Miracle-dz/UniFAR-FTUs huggingface dataset:
Elementary Engineering as a Synergistic Site for Disciplinary and Linguistic Learning in an Urban Classroom

This case study of new English-language learners in an urban elementary U.S. classroom addresses the synergy between disciplinary language and science, technology, engineering, math (STEM) learning. Social semiotic theory frames the discourse demands related to engineering design and the active use of discursive resources in students’ responses to these demands. Discourse analysis of students’ interactions and writing provides a fine-grained view of “language in use” within an engineering design space where students demonstrated linguistic agency and productive engineering accomplishments. The case provides insights for educators who seek to optimize the integration of the language of STEM with culturally and linguistically responsive engineering education.
Quantitative in vivo receptor binding. II. Autoradiographic imaging of muscarinic cholinergic receptors

The in vivo distribution of [3H]scopolamine in rat brain following establishment of constant, saturating arterial tracer concentrations was examined with the use of quantitative autoradiography. The equilibrium drug distribution, studied 240 min after initiation of tracer infusion, was highly correlated with the regional density of muscarinic receptor sites determined in vitro in the same animals by autoradiographic analysis of [3H]quinuclidinyl benzilate binding. Brain regions of highest receptor density were generally correlated with known terminal fields of cholinergic neurons, and they demonstrated a protracted time course of in vivo labeling. An exception was noted in the basal pons, where a receptor population of high density without documented cholinergic innervation was rapidly labeled. It is suggested that synaptic muscarinic receptors are labeled slowly, as a consequence of either restricted tracer accessibility or competition between tracer and endogenous acetylcholine for available binding sites, and that the pontine receptors may be functionally distinct from those in other brain regions. The in vivo equilibrium binding technique used in the present study results in regional tissue radioligand concentrations directly proportional to receptor density and may, thus, provide a basis for receptor imaging in the human brain by means of positron emission tomography.
Verification for Timed Automata Extended with Unbounded Discrete Data Structures

We study decidability of verification problems for timed automata extended with unbounded discrete data structures. More detailed, we extend timed automata with a pushdown stack. In this way, we obtain a strong model that may for instance be used to model real-time programs with procedure calls. It is long known that the reachability problem for this model is decidable. The goal of this paper is to identify subclasses of timed pushdown automata for which the language inclusion problem and related problems are decidable.
Improving classification accuracy using Fuzzy Clustering Coefficients of Variations (FCCV) feature selection algorithm

One of the challenges in inferring a classification model with good prediction accuracy is to select the relevant features that contribute to maximum predictive power. Many feature selection techniques have been proposed and studied in the past, but none so far claimed to be the best. In this paper, a novel and efficient feature selection method called Fuzzy Clustering Coefficients of Variation (FCCV) is proposed. FCCV is based on a very simple principle of variance-basis which finds an optimal balance between generalization and over-fitting. Through a computer simulation experiment, 44 datasets with substantially large number of features are tested by FCCV in comparison to four popular feature selection techniques. Results show that FCCV outperformed them in all aspects of averaged performances and speed. By the simplicity of design it is anticipated that FCCV will be a useful alternative of preprocessing method for classification especially with those datasets that are characterized by many features.
Applying hidden topics in ranking social update streams on Twitter

As the number of users using Twitter1 increases, an user may have a lot of friends whose tweet (posting) list (also called as “social update stream” [5, 8, 18]) may overwhelm his/her homepage. This can lead to the situation where important tweets (i.e. the tweets the user is interested in) are pushed down on the list, thus, it takes time to find them. Social update stream ranking is a possible solution that puts important tweets on the top of the page, so that the user can easily read it. In this paper, we propose to apply hidden topics [1, 15, 20] in the Combined Regression Ranking algorithm [2] to rank social update streams. The proposed system works like a content based recommendation system. The experimental results show a significant improvement proving that our proposal is a suitable direction.
SIMULTANEOUS LOCALIZATION AND MAP BUILDING BY A MOBILE ROBOT USING SONAR SENSORS

This paper presents a methodology to self localization of autonomous mobile robot using two distinct structures of metric maps. Ultrasonic sonar ranger sensors are used to build an occupancy grid, the ﬁrst structure, and a map based on line segments extracted from the occupancy grid is built. The two maps are used to estimate an correct errors on odometric sensors.
Are International Equity Market Returns Predictable?

The slope coefficient estimator in predictive regressions for stock returns is biased by a lagged stochastic regressor. There is also a spurious regression if the underlying expected return is highly persistent. This paper studies how the interactions between the two biases affect inferences about the predictability in international equity market returns. The analysis considers how the biases work in the presence of data mining for the predictive variables. I find that the two biases can reinforce or offset each other, depending on the parameters of the model. I present a new correction for the bias in the presence of both effects and evaluate its economic significance. Adjusting for data mining associated with both effects, I find that many of the global predictors have a weak explanatory power when they are individually regressed against the world market returns. Using global and local predictors, we cannot reject the null hypothesis that the predictability is an outcome of data mining for 10 of the 18 national equity market returns once we account for the apparent number of searches.
Color image compression using multiwavelets with modified SPIHT algorithm

Color Image compression is now essential for applications such as transmission and storage in data bases since color gives a natural and pleasing nature for any object. For still image compression, the ‘Joint Photographic Experts Group’ standard has been established by International Standards Organization (ISO). The performance of existing image coding standards generally degrades at low bit-rates because of the underlying block based Discrete Cosine Transform (DCT) scheme. Over the past decade, the success of wavelets in solving many different problems has contributed to its unprecedented popularity. Due to implementation constraints, scalar wavelets do not possess all the properties which are needed for a better performance in compression. The new class of wavelets, called multiwavelets, which possess more than one scaling filters overcomes this problem. The objective of this paper is to develop an efficient color compression scheme and to obtain better quality and higher compression ratio through multiwavelet transform and embedded coding of multiwavelet coefficients through Set Partitioning In Hierarchical Trees (SPIHT) algorithm. A comparison of the best known multiwavelets is made to the best known scalar wavelets. Both quantitative and qualitative measures of performance are examined.
Ting: making publics through provocation, conflict and appropriation

In Swedish the word "ting" has different meanings. It can mean "things", "matters" and "a session at court" as well as the act of appropriating space. This one-day workshop starts in the notion of the artifact as a "ting", and design as something that raises a question, provokes a discussion, and creates a public through which agonistic encounters occur. This particular lens allows us to approach design beyond 'merely producing artifacts'. Instead, we come to see it as a production of provocations, speculations, and alternative interpretations of the social world as well as new sets of relationships between participants in this public. Because of the importance of the role and embodiment of the designer/artist in making publics, this workshop calls attention to self-reflective practices in participatory design, and questions how these practices can be embedded in the functionality of new publics and design practices.
Nucleus Accumbens Dopamine/Glutamate Interaction Switches Modes to Generate Desire versus Dread: D1 Alone for Appetitive Eating But D1 and D2 Together for Fear

The medial shell of nucleus accumbens (NAc) and its mesolimbic dopamine inputs mediate forms of fearful as well as of incentive motivation. For example, either appetitive and/or actively fearful behaviors are generated in a keyboard pattern by localized glutamate disruptions in NAc (via microinjection of the AMPA receptor antagonist DNQX) at different anatomical locations along a rostrocaudal gradient within the medial shell of rats. Rostral glutamate disruptions produce intense increases in eating, but more caudally placed disruptions produce increasingly fearful behaviors: distress vocalizations and escape attempts to human touch, and a spontaneous and directed antipredator response called defensive treading/burying. Local endogenous dopamine is required for either intense motivation to be generated by AMPA disruptions. Here we report that only endogenous local signaling at D1 dopamine receptors is needed for rostral generation of excessive eating, potentially implicating a direct output pathway contribution. In contrast, fear generation at caudal sites requires both D1 and D2 signaling simultaneously, potentially implicating an indirect output pathway contribution. Finally, when motivation valence generated by AMPA disruptions at intermediate sites was flipped by manipulating environmental ambience, from mostly appetitive in a comfortable home environment to mostly fearful in a stressful environment, the roles of local D1 and D2 signaling in dopamine/glutamate interaction at microinjection sites also switched dynamically to match the motivation valence generated at the moment. Thus, NAc D1 and D2 receptors, and their associated neuronal circuits, play different and dynamic roles in enabling desire and dread to be generated by localized NAc glutamate disruptions in medial shell.
Cooperative secret delivery in wireless sensor networks

In the technical literature, many random key pre-distribution techniques have been proposed to secure wireless sensor networks WSNs. Such techniques only establish keys for some pairs of physically connected sensors. On the contrary, in many WSN applications, a source node must securely communicate with all of its neighbours. In this work, we address the issue of delivering secret link keys to each of the source's neighbours in WSNs. We propose a scheme called cooperative secret delivery CSD that finds bridge nodes to deliver keys to the insecure neighbours, which share no prior keys with the source. The novelty of our scheme is to deliver multiple keys through these bridge nodes and regular paths instead of multi-hop secure paths. Since the secret link keys are delivered cooperatively by the bridge nodes in the CSD scheme, secret disclosure probability is significantly lower compared to other delivery techniques. We perform extensive theoretical analysis and performance evaluation on the CSD scheme and demonstrate its salient features.
EVIDENCE FOR A SUPRASPINAL CONTRIBUTION TO HUMAN MUSCLE FATIGUE

1 Muscle fatigue can be defined as any exercise‐induced loss of ability to produce force with a muscle or muscle group. It involves processes at all levels of the motor pathway between the brain and the muscle. Central fatigue represents the failure of the nervous system to drive the muscle maximally. It is defined as a progressive exercise‐induced reduction in voluntary activation or neural drive to the muscle. Supraspinal fatigue is a component of central fatigue. It can be defined as an exercise‐induced decline in force caused by suboptimal output from the motor cortex. 2 When stimulus intensity is set appropriately, transcranial magnetic stimulation (TMS) over the motor cortex during an isometric maximal voluntary contraction (MVC) of the elbow flexors commonly evokes a small twitch‐like increment in flexion force. This increment indicates that, despite the subject's maximal effort, motor cortical output at the moment of stimulation was not maximal and was not sufficient to drive the motoneurons to produce maximal force from the muscle. An exercise‐induced increase in this increment demonstrates supraspinal fatigue. 3 Supraspinal fatigue has been demonstrated during fatiguing sustained and intermittent maximal and submaximal contractions of the elbow flexors where it accounts for about one‐quarter of the loss of force of fatigue. It is linked to activity and the development of fatigue in the tested muscles and is little influenced by exercise performed by other muscles. 4 The mechanisms of supraspinal fatigue are unclear. Although changes in the behaviour of cortical neurons and spinal motoneurons occur during fatigue, they can be dissociated from supraspinal fatigue. One factor that may contribute to supraspinal fatigue is the firing of fatigue‐sensitive muscle afferents that may act to impair voluntary descending drive.
EMOTION REGULATION STRATEGIES AS TRANSDIAGNOSTIC PROCESSES: A CLOSER LOOK AT THE INVARIANCE OF THEIR FORM AND FUNCTION

Recent investigations suggest that emotion regulation can be conceptualized as a trans- diagnostic process (Kring & Sloan, 2010). Specifically, the habitual use of putatively maladaptive emotion regulation strategies (e.g., rumination, suppression), and the infrequent use of putatively adaptive strategies (e.g., acceptance, reappraisal) have been shown to predict various symptoms of psychopathology (Aldao et al., 2010). However, little is known about the extent to which the dif- ferent facets that constitute the process of implementing such strategies can be conceptualized as transdiagnostic. I propose the adoption of a functional behavioral approach to delineate which aspects of such implementation (i.e., form, function) are variant and which are invariant across disorders. This approach has the potential to further our understanding of the transdiagnostic and disorder- specific mechanisms by which emotion regulation is associated with the development, maintenance, and treatment of mental disorders.
TRANSIENT AND DELAY ANALYSIS FOR ON-CHIP HIGH SPEED VLSI RLCG INTERCONNECTION NETWORK IN 0.18µm TECHNOLOGY

In this paper, the time domain waveform is approximated for calculation of delay, rise, settling time, damping ratio and natural frequency of a second order RLCG on-chip VLSI interconnect line. It can also be evaluated for multiple interconnect systems but due to harmonics higher order systems are ignored. The model is applied to a single RLCG interconnect line which can also be extended for multi-interconnect systems to analyze crosstalk noise. The model evaluates the performance of a system which is expressed in terms of the transient response due to a unit step input. It is easy to generate and evaluate the delay analytically. A closed form expression for the propagation delay of a CMOS gate driving a distributed RLCG line is introduced. On-chip inductance and conductance are expected to have a profound effect on traditional high performance IC design methodologies. In the proposed model, it is shown that when the value of G is increased, the time at which the rise time, settling time and the time when the steady state condition is reached are all increased. So, for high speed circuits one must increase the value of G so that the steady state condition is reached quickly and it is also shown that with the increase in the value of G the delay will reduce. The simulation results performed in SPICE environment justify the efficacy of the proposed model.
New fast QR decomposition least squares adaptive algorithms

This paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obtained via a QR decomposition (QRD). Both algorithms are of O(p) computational complexity, with p being the order of the system. The first algorithm is a fixed order QRD scheme with enhanced parallelism. The second is an order recursive lattice type algorithm based exclusively on orthogonal Givens rotations, with lower complexity compared to previously derived ones. Both algorithms are derived following a new approach, which exploits efficient the and order updates of a specific state vector quantity.
Ensuring Energy Efficient 5G User Equipment by Technology Evolution and Reuse

Research on fifth generation (5G) radio access technology (RAT) is ramping up, with the goal of significantly improving user data rates and latency compared to previous RAT generations. While energy efficiency (EE) of the user equipment (UE) was not a key optimization parameter for the current wireless standards, it is anticipated to become a distinguishing factor for 5G. In this paper, we analyze established and emerging technological solutions for features such as waveform, frame structure, duplexing and multiple antenna transmission from an EE perspective. Our contribution is to identify and discuss the features' pros and cons in achieving high performance in terms of data rate and/or latency while limiting their effect on the UE power consumption. Based on the discussion we give general recommendations for an energy efficient 5G design in the context of a previously proposed RAT concept.
Learning Occupancy in Single Person Offices with Mixtures of Multi-lag Markov Chains

The problem of real-time occupancy forecasting for single person offices is critical for energy efficient buildings which use predictive control techniques. Due to the highly uncertain nature of occupancy dynamics, the modeling and prediction of occupancy is a challenging problem. This paper proposes an algorithm for learning and predicting single occupant presence in office buildings, by considering the occupant behaviour as an ensemble of multiple Markov models at different time lags. This model has been tested using real occupancy data collected from PIR sensors installed in three different buildings and compared with state of the art methods, reducing the error rate by on average 5% over the best comparator method.
MBMS - IP Multicast/Broadcast in 3G Networks

In this article, the Multimedia Broadcast and Multicast Service (MBMS) as standardized in 3GPP is presented. With MBMS, multicast and broadcast capabilities are introduced into cellular networks. After an introduction into MBMS technology, MBMS radio bearer realizations are presented. Different MBMS bearer services like broadcast mode, enhanced broadcast mode and multicast mode are discussed. Streaming and download services over MBMS are presented and supported media codecs are listed. Service layer components as defined in Open Mobile Alliance (OMA) are introduced. For a Mobile TV use case capacity improvements achieved by MBMS are shown. Finally, evolution of MBMS as part of 3GPP standardization is presented.
Pure and cued recall-based graphical user authentication

Nowadays, user authentication is one of the important topics in information security. Text-based strong password schemes could provide with certain degree of security. However, the fact that strong passwords being difficult to memorize often leads their owners to write them down on papers or even save them in a computer file. Graphical authentication has been proposed as a possible alternative solution to text-based authentication, motivated particularly by the fact that humans can remember images better than text. In recent years, many networks, computer systems and Internet-based environments try used graphical authentication technique for their user's authentication. All of graphical passwords have two different aspects which are usability and security, unfortunately none of these algorithms were not being able to cover both of these aspects at the same time. This paper presents a review on the pure and cued recall-based algorithms in graphical password authentication. On each of these algorithms the lacks and attacks are indentified. The most common lacks and attacks for recall-based algorithms are then identified and described.
Direction estimation of mixed noncoherent and coherent signals with oblique projector

In this paper, we investigate the direction-of-arrivals (DOAs) estimation of a mixed noncoherent and coherent signals impinging on a uniform linear array (ULA). The DOAs of noncoherent and coherent signals are estimated separately, and a new oblique projector is obtained to isolate the coherent signals from the noncoherent ones. Compared with previous works, the proposed method overcomes the “saturation effect” encountered by most differencing and oblique projection based methods where the estimated DOAs of coherent signals have high elevated error floors. Moreover, the computationally intensive eigendecomposition is avoided and the numerical examples confirm the effectiveness of the proposed method.
A Taxonomy of Fatigue Concepts and Their Relation to Hearing Loss

Fatigue is common in individuals with a variety of chronic health conditions and can have significant negative effects on quality of life. Although limited in scope, recent work suggests persons with hearing loss may be at increased risk for fatigue, in part due to effortful listening that is exacerbated by their hearing impairment. However, the mechanisms responsible for hearing loss-related fatigue, and the efficacy of audiologic interventions for reducing fatigue, remain unclear. To improve our understanding of hearing loss-related fatigue, as a field it is important to develop a common conceptual understanding of this construct. In this article, the broader fatigue literature is reviewed to identify and describe core constructs, consequences, and methods for assessing fatigue and related constructs. Finally, the current knowledge linking hearing loss and fatigue is described and may be summarized as follows: Hearing impairment may increase the risk of subjective fatigue and vigor deficits; adults with hearing loss require more time to recover from fatigue after work and have more work absences; sustained, effortful, listening can be fatiguing; optimal methods for eliciting and measuring fatigue in persons with hearing loss remain unclear and may vary with listening condition; and amplification may minimize decrements in cognitive processing speed during sustained effortful listening. Future research is needed to develop reliable measurement methods to quantify hearing loss-related fatigue, explore factors responsible for modulating fatigue in people with hearing loss, and identify and evaluate potential interventions for reducing hearing loss-related fatigue.