Miracle-dz/UniFAR-FTUs huggingface dataset:
"You Learn Best When You're in There": ESOL Teacher Learning in the Practicum.

Th is study relied on sociocultural understanding of teacher learning, which highlights how teacher candidates construct their own learning and adjust or extend their instructional values, priorities, and beliefs within their teaching contexts (Johnson, 2009). It used activity theory as a conceptual framework (Engeström, 1999) and explored how teaching practicum experiences contributed to 5 ESOL teacher candidates’ learning in a 13-month intensive MA TESOL program. Findings from the study illustrate that the teaching practicum made signifi cant contributions to ESOL teacher candidates’ learning to teach in the program. Th rough the teaching practicum, teacher candidates (a) learned how to navigate in the school context, (b) learned about the nature of establishing relationships with the other members of the teaching community, (c) used the mediating artifacts with the support of mentors and supervisors, (d) found opportunities for constructing a mutually informative and dialogical relationship between theory and practice, and (e) gained closer understanding of ELLs.
A new crossbar architecture based on two serial memristors with threshold

This paper presents a memory crossbar based on two serial memristors with threshold characteristic to eliminate the effect of sneak paths, which is a key issue in crossbar memory system leading to great degradation in their performance and power efficiency. At first, we analyze the threshold characteristic of memristor and propose a memristor model with threshold. Based on this model, the paper presents the design and simulation of a non-volatile memory system utilizing two serial memristors with different polarities as a memory cell. This scheme solves the sneak-path problem by taking advantage of the threshold characteristic and the performance with having always high resistance state in all the memory cells, which is validated by simulation results. The scheme also possesses the superior properties of remarkable compatibility and high density.
Comparison of Tourism Data Using Double Ranking

The prompt discovery and mining of user's reputation, opinion and complaint are becoming a hot topic in the field of search engine for Blog and Twitter. This paper proposes "Double Rank" method to analyze the search result using two viewpoints, where the polarity degree of keywords in the search results are evaluated from the viewpoints. Most previous researches concern mainly in positive and negative evaluation as for the polarity degree. Two viewpoints are specified as the search condition in the present paper. The blog articles related to sightseeing are analyzed as case studies, where the characteristics and the sightseeing situation are compared for two prefectures.
A clinical comparison between MDVP and Praat softwares: is there a difference?

MDVP and Praat are computer programs commonly used for acoustic analysis of voice in clinical and research settings. Both softwares extract a set of acoustic parameters, many of which are defined similarly. The purpose of the present study was to compare the results obtained by both programs, and examine whether they can clinically distinguish among pathological groups differently than the other. Fifty-eight women participated in the study. Of these women, 28 were diagnosed with functional dysphonia and 30 women were diagnosed with benign mass-lesions (ten nodules, ten polyps and ten cysts). Voice samples, which consisted of six productions of the vowels /a/ and /i/, were analyzed using MDVP and Praat. Results show similar mean fundamental-frequency (mF0) values for both programs (P>0.05). However, jitter, shimmer, Noise-to-harmonic ratio (NHR) and degree of unvoiced (DUV) were significantly lower using Praat, in comparison with MDVP. High correlation coefficients were found between the parallel pairs of acoustic parameters extracted by the two programs. Jitter values obtained using MDVP, for the vowel /i/, revealed a significant group difference between the nodule and cyst groups (P<0.05). This group contrast was not observed using Praat. Results suggest that although high correlations are found between values obtained by both programs, individual numerical values vary greatly. Therefore, combining results from both programs is not advisable. In addition, there are indications that linear transformation for the results from one program to the other might lead to erroneous conclusions, and should be carried out with caution.
Heuristic Task Scheduling with Artificial Bee Colony Algorithm for Virtual Machines

Cloud computing is one of the Information Technology services which are provided from IT infrastructures to application services. It is the combination of Distributed computing and virtualization technology using virtual machines, an essential component in Cloud computing. Therefore, task scheduling is an important matter to consider for virtual machines to balance load of each machine and to efficiently use the resources in Cloud computing. This paper proposes the use of Heuristic task scheduling with Artificial Bee Colony algorithm for virtual machines in heterogeneous Cloud computing, called HABC. The research aim is to introduce HABC, which is a new task scheduling and load balancing algorithm, for virtual machines in heterogeneous environments to reduce the makespan in the system. In the experiments, CloudSim was simulated to compare various types of the optimization task scheduling in using the virtual machines. The experimental results indicated that using the proposed Artificial Bee Colony algorithm when large job was considered first (HABC_LJF) in virtual machine scheduling, improved the efficiency in task scheduling and load balancing of virtual machines in Cloud computing. In addition, the proposed algorithm can minimize the makespan even if the tasks are increased and the different types of data are distributed.
Traditional and Molecular Techniques for the Study of Emerging Bacterial Diseases: One Laboratory’s Perspective

Identification of emerging bacterial pathogens generally results from a chain of events involving microscopy, serology, molecular tools, and culture. Because of the spectacular molecular techniques developed in the last decades, some authors think that these techniques will shortly supplant culture. The key steps that led to the discovery of emerging bacteria have been reviewed to determine the real contribution of each technique. Historically, microscopy has played a major role. Serology provided indirect evidence for causality. Isolation and culture were crucial, as all emerging bacteria have been grown on artificial media or cell lines or at least propagated in animals. With the use of broad-range polymerase chain reaction, some bacteria have been identified or detected in new clinical syndromes. Culture has irreplaceable advantages for studying emerging bacterial diseases, as it allows antigenic studies, antibiotic susceptibility testing, experimental models, and genetic studies to be carried out, and remains the ultimate goal of pathogen identification.
Framing the scope of value in exploratory projects: An expansive value management model

Organizations often launch exploration projects (EP) aiming at developing innovative products (or services) by the exploration of new technologies, users, ecosystems or business models. Because a fundamental purpose of any project is to create value, the approach of value management (or value engineering) has been largely adopted in the organizations to manage the projects. However, the fact to move beyond the existing markets and the established technologies imply great difficulties and uncertainties for managing creative projects. Indeed, because exploration projects precisely aim to invent products (or services) that do not exist before, the value to create is unknown at the start of such project. So, what does value management precisely mean in situation of exploration project? This research aims to clarify the nature, the beneficiaries, and the ways to manage the value in such situations. After reviewing the historical development of the two traditional approaches of value management in project management literature, we then show we show their inadequacies for managing exploratory situations. This article is based on a longitudinal of two case-studies into a collaborative management research conducted with a major French car manufacturer. The two case-studies are an inter-firm EP corresponding to the joint exploration of an innovative multimodal urban platform by the automotive firm and two other industrial partners and an intra-firm EP aiming at generating innovative projects for the development of the electric vehicles. We propose an expansive value management model (EVM) towards three main propositions: 1) evaluating and stimulating the creation of value with a constant comparison with the dominant designs - (2) sustaining the exploration by tuning the degree of undecidability - (3) stimulating the emergence of new ecosystems by the creation of new platforms projects. Finally, this research proposes key managerial principles for EP management and a set of indicators to monitor the exploration process (i.e. identifying design rules to break, managing two kind of design paths.) and the collective dimension (i.e. the beneficiaries.) of EP.
Two New Weight Initialization Strategies of LMS Adaptive Linear Equalizer in Underwater Acoustic Communication

Underwater acoustic (UWA) communication is a cross subject of the communication technology and underwater acoustic signal processing technology, which is very valuable in military and civil applications. But the multipath effect of UWA channel leads to inter symbol interference ¿ISI¿more than hundreds of code intervals, so it is necessary to apply an equalizer to eliminate the ISI in the receiving unit. This paper proposes two new weight initialization strategies for the least mean square (LMS) adaptive linear equalizer due to the bad performance with all zero initialization algorithm. Both the two new strategies improve the equalization performance of LMS adaptive linear equalizer and reduce the error code rate of the UWA communication system greatly.
New Ternary Logic Subtractor Using Carbon Nanotube Field-Effect Transistors

— In this paper, we present a new Ternary logic Subtractor (TLS) that is implemented by CNTFET. In addition, we investigate the design of two Novel subtractors based on the proposed TLS. Ternary results are better than the Binary ones. Results show large decrements in delay time. Further, the second presented circuit with its Simulation results has demonstrated significant development in speed, area and power consumption. In the past extensive design techniques, Multiple-Valued Logic (MVL) circuits (especially ternary logic inverters) have been proposed by CMOS Technology. Here, the new TLS based on CNTFETs is presented, and wide simulation results have been done by HSPICE.
Quantitative Evaluation of Percussive Gestures by Ranking Trainees versus Teacher

In this paper we characterize timpani gestures by temporal kinematic features, containing most information responsible for the sound-producing actions. In order to evaluate the feature sets, a classification approach is conducted under three main attack categories (legato, accent and vertical accent) and sub-categories (dynamics, striking position). Two studies are carried out: intra-subject and inter-subjects classification. Results are presented in terms of a quantitative ranking of students, using professional gestures as training set, and their gestures as test set.
Process Mining application considering the organizational perspective using Social Network Analysis

Process Mining aims to extract useful information from event log by providing techniques and tools that are used for discovering process, control flow, organizational, and social structures from these logs. During this work, we will cover definitions of process mining, social network analysis and how we can mine a social network using process mining techniques. Event logs normally record information about the users executing the activities recorded in the log, so it is possible to extract social network from these logs for further analysis. To do so we combine concepts from process mining and social network analysis. Also a case study will be executed in order to proof the applicability of what has been theoretically mentioned.
Review: Information, Sensation, and Perception

One might expect a book under this title to be simply an application of information theory, once very fashionable in psychology, to problems of sensation and perception. But the author declares that his ultimate concern is with the epistemological intuitions of George Berkeley, the 18th century English philosopher; information theory enters merely as a vehicle for expressing those intuitions in operational terms. Present-day perceptual psychologists, however, will be interested chiefly in the author's attempt to accommodate some ten empirical relationships ('laws') within a coherent mathematical theory, a theory consciously constructed after the pattern of physical science, borrowing especially from the ideal communication theory of Shannon (1948) and also from thermodynamics. Mathematical argument is more precise than verbal, permitting thereby the formulation of much more delicate arguments, but it is otherwise no different in kind. At the end of the day it has to make psychological sense, such as any verbal argument. The author may choose his symbols to signify what he pleases, but thereafter each formula is a precise expression which must transpose into some meaningful psychological statement. However, many readers will be sufficiently unsure in following the algebraic manipulations to be confident that their interpretation of the formulae is accurate. The chief task of this review, therefore, is to decode the principal equations and express their meanings in psychological terms. This is not a trivial matter. At the heart of the mathematical argument is the equation (page 140)
Neurotransmitters and Brain Maturation: Early Paracrine Actions of GABA and Glutamate Modulate Neuronal Migration

Migration of neurons from their birthplace to their final destination is an extremely important step in brain maturation, and cortical migration disorders are the most common brain developmental alteration observed in human patients. Among the mechanisms that govern neuronal migration, the neurotransmitters GABA and glutamate deserve particular attention: 1) neurotransmitters and receptors are expressed early in the developing brain, 2) neurotransmitters may act as paracrine signaling molecules in the immature brain, and 3) neurotransmitters regulate intracellular calcium required for many cellular functions, including cytoskeletal dynamic changes. Thus, many reports reviewed here aimed to demonstrate that the activation of specific GABA and glutamate receptors is instrumental in cell migration by acting as motility promoting, acceleratory, or stop signal. Interestingly, the regulation of migration by neurotransmitters and receptors depends on the type of migration (radial, tangential, or chain migration), the type of cells (principal glutamatergic neurons vs. GABAergic interneurons), and the brain area (neocortex, cerebellum, rostral migratory stream). A hypothesis is proposed that these differential actions in different cell types arise from a “homeostatic-like” regulation that controls final position, timing, and number of cells at destination. NEUROSCIENTIST 13(3):268—279, 2007.
High-Dimensional CSI Acquisition in Massive MIMO: Sparsity-Inspired Approaches

Massive multiple-input–multiple-output (MIMO) has been regarded as one of the key technologies for fifth-generation wireless networks, as it can significantly improve both the spectral efficiency and the energy efficiency. The availability of high-dimensional channel side information (CSI) is critical for its promised performance gains, but the overhead of acquiring CSI may potentially deplete the available radio resources. Fortunately, it has recently been discovered that harnessing various sparsity structures in massive MIMO channels can lead to significant overhead reduction, and thus improve the system performance. This paper presents and discusses the use of sparsity-inspired CSI acquisition techniques for massive MIMO, as well as the underlying mathematical theory. Sparsity-inspired approaches for both frequency-division duplexing and time-division duplexing massive MIMO systems will be examined and compared from an overall system perspective, including the design tradeoffs between the two duplexing modes, computational complexity of acquisition algorithms, and applicability of sparsity structures. Meanwhile, some future prospects for research on high-dimensional CSI acquisition to meet practical demands will be identified.
Anti-CD7 antibody and immunotoxin treatment of human CD7+T-cell leukaemia is significantly less effective in NOD/LtSz-scid mice than in CB.17 scid mice

Groups of 8 to ten SCID (CB.17 scid/scid) or NOD/SCID (NOD/LtSz- scid/scid) mice were injected i.v. with two million human HSB-2 T-ALL cells on day 1 (SCID-HSB-2 and NOD/SCID-HSB-2 mice) and treated later with 3 i.v. 10 μg doses of the anti-CD7 antibody HB2 on days 7, 9 and 11 or with a single 10 μg dose of HB2-SAPORIN or a 7.4 μg dose of HB2-F(ab)2-SAPORIN immunotoxin (IT) on day 7. Treatment of SCID-HSB-2 mice with HB2-SAPORIN led to a significant prolongation in the time to development of signs and symptoms of disease compared with PBS sham-treated controls with 80% of animals surviving disease-free. In contrast treatment with HB2-F(ab)2-SAPORIN was significantly less effective in SCID-HSB-2 mice with 80% of animals in this treatment group developing leukaemia over the course of the study. HB2 antibody treatment of SCID-HSB-2 mice also led to a significant prolongation in time to leukaemia development compared with sham-treated controls with 37% of animals in this treatment group disease-free at termination of the study. In contrast HB2 antibody treatment of NOD/SCID-HSB-2 mice had no therapeutic effect in these animals and the therapeutic effectiveness of both HB2-SAPORIN and HB2-F(ab)2-SAPORIN ITs was similar and significantly reduced compared to the effect observed in SCID-HSB-2 mice. It was initially thought that the lack of therapeutic effect of antibody and IT in NOD-SCID-HSB-2 mice might relate to their putative lack of NK cells but flow cytometric and functional studies with NOD-SCID mouse splenocytes revealed that these animals do have some functional NK cells though fewer in number and possibly lower in functionality than those of SCID mice. We reason that the complete lack of therapeutic effect of HB2 antibody and the reduced effect of HB2-SAPORIN in NOD/SCID mice is due to the reduced cytolytic activity of NOD/SCID NK cells which is probably below a certain critical threshold value in these animals. We conclude from this that immunotherapeutics like HB2-SAPORIN would be more accurately assessed for intrinsic potency in NOD/SCID mice where the effects of NK cell and possibly other non-adaptive immune mechanisms would not have a significant influence. © 2000 Cancer Research Campaign http://www.bjcancer. com
REODM: Identify Local Outliers in Big Data

Outlier detection is now widely used in various fields. It attracts more and more interests in research. The density based outlier detection methods and the distance based outlier detection methods are the most frequently used outlier detection methods. In big data, the size and dimensions of data is very large. Those features make the conventional methods not suitable for big data. According to the features of big data, we propose a novel REODM method. Based on the rough set theory, we propose a relevant set, which is used to replace the universe set to improve the calculation speed. The REODM method is based on the ensemble learning. It is robust and accurate. We compare the performance of REODM, LOF and KNN methods. The experimental results show that the recall rate and precision of REODM is much better than LOF and KNN method.
Yaşama Anlam Yükleme-Yaşam Amaçları Belirleme: Madde Bağımlısı Olan ve Olmayan Gençlerin Karşılaştırılması

The present study aims to make a comparison between young men who are substance-abusers and non-abusers in terms of how they set their life goals and attribute meanings to life. In line with this purpose, this study was conducted through quantitative and qualitative method. In the quantitative analysis, the study group consists of 108 participants between 20 and 24 years old, 56 of whom are substance abusers and 52 of whom are non-substance abusers. In the qualitative analysis, the study group involves 30 substance abusers and 30 non-substance abusers. The scale of setting life goals in terms of positive psychotherapy and the semi-structured qualitative interview form was used in order to collect data. The independent t-test and sentence-based content analysis technique was used to analyze data. The findings revealed that the substance abusers were having difficulty in attributing meaning to their lives when compared to the non-abusers. Moreover, the substance abusers were capable of setting far fewer life goals than were the non-abusers.
Fatigue detection based on isophote curve

In order to improve the fatigue detection timeliness and accuracy, the optimization of isophote cure is used to locate the eyes, which reduces the amount of computation and improves the processing speed. First, according to facial features, the skin's Gaussian model is established to differentiate face. The integral projection is used to locate the face. The area of eye is separated on the basis of three court five, and it uses the optimization of isophote cure to locate exactly eye. The gray value of the tiny area of eye is calculated and is used for the information of eye's open and close, that is the PERCLOS value, and to determine whether one is fatigue or not. From the experiment, the system has a good timeliness and high detection accuracy.
3-D transfered control using spilling avoidance control for meal assist robot by using CFD simulator

In the near future, there will be a significant problem obtaining workers in the fields of welfare and nursing care because of a labor shortage. To solve this problem, many welfare robots, such as an upper extremity motion assistance robot and a meal assistance robot, have been studied. The purpose of this paper is to avoid spilling of the liquid when the spoon is transferred. In order to avoid spilling of the liquid, a spilling model was evaluated by using a CFD simulator. Thus, it was not necessary to build an exact model of the spilling model mechanism. The effectiveness of the proposed control is shown by CFD simulations and experiments.
An Alternating Least Squares Algorithm with Application to Image Processing

Least Squares (LS) estimation is a classical problem, often arising in practice. When the dimension of the problem is large, the solution may be difficult to obtain, due to complexity reasons. A general way to reduce the complexity is that of breaking the problem in smaller sub-problems. Following this approach, in the paper we introduce an Alternating Least Squares (ALS) algorithm that finds the LS estimate by iteratively solving two sub-problems. The algorithm can speed up the solution of any LS problem, but it is especially well suited for applications where the partition arises naturally so that the sub-problems have a structure and are simple to solve. To illustrate this fact, we discuss the application of the ALS to an image formation system affected by noise and drift, describing an efficient implementation and showing that the ALS is an effective image formation method. Key–Words: Least Squares, Image Formation