Miracle-dz/UniFAR-FTUs huggingface dataset:
Large structure in the far wakes of two-dimensional bluff bodies

Smoke-wire flow visualization and hot-wire anemometry have been used to study near and far wakes of two-dimensional bluff bodies. For the case of a circular cylinder at 70 < Re < 2000, a very rapid (exponential) decay of velocity fluctuations at the Kármán-vortex-street frequency is observed. Beyond this region of decay, larger-scale (lower wavenumber) structure can be seen. In the far wake (beyond one hundred diameters) a broad band of frequencies is selectively amplified and then damped, the centre of the band shifting to lower frequencies as downstream distance is increased. The far-wake structure does not depend directly on the scale or frequency of Kármán vortices shed from the cylinder; i.e. it does not result from amalgamation of shed vortices. The growth of this structure is due to hydrodynamic instability of the developing mean wake profile. Under certain conditions amalgamation can take place, but is purely incidental, and is not the driving mechanism responsible for the growth of larger-scale structure. Similar large structure is observed downstream of porous flat plates (Re ≈ 6000), which do not initially shed Kármán-type vortices into the wake. Measured prominent frequencies in the far cylinder wake are in good agreement with those estimated by two-dimensional locally parallel inviscid linear stability theory, when streamwise growth of wake width is taken into account. Finally, three-dimensionality in the far wake of a circular cylinder is briefly discussed and a mechanism for its development is suggested based on a secondary parametric instability of the subharmonic type.
Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

In the last decade, cooperative vehicular network has been one of the most studied areas for developing the intelligent transportation systems (ITS). It is considered as an important approach to share the periodic traffic situations over vehicular ad hoc networks (VANETs) to improve efficiency and safety over the road. However, there are a number of issues in exchanging traffic data over high mobility of VANET, such as broadcast storms, hidden nodes and network instability. This paper proposes a new model to detect the traffic conditions using clustering traffic situations that are gathered from the nodes (vehicles) in VANET. The model designs new principles of multi-level clustering to detect the traffic condition for road users. Our model (a) divides the situations of vehicles into clusters, (b) designs a set of metrics to get the correlations among vehicles and (c) detects the traffic condition in certain areas. These metrics are simulated using the network simulator environment (NS-3) to study the effectiveness of the model.
Pedestrian localization and tracking system with Kalman filtering

This work presents an implementation of a vision-based system for recognizing pedestrians in different environments and precisely localizing them with the use of a Kalman filter estimator configured as a tracker. Pedestrians, in various poses and with different kinds of clothing, are first recognized by the vision subsystem through the use of algorithms based on edge density and symmetry maps. The information produced in this way is then passed on to the tracker module which reconstructs an interpretation of the pedestrians positions in the scene. An appropriately configured indoor system setup with an accurate measurement of the imposed human trajectory has been realized. This setup has permitted an accurate evaluation of the accuracy of the results, when the new auxiliary tracker is activated.
Layering in Provenance-Aware Storage Systems

Digital provenance describes the ancestry or history of a digital document. Provenance provides answers to questions such as: “How does the ancestry of these objects differ? ” “Are there source code files tainted by proprietary software? ” “How was this object created? ” Prior systems used to collect and maintain provenance operate within a single layer of abstraction: the system call boundary, a workflow specification language, or in a domain-specific application level. The provenance collected at each of these layers of abstraction is different, and all of it is important at one time or another. All of these solutions fundamentally fail to account for the different layers of abstraction at which users need to reason about their data and processes. None of these systems support queries across different layers of abstraction to answer a question such as “The calculated values in my spreadsheet have changed. Is this due to a change in the spreadsheet, a difference in the spreadsheet application, the libraries being used, or the operating system being used? ” We present an architecture for provenance collection that facilitates the integration of provenance across multiple layers of abstraction and across network boundaries. We show how the need to support provenance collection at multiple layers drives the architecture. We present provenance-aware use cases from the field of thermography and quantify system overheads, showing that we can provide new functionality with acceptable overhead.
Extracellular Vesicles: Evolving Factors in Stem Cell Biology

Stem cells are proposed to continuously secrete trophic factors that potentially serve as mediators of autocrine and paracrine activities, associated with reprogramming of the tumor microenvironment, tissue regeneration, and repair. Hitherto, significant efforts have been made to understand the level of underlying paracrine activities influenced by stem cell secreted trophic factors, as little is known about these interactions. Recent findings, however, elucidate this role by reporting the effects of stem cell derived extracellular vesicles (EVs) that mimic the phenotypes of the cells from which they originate. Exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell-EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations. This review therefore discusses stem cell-EVs as evolving communication factors in stem cell biology, focusing on how they regulate cell fates by inducing persistent and prolonged genetic reprogramming of resident cells in a paracrine fashion. In addition, we address the role of stem cell-secreted vesicles in shaping the tumor microenvironment and immunomodulation and in their ability to stimulate endogenous repair processes during tissue damage. Collectively, these functions ensure an enormous potential for future therapies.
A Study on Transmission Delay with Finite Coding Length in Wireless Cooperative Networks

In this paper, we consider the problem of transmission delay in terms of finite coding length derived from the random coding bound for different cooperative protocols. Specifically, we first study the impact of cooperative transmission on the routing decision for wireless ad-hoc networks, where a routing optimization problem is formulated to minimize the endto-end delay that ensures a satisfactory error performance. The closed-expression of the optimal solution is developed through the optimization problem and later used as quantitative criterion of routing decision. Furthermore, consider the interference impact on system performance along a multi-hop routing, we then investigate performance gain on transmission delay for wireless cooperative networks by using a simple multi-user detection scheme, called overlapped transmission, in which multiple transmissions are allowed only when the information in the interfering signal is known at the receiver. As a result, both analytical and numerical results demonstrate the significant improvement on the system performance by using cooperative transmission with overlapping as well as the trade-off between the end-to-end delay and network throughput.
Switched observer based impedance control for an assistive robotic cart under unknown parameters

This paper presents a new control scheme of an assistive robotic cart that helps a user easily transport objects in various weights. The maneuverability of the cart would be highly affected by the loaded weight of the cart and the friction between the wheel and the floor. Our focus is placed on how to enable the cart to offer easy maneuverability by creating desired interactions with a user. For this, a switched observer based impedance control scheme is proposed to allow the cart to autonomously adapt to changes in the weight of the load and the friction. Specifically, a pre-determined impedance between the user and the cart is regulated to generate an assist force using the user's input force and the velocity of the cart. The switched observer is designed to estimate the loaded weight and the friction coefficient for the precise computation of the amount of assistance. Further, using the process integration and design optimization approach, the observer gains are automatically adjusted, resulting in enhancing the control performance. We describe the proposed scheme in detail, and perform extensive simulations to demonstrate its effectiveness.
Use of the Choquet integral for combination of classifiers in P300 based brain-computer interface

One of the key issues in the development of brain-computer interfaces (BCIs) is the improvement of their current information transfer rate. In order to achieve that objective at least two aspects of BCI design should be considered: classification accuracy and protocol specification. In this paper we show how combination of classifiers using fuzzy measures and the Choquet integral can be applied to the context of visual P300 BCI in order to lower the number of misclassifications. Results of an offline analysis are provided and possible benefits in terms of the information transfer rate are briefly discussed.
The internationalisation of early childhood education: Case study from selected kindergartens in Bandung, Indonesia

For the past 20 years, early childhood education has undergone changes that have resulted from an alteration in Indonesian socio-political situations. One of the changes has resulted in the emergence of the internationalisation of early childhood education in Indonesia. This paper unpacks the complexity of the process. Three teachers from three different kindergartens in Bandung, Indonesia were selected to participate in this study. Drawing from postcolonial theories, the findings of the study illuminate the extent to which international schooling perpetuates the legacy of colonialisation, while at the same time sustaining the legacy of neo-liberal policy. However, the findings also suggest that the schools have become a hybrid space where global and local values are interacting and negotiating with one another.
Design of Feed-Forward Neural Network Based On-line Flux Estimator for Sensor-less Vector Controlled Induction Motor Drives

The sensor-less vector controlled induction motor drive requires accurate estimation of speed and flux. The speed estimation depends on the motor flux, which has to be measured or estimated. The flux measurement is difficult and expensive and hence generally estimated. Conventional voltage model equations for flux estimation encounter major drawbacks at low frequencies/speed. Neural network based estimators for flux provides an alternate solution with added robustness to motor parameter variation. Hence such model assumes importance for real time/on-line estimation. The required neural model uses feed-forward architecture whose design is more an art than a science. This paper proposes a novel design methodology to optimize both performance and cost. Using the proposed methodology an on-line flux estimator is designed and validated through simulation. The results obtained are presented.
Performance Comparison of classification algorithms for EEG-based remote epileptic seizure detection in Wireless Sensor Networks

Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems. Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes. In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI. The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands. In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers. Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets. The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.
Three-Dimensional Structure of a Protozoal Double-Stranded RNA Virus That Infects the Enteric Pathogen Giardia lamblia

ABSTRACT Giardia lamblia virus (GLV) is a small, nonenveloped, nonsegmented double-stranded RNA (dsRNA) virus infecting Giardia lamblia, the most common protozoan pathogen of the human intestine and a major agent of waterborne diarrheal disease worldwide. GLV (genus Giardiavirus) is a member of family Totiviridae, along with several other groups of protozoal or fungal viruses, including Leishmania RNA viruses and Trichomonas vaginalis viruses. Interestingly, GLV is more closely related than other Totiviridae members to a group of recently discovered metazoan viruses that includes penaeid shrimp infectious myonecrosis virus (IMNV). Moreover, GLV is the only known protozoal dsRNA virus that can transmit efficiently by extracellular means, also like IMNV. In this study, we used transmission electron cryomicroscopy and icosahedral image reconstruction to examine the GLV virion at an estimated resolution of 6.0 Å. Its outermost diameter is 485 Å, making it the largest totivirus capsid analyzed to date. Structural comparisons of GLV and other totiviruses highlighted a related “T=2” capsid organization and a conserved helix-rich fold in the capsid subunits. In agreement with its unique capacity as a protozoal dsRNA virus to survive and transmit through extracellular environments, GLV was found to be more thermoresistant than Trichomonas vaginalis virus 1, but no specific protein machinery to mediate cell entry, such as the fiber complexes in IMNV, could be localized. These and other structural and biochemical findings provide a basis for future work to dissect the cell entry mechanism of GLV into a “primitive” (early-branching) eukaryotic host and an important enteric pathogen of humans. IMPORTANCE Numerous pathogenic bacteria, including Corynebacterium diphtheriae, Salmonella enterica, and Vibrio cholerae, are infected with lysogenic bacteriophages that contribute significantly to bacterial virulence. In line with this phenomenon, several pathogenic protozoa, including Giardia lamblia, Leishmania species, and Trichomonas vaginalis are persistently infected with dsRNA viruses, and growing evidence indicates that at least some of these protozoal viruses can likewise enhance the pathogenicity of their hosts. Understanding of these protozoal viruses, however, lags far behind that of many bacteriophages. Here, we investigated the dsRNA virus that infects the widespread enteric parasite Giardia lamblia. Using electron cryomicroscopy and icosahedral image reconstruction, we determined the virion structure of Giardia lamblia virus, obtaining new information relating to its assembly, stability, functions in cell entry and transcription, and similarities and differences with other dsRNA viruses. The results of our study set the stage for further mechanistic work on the roles of these viruses in protozoal virulence.
Constructivism and Connectivism in Education Technology: Active, Situated, Authentic, Experiential, and Anchored Learning

The main objectives of this theoretical paper are to compare some constructivist-related learning theories and explore how they can be adequately used in educational technology and distance education. After a brief introduction, constructivism is defined as a general philosophy of education encompassing several different learning theories. The article then presents and discusses the following theories: situated cognition, activity theory, experiential learning, anchored instruction, and authentic learning. Connectivism or distributed learning is also presented as a new and important theory, including its pedagogical view and practice in massive open online courses (MOOCs). These theories are then organized in a coherent way, classified under the constructivist umbrella, pointing their common and distinctive features. Connectivism is positioned as a new philosophy of education for the digital age, making Vygotsky’s concept of zone of proximal development (ZPD) more flexible and stretching it to include learning that lies outside the learner, in social networks and technological tools. The text finally proposes further work on how these theories can be properly combined and used as frameworks for constructivist projects and activities in the fields of educational technology and distance education. The article is based on the search and review of peer-reviewed articles on constructivism, connectivism, the other aforementioned theories, and education technology and distance education.
Testing Equivalence Probabilistically

Although the equivalence of two Ordered Binary Decision Diagrams (OBDDs) can be decided in polynomial time, the equivalence of two Free Binary Decision Diagrams (FBDDs) is only known to be probabilistically decidable in polynomial time. FBDDs are a strict superset of OBDDs, and are more succinct than OBDDs, which explains the interest in testing their equivalence. We show that the probabilistic equivalence test for FBDDs holds for the class of deterministic, decomposable negation normal forms (d-DNNFs), which forms a strict superset of FBDDs and is more succinct than FB-DDs. Our theoretical results are backed up by experiments on a suite of combinational circuits.
Is Religiosity an Important Factor in Influencing the Intention to Undertake Islamic Home Financing in Klang Valley

The paper is intended to determine whether religiosity is an important factor in influencing the intention to undertake Islamic home financing in Malaysia. A consumer survey comprised a sample of 300 Muslim respondents from various range of age and income group resided mainly in Klang Valley areas. A conceptual framework is constructed based on Ajzen's (15) Theory of Planned Behaviour (TPB) and research hypothesis are developed in order to focus attention on sets of factors that influences intention to use Islamic home financing in Malaysia. The findings indicated that religiosity had significant influences on the intention of Islamic home financing among Muslims in Klang Valley. In addition, this study also confirms that the TPB components namely attitude and perceived behavior are significant factors as well.
Peripheral engraftment of fetal intestine into athymic mice sponsors T cell development: direct evidence for thymopoietic function of murine small intestine

Adult athymic, lethally irradiated, F1-->parent bone marrow- reconstituted (AT x BM) mice were engrafted bilaterally with day 16-18 fetal intestine or fetal thymus into the kidney capsule and were studied for evidence of peripheral T cell repopulation of 1-12 wk postengraftment. Throughout that time period, both types of grafts were macroscopically and histologically characteristic of differentiated thymus or intestine tissues, respectively. Beginning at week 2 postengraftment, clusters of lymphocytes were present within intestine grafts, particularly in subepithelial regions and in areas below villus crypts. As determined by immunofluorescence staining and flow cytometric analyses, lymphocytes from spleen and lymph nodes of sham- engrafted mice (AT x BM-SHAM) were essentially void of T cells, whereas in AT x BM thymus-engrafted (AT x BM-THG) mice, which served as a positive control for T cell repopulation, normal levels of T cells were present in spleen and lymph nodes by week 3 postengraftment, and at times thereafter. Most striking, however, was the finding that T cell repopulation of the spleen and lymph nodes occurred in AT x BM fetal intestine-engrafted (AT x BM-FIG) mice beginning 3 wk postengraftment. Based on H-2 expression, peripheral T cells in AT x BM-FIG mice were of donor bone marrow origin, and consisted of CD3+, T cell receptor (TCR)- alpha/beta+ T cells with both CD4+8- and CD4-8+ subsets. Peripheral T cells in AT x BM-FIG mice were functionally mature, as demonstrated by their capacity to proliferate after stimulation of CD3 epsilon. Moreover, alloreactive cytotoxic T lymphocytes were generated in primary in vitro cultures of spleen cells from AT x BM-FIG and AT x BM- THG mice, though not in spleen cell cultures from AT x BM-SHAM mice. Histologic studies of engrafted tissues 3-4 wk postengraftment demonstrated that thymus leukemia (Tl) antigens were expressed on epithelial surfaces of intestine grafts, and that both TCR-alpha/beta+ and TCR-gamma/delta+ lymphocytes were present in intestine grafts. Collectively, these findings indicate that the murine small intestine has the capacity to initiate and regulate T cell development from bone marrow precursors, thus providing a mechanism by which extrathymic development of intestine lymphocytes occur.
Privacy-Preserving Ubiquitous Social Mining via Modular and Compositional Virtual Sensors

The introduction of ubiquitous systems, wearable computing and 'Internet of Things' technologies in our digital society results in a large-scale data generation. Environmental, home, and mobile sensors are only a few examples of the significant capabilities to collect massive data in real-time from a plethora of heterogeneous social environments. These capabilities provide us with a unique opportunity to understand and tackle complex problems with new novel approaches based on reasoning about data. However, existing 'Big Data' approaches often turn this opportunity into a threat of citizens' privacy and open participation by surveilling, profiling and discriminating people via closed proprietary data mining services. This paper illustrates how to design and build an open participatory platform for privacy-preserving social mining: the Planetary Nervous System. Building such a complex platform in which data sharing and collection is self-determined by the user and is performed in a decentralized fashion within different ubiquitous environments is a challenge. This paper tackles this challenge by introducing a modular and compositional design approach based on a model of virtual sensors. Virtual sensors provide a holistic approach to build the core functionality of the Planetary Nervous System but also social mining applications that extend the core functionality. The holistic modeling approach with virtual sensors has the potential to simplify the engagement of citizens in different innovative crowd-sourcing activities and increase its adoption by building communities. Performance evaluations of virtual sensors in the Planetary Nervous System confirm the feasibility of the model to build real-time ubiquitous social mining services.