Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of A 0.3V–1.2V wide input range solar energy harvesting circuit with high converting power efficiency

This paper proposes a method to take advantage of the configurable capacitor array to cope with the input voltage instability caused by changes in ambient energy input variation. The proposed energy harvesting circuit can extend its input voltage to a much wider range in theory. Moreover, with our proposed adaptive conversion ratio technique, the input voltage range is not limited by the boundary of set-up or step-down conversion when implemented only one style, but not both. According to the measurement results, this design achieves about 70% in overall end-to-peak efficiency while start-up voltage is around 750mV. With adaptive conversion ratio control, the proposed circuit can maintain its conversion efficiency over 40% for the input voltage range from 300mV to 1.2V.
Engineered nanoparticles for targeted drug delivery

DNA based nanostructures and advances in DNA origami techniques have shown great potential in fabrication and of nanostructures and devices. Though a large number of DNA origami structures have been reported [1-3], very few applications of DNA structures have been presented. Custom shapes formed by programmable DNA self assembly can be used to engineer nanoscale devices such as a biological antenna. The focus of our research is to design a nanoscale antenna using DNA biostructure as a scaffold. Conductivity of such a biological antenna can be achieved by using conductive nanoparticles coating on DNA [4] or by attaching conducting polymers to DNA structures[5]. In this paper, we will present design of engineered nano-antennas with well defined engineering characteristics. Engineered nano-antennas have a resonant frequency, that can be used for diagnostic and drug delivery. The ability of such antennas to resonate at a particular frequency will give researchers the ability to communicate and control the nanoparticles. Such nanoparticles are carriers that can be used as advanced detection systems to help identifying toxicity of nanoparticles in the body. Organic molecules, such as folic acid, can be easily bonded to the surface of antenna to detect cancerous cells. We will further discuss detailed DNA origami techniques that can be used to realize such nanostructures.
About the Author 4 Future Directions

Memory disambiguation is a technique for removing spurious data dependences that severely limit the compiler’s freedom of code-scheduling. Though dependence tests for linear array references work well in many scientific applications, they are incapable of handling pointer dereferences, which are very common in general-purpose applications written in C-like languages. This paper 1 is a survey of several recently proposed memory disambiguation schemes that can handle pointer dereferences. They are classified as eitherstatic or dynamic. Static disambiguation uses data-flow analysis to compute an approximation of the set of memory aliases at each program point. Four static disambiguators are compared. Some evidences show that they may have already achieved high accuracy in practice. Dynamic disambiguation resolves at run-time any ambiguous data dependences that cannot be determined during compilation. A pure softwarebased and two hardware-assisted dynamic disambiguators are examined. While they can bridge part of the gap between a raw static disambiguator and a perfect one, there is still room for improvement. Based on our studies, we propose a number of future directions to develop memory disambiguators of better performance/cost. 1. The IBM contact for this paper is Graham Warren, manager, TOBEY Compiler Development, Compiler Back-End Technology, IBM Canada Laboratory.
Approximation and Randomization for Quantitative Information-Flow Analysis

Quantitative information-flow analysis (QIF) is an emerging technique for establishing information-theoretic confidentiality properties. Automation of QIF is an important step towards ensuring its practical applicability, since manual reasoning about program security has been shown to be a tedious and expensive task. Existing automated techniques for QIF fall short of providing full coverage of all program executions, especially in the presence of unbounded loops and data structures, which are notoriously difficult to analyze automatically. In this paper we propose a blend of approximation and randomization techniques to bear on the challenge of sufficiently precise, yet efficient computation of quantitative information flow properties. Our approach relies on a sampling method to enumerate large or unbounded secret spaces, and applies both static and dynamic program analysis techniques to deliver necessary over- and under-approximations of information-theoretic characteristics.
Conceptual grounding of language in action and perception: a neurocomputational model of the emergence of category specificity and semantic hubs

Current neurobiological accounts of language and cognition offer diverging views on the questions of ‘where’ and ‘how’ semantic information is stored and processed in the human brain. Neuroimaging data showing consistent activation of different multi‐modal areas during word and sentence comprehension suggest that all meanings are processed indistinctively, by a set of general semantic centres or ‘hubs’. However, words belonging to specific semantic categories selectively activate modality‐preferential areas; for example, action‐related words spark activity in dorsal motor cortex, whereas object‐related ones activate ventral visual areas. The evidence for category‐specific and category‐general semantic areas begs for a unifying explanation, able to integrate the emergence of both. Here, a neurobiological model offering such an explanation is described. Using a neural architecture replicating anatomical and neurophysiological features of frontal, occipital and temporal cortices, basic aspects of word learning and semantic grounding in action and perception were simulated. As the network underwent training, distributed lexico‐semantic circuits spontaneously emerged. These circuits exhibited different cortical distributions that reached into dorsal‐motor or ventral‐visual areas, reflecting the correlated category‐specific sensorimotor patterns that co‐occurred during action‐ or object‐related semantic grounding, respectively. Crucially, substantial numbers of neurons of both types of distributed circuits emerged in areas interfacing between modality‐preferential regions, i.e. in multimodal connection hubs, which therefore became loci of general semantic binding. By relating neuroanatomical structure and cellular‐level learning mechanisms with system‐level cognitive function, this model offers a neurobiological account of category‐general and category‐specific semantic areas based on the different cortical distributions of the underlying semantic circuits.
Image Retrieval Using Fuzzy and Neuro-fuzzy Approaches with Fuzzy Color Semantics

In this paper, two different approaches to color binning and subsequent JNS (Just Not the Same) color histogram computation are discussed. The First approach is based on a Neural Network Color Classifier trained using error back prorogation training algorithm. The second approach is based on heuristically designed fuzzy classifier using fuzzy if-then rules for classifying color pixels into one of the eleven JNS colors. Color signatures for images in the database are obtained using both the methods. Further a fuzzy set theoretic approach is proposed to describe and extract the fuzzy color semantics that attempt to reduce the semantic gap between the low-level visual features and the high-level semantic features. Five linguistic variables are used to represent the image color semantics providing a flexible query scheme that is able to effectively represent vagueness in human color perception. The calibration images are inserted in the database for verifying correctness of the two approaches. The comparison of the image retrieval results obtained using fuzzy and fuzzy-neural approaches are presented at the end.
Sum rate maximization for multi-pair two-way relaying with single-antenna amplify and forward relays

We consider a multi-pair two-way relay network with multiple single antenna amplify-and-forward relays. The sum rate maximization problem subject to a total transmit power constraint is studied for such network. The optimization problem is non-convex. First, we show that the problem is a monotonic optimization problem and propose a polyblock approximation algorithm for obtaining the global optimum. However, this algorithm is only suitable for benchmarking because of its high computational complexity. After observing that the necessary optimality condition for our problem is similar to that of the generalized eigenvalue problem, we propose to use the generalized power iterative algorithm which can approach the global optimum recursively. Finally, we propose the total signal-to-interference-plus-noise ratio (SINR) eigen-beamformer which is a closed-form suboptimal solution that reduces the computational complexity significantly. Simulation results show that the proposed algorithms outperform the existing scheme. Moreover, the total SINR eigen-beamformer almost achieves the performance of the optimal solution.
ASKNAO apps targeting at social skills development for children with autism

This paper aims to review the ASKNAO apps targeting at social skills of children with autism. The ASKNAO Apps is a system that designed to teach children with autism the basic skills that are naturally learned by the typical children. Since ASKNAO apps is a commercial based system, the contents are yet to be categorized technically and specifically in accordance to the three autism criteria which are social skills, communication skills and repetitive behavior. By taking the first step in identifying the Apps suitability focusing on social skills, further study on application and assessment of ASKNAO can be conducted to teach the child in the direction of the user's requirements.
The Role of Mislocalized Phototransduction in Photoreceptor Cell Death of Retinitis Pigmentosa

Most of inherited retinal diseases such as retinitis pigmentosa (RP) cause photoreceptor cell death resulting in blindness. RP is a large family of diseases in which the photoreceptor cell death can be caused by a number of pathways. Among them, light exposure has been reported to induce photoreceptor cell death. However, the detailed mechanism by which photoreceptor cell death is caused by light exposure is unclear. In this study, we have shown that even a mild light exposure can induce ectopic phototransduction and result in the acceleration of rod photoreceptor cell death in some vertebrate models. In ovl, a zebrafish model of outer segment deficiency, photoreceptor cell death is associated with light exposure. The ovl larvae show ectopic accumulation of rhodopsin and knockdown of ectopic rhodopsin and transducin rescue rod photoreceptor cell death. However, knockdown of phosphodiesterase, the enzyme that mediates the next step of phototransduction, does not. So, ectopic phototransduction activated by light exposure, which leads to rod photoreceptor cell death, is through the action of transducin. Furthermore, we have demonstrated that forced activation of adenylyl cyclase in the inner segment leads to rod photoreceptor cell death. For further confirmation, we have also generated a transgenic fish which possesses a human rhodopsin mutation, Q344X. This fish and rd10 model mice show photoreceptor cell death caused by adenylyl cyclase. In short, our study indicates that in some RP, adenylyl cyclase is involved in photoreceptor cell death pathway; its inhibition is potentially a logical approach for a novel RP therapy.
Teachers Learn to Set Goals with Students: Cooperative Process Brings Wisconsin School to New Heights of Innovation and Success.

L eaving Interstate 94 north of Milwaukee and driving east toward Brookfield, Wis. , you cross through flat cornfields stretching to the horizon, dotted by red barns, a few white farmhouses, and the occasional herd of Hereford cows. Within five miles, though, the scene turns to precisely landscaped suburban homes skirted by straight white sidewalks and tall shade trees. On the edges of this manicured part of the community sits Burleigh Elementary School. The large, modern building has the look and feel of suburbia: new play equipment, grassy open fields, a clean, expansive parking lot. A bright welcome sign greets visitors at the door: “We welcome all parents and visitors. Please stop in our office to introduce yourself and pick up a visitor’s pass. ” Inside, the hallways are wide, clean, and well-lit. Every 12 feet or so the plain walls are enhanced with large, wildly colorful murals that office and custodial staff designed and children, parents, and staff painted together. Today, Burleigh is a high-performing school. Teachers and students are empowered and share responsibility for learning using a goal-setting and monitoring process deemed the SMART (Specific and Strategic, Measurable, Attainable, Results-based, and Timebound) Goals Process. Others in the district view Burleigh as cutting-edge and willing to innovate. Today at Burleigh El e m e n t a ry, students set learning goals for themselve s and self-assess at eve ry grade level and
Real-Time Intelligent Gripping System for Dexterous Manipulation of Industrial Robots

This paper describes a concept and presents the experimental results for robotic end-effector operation for handling product items that are flexible or variable in physical properties such as size, shape or firmness and also describes a scheme by which a manipulator can use dynamic tactile sensing to detect when it is about to lose hold of a grasped object and take preventive measures before gross sliding occurs. This paper also elaborates the mechanical, sensing and control issues of such a system and presents results on a novel modular gripping system developed for this purpose. By detecting localized slips on the gripping surface which precede gross slip, the controller can modify the grasp force to prevent the object from slipping. Accurate knowledge of slip is essential when grasping fragile objects or manipulations with sliding. A tactile sensor enables a robot, cybernetic device or other appropriate automatic mechanism to sense an object, to measure the force of contact, and to determine the force required to seize an object. The tactile sensor used in this experiment predicts the partial slip of a tactile surface by sensing micro vibrations in tangential forces which are caused by the expansion of the slip regions within the contact area. Finally a summary of contributions is listed and the advantages of using this intelligent gripping system is elaborated.
Efficiently CCA Secure HIBE Schemes under Double Models with Constant Ciphersize

Identity-based encryption schemes simplify the problem of the management and maintenance of digital certificates in the PKI environment. If the number of identities is large enough in a KGC (key generation center) domain, a single KGC will be a bottleneck of computation and communication. HIBE (Hierarchical identity-based encryption) has been introduced to solve this problem. For the present HIBEs, the size of public parameters is large and is twice as the number of hierarchy, and the analysis method is unique. Most of the existing HIBEs are either proved secure under RO (random oracle) model, or complicated and proved secure under standard mode. This paper further investigates both efficient and provably secure HIBE schemes with small public key size under multi-models. The size of public parameters of the proposed scheme is small and is independent of bit representation of an identity, and is about the same size as the number of hierarchy. The proposed scheme also has the advantage of constant size of cipher text, which is composed of 4 group elements. At last, the proposed scheme is proved sID-IND-CCA secure under both RO and standard models based on the standard DBDH problem. Investigations on the method of cryptographic scheme design and proof of security under multi-models can improve the confidence on its security.
Back to work bang! Difficulties, emotions and adjustment strategies when returning to work after a vacation

Abstract In our day-to-day lives, we are all confronted with situations that we have to adapt and adjust to. When we return to work after a vacation, we also go through an adjustment process. The aim of this study is to identify the difficulties of adjusting to work after the vacation, the emotions and feelings associated with this transition period and what strategies people use to overcome them. Through 93 semistructured interviews, the results show that the main difficulties can be grouped into four dimensions (work-related difficulties, social-level difficulties, general difficulties and the feeling of dis-identification). The emotions and feelings reported have two facets (positive and negative) and companies do not have any type of strategy to facilitate readjustment to work. Thus, the identification of the main difficulties and emotions felt by the respondents is of extreme importance for the design of intervention practices that facilitate this moment of transition, aiming to enhance motivation, well-being and productivity. On the other hand, the emotions associated with this period of return can act as possible predictors of attitudes toward work, presenting an added value to the enrichment and to an improvement of the processes underlying the management of human resources.
Result Ranking for Structured Queries against XML Documents

XML allows to represent both content and structure of documents. Querying XML data therefore requires a combination of a formal query language with the concept of relevance used in Information Retrieval. In this paper we present such a combination: First, we review Tree Matching as a simple and elegant means to formulate queries without knowing the exact structure of the data. Second, we propose a dynamic document concept by deciding on the document boundaries at query time. Third, we marry structured queries with term-based ranking by extending the term concept to structural terms which include substructures of queries and documents. We show how the notions of term frequency and inverse document frequency can be adopted to dynamically de ned documents and structural terms. We introduce an eAEcient technique to calculate both term frequencies and inverse document frequencies at query time. By adjusting parameters of the retrieval process we are able to model two contrary approaches: the classical Vector Space Model, and the original Tree Matching approach.
Reduction of the Temporal Complexity of N-gram Transducers for Dialogue Annotation ?

The annotation of dialogues with Dialogue Acts is important to develop dialogue systems. One way to do this annotation is using a method called N-gram Transducer (NGT), that has shown very good results in unsegmented turns compared with other models, but has a high time complexity. In this paper we propose a modification of the NGT search, based on expanding only n different alternatives at each step, that produces an important reduction of the execution time.
Audio-Only Character Narration Overcoming Resistance to Narrative Persuasion

Using an entertainment overcoming resistance framework, a posttest-only randomized experimental design demonstrated that, compared to no audio-only character narration (n = 57), audio-only character narration (n = 71) elicited more identification with the narrating character, and identification initiated a process of overcoming counterarguing against a subjectively perceived narrative lesson embedded in an episode of The Wonder Years (1998–1993). Although reduced counterarguing did not significantly influence favorable evaluations of the narrative lesson, it significantly increased the importance of those evaluations. Results are discussed in terms of the influence of audio-only character narration on identification, self-reports of a narrative lesson, and the relative influence of entertainment on attitude favorability versus attitude importance.
On the single-slot capacity of random access over a Gaussian MAC

Consider a Gaussian multiple access channel (MAC) with two users, which do not always have a message to transmit. Neither user knows if the other is transmitting or not. Each user has two possible achievable rates depending on whether the other user is transmitting or not. Hence, in general, any coding scheme is characterized by a 4-tuple of rates. For given power constraints, we prove inner and outer bounds to the (4-dimensional) capacity region.
A Comparison of Approaches to Modeling NOW in Bitemporal Databases

A comparison of proposed approaches to representing now in the bitemporal database is provided in this paper. An attempt is made to identify the problems with each approach, the results of each method, and the affect each approach has on index structures. A graphical representation is provided to enhance the differences between the approaches. A method for comparing query performance is defined with results of performance experiments using the method.
The dominant processes of sediment distribution and focusing in a small, eutrophic, monomictic lake

There is evidence for 10 mechanisms of sediment distribution in small lakes. The sediment accumulation rates measured from a common horizon in cores from 64 sites on Esthwaite Water, U.K., were used to determine the relative importance of these mechanisms on the distribution of sediment in the lake. River inflows generally produced localized effects but there were indications of periodic turbidity flows to the deepest point of the lake from the major inflow. Active sediment focusing processes were the dominant distribution mechanisms, a major resuspension of sediment at autumn overturn probably being the most important. The remaining variance was much greater than observed in similar work elsewhere, suggesting that redistribution of sediment by direct and indirect wave action may be taking placeall over the lakebcd during isothermal periods. The relative contributions of the different processes were corroborated by analysis of previously published sediment trap data.
A GENETIC ALGORITHM APPROACH TO SINGULARITY AVOIDANNCE IN THE ANALYSIS OF WEIGHT LIFTING PERFORMANCE

The existing publications on biomechanics of weight lifting tend to concentrate on injury prevention or performance evaluation through various kinetic or kinematic evaluation of the athletes (GAR98, CAR04). An analytical model could prove effective in an individualized approach to performance enhancement. The athlete can be represented by a planar 6 degrees of freedom robotic manipulator where the barbell trajectory is an input to an inverse kinematics problem. Closed form approach and many iterative solutions face a major upheaval in avoiding singularities and thus find it difficult to ensure a smooth motion of the resulting configurations. The convergence potentials of GAs through an efficient search in such large and complex solution spaces are theoretically and empirically exhibited in a number of articles (GOL89, JAV03 and HUA06). A genetic algorithm approach is therefore adopted in determination of a near optimum solution to a highly redundant inverse kinematics problem. Implementation of GA is taken place through adoption of two categories of constraints, the first of which defines the barbell trajectory and the second containing two sets of physiological and kinesiological constraints. The physiological constraints are defined by joint torques and the kinesiological constraints represent joint angles and velocities. METHODS