Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcranial Direct Current Stimulation for Treatment of ADHD: A Review of the Mechanisms of Action

Background and Objective: Attention deficit hyperactivity disorder (ADHD) is a common neuropsychiatric disorder. The current pharmaceutical treatments are associated with side effects and with low efficacy so that about one third of the adults do not respond to these treatments. Transcranial direct current stimulation (tDCS) is a non-invasive and safe brain modulation technique with promising therapeutic effects on ADHD symptoms. This paper aims to comprehensively review the clinical trials of tDCS conducted in humans for the treatment of ADHD. We aim to review the clinical efficacy and mechanisms of action of the technique in ADHD treatment. Method: The databases of PubMed (1990-2017), Web of Sciences (1990-2017), Google Scholar (1990-2017) and Scopus (1990-2017) were searched using the keywords “Attention deficit hyperactivity disorder” OR “ADHD” AND “Transcranial direct current stimulation” OR “tDCS” AND "treatment" AND "mechanism". The title and abstract of the papers were reviewed by at least two authors and the relevant papers were selected for in depth review. We selected the preclinical and clinical trials that studied the effects of tDCS on ADHD patients through measuring behavioral, hemodynamic, or neurophysiological features. Results: The current evidence supports the therapeutic efficacy of tDCS in the improvement of ADHD, but, the findings are controversial. Anodal tDCS seems to be more effective than cathodal in ADHD. In addition, the appropriate sites of stimulation are frontal cortex in particular left dorsolateral prefrontal cortex and right inferior frontal gyrus. The tDCS can improve inhibitory control and interference control in ADHD patients. Conclusion: tDCS has shown promising but limited clinical efficacy for ADHD treatment. However, the current evidence supports continuing the preclinical and clinical studies to determine physiological mechanisms and dose response of tDCS in ADHD to establish a clinical protocol.
Long-Term Activity Recognition from Wristwatch Accelerometer Data

With the development of wearable devices that have several embedded sensors, it is possible to collect data that can be analyzed in order to understand the user's needs and provide personalized services. Examples of these types of devices are smartphones, fitness-bracelets, smartwatches, just to mention a few. In the last years, several works have used these devices to recognize simple activities like running, walking, sleeping, and other physical activities. There has also been research on recognizing complex activities like cooking, sporting, and taking medication, but these generally require the installation of external sensors that may become obtrusive to the user. In this work we used acceleration data from a wristwatch in order to identify long-term activities. We compare the use of Hidden Markov Models and Conditional Random Fields for the segmentation task. We also added prior knowledge into the models regarding the duration of the activities by coding them as constraints and sequence patterns were added in the form of feature functions. We also performed subclassing in order to deal with the problem of intra-class fragmentation, which arises when the same label is applied to activities that are conceptually the same but very different from the acceleration point of view.
Linear Order and Constituency

This article presents a series of arguments that syntactic structures are built incrementally, in a strict left-to-right order. By assuming incremental structure building it becomes possible to explain the differences in the range of constituents available to different diagnostics of constituency, including movement, ellipsis, coordination, scope, and binding. In an incremental derivation structure building creates new constituents, and in doing so it may destroy existing constituents. The article presents detailed evidence for the prediction of incremental grammar that a syntactic process may refer only to those constituents that are present at the point in the derivation when the process applies.
Interactive performance environments and the visualisation of actor movement

The recent production of Eugene Ionesco's Macbett at the UCLA Department of Theater was the department's first performance to incorporate 'interactive systems' that allowed lighting and sound to adapt automatically to performer position and movement. Sensing and response technology on the stage is introduced here as a precursor to the smart home and office environments imagined by proponents of 'ubiquitous computing'. This paper presents early two-dimensional visualisations of the performer tracking data and discusses their influence on systems development. A few possible extensions to the visualisation techniques given here are also discussed.
The Glycome of Normal and Malignant Plasma Cells

The glycome, i.e. the cellular repertoire of glycan structures, contributes to important functions such as adhesion and intercellular communication. Enzymes regulating cellular glycosylation processes are related to the pathogenesis of cancer including multiple myeloma. Here we analyze the transcriptional differences in the glycome of normal (n = 10) and two cohorts of 332 and 345 malignant plasma-cell samples, association with known multiple myeloma subentities as defined by presence of chromosomal aberrations, potential therapeutic targets, and its prognostic impact. We found i) malignant vs. normal plasma cells to show a characteristic glycome-signature. They can ii) be delineated by a lasso-based predictor from normal plasma cells based on this signature. iii) Cytogenetic aberrations lead to distinct glycan-gene expression patterns for t(11;14), t(4;14), hyperdiploidy, 1q21-gain and deletion of 13q14. iv) A 38-gene glycome-signature significantly delineates patients with adverse survival in two independent cohorts of 545 patients treated with high-dose melphalan and autologous stem cell transplantation. v) As single gene, expression of the phosphatidyl-inositol-glycan protein M as part of the targetable glycosyl-phosphatidyl-inositol-anchor-biosynthesis pathway is associated with adverse survival. The prognostically relevant glycome deviation in malignant cells invites novel strategies of therapy for multiple myeloma.
Shape Display Shader Language (SDSL): A New Programming Model for Shape Changing Displays

Shape-changing displays' dynamic physical affordances have inspired a range of novel hardware designs to support new types of interaction. Despite rapid technological progress, the community lacks a common programming model for developing applications for these visually and physically-dynamic display surfaces. This results in complex, hardware-specific, custom-code that requires significant development effort and prevents researchers from easily building on and sharing their applications across hardware platforms. As a first attempt to address these issues we introduce SDSL, a Shape-Display Shader Language for easily programming shape-changing displays in a hardware-independent manner. We introduce the (graphics-derived) pipeline model of SDSL, an open-source implementation that includes a compiler, runtime, IDE, debugger, and simulator, and show demonstrator applications running on two shape-changing hardware setups.
Gimbals control with the camera for aerial photography in RC helicopter

In this paper, PD parameters tuning method for controlling a Gimbals device is proposed. The controlled object the gimbals device is the hanging device, and it is used to keep the camera to be the horizontal position. For example this technique has been paid to attention in the aerial photography by the RC helicopter.However, it is thought as problem that the camera vibrates and the image shakes in the aerial photography by the RC helicopter. Therefore, the position of the camera is first controlled so that the camera may always move to the horizontal position in the ground. As the control technique, the system parameters are estimated by the least squares method. Next, the PD parameters are computed by the generalized minimum variance control law, and control the gimbals device by the gimbals control using the PD control technique. In this paper, the design scheme of the control system is discussed, and the behavior of the control system is examined in the experimental equipment.
Metrological Array of Cyber-Physical Systems. Part 7. Additive Error Correction for Measuring Instrument

Since during design it is impossible to use the uncertainty approach because the measurement results are still absent and as noted the error approach that can be successfully applied taking as true the nominal value of instruments transformation function. Limiting possibilities of additive error correction of measuring instruments for Cyber-Physical Systems are studied basing on general and special methods of measurement. Principles of measuring circuit maximal symmetry and its minimal reconfiguration are proposed for measurement or/and calibration. It is theoretically justified for the variety of correction methods that minimum additive error of measuring instruments exists under considering the real equivalent parameters of input electronic switches. Terms of self-calibrating and verification the measuring instruments in place are studied. Copyright © 2015 IFSA Publishing, S. L.
Treebank-based multilingual unification-grammar development

Broad-coverage, deep unification grammar development is time-consuming and costly. This problem can be exacerbated in multilingual grammar development scenarios. Recently (Cahill et al., 2002) presented a treebank-based methodology to semi-automatically create broadcoverage, deep, unification grammar resources for English. In this paper we present a project which adapts this model to a multilingual grammar development scenario to obtain robust, wide-coverage, probabilistic Lexical-Functional Grammars (LFGs) for English and German via automatic f-structure annotation algorithms based on the Penn-II and TIGER treebanks. We outline our method used to extract a probabilistic LFG from the TIGER treebank and report on the quality of the f-structures produced. We achieve an f-score of 66.23 on the evaluation of 100 random sentences against a manually constructed gold standard.
User‐guided volumetric approximation using swept sphere volumes for physically based animation

We present an efficient, user‐guided volumetric approximation algorithm, specifically designed for physically based animation. Our method combines automatic and interactive segmentation methods to give users an intuitive and easy way to approximate 3D meshes. Our approach first constructs the simplified medial axis transform of the input mesh object, and segments the medial axis into parts in terms of swept sphere volumes using a region growing method. Then, we decompose the object surface into regions based on the mapping between the segmented medial axis and the object surface. Each segmented region is approximated with a swept sphere volume. These decomposed surface regions can be interactively refined further by splitting and/or merging using a sketch‐based input. Experimental results show that our approach produces good volumetric approximation results for different types of object shapes. Moreover, rigid‐body dynamics simulation based on our volumetric approximation provides a visually pleasing result. Copyright © 2012 John Wiley & Sons, Ltd.
Improving the description of instrumental sounds by using ontologies and automatic content analysis

Browsing sound collections in a social database is a complex task when no uniformity in the classification of the sounds and tags is applied; the relation between tag concepts and sounds can vary extremely from one user to another, as well as the types of sounds associated to them. Social databases are environments that allow users to have many different approaches and classification systems when tagging their contents, since a sound can be described and tagged according to different characteristics and with different perspectives and purposes. Browsing through such databases is often complex and inaccurate, returning results are often very distant in either their sound characteristics or the tags being used. Collaborative sound databases are a perfect environment to study the problems derived from an inaccurate or a multidimensional description. Using an ontology as the basis of the classification tags applied to sounds, may not only ease the browsing of sounds through the collection, but also help to define common definitions within the community of its users. This thesis defines a methodology to build a sound collection by using a proposed ontology of tags and the content analysis of its sounds. A corpus of 700 samples has therefore been recorded, classified according to a designed ontology, integrated in the database and analyzed. In addition, similarity measures between content based descriptions and semantic descriptions of this sounds is defined by extracting six different models, providing the possibility of automatically describing eventual new sounds to be integrated within our collection. Finally, the proposed models are evaluated within three different experiments and a preliminary survey of expert users acceptance.
Biped Locomotion: Stability, Analysis and Control

Abstract In this paper, researches and advances in biped locomotion are reviewed. A detailed survey is presented describing the various research problems and the approaches reported in the literature to analyze and control biped locomotion. A method of Zero-Moment-Point (ZMP) compensation is discussed to improve the stability of locomotion of a biped which is subjected to disturbances. A compensating torque, computed from the force sensor reading, is injected into the ankle-joint of the foot of the robot to improve stability. The effectiveness of the method is demonstrated on a humanoid robot, MaNUS-I, to reject disturbances of various form.
Personalization in Digital Libraries: An Intelligent Service based on Semantic User Profiles

Suppose you registered to a large scientific congress and you got from the Web site the conference program containing a long list of papers which will be presented. Which presentations do you choose to attend? Usually either you try to guess the most interesting talks from their titles and authors or you are forced to have a quick look at the conference proceedings. A recommender system able to learn your research interests from the latest papers you wrote or read, and use them to provide suggestions, might be of valuable help for you in this scenario. Content-based recommenders analyze documents previously rated by a target user, and build a profile exploited to recommend new interesting documents. One of the main limitations of traditional keyword-based approaches is that they are unable to capture the semantics of the user interests, due to the natural language ambiguity. We developed a semantic recommender system, called ITem Recommender, able to disambiguate documents before using them to learn the user profile. The Conference Participant Advisor service relies on the profiles learned by ITem Recommender to build a personalized conference program, in which relevant talks are highlighted according to the participant interests.
Creation of ESTELLE/Ag Specifications Using Knowledge Bases

The paper presents a technique that defines creation of ESTELLE/Ag specifications using knowledge bases (KB). Application KB is created using the knowledge acquisition technique joined with a piece-linear aggregate model. The production rules of the application KB are transformed to decision tables, and the static properties of the KB are checked in PROLOGA system. Further, the application KB is combined with the defined KB of validated properties and validation method, and application KB dynamic properties are checked in the expert system in CLIPS. A validated application KB is used defining a framework of ESTELLE/Ag specification using PRAXIS editor and supplementing PRAXIS generated framework with the application functional description. The technique is illustrated with an example of a single channel queuing system.
Crowd Sensing of Urban Emergency Events Based on Social Media Big Data

Detection about urban emergency events, e.g., The fires, storms, traffic jams is of great importance to protect the security of humans. While there are limited physical sensors such as surveillance cameras in a city, urban emergency events are still difficult to be detected for their real-time feature. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. The content from social media often includes references to urban emergency events occurring at, or affecting specific locations. In this paper, the real-time detection of urban emergency events based on social media is proposed. Firstly, users of social media are set as the target of crowd sensing. Secondly, the spatial and temporal information from the social media are extracted to detect the real-time event. Thirdly, a GIS based annotation of the detected urban emergency event is shown. The proposed method is evaluated with extensive experiments based on five real urban emergency events. The result show the accuracy and efficiency of the proposed method.
Perceptions , Attitudes , and Needs of Undergraduate Student towards Career in the Hospitality Industry-An Example from the Undergraduate Students in Taiwan Shoufu University

Questionnaire was designed to measure perceptions and attitudes of undergraduate students towards careers in the hospitality industry in Taiwan Shoufu University, and a deep review was properly executed to understand what respondents believe behind their behavior. The result appeared that working experience enforced student’s attitudes to have a career of restaurant industry during progressing in their education and gaining more practical experience. Junior’s students have had positive effective student’s career perceptions and attitudes. Interview with respondents found juniors changed their opinion to school education evaluation although they still keeping a higher positive career perceptions and attitudes. Juniors strong asked to change curriculum planning having practical lessons such as culinary, baking, Chinese cooking from the first semester of study which different from the current curriculum planning from the second year. Respondents preferred practical lessons before theoretical courses. Respondents want to have a higher ratio curriculum proportion of practical lessons to theoretical courses 6:4. Respondents desired to have well professional technique training before academic study. Finally, respondents wanted to arrange more efficient lessons with different experience level groups of students. In generally, respondents have optimism with a career development in hospitality industry in future.
Enhancement of piezoelectric vibration energy harvester output power level for powering of wireless sensor node in large rotary machine diagnostic system

The paper presents results of experimental and theoretical studies on small-size piezoelectric generators, in which energy of machine mechanical vibrations is harvested and converted to electric energy. These piezoelectric generators were proposed, as an alternative to a battery-based solution, for powering of sensor nodes in condition monitoring systems of large rotary machines such as turbogenerators in power plants. Initial studies conducted for three bending-beam piezogenerators were focused on maximization of generated electric power by matching load impedance to piezoelectric element output impedance and designing suitable weighting mass for mechanical resonance. As a performance of the piezoelectric element and the weighting mass setup turned out to be unsatisfactory when tested in real conditions on a turbogenerator, Synchronized Switch Harvesting on Inductor technique has been recently applied for an enhancement of generated power levels. A test interface circuit is described. The obtained laboratory results confirm possible usefulness of this solution and are a basis for a future work on power-processing blocks operating with piezoelectric generators.
Utility-preserving K-anonymity

As technology advances and more and more person-specific data like health information becomes publicly available, much attention is being given to confidentiality and privacy protection. On one hand, increased availability of information can lead to advantageous knowledge discovery; on the other hand, this information belongs to individuals and their identities must not be disclosed without consent. A recently proposed concept called k-Anonymity addresses this conflict between doctor-patient confidentiality and society-beneficial research. Several k-Anonymity-based problems have been proposed in the literature; however, these problems do not adequately address preserving utility for the researcher and their algorithms are not computationally efficient. This thesis highlights these inadequacies through a comprehensive overview of previous research, where it is shown that previous solutions lack sufficient ability to meet specific researcher needs. To this end, new utility-preserving problems are proposed and their computational complexities are analyzed. Many results for k-Anonymity-based problems are systematically derived through this analysis, including two of particular interest: (1) the first known polynomial-time solvable k-Anonymity-based problem and (2) the first known algorithm-independent polynomial-time approximation intractability results for k-Anonymity-based problems.
Dynamic Regulation of Auxin Response during Rice Development Revealed by Newly Established Hormone Biosensor Markers

The hormone auxin is critical for many plant developmental processes. Unlike the model eudicot plant Arabidopsis (Arabidopsis thaliana), auxin distribution and signaling in rice tissues has not been systematically investigated due to the absence of suitable auxin response reporters. In this study we observed the conservation of auxin signaling components between Arabidopsis and model monocot crop rice (Oryza sativa), and generated complementary types of auxin biosensor constructs, one derived from the Aux/IAA-based biosensor DII-VENUS but constitutively driven by maize ubiquitin-1 promoter, and the other termed DR5-VENUS in which a synthetic auxin-responsive promoter (DR5rev) was used to drive expression of the yellow fluorescent protein (YFP). Using the obtained transgenic lines, we observed that during the vegetative development, accumulation of DR5-VENUS signal was at young and mature leaves, tiller buds and stem base. Notably, abundant DR5-VENUS signals were observed in the cytoplasm of cortex cells surrounding lateral root primordia (LRP) in rice. In addition, auxin maxima and dynamic re-localization were seen at the initiation sites of inflorescence and spikelet primordia including branch meristems (BMs), female and male organs. The comparison of these observations among Arabidopsis, rice and maize suggests the unique role of auxin in regulating rice lateral root emergence and reproduction. Moreover, protein localization of auxin transporters PIN1 homologs and GFP tagged OsAUX1 overlapped with DR5-VENUS during spikelet development, helping validate these auxin response reporters are reliable markers in rice. This work firstly reveals the direct correspondence between auxin distribution and rice reproductive and root development at tissue and cellular level, and provides high-resolution auxin tools to probe fundamental developmental processes in rice and to establish links between auxin, development and agronomical traits like yield or root architecture.