Miracle-dz/UniFAR-FTUs huggingface dataset:
Light-Intensity Physical Activity and Cardiometabolic Risk Among Older Adults With Multiple Chronic Conditions

Purpose: To assess the relationship between light-intensity physical activity (LIPA) and cardiometabolic risk factors among middle-aged and older adults with multiple chronic conditions. Design: Cross-sectional design utilizing data from the Health and Retirement Study (2010, 2012). Setting: Laboratory- and survey-based testing of a nationally representative sample of community-dwelling middle aged and older adults. Participants: Adults aged 50 years and older (N = 14 996). Measures: Weighted metabolic equivalent of tasks was calculated using self-reported frequency of light, moderate, and vigorous physical activity. Cardiometabolic risk factors (systolic and diastolic blood pressure, glycosylated hemoglobin [HbA1c], high-density lipoprotein cholesterol [HDL-C], total cholesterol, and non-HDL-C) were objectively measured. A multiple chronic condition index was based on 8 self-reported chronic conditions. Analysis: Weighted multivariate linear regression models. Results: Light-intensity physical activity was independently associated with favorable HDL-C (β = 1.25; 95% confidence interval [CI]: 0.46-2.05) and total cholesterol (β = 2.72; 95% CI: 0.53-4.90) after adjusting for relevant confounders. The HDL-C health benefit was apparent when stratified by number of chronic conditions, for individuals with 2 to 3 conditions (β = 1.73; 95% CI: 0.58-2.89). No significant associations were observed between LIPA and blood pressure, HbA1c, or non-HDL-C. Conclusions: Engaging in LIPA may be an important health promotion activity to manage HDL-C and total cholesterol. Additional longitudinal research is needed to determine the causal association between LIPA and cardiometabolic risk which can potentially inform physical activity guidelines targeting older adults with multiple chronic conditions.
A Three-Terminal Edge-Triggered Mott Switch

We demonstrate a novel $\mathrm{VO}_{2}-\mathrm{based}$ edge-triggered (ET) three-terminal Mott switch that leverages the displacement current induced by the switching of the gate voltage pulse to trigger an IMT in the $\mathrm{VO}_{2}$ channel. The design overcomes a long-standing challenge of realizing a three-terminal $\mathrm{VO}_{2}$ switch due to the absence of field-effect induced IMT in VO2. The ET Mott switch also enables isolation between the input & the output (at steady state), and facilitates reduction in the effective trigger voltage in comparison to the two-terminal configuration. We show using simulations that these properties can be exploited to enable a BEOL-compatible 3T selector for MTJ-based cross-point memory, showing $3.4\times$ higher cell TMR, as well as 45% & 40% lower sneak-path current & power, respectively.
Navigation Method of AUV to Target Point by Optical and Acoustic Sensor Switching Strategy

We propose a method that uses both optical and acoustic images to generate an optimal path and compensate for error while AUV visits to a target point. We used SURF detection algorithm to store more reliable images between a pair of optical and acoustic images at each trajectory point. We calculated and compared the reliability value of optical image and acoustic image by using a weight W and a bias b. Then we selected waypoints for the optimal visiting path. The accuracy of our image selection method was 75.13%, and processing a pair of optical and acoustic images takes 180 ms. This method will increase the accuracy of visiting navigation of AUV to any target points and will decrease the sensitivity to water conditions.
Small-Signal Stability Analysis of Inverter-Fed Power Systems Using Component Connection Method

 Abstract --The small time constants of power electronics devices lead to dynamic couplings with the electromagnetic transients of power networks, and thus complicate the modeling and stability analysis of power-electronics-based power systems. This paper presents a computationally-efficient approach to assess the small-signal stability of inverter-fed power systems. The power system is partitioned into individual components, including the power inverters, network impedances, and power loads. The state-space model of individual inverter is first built, where the frequency response and eigenvalue analysis collectively characterize the contributions of different controller parameters to the terminal behavior in a wide frequency range. These component models, together with the network equations, are then algebraically assembled based on the interconnection relations at their terminals. As a consequence, the state matrix of the whole system, which is essential to the system stability analysis, can be reformulated in a computationally-efficient way. The experimental results are finally given to validate the effectiveness of the modeling method and system stability analysis.
Taxi Demand Prediction using Ensemble Model Based on RNNs and XGBOOST

Taxis play an important role in urban transportation. Understanding the taxi demand in the future gives an opportunity to organize the taxi fleet better. It also reduces the waiting time of passengers and cruising time of taxi drivers. Even, there are some works proposed to predict the demand of taxi but there are few studies that consider the function of areas such as hospital area, department store area, residential area, and tourist attraction. One predictive model may not fit with all types of area. We use a point of interest (POI) to match taxi demand with a place to study the taxi demand in the area with a different function. In this paper, we investigate the best predictive models that can forecast demand of taxi hourly with 7 types of area function. The models that were selected for the experiment are long short term memory (LSTM), gated recurrent unit (GRU) and extreme gradient boosting (XGBOOST). Then, we proposed the ensemble model that can forecast the taxi demand well with all types of area function using the information from those machine learning models. We build the models based on a real-world dataset generated by over 5,000 taxis in Bangkok, Thailand for 4 months. The result shows that the proposed ensemble model can outperform other models in overall.
Online Sequential Extreme Learning Machine for Partial Discharge Pattern Recognition of Transformer

Traditional pattern recognition algorithms have limitations including slow training speed and low recognition accuracy in practical engineering applications. In this paper, a new method based on Online Sequential Extreme Learning Machine (OS-ELM) is proposed. Data samples have been obtained from PD experiment of real transformer based on Ultra High Frequency (UHF) detection method. In addition, OS-ELM is compared with Extreme Learning Machine (ELM), Support Vector Machine (SVM) and Back Propagation Neural Network (BPNN) in both recognition accuracy and performance aspects. The results show that OS-ELM is not only much faster in learning speed, but also more excellent in recognition accuracy, thus more suitable for engineering applications with large volume of data samples.
Energy-Efficient Joint Source and Relay Precoding for Two-Hop MIMO-AF Two-Relay Networks

This paper focuses on improving the energy efficiency of two-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems having two relays (in parallel) by relying on optimisation theory. Although the joint optimisation of the source and relays precoding structures is non-convex by nature, we first formulate the energy consumption of the system as an optimisation function and prove that the latter is unimodal when the source and/or relay precoding matrices are known. In turn, we derive an optimal source and robust relays precoding structures; joint optimisation of the source and relays precoding matrices is then performed via an iterative process. Simulation results show that our novel approach can reduce the energy consumption of two-hop MIMO-AF systems by up to 30% when compared to the most relevant existing approaches.
Optimal Torque Ripple Reduction Technique for Outer Rotor Permanent Magnet Synchronous Reluctance Motors

Torque ripple reduction has been one of the main considerations in the optimal design of traction motors, such as permanent magnet assisted synchronous reluctance motors. Several design techniques including optimal slot/pole combination, stator slot and rotor magnet skewing, and shape optimization of rotor flux barriers have been studied intensively to reduce the torque pulsations in the internal rotor reluctance motors. However, internal rotor reluctance motors involve power train complexity and space constraints in the traction application. On the other hand, outer rotor motors can be designed optimally to eliminate these drawbacks and in addition, produce higher power density. In such outer rotor reluctance motor designs, torque ripple plays crucial role as the in-wheel motor is under duress of consistent rotational forces. Furthermore, optimization of outer rotor in-wheel motors needs to be thoroughly investigated to reduce the torque ripple and to generate higher torque density. In this paper, a rotor shape optimization based on design of notches and rotor flux barrier is presented. Detailed optimization process in adjunct to analytical and simulation results comparison is presented. Finally, optimal designs are fabricated and tests are conducted on the 3.7-kW prototypes to validate the proposed design-optimization theory.
Emotional Recognition System by Facial Land Marking Analysis

This paper highlights a method of identifying emotional responses of any person based on a single front facial image by measuring distances between various face land marking points like the center of the eye, eyebrows, edge of the mouth & cheeks. We propose a method to determine the degree to which a person is smiling. This could vastly improve human-robot interactions, understanding customer feedback & overall product analytics.
New Potentiometric Sensor Based on Molecularly Imprinted Polymer for Dipicolinic Acid Detection in Aqueous Media

A new molecularly imprinted polymer (MIP) was introduced herein for specific detection of dipicolinic acid (DPA) in the complex biological milieu. The MIP was synthesized by precipitation polymerization after a systematic investigation of influential parameters on its adsorption performance. The appropriate functional monomer was selected to be acrylic acid (AA) based on the results of molecular dynamics simulation. The ratio of DPA to AA and to cross-linker was experimentally examined using the full factorial method. The optimal molar ratio of 1:8:24 resulted in the highest adsorption capacity of 47.69 mg g−1 and imprinting factor of 4.43. The synthesized polymers were characterized by a scanning electron microscopy, a Fourier transform infrared spectroscopy, and an atomic force microscopy. The spherical MIPs possessing a diameter of 483 nm and an imprinting factor of 4.43 was found to play the major role in the development of an efficient MIP-modified carbon paste electrode. This electrode can be cheaply constructed in bulk and be applied for potentiometric DPA sensing in aqueous solutions with a response time and detection limit of 5 min and $0.1~\mu \text{M}$ , respectively.
NaoBlocks: A Case Study of Developing a Children's Robot Programming Environment

Developing a robotics system can be a complex process, with competing requirements between programmers and end-users. This paper presents a case study on the development of NaoBlocks, a block-based programming environment that allows children to program a Nao robot. NaoBlocks was developed over three phases, with feedback from the end-users (children) guiding the process. Lessons learnt include providing feedback often and early, keeping the editor simple, making the environment robust, allowing override functionality and allowing progressive functionality.
Conceptual development and learning

espanolEste texto menciona brevemente algunas de las ideas que se pueden tomar prestadas de Piaget y Vygotsky para exponer los elementos que parecen esenciales hoy en dia a la luz de la investigacion psicologica en la formacion de competencias en educacion y en el trabajo. El desarrollo cognitivo es conceptual o no lo es. La actividad en situacion es esencial. El desarrollo de competencias reclama las formas operatoria y predicativa del conocimiento. Los conceptos de esquema y situacion son homologos duales uno del otro. El primer acto de mediacion de los docentes es la eleccion de las situaciones en algun campo conceptual. Otros actos de mediacion consisten en la expresion de los nuevos conocimientos adquiridos en el lenguaje natural y otros sistemas simbolicos de representacion. EnglishThis paper mentions shortly some of the ideas one can borrow from Piaget and Vygotsky to present those elements that seem essential today in the light of psychological research to the formation of competences in education and work. Cognitive development is either conceptual or it is not. Activity in situations is essential and the development of competences comprises the operative and predicative forms of knowledge. The concepts of scheme and situation are dual counterparts of each other. The first mediation act of teachers is the choice of situations in some conceptual field. Other mediation acts consist in expressing the new knowledge acquired in natural language and other symbolic systems of representation.
An Annotated Corpus of Picture Stories Retold by Language Learners

Corpora with language learner writing usually consist of essays, which are difficult to annotate reliably and to process automatically due to the high degree of freedom and the nature of learner language. We develop a task which mildly constrains learner utterances to facilitate consistent annotation and reliable automatic processing but at the same time does not prime learners with textual information. In this task, learners retell a comic strip. We present the resulting task-based corpus of stories written by learners of German. We designed the corpus to be able to serve multiple purposes: The corpus was manually annotated, including target hypotheses and syntactic structures. We achieve a very high inter-annotator agreement: κ = 0.765 for the annotation of minimal target hypotheses and κ = 0.507 for the extended target hypotheses. We attribute this to the design of our task and the annotation guidelines, which are based on those for the Falko corpus (Reznicek et al., 2012).
The Design and Analysis of a Light Explosive Ordnance Disposal Manipulator

In this paper, the parameters of a light explosive ordnance disposal manipulator (EOD manipulator) is designed to meet the requirements of large ratio of load to self weight, which could be carried easily by single soldier in the war field. For compact and light design, the motion space, kinematics and dynamics simulation is carried out to obtain the kinematics and dynamics indicators of the EOD manipulator. On this basis, the arm type, joint drive system and control system are designed. The joints are designed as modular so as to replace and maintain the joint conveniently. The joint adopts the “motor-planetary reducer-turbine worm” drive chain to achieve the large ratio of load to self weight. At the same time, the self-lock protection caused by power failure and complex work environment could also be accomplished. The automatic capture is realized by the end of EOD manipulator coordinated with the auxiliary vision camera. Finally the grabbing experiments prove the effectiveness of the design and analysis method, thereby suitable to be promoted to other miniaturized robot designs.
A Simple Method for Estimation of Silicon Film Thickness in Tri-Gate Junctionless Transistors

Junctionless transistors (JLTs) without PN-junctions near the source/drain are promising candidates for further development of CMOS technology. The Si thickness of tri-gate JLTs is crucial to understand their unique electrical properties related to bulk neutral and surface accumulation conduction. A simple method based on a unique operation mechanism is suggested for extraction of <inline-formula> <tex-math notation="LaTeX">$\text{t}_{\mathrm {si}}$ </tex-math></inline-formula> from measurements on tri-gate JLTs. The method was successfully applied to fabricated tri-gate JLTs and the extracted <inline-formula> <tex-math notation="LaTeX">$\text{t}_{\mathrm {si}}$ </tex-math></inline-formula> values were comparable with those of transmission electron microscopy. Furthermore, the validity of the method was confirmed by 2-D numerical simulation.
Optimal Joint Bidding and Pricing of Profit-Seeking Load Serving Entity

The demand response provides an opportunity for load serving entities (LSEs) that operate retail electricity markets (REMs) to strategically purchase energy and provide reserves in wholesale electricity markets (WEMs). This paper concerns with the problem of simultaneously determining the optimal energy bids and reserve offers an LSE submits to the WEM as well as the optimal energy and reserve prices it sets in the REM so as to maximize its profit. To this end, we explicitly model the trilayer market structure that consists of a WEM, a REM, and a set of end user customers, so as to capture the coupling between the bidding problem and the pricing problem. Based on the trilayer market model, we then formulate the joint bidding and pricing problem as a bilevel programming problem and further transform it into a single-level mixed integer linear programming problem, which can be solved efficiently. Numerical studies using the IEEE test cases are presented to illustrate the application of the proposed methodology as well as to reveal several interesting characteristics of the LSE's profit-seeking behavior.
Synchronous Reluctance Machine Optimization for High-Speed Applications

The synchronous reluctance machines with transversally laminated rotor and multi flux barriers per pole reach a high torque density, so that they are proposed as a valid alternative to permanent magnet machines. Such machines have been analyzed for different applications, mainly home appliance, industrial tool, traction, up to low-speed high-power generators. On the contrary, the use of synchronous reluctance machines for high-speed applications remains almost unexplored yet. The aim of this paper is to investigate the potential of a high-speed synchronous reluctance machine. An optimization is carried out so as to maximize the machine performance (high power, proper power factor, low vibration) at a given speed. The machine size is fixed and the focus is on the rotor geometry, with the purpose of maximizing the electromagnetic torque, according to the necessary thickness of the ribs. It is shown that, even if the ribs are thick, it is possible to reach a proper torque density. It is shown that different solutions exist, which allow to reach high torque and minimum torque ripple. However, the optimal solutions are quite sensitive to the geometrical variations, so that a particular care is required in the manufacturing of the machine. Finally, the power limit of the synchronous reluctance motor with barrier rotor is found.
Sunbed use 2007–2015 and skin cancer projections of campaign results 2007–2040 in the Danish population: repeated cross-sectional surveys

Objective To evaluate the effect of the Danish Sun Safety Campaign 2007–2015 on the prevalence of sunbed use and to model future effects on the skin cancer incidences 2007–2040. Design The study has a repeated, cross-sectional design. Setting Exposure to ultraviolet radiation is the main risk factor for skin cancer. Denmark has the highest prevalence of sunbed use reported and one of the highest incidences of skin cancer worldwide. Participants During 2007–2015, survey data were collected for 37 766 Danes, representative of the Danish population with regards to age, gender and region. Interventions In 2007, an ongoing long-term antisunbed campaign was launched in Denmark. Primary and secondary outcome measures Sunbed use was evaluated by annual cross-sectional surveys. Skin cancer incidence was modelled in the Prevent programme, using population projections, historic cancer incidence, sunbed use exposure and relative risk of sunbed use on melanoma. Results The prevalence of recent sunbed use in Denmark was reduced from 32% and 18% to 13% and 8% for women and men, respectively. The campaigns results during 2007–2015 are estimated to reduce the number of skin cancer cases from more than 5000 (746malignant melanoma, 1562 SCC, 2673 BCC) totally during 2007–2040. Keeping the 2015 level of sunbed use constant by continued campaign pressure or introduction of structural interventions would potentially prevent more than 750 skin cancer cases annually in 2040 and 16 000 skin cancer cases in total during 2007–2040. Conclusion We have shown the value of prevention and of long-term planning in prevention campaigning. Sunbed use was reduced significantly during 2007–2015 and further reductions are possible by structural interventions. Consequently, significantly fewer skin cancer cases are anticipated during 2007–2040. The Danish Parliament has population support to enforce structural interventions to avoid a large burden of this disease.
Discrete-Time IDA-PBC for Underactuated Mechanical Systems with Input-Delay and Matched Disturbances

This work investigates the control problem of discrete-time underactuated mechanical systems with fixed input-delay and matched disturbances. A new control strategy is proposed, which builds upon a discrete-time implementation of the interconnection-and-damping-assignment passivity-based control (IDA-PBC) and extends it in two ways: the disturbances are estimated adaptively; the input-delay is compensated with a recursive algorithm. The resulting control law is constructed from IDA-PBC without solving any additional partial-differential-equation (PDE). Stability conditions are discussed and compared to alternative designs. Numerical simulations for the ball-on-beam system and for the Acrobot system demonstrate the effectiveness of the proposed approach.
Data Center Server Energy Consumption Optimization Algorithm

Understanding, modelling and reducing data center power consumption is a complicated undertaking. Individual data centers are highly complex systems, with a number of interacting mechanical, electrical and computational subsystems. The paper presents an optimization algorithm which reduces the energy consumed by the informational systems by assign virtual machines to physical servers. This action is achieved taking into account the different degrees of freedom of the used resources. The considered problem is formulated as a mixed integer linear programming problem where all transfer functions, constraint functions and objective function are expressed under a linear form.