Miracle-dz/UniFAR-FTUs huggingface dataset:
Sunflower Protein Precipitation in a Tubular Precipitator

lsoelectric precipitation of sunflower protein was carried out in a 20 m long, 6 mm internal diameter glass tubular precipitator. Effects of feed flow rate, protein concentration in the feed stream, and mean residence time on particle size distribution (PSD) were studied. The population balance equation (PBE) for the tubular precipitator was solved using thc orthogonal collocation multiple shooting method. A simulated annealing method was used to determine the precipitation kinetic parameters for the nucleation rate, growth rate, aggregation rate, and breakage rate from the experimental data. Due to the lack of experimental data on the kinetics of sunflower protein precipitation in the literature, the extracted kinetics from our experiments were used to evaluate the predictive capability of the present model for experiments whose results had not been used to derive the kinetics. The model predictions of the particle size distribution along the tubular precipitator showed better agreement with the experimental data for large particles in comparison to the small particles (< 10 pm).
Accretion in the Early Kuiper Belt. II. Fragmentation

We describe new planetesimal accretion calculations in the Kuiper Belt that include fragmentation and velocity evolution. All models produce two power-law cumulative size distributions, NC ∝ r-2.5 for radii ≲0.3–3 km and NC ∝ r-3 for radii ≳1–3 km. The power-law indices are nearly independent of the initial mass in the annulus, M0; the initial eccentricity of the planetesimal swarm, e0; and the initial size distribution of the planetesimal swarm. The transition between the two power laws moves to larger radii as e0 increases. The maximum size of objects depends on the intrinsic tensile strength, S0; Pluto formation requires S0 ≳ 300 ergs g-1. The timescale to produce Pluto-sized objects, τP, is roughly proportional to M and e0 and is less sensitive to other input parameters. Our models yield τP ≈ 30–40 Myr for planetesimals with e0 = 10-3 in a minimum mass solar nebula. The production of several "Plutos" and ∼105 Kuiper Belt objects with 50 km radius leaves most of the initial mass in 0.1–10 km radius objects that can be collisionally depleted over the age of the solar system. These results resolve the puzzle of large Kuiper Belt objects in a small-mass Kuiper Belt.
The relation between the exposure to mobbing and burnout levels of secondary school teachers

This study was conducted to determine the relation between the level of burnout and the level of exposure to mobbing. The research is in relational survey model. The population of the research is composed of 1153 secondary school teachers working in Siirt city center in 2014-2015 academic year.As the number of teachers included in the research population is not high, sampling was not madeand 354 of the distributed scales were analysed. In the study, “Negative Acts Questionnaire” Scale developed by Einarsen and Raknes (1997) was used to measure the frequency of teachers’ exposure to mobbing behaviours. To determine the teachers’ burnout levels“Maslach Burnout Inventory” (MBI- Educators Survey) developed by Maslach and Jackson (1981) was used. The results showed that teachers are exposed to negative behavioursunder the sub-dimensions of “work related mobbing” and “mobbing directed at social relations” at "occasional" level. With regard to the burnout levels of the secondary school teachers, the highest value is observed in “emotional exhaustion” sub-dimension while the lowest is in “depersonalization"; and the personal accomplishment is at moderate level. As a result of the research, basedon the perceptions of the teachers, a positive and medium levelof relation was determined between the “work related mobbing” and “mobbing directed at social relations” sub-dimensions of mobbing and “emotional exhaustion” and “depersonalization" sub-dimensions of burnout, while the relation with the personal accomplishment dimension was at a negative and medium level. As a result of the regression analysis, it was found out that both sub-dimensions of mobbing significantly predict all the dimensions of burnout subscales. Keywords: Mobbing, burnout, secondary school, teacher
Solid Cellular Automaton Method for the Solution of Physical Field

This paper introduces a new computational technique—solid cellular automaton—for the solution of physical field. The thought of cellular automaton comes from the self-organization theory in biology. In this theory, the state of a cell is determined by the states of itself and its neighbors. The information outside the neighbor domain does not contribute to the state of the cell. The global analysis of structure is converted to a series of local analyses by using the idea of cellular automaton. Based on the control equations in physical field, the updating rule to describe the relation between cell and its neighbors is developed. This method is used to the analysis of fluid flow and the computational steps as well as the results are presented. Comparisons among solid CA modeling result, finite element method modeling result and analytical result indicate that the solid CA is a reliable method in the solution of physical field.
Reference Intervals for Platelet Parameters in Korean Adults Using ADVIA 2120

Analysis of thrombopoiesis is important in evaluating hemato-logic and non-hematologic diseases. Recent improvements in automated blood 4cell analyzers allow measurement of several platelet parameters, providing additional information on the un-derlying mechanisms of thrombocytosis and thrombocytopenia. The ADVIA
Uml-Based Definition of Integration Models for Incremental Development Processes in Chemical Engineering

In development processes, multiple tools are used to describe different aspects of the developed product. The resulting information is stored in heterogeneous documents that are technically independent but whose contents are closely related on the semantic level. Thus, if one document is changed, these changes have to be propagated to dependent documents in order to restore mutual consistency. Therefore, there is a need for incremental integration tools, which assist developers in consistency maintenance. Driven by this need, we realized a framework for building incremental integration tools, which is currently being used in the chemical engineering domain. Integration tools are based on models of the related documents and their mutual relationships. These models are defined in the Unified Modelling Language (UML).
COD: blind path separation with limited antenna size

This paper proposes a generalized multipath separability condition for subspace processing and derives a novel COD (combined oversampling and displacement) algorithm to utilize both spatial and temporal diversities for path separation and DOA estimation. A unique advantage lies in its ability to cope with the situation where the number of multipaths is much larger than that of antenna elements, which arises in many practical situations. The traditional data matrix or any of its horizontally expanded versions cannot yield a sufficient matrix rank to satisfy the condition, when there is antenna deficiency. Neither can a vertical expansion via oversampling, except when there is no overlapping among intra-user paths (a much stronger condition than the asynchrony condition). The COD strategy solves the antenna deficiency problem by combining vertical expansion with temporal oversampling and horizontal expansion with spatial displacement. Another unique advantage of COD is its multiplicity of eigenvalues which greatly facilitates the later signal recovery processing. The paper first analyzes the theoretical footings for COD and follows with some illustrative simulation results in noisy channels.
Tradeoff Issues in Local Search Guidance for SAT

A method for displaying the availability of videocassette films for rental including the following steps: producing indicating cards having indicia printed thereon identifying the films available for rental; positioning indicating cards for various videocassette films at different locations on a display board; positioning a plurality of indicating cards for identical videocassette films at the same location; selectively removing the reproductions individually from the display board as the videocassette corresponding thereto is rented; and selectively repositioning the reproductions as the videocassette corresponding thereto is returned.
The influence of film music on moral judgments of movie scenes and felt emotions

Music can modulate perceptions, actions, and judgments in everyday situations. The aim of this study was to investigate a potential influence of music on moral judgments in the context of film reception. In the course of an online experiment, 252 participants were assigned to three different experimental conditions (no, positive, or negative music). Participants were requested to assess actions shown in two 2–3-minute audio-visual film excerpts with regard to their perceived moral rightness and to report induced emotions after watching the film clips. Afterwards, they were asked to complete the MFQ-30 questionnaire measuring the foundations of their moral judgments. Results revealed that in one of four cases (i.e. happiness in film excerpt 1), music had a significant effect on recipients’ emotions and also indirectly influenced their moral judgment. In three of four cases, however, the intended emotion induction through film music did not succeed, and thus a significant indirect influence of music on moral judgment was not found. Furthermore, associations between moral foundations, perceived rightness of action, and induced emotions were observed. Future lab studies are indicated to investigate potential moderating influences of the experimental environment on emotion induction through film music.
Intravoxel water diffusion heterogeneity imaging of human high‐grade gliomas

This study aimed to determine the potential value of intravoxel water diffusion heterogeneity imaging for brain tumor characterization and evaluation of high‐grade gliomas, by comparing an established heterogeneity index (α value) measured in human high‐grade gliomas to those of normal appearing white and grey matter landmarks. Twenty patients with high‐grade gliomas prospectively underwent diffusion‐weighted magnetic resonance imaging using multiple b‐values. The stretched‐exponential model was used to generate α and distributed diffusion coefficient (DDC) maps. The α values and DDCs of the tumor and contralateral anatomic landmarks were measured in each patient. Differences between α values of tumors and landmark tissues were assessed using paired t‐tests. Correlation between tumor α and tumor DDC was assessed using Pearson's correlation coefficient. Mean α of tumors was significantly lower than that of contralateral frontal white matter (p = 0.0249), basal ganglia (p < 0.0001), cortical grey matter (p < 0.0001), and centrum semiovale (p = 0.0497). Correlation between tumor α and tumor DDC was strongly negative (Pearson correlation coefficient, −0.8493; p < 0.0001). The heterogeneity index α of human high‐grade gliomas is significantly different from those of normal brain structures, which potentially offers a new method for evaluating brain tumors. The observed negative correlation between tumor α and tumor DDC requires further investigation. Copyright © 2009 John Wiley & Sons, Ltd.
Utility-Based Scheduling for Bulk Data Transfers between Distributed Computing Facilities

Today's scientific applications increasingly involve large amounts of input/output data that must be moved among multiple computing facilities via wide-area networks (WANs). The bandwidth of WANs, however, is growing at a much smaller rate and thus becoming a bottleneck. Moreover, the network bandwidth has not been viewed as a limited resource, and thus coordinated allocation is lacking. Uncoordinated scheduling of competing data transfers over shared network links results in suboptimal system performance and poor user experiences. To address these problems, we propose a data transfer scheduler to coordinate and schedule data transfers between distributed computing facilities over WANs. Specifically, the scheduler prioritizes and allocates resources to data transfer requests based on user-centric utility functions in order to achieve maximum overall user satisfaction. We conducted trace-based simulation and demonstrated that our data transfer scheduling algorithms can considerably improve data transfer performance as well as quantified user satisfaction compared with traditional first-come, first-serve or short-job-first approaches.
Comparative Analysis For Kinematics Of 5-DOF Industrial Robotic Manipulator

Abstract This paper gives the kinematic analysis of a 5-DOF industrial robotic manipulator while considering wrist in motion. Analytical solutions have been obtained for forward kinematics and inverse kinematics to accurately position the end-effector of robotic manipulator in three dimensional spaces. For the first time, a hybrid neuro-fuzzy intelligent technique with two different membership functions has been studied and their performances are comparatively evaluated with analytical solutions. An experiment has been performed for a desired trajectory. It is seen that the results for the intelligent technique are reasonably in agreement with experiment. Also, the results obtained highlight the importance of selection of a particular membership function for robotic manipulators of industrial use.
2016 Ieee International Conference on Big Data (big Data) Telcoflow: Visual Exploration of Collective Behaviors Based on Telco Data

—Collective behavior is an important concept defined to capture behavioral patterns emerged among the crowd spontaneously. In social science, people's behaviors can be regarded as temporal transitions between a set of typical states (e.g., home and work) which are always associated with certain locations. This fact leads to an interesting research topic in developing ways to explore people's collective behavior patterns through movement analysis, which is our focus in this paper. In recent years, massive volumes of spatio-temporal data generated by mobile phones, called telco data, bring an unprecedented opportunity to study collective behaviors in terms of large coverage and fine-grained resolution. However, distilling valuable collective behavior patterns from the large scale of telco data is not an easy task. The challenge is rooted in two aspects, including the data uncertainty as well as the lack of methods to characterize, compare and understand dynamic crowd behaviors, which triggers the use of visual analytics to take full advantage of machines' computational power as well as human's domain knowledge and cognitive abilities. In this paper, we propose TelcoFlow, a comprehensive visual analytics system which incorporates advanced quantitative analyses (e.g., state-based behavior model) and intuitive visualizations (e.g., an extended flow view embedded with state glyphs) to support an efficient and in-depth analysis of collective behaviors based on telco data. Case studies with a real-world dataset and expert interviews are carried out to demonstrate the effectiveness of our system for analysts to gain insights into collective behaviors and facilitate various analytical tasks.
Non-Rigid Structure-From-Motion With Uniqueness Constraint and Low Rank Matrix Fitting Factorization

Non-rigid structure-from-motion is one of the difficult and challenging problems in computer vision, especially when the only input available is 2D correspondences in monocular video sequence. This paper proposed a new constraint based framework for underconstrained non-rigid structure-from-motion problem to constrain the space of solution. The proposed method is based on a point trajectory approach with an additional uniqueness constraint applied to shape coefficients to reduce the basis required to construct the non-rigid 3D shape. A framework for occluded and incomplete measured data is also proposed using low rank matrix fitting which is a robust factorization scheme for the matrix completion problem. This method offers not only new theoretical insight, but also a practical, everyday solution, to non-rigid structure-from-motion. The proposed method is positively compared to the state-of-the-art in non-rigid structure-from-motion, providing improved results on high-frequency deformations of both articulated and simpler deformable shapes.
More Than Just Class: School Mobility Among Black Children in the Great Recession

The United States experienced the Great Recession between 2007 and 2009 and many cities, suburbs, and communities are still suffering from its legacy. Yet, little is known about whether or not the crisis led to increases in student mobility, particularly for minority households. This study analyzed data from a large urban district located in San Bernardino, California, to examine the interplay of school mobility and race and class during the economic downturn. Using a logit model, findings show that race and class together interacted in ways that made Black students particularly vulnerable to school changes. Research and policy implications are discussed.
On email spam filtering using support vector machine

Electronic mail is a major revolution taking place over traditional communication systems due to its convenient, economical, fast, and easy to use nature. A major bottleneck in electronic communications is the enormous dissemination of unwanted, harmful emails known as "spam emails". A major concern is the developing of suitable filters that can adequately capture those emails and achieve high performance rate. Machine learning (ML) researchers have developed many approaches in order to tackle this problem. Within the context of machine learning, support vector machines (SVM) have made a large contribution to the development of spam email filtering. Based on SVM, different schemes have been proposed through text classification approaches (TC). A crucial problem when using SVM is the choice of kernels as they directly affect the separation of emails in the feature space. We investigate the use of several distance-based kernels to specify spam filtering behaviors using SVM. However, most of used kernels concern continuous data, and neglect the structure of the text. In contrast to classical blind kernels, we propose the use of various string kernels for spam filtering. We show how effectively string kernels suit spam filtering problem. On the other hand, data preprocessing is a vital part of text classification where the objective is to generate feature vectors usable by SVM kernels. We detail a feature mapping variant in TC that yields improved performance for the standard SVM in filtering task. Furthermore, we propose an online active framework for spam filtering. We present empirical results from an extensive study of online, transductive, and online active methods for classifying spam emails in real time. We show that active online method using string kernels achieves higher precision and recall rates.
Development of autonomous hybrid UAV U-Lion with VTOL and cruise flying capabilities

In this paper, we present a novel hybrid UAV, U-Lion, which has autonomous VTOL and cruise flying capabilities. The reconfigurable wings are designed so that the structure of U-Lion is aerodynamically efficient in both flying modes. Vectoring thrust and the multiple control surfaces tail are implemented to increase the controllability for better maneuverability and stronger rejection to wind gust disturbance. A complete control framework is developed for the autonomous flight for both flying modes as well as the bi-directional transitions. An autonomous outdoor flight test result is presented to demonstrate the effectiveness of the platform design and the entire control framework.
Neuronal nitric oxide synthase and the autonomic innervation of the mouse lacrimal gland.

PURPOSE To determine the expression patterns of the vesicular acetylcholine transporter (VAChT), tyrosine hydroxylase (TH) and neuronal nitric oxide synthase (nNOS) in the pterygopalatine ganglion (PPG) and the exorbital lacrimal gland of normal mice. METHODS Mouse PPG and lacrimal glands were processed for single- and double-labeled indirect immunofluorescence studies. Slides were examined with conventional fluorescence microscopy and confocal laser scanning microscopy. RESULTS All the somata in the PPG expressed both VAChT and nNOS immunoreactivity (IR). The postganglionic axons within the ganglion showed less VAChT-immunoreactive intensity than that seen in the somata, whereas nNOS IR was almost undetectable. In the lacrimal gland, nNOS-positive nerve bundles and fibers were observed to be associated with tear-collecting ducts, blood vessels, and acini. Some nNOS-positive punctate elements appeared to be distributed among acini. Many nerve fibers were VAChT immunoreactive and a small number of fibers were TH immunoreactive in the gland. Most of the VAChT-positive fibers and some of the TH-positive nerves displayed nNOS IR. CONCLUSIONS The expression of nNOS in cells of the PPG and in lacrimal gland nerves suggests that NO may play a role in modulating tear production. The site of action may include the PPG, ducts, blood vessels, acini, nerve fibers, and myoepithelial cells within the gland. NO may modulate parasympathetic and/or sympathetic synaptic transmission or by acting directly on lacrimal gland components. The interaction between NO-ergic and the conventional autonomic input illustrates the complexity of the innervation pattern of the mouse lacrimal gland.
STRING 7—recent developments in the integration and prediction of protein interactions

Information on protein–protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives

Sparse coding has recently become a popular approach in computer vision to learn dictionaries of natural images. In this paper we extend the sparse coding framework to learn interpretable spatio-temporal primitives. We formulated the problem as a tensor factorization problem with tensor group norm constraints over the primitives, diagonal constraints on the activations that provide interpretability as well as smoothness constraints that are inherent to human motion. We demonstrate the effectiveness of our approach to learn interpretable representations of human motion from motion capture data, and show that our approach outperforms recently developed matching pursuit and sparse coding algorithms.