Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Pattern and Data Clustering for Pattern Cluster Analysis

In data mining and knowledge discovery, pattern discovery extracts previously unknown regularities in the data and is a useful tool for categorical data analysis. However, the number of patterns discovered is often overwhelming. It is difficult and time-consuming to 1) interpret the discovered patterns and 2) use them to further analyze the data set. To overcome these problems, this paper proposes a new method that clusters patterns and their associated data simultaneously. When patterns are clustered, the data containing the patterns are also clustered; and the relation between patterns and data is made explicit. Such an explicit relation allows the user on the one hand to further analyze each pattern cluster via its associated data cluster, and on the other hand to interpret why a data cluster is formed via its corresponding pattern cluster. Since the effectiveness of clustering mainly depends on the distance measure, several distance measures between patterns and their associated data are proposed. Their relationships to the existing common ones are discussed. Once pattern clusters and their associated data clusters are obtained, each of them can be further analyzed individually. To evaluate the effectiveness of the proposed approach, experimental results on synthetic and real data are reported.
Recent Advances in the Emission and Functions of Plant Vegetative Volatiles

Plants synthesize and emit a large variety of volatile organic compounds, which possess extremely important ecological functions. In most case, most plant volatiles are liquids, rather than gases, at room temperature. Some volatiles are emitted “on demand” when plants, especially vegetative parts, are exposed to abiotic or biotic stress. In this review, we summarize some of the highlights of plant vegetative volatile emission and functions research published during the past few years.
Visual Cryptography in Internet Voting System

Internet Voting System (IVS) Using Visual Cryptography (VC) aims at providing a facility to cast vote for critical and confidential internal corporate decisions. It has the flexibility to allow casting of vote from any remote place, even when key stakeholders of election process are not available at workplace. This is enabled by leveraging and implementing the features provided by the VC in IVS. The election is held in full confidentiality by applying appropriate security measures to allow the voter to vote for any participating candidate only if he logs into the system by entering the correct password which is generated by merging the two shares (Black & White dotted Images)using VC scheme. Where, Administrator (Election officer) sends share 1 to voter e-mail id before election and share 2 will be available in the voting system for his login during election. Voter will get the secret password to cast his vote by combining share 1 and share 2 using VC. Visual Cryptography (VC) is a secret sharing scheme in which an image is converted into shares. No information can be revealed by observing any share (Black & White dotted Image). The information about the original image (Voter Password) will be revealed only after stacking sufficient number of shares. There are various schemes present in VC, 2 out of 2, k out of n, n out of n, etc. In the proposed method, IVS with 2-out-of-2 VC has been used for an efficient authentication voting system. Even if the hacker gets one share of the password, it is impossible to get the other share of the password, as it will be sent to the E-Mail Id of the voter. Thus IVS provides two way securities to the voting system, which is very much in need.
Self-propelled Droplets from Bioinspired Directional Microstructured Surfaces

Directional and ratchet like functionalized surfaces can induce liquid transport without the use of an external force. In this paper, we investigate the motion of liquid droplets near the Leidenfrost temperature on functionalized bioinspired asymmetric microstructured surfaces. The surfaces, which we have named “fish scale” microstructures, display unidirectional properties. The surfaces are fabricated on stainless steel through the use of a femtosecond laser-assisted process. Through this femtosecond process, mound-like microstructures on the surface are formed through a combination of material ablation, fluid flow, and material redeposition. In order to achieve the asymmetry of the structures and geometry, the femtosecond laser is focused at an angle with respect to the sample surface to give the microstructures a fish scale or ratchet like appearance. Two surfaces with 45° and 80° microstructures were fabricated. Droplet experiments were carried out to characterize the directional and self-propelling properties of the surfaces. It was found that the velocity of the liquid droplet deposited on such heated surfaces is a function of surface temperature. It was found that the maximum velocities were 12.5 and 17.8 cm/s for the 80° and 45° samples, respectively. It was also found that the droplet motion direction is opposite of that for a surface with conventional ratchet microstructures. A new mechanism for a selfpropelled droplet on an asymmetric three dimensional self-organized microstructured surfaces has been proposed.
Managing risks and opportunities in multilingual knowledge economies: The possibilities of ethical investment movement to sustaining biolinguistic diversity

This paper argues that the ethical investment view of business, which acknowledges the interdependent relationships between financial, social and environmental risks, can be justifiably extended to include the sustainability of linguistic diversity. The first section of this paper briefly summarises the current state of the world's languages, noting that the vast majority of the world's languages are at risk of extinction. The reasons for declining linguistic diversity are explored in some detail. This is followed by a consideration of the intimate connections between language, knowledge and environmental sustainability. The next section explores the increasing significance of the multilingual knowledge economies including the emergence of linguistic niche markets, diasporic market segments and the cosmopolitan marketplace (Singh, 2001 b). Given the interrelationships between language, knowledge, ecological sustainability and the limits of economic over-development, the final section explores the potential for the ethical investment view of business, which acknowledges these interrelatioships, to be explicitly extended to sustaining multicultural and linguistic diversity.
Statistical Survey of Monophthong Formants in Mandarin for Students Being Trained as Broadcasters

To study the group characteristics of Mandarin monophthong formants, the monophthongs of 212 female students and 126 male students from the department of broadcasters were recorded. The monophthong formants were measured using LPC method. The mean value and deviation of formants were given with statistical meaning. The results show the difference from the previous measurements by other researchers decades ago.
Graph grammar representation for collaborative sample-based music creation

This paper proposes a music representation for collaborative music creation using shared repositories of audio samples. We explore the use of the graph grammar formalism to organize collective work on musical compositions stored as graphs of samples, and describe an experimental prototype that implements this concept. We then use the compositions created by different users with the prototype to show how this representation allows tracking and analyzing the music creation process. Potential applications of this include finding similarities between artists or suggesting sounds for a given compositional context.
SLEEP: WHAT IT IS? (ON DEFINITION OF THE NOTION)

Summary It is assumed that the biological function of sleep is to compensate the limitation imposed by internal properties underlying the principle of chemical synaptic transmission (as high sensitivity to changes of ionic gradients, limited supplies of the mediator accessible to discharge, tendency toward synaptic depression etc.) and provide the reliability of the synaptic apparatus of CNS neural networks. This function is performed by slow wave fraction of sleep which, depending on conditions, can be triggered by switch-on the internal (microsleep or essential sleep) or external (normal physiological or preventive sleep) contours of the CNS mechanisms of selfregulation.
Transcriptome Analysis on the Inflammatory Cell Infiltration of Nonalcoholic Steatohepatitis in Bama Minipigs Induced by a Long-Term High-Fat, High-Sucrose Diet

Long-term adherence to a high-fat, high-calorie diet influences human health and causes obesity, metabolic syndrome and nonalcoholic steatohepatitis (NASH). Inflammation plays a key role in the development of NASH; however, the mechanism of inflammation induced by over-nutrition remains largely unknown. In this study, we fed Bama minipigs a high-fat, high-sucrose diet (HFHSD) for 23 months. The pigs exhibited characteristics of metabolic syndrome and developed steatohepatitis with greatly increased numbers of inflammatory cells, such as lymphocytes (2.27-fold, P<0.05), Kupffer cells (2.59-fold, P<0.05), eosinophils (1.42-fold, P<0.05) and neutrophils (2.77-fold, P<0.05). High-throughput RNA sequencing (RNA-seq) was performed to explore the systemic transcriptome of the pig liver during inflammation. Approximately 18.2 gigabases of raw sequence data were generated, and over 303 million high-quality reads were assembled into 21,126 unigenes. RNA-seq data analysis showed that 822 genes were differentially expressed in liver (P<0.05) between the HFHSD and control groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the process of inflammation involved the inflammatory signal transduction-related toll-like receptor, MAPK, and PPAR signaling pathways; the cytokine-related chemokine signaling, cytokine-cytokine receptor interaction, and IL2, IL4, IL6, and IL12 signaling pathways; the leukocyte receptor signaling-related T cell, B cell, and natural killer cell signaling pathways; inflammatory cell migration and invasion- related pathways; and other pathways. Moreover, we identified several differentially expressed inflammation-related genes between the two groups, including FOS, JUN, TLR7, MYC, PIK3CD, VAV3, IL2RB and IL4R, that could be potential targets for further investigation. Our study suggested that long-term HFHSD induced obesity and liver inflammation, providing basic insight into the molecular mechanism of this condition and laying the groundwork for further studies on obesity and steatohepatitis.
Recurrent neural networks and robust time series prediction

We propose a robust learning algorithm and apply it to recurrent neural networks. This algorithm is based on filtering outliers from the data and then estimating parameters from the filtered data. The filtering removes outliers from both the target function and the inputs of the neural network. The filtering is soft in that some outliers are neither completely rejected nor accepted. To show the need for robust recurrent networks, we compare the predictive ability of least squares estimated recurrent networks on synthetic data and on the Puget Power Electric Demand time series. These investigations result in a class of recurrent neural networks, NARMA(p,q), which show advantages over feedforward neural networks for time series with a moving average component. Conventional least squares methods of fitting NARMA(p,q) neural network models are shown to suffer a lack of robustness towards outliers. This sensitivity to outliers is demonstrated on both the synthetic and real data sets. Filtering the Puget Power Electric Demand time series is shown to automatically remove the outliers due to holidays. Neural networks trained on filtered data are then shown to give better predictions than neural networks trained on unfiltered time series.
Improved Method for Watershed Segmentation of Lung CT Scan Images for Early Diagnosis of Cancer

The purpose of this research work is to segment human lung CT scan images for early detection of cancer. As a part of this work 'Watershed Technique' is implemented as the 'Segmentation' method. This method is based on the filters available in the 'Insight Segmentation and Registration Toolkit' (ITK) (9). Image segmentation plays a vital role in several medical imaging programs by automating or assisting the delineation of physiological structures along with other parts of interest. NIH/NCI Lung Image Database Consortium (LIDC) served as the repository of lung images in the DICOM format. In this short article, different methods that can be used for efficient visualization as well as automatically extracting the organ regions from abdominal CT (Computerized tomography) data especially from lung that can be further used in various medical diagnosis applications like CBMIR (Content-based medical image retrieval) have been suggested. The achieved results support the use of the proposed algorithm for extraction of lung nodules from the image.
Development of a 3 freedom ankle robot to assist the rehabilitation training

With the developments of robotics, more and more rehabilitation robots are used to assist traditional training in rehabilitation field. In this paper, a novel ankle robot combined with 3 degrees of freedom, full fill passive-active training, subjective awareness and objective training requirements was proposed. The requirement of ankle robot was analyzed based on the ankle physical structure and real rehabilitation. Based on traditional rehabilitation therapy, a novel robot-assist rehabilitation therapy to combine subjective awareness with objective training was proposed. In this robot, a novel mechanism structure of cross-circle was proposed to robot movement around ankle center. The mechanical structure includes four parts, adduction/abduction parts, dorsiflexion/plantar flexion parts, inversion/eversion parts and sensing unit. Each part of ankle rehabilitation robot was introduced in detail. Finally, the core control strategy, position control and force control were proposed. With the robot, several primary experiments are performed. The feasibility of the robot was verified.
A Systematic and Semi-Automatic Safety-Based Test Case Generation Approach Based on Systems-Theoretic Process Analysis

Software safety is a crucial aspect during the development of modern safety-critical systems. Software is becoming responsible for most of the critical functions of systems. Therefore, the software components in the systems need to be tested extensively against their safety requirements to ensure a high level of system safety. However, performing testing exhaustively to test all software behaviours is impossible. Numerous testing approaches exist. However, they do not directly concern the information derived during the safety analysis. STPA (Systems-Theoretic Process Analysis) is a unique safety analysis approach based on system and control theory, and was developed to identify unsafe scenarios of a complex system including software. In this paper, we present a systematic and semi-automatic testing approach based on STPA to generate test cases from the STPA safety analysis results to help software and safety engineers to recognize and reduce the associated software risks. We also provide an open-source safety-based testing tool called STPA TCGenerator to support the proposed approach. We illustrate the proposed approach with a prototype of a software of the Adaptive Cruise Control System (ACC) with a stop-and-go function with a Lego-Mindstorms EV3 robot.
Improving Emergency Department Processes Using Coloured Petri Nets

With increasing demand for medical services, emergency departments (ED) are facing problems such as overcrowding and dissatisfaction. Improving the key performance indicators of EDs has been the focal point of healthcare management. This paper addresses performance analysis of ED of a general hospital. To this aim, a discrete event dynamic modeling approach is used to model the ED processes. The model employs a hierarchical timed Coloured Petri net framework in a concise and detailed way to capture patient flow and care processes within the ED. The simulation model was validated against historical data and then different types of scenarios were used to assess, compare and improve ED key performance indicators, such as patients waiting time, length of stay (LOS), and resource utilization rate. The proposed model helped the hospital policy makers to configure the ED in a way to improve its efficiency and staff satisfaction.
A Multiphasic Approach to Discovering How Scientists Develop Career-Related Interests and Careers.

Currently, there is little in-depth understanding of how individuals effectively orchestrate school and workrelated experiences over time from high school through college and beyond to pursue careers in Science, Technology, Engineering and Mathematics (STEM). This appears important because, unlike societies such as Germany, youth in the U.S. face an almost complete lack of structured pathways from school to work. Presently in the first year of a two-year project, this study uses a mixed methods approach to address a set of research questions from a wide variety of perspectives, and works toward developing an integrated synthesis of the important factors in this process. This study deals with the human systems that underlie all other systems, as well as those human systems’ interactions with other types of systems that may range from mechanical to socio-cultural systems.
Relations between executive function, language, and functional communication in severe aphasia

ABSTRACT Background: Intervention in severe aphasia often means aiming for access to meaningful social interaction in spite of linguistic barriers that might not be treatable. This demands knowledge about the different factors that influence functional communication. Apart from linguistic ability, executive functions are thought to play an important role. Aims: To expand the understanding of the relations of executive functions and linguistic ability to functional communication in severe aphasia. Methods and Procedures: Executive functions, linguistic ability, and functional communication were assessed in 47 participants with severe aphasia. The results were analysed for the total sample and for a verbal and a nonverbal subgroup. Outcomes and Results: Impairment of executive function was found in 79% of the participants. There were moderate to strong correlations between all subtests of executive functions and linguistic ability. In the total sample, significant partial correlation was found between functional communication and verbal output. In the nonverbal subgroup, there was a significant partial correlation between executive function and functional communication, when controlling for linguistic ability. In the verbal subgroup, no relations were found between executive functions or language and functional communication. Conclusions: Impairments of executive functions are common in people with severe aphasia, and executive function and linguistic ability are closely related. The ability to produce verbal output is strongly related to functional communication, but in people with extreme limitation or total absence of verbal output, executive functions seem to be an important factor for functional communication. There is a large variation of executive functions and functional communication in people with severe aphasia, especially in the nonverbal subgroup. It is important that people with severe aphasia are given a complete and proper evaluation of their abilities, and that the possible importance of executive function to communication is considered in communication intervention.
Intercultural Communication Competence and Conflict Negotiation Strategies: Perceptions of Park Staff and Diverse Park Users

A culturally and ethnically diverse U.S. population not only reflects changing park and recreation demographics, but also reflects changing interpersonal communication issues; particularly, intercultural communicative behaviors within public recreation spaces. To better understand such issues and behaviors, this exploratory study tested significant relationships between park and recreation practitioners and Latino and African American park users’ perceptions of intercultural communication competence and conflict negotiation strategies. Overall, findings indicated that park staff was shown to perceive Latino park users as possessing less intercultural communication competence than Latino park users were shown to perceive of themselves; conversely, park staff was shown to perceive African American park users as possessing more intercultural communication competence than African American park users were shown to perceive of themselves. In addition, intercultural conflict negotiation strategy differences were found to exist between park staff’s perceptions of Latino and African American park users, and the park users’ perceptions of themselves. Such findings call attention to the notion that park and recreation practitioners can not underestimate the influence that one’s racial and ethnic background has on interpersonal communication behaviors. Recommendations for park and recreation practitioners are discussed.
Quark-hadron mixed phases in protoneutron stars

We consider the possible formation of the quark hadron mixed phase in protoneutron stars. We discuss two cases: the first one, corresponding to a vanishingly small value of the surface tension of quark matter, is the well known mixed phase in which the global electric charge neutrality condition is imposed. In turn, this produces a non-constant pressure mixed phase. In the second case, corresponding to very large values of the surface tension, the charge neutrality condition holds only locally. However, the existence in protoneutron star matter of an additional globally conserved charge, the lepton number, allows for a new type of non-constant pressure mixed phase. We discuss the properties of the new mixed phase and the possible effects of its formation during the evolution of protoneutron stars.
A retina-like model for motion detection

A model is presented for motion detection based on the anatomy and physiology of biological retinas. This model is capable of handling realistic images at rates of up to 5 per minute on a workstation. It is fully interactive with the user. The code was written so as to be extendable and modular. The authors describe the model and point out analogies to biological retinas. The model tracks better than thresholding algorithms followed by Kalman filtering. Its implementation in VLSI is conceptually straightforward. The need to develop better performance measures is outlined. <<ETX>>