Khansa Family Planning Centers in Mosul and started (for the first time) to use DMPA injections (150 mg medroxyprogesterone acetate), called "Depo-Provera" as contraceptive. These (DMPA users group) were compared to another 30 healthy married women who did not use any hormonal contraceptives (non users group). Both groups were followed for one year, during which blood samples were obtained from both groups, before starting to use DMPA, after 6 months and after 12 months. Sera were used for the estimation of the biochemical studied parameters using commercial kits except serum low density lipoprotein (LDL) and atherogenic index (AI) which were calculated by special equations. Results: DMPA injections caused a non significant increase in body weight but a significant increase in BMI after 12 months. There was a significant increase in the mean diastolic blood pressure (DBP) of DMPA users according to the duration of use. The DMPA caused non significant changes in the CRP levels. There was a significant increase in serum triglycerides (TG) after 6 months of DMPA uses with respect to the duration of use. But there were non significant changes in mean serum total cholesterol (TC), high density lipoprotein (HDL), LDL and AI. Among all variables that were studied, only body weight and BMI showed a significant positive correlations with CRP. Using a stepwise multiple regression analysis, it was found that the predictors that significantly predict the risk of CVD among DMPA users were AI, DBP and TG. Conclusion: This study found that there is a significant positive association between CRP and CVD risk factors in DMPA injections users as contraceptive. Furthermore AI, DBP and TG were found to be significant predictors for the risk of CVD among DMPA users. This study confirmed the safety of DMPA use as contraceptive medication, but that special care should be directed for patients with CVD and other patients who were more sensitive to the harmful effects of lipid in the blood.
Implementing a non-strict purely functional language in JavaScript

This paper describes an implementation of a non-strict purely functional language in JavaScript. This particular implementation is based on the translation of a high-level functional language such as Haskell or Clean into JavaScript via the intermediate functional language Sapl. The resulting code relies on the use of an evaluator function to emulate the non-strict semantics of these languages. The speed of execution is com- petitive with that of the original Sapl interpreter itself and better than that of other existing interpreters.
Effect of Conceptual Change Oriented Instruction on Students' Conceptual Understanding and Decreasing Their Misconceptions in DC Electric Circuits

nd , 2013; revised March 25 th , 2013; accepted April 8 th , 2013 Copyright © 2013 Erdal Taslidere. This is an open access article distributed under the Creative Commons At- tribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The purpose of this study was twofold: first to investigate the effect of conceptual change oriented in- struction accompanied by concept cartoon worksheet with simulation on students' conceptual under- standing and second to remedy their misconceptions of direct current electric circuits. Participants were 139 pre-service science teachers from four intact classes. A quasi-experimental design was used in the study. The experimental group studied the concept with the application of concept cartoon worksheet and simulation, and the control group studied it with traditional instruction. Students' conceptual understand- ing and misconceptions were measured by a tree-tired misconception test. It was administered as pre-and-posttest. There was no significant difference between the means of pre-test scores of experimen- tal and control groups. The main effect of treatment on post-test scores was examined via ANCOVA with pre-test scores used as covariate. The frequency of each misconception was calculated for both groups, from pre to post-tests regarding all tiers of items. The analysis yielded a significant treatment effect on students' post-test performances. The findings indicated that the conceptual change oriented instruction accompanied by concept cartoon worksheet and simulation is likely to be effective for conceptual under- standing and decreasing most of students' misconceptions in direct current electric circuits.
Effect of agent embodiment on the elder user enjoyment of a game

This paper presents a study that compared the elder user enjoyment of a game of trivia in three conditions: participants playing the game with a laptop PC vs. a robot vs. a virtual agent. Statistical analysis did not show any significant difference of the three devices on user enjoyment while qualitative analysis revealed a preference for the laptop PC condition, followed by the robot and the virtual agent. The elderly participants were concentrated on the task performance rather on the interaction with systems. They preferred laptop PC condition mainly because there were less interfaces distracting them from performing the task proposed by the game. Further, the robot was preferred to a virtual agent because of its physical presence. Some issues of the experiment design are raised and directions for future research are suggested to gain more insight into the effects of agent embodiment on human-agent interaction.