Miracle-dz/UniFAR-FTUs huggingface dataset:
Project ReFresh: Testing the Efficacy of a School-Based Classroom and Cafeteria Intervention in Elementary School Children.

BACKGROUND The purpose of this study was to assess the effect of a school-based nutrition program using a cafeteria environment intervention and classroom nutrition education on self-reported fruit and vegetable (FV) consumption, self-efficacy to select FV, and preference for healthy foods. METHODS Using quasi-experimental pre-post design with 3 study conditions, a total of 665 fourth- and fifth-grade students participated in the study. The comprehensive intervention included a behavioral economics cafeteria intervention and weekly classroom nutrition education for 1 academic year. The intervention was designed and delivered by the extension system. RESULTS The comprehensive group showed significant improvement in some indicators including eating vegetables for lunch (p = .007), number of days eating vegetables (p < .001) and fruits (p < .001) in the last week, and self-efficacy in preparing FV at home (p = .034) compared to the control and cafeteria groups. Food preference of some food items, including oatmeal (p = .036 for cafeteria group, p < .001 for comprehensive group), whole grain noodles (p = .011 for comprehensive group), and vegetables (p = .003 for comprehensive group), significantly improved in the cafeteria and/or comprehensive group. CONCLUSIONS Classroom nutrition education combined with cafeteria improvement has the potential to improve diet-related behavior of elementary school children. Also, collaborative partnership between schools and extension can enhance program sustainability.
Active learning for dimensional speech emotion recognition

State-of-the-art dimensional speech emotion recognition systems are trained using continuously labelled instances. The data labelling process is labour intensive and time-consuming. In this paper, we propose to apply active learning to reduce according efforts: The unlabelled instances are evaluated automatically, and only the most informative ones are intelligently picked by an informativeness measure function for a human to label. Speciﬁcally, we estimate the informativeness of each unlabelled instance based on a binary-classiﬁcation conﬁdence score for an emotion being predicted to be negative or positive on a given emotional dimension. For veriﬁcation, we consider a pool-based and a stream-based scenario run on part of the continuous AVEC 2012 task to demonstrate the feasibility of the proposed approach in practice. In the result, our approach requires signiﬁcantly less human labelled data instances to reach a given performance than passive learning does in both scenarios.
Combining PREM compilation and ILP scheduling for high-performance and predictable MPSoC execution

Many applications require both high performance and predictable timing. High-performance can be provided by COTS Multi-Core System on Chips (MPSoC), however, as cores in these systems share the memory bandwidth they are susceptible to interference from each other, which is a problem for timing predictability. We achieve predictability on multi-cores by employing the predictable execution model (PREM), which splits execution into a sequence of memory and compute phases, and schedules these such that only a single core is executing a memory phase at a time. We present a toolchain consisting of a compiler and an Integer Linear Programming scheduling model. Our compiler uses loop analysis and tiling to transform application code into PREM compliant binaries. Furthermore, we solve the problem of scheduling execution on multiple cores while preventing interference of memory phases. We evaluate our toolchain on Advanced-Driver-Assistance-Systems-like scenario containing matrix multiplications and FFT computations on NVIDIA TX1. The results show that our approach maintains similar average performance and improves variance of completion times by a factor of 9.
Relevance of Nonlinear Fracture Mechanics to Creep Cracking

Creep crack growth tests, conducted on contoured double cantilever beam (DCB) specimens are described for aluminium alloy RR58 and a chromium-molybdenum-vanadium steel. The results are analyzed in terms of J, the rate equivalent of the J contour integral, which is a nonlinear fracture mechanics parameter. Direct proportionality is found between crack growth rate, ˙a and j. The treatment is shown to reveal a unification of the linear elastic fracture mechanics and net section or reference stress descriptions of creep cracking.
What really matters — An information gain analysis of questions and reactions in automated PTSD screenings

Post-traumatic stress disorder (PTSD) is a mental health condition which severely affects society on many levels. However, PTSD remains often undiagnosed and untreated. To improve screening access and acceptance, a fully automated virtual human was designed to conduct many PTSD screening interviews (N=198). Here, we investigate which questions elicit the most indicative multimodal behaviors for PTSD. To this effect, we employ an information gain driven ranking procedure to identify the most informative questions. Further, we look into question dependent behaviors. To evaluate the question ranking, we investigate the discriminative faculty of the top questions using support vector machines. Our results reveal that only a subset of posed questions are required to robustly detect symptoms of PTSD in subject-independent machine learning experiments. We observe strong performance and can confirm that many of the identified behaviors correspond to commonly found behavioral indicators related to PTSD and depression.
Autocrine IL-6 mediates pituitary tumor senescence

Cellular senescence is a stable proliferative arrest state. Pituitary adenomas are frequent and mostly benign, but the mechanism for this remains unknown. IL-6 is involved in pituitary tumor progression and is produced by the tumoral cells. In a cell autonomous fashion, IL-6 participates in oncogene-induced senescence in transduced human melanocytes. Here we prove that autocrine IL-6 participates in pituitary tumor senescence. Endogenous IL-6 inhibition in somatotroph MtT/S shRNA stable clones results in decreased SA-β-gal activity and p16INK4a but increased pRb, proliferation and invasion. Nude mice injected with IL-6 silenced clones develop tumors contrary to MtT/S wild type that do not, demonstrating that clones that escape senescence are capable of becoming tumorigenic. When endogenous IL-6 is silenced, cell cultures derived from positive SA-β-gal human tumor samples decrease the expression of the senescence marker. Our results establish that IL-6 contributes to maintain senescence by its autocrine action, providing a natural model of IL-6 mediated benign adenoma senescence.
Link prediction in human mobility networks

The understanding of how humans move is a long-standing challenge in the natural science. An important question is, to what degree is human behavior predictable? The ability to foresee the mobility of humans is crucial from predicting the spread of human to urban planning. Previous research has focused on predicting individual mobility behavior, such as the next location prediction problem. In this paper we study the human mobility behaviors from the perspective of network science. In the human mobility network, there will be a link between two humans if they are physically proximal to each other. We perform both microscopic and macroscopic explorations on the human mobility patterns. From the microscopic perspective, our objective is to answer whether two humans will be in proximity of each other or not. While from the macroscopic perspective, we are interested in whether we can infer the future topology of the human mobility network. In this paper we explore both problems by using link prediction technology, our methodology is demonstrated to have a greater degree of precision in predicting future mobility topology.
Writing abilities and the role of working memory in children with symptoms of attention deficit and hyperactivity disorder

ABSTRACT The writing abilities of children with ADHD symptoms were examined in a simple dictation task, and then in two conditions with concurrent verbal or visuospatial working memory (WM) loads. The children with ADHD symptoms generally made more spelling mistakes than controls, and the concurrent loads impaired their performance, but with partly different effects. The concurrent verbal WM task prompted an increase in the phonological errors, while the concurrent visuospatial WM task prompted more non-phonological errors, matching the Italian phonology, but not the Italian orthography. In the ADHD group, the children proving better able to cope with a concurrent verbal WM load had a better spelling performance too. The ADHD and control groups had a similar handwriting speed, but the former group’s writing quality was poorer. Our results suggest that WM supports writing skills, and that children with ADHD symptoms have general writing difficulties, but strength in coping with concurrent verbal information may support their spelling performance.
GS1 Video: Open Service System for Video Using MPEG 7 and GS1 Standard

Recently, the video system changes from the limited device based uni-directional to various devices based bi-directional system. Therefore, users can easily access video contents from anywhere, anytime via a various type of devices such as smartphone and tablet. It is expected that various services will be generated by heterogeneous video platforms. With these changes, the video system is required to interactively present further information of video content and connect users with various services produced from heterogeneous video platforms. In this paper, we propose the GS1 video system which provides annotation tool and data representation model based on MPEG7 and suggests a method that connects video contents with related services based on GS1 standard. The proposed system allows all objects in the video to be annotated and globally identified by GS1 ID, and users can get access to video related services on heterogeneous video platforms. To show feasibility, we implement the pilot system and conducted an experiment which shows that a system delivers related service list to users in 2ms for 100 objects and the service discovery network delivers result by 9,794.5 TPS and 79.25 MTT on average when 1,000 Vusers using same ONS server.
Target Reconstruction From Deceptively Jammed Single-Channel SAR

This paper considers the problem of reconstructing true targets in a single-channel synthetic aperture radar (SAR) imaging system, which has been disturbed by deceptive jammings. Since the deceptive jammings are usually confined to the main lobe of an SAR antenna, their time–frequency distributions are different from those of the true echoes. This enables us to utilize a dynamic synthetic aperture (DSA) scheme to extract the characteristics of the true and false targets. Dictionaries about the true and false targets are constructed by taking interactions between scatterers into account. Then a sparsity-driven optimization problem is solved to reconstruct the true and false targets separately with super-resolution. Moreover, the deceptively jammed SAR data are divided into different areas to handle various scenarios efficiently, and strategies for DSA selection are addressed as well. Simulations are provided to verify the effectiveness of the proposed algorithm.
Concomitant inhibition of receptor tyrosine kinases and downstream AKT synergistically inhibited growth of KRAS/BRAF mutant colorectal cancer cells

Receptor tyrosine kinase (RTK) signaling pathways are frequently activated in cancer cells due to mutations of RTKs and/or their downstream signaling proteins such as KRAS and BRAF. About 40% colorectal cancers (CRCs) contain KRAS or BRAF mutant genes and are resistant to treatments with individual inhibitors of RTKs, AKT, MEK, or BRAF. Therefore, an understanding of the molecular mechanisms of the drug resistance is necessary for developing effective strategies to treat the diseases. Here we report the discovery of an AKT/ERK reactivation mechanism that account for the cancer cell resistance to the AKT and MEK inhibitors treatments. The reactivations of AKT and ERK after the AKT or MEK inhibitor treatment were caused by a relief of an AKT or ERK-mediated feedback inhibition of the RTKs and/or their downstream pathways. A combination of RTK inhibitors, based on the RTK activation/phosphorylation profile, synergized with the AKT inhibitor, but not the MEK inhibitor, to completely inhibit the AKT phosphorylation and to block the growth of KRAS/BRAF mutant CRC cells. These results underscored the importance of AKT and the AKT feedback signaling to cancer cell growth and offered a novel therapeutic approach for the treatment of KRAS/BRAF mutant CRC cells.
Dynamic walking and whole-body motion planning for humanoid robots: an integrated approach

This paper presents a general method for planning collision-free whole-body walking motions for humanoid robots. First, we present a randomized algorithm for constrained motion planning, that is used to generate collision-free statically balanced paths solving manipulation tasks. Then, we show that dynamic walking makes humanoid robots small-space controllable. Such a property allows to easily transform collision-free statically balanced paths into collision-free dynamically balanced trajectories. It leads to a sound algorithm which has been applied and evaluated on several problems where whole-body planning and walk are needed, and the results have been validated on a real HRP-2 robot.
Integration of electrochemical detection into micropumps for continuous monitoring system

This paper proposes the integration of electrochemical detection to micropumps for continuous monitoring of ferrocyanide ions. A homemade device is fabricated using 3D printing and casting techniques with a top and bottom layer of 0.5 mm and 3.0 mm, respectively. The volumetric flow and cyclic voltammetry performances of the device are evaluated at the actuator frequency of 10-50 Hz, in 10 Hz increments at concentrations of 2-10 mM, in 2 mM increments. The fabricated device exhibits maximum flow rate of 0.30405 ml/min in the reverse direction with resonance frequency of 20 Hz. The oxidation peak current at 16.02018 μA of 10 mM potassium ferrocyanide in 1 M potassium nitrate is noted. Among the various concentrations of potassium ferrocyanide, 10 mM of potassium ferrocyanide in 1 M potassium nitrate at the maximum flow rate shows the highest oxidation peak current at 16.02018 μA. The presented device offers the advantage of an affordable miniaturized bedside patient continuous monitoring system, due to its low fabrication cost. Additionally, the disposability nature of the device assures collected samples are unpolluted.
Isolated Capsulorhexis Flap Technique in Femtosecond Laser-Assisted Cataract Surgery to Protect the Corneal Endothelial Cells

ABSTRACT Purpose: To present a novel technique that using capsulorhexis flap to protect corneal endothelial cells during femtosecond laser-assisted cataract surgery. Methods: During the procedure, an isolated capsulorhexis flap was used to lift it up carefully by using OVD until the flap attached to the corneal inner layer. It kept steady during the phaco phase, and been removed by I/A tip after intraocular lens implantation. Results: In our pilot study, the damage to the corneal endothelial cells from the phacoemulsification procedure were no more than the traditional phaco procedure, even femtosecond laser assisted cataract surgery. Conclusion: Isolated capsulorhexis flap technique initiate a new approach to protect the endothelial cell. It is a simple technique with a short learning curve, but still need a further investigation to prove the protection of corneal endothelial cells.
Character-Cluster-Based Segmentation using Monolingual and Bilingual Information for Statistical Machine Translation

We present a novel segmentation approach for Phrase-Based Statistical Machine Translation (PB-SMT) to languages where word boundaries are not obviously marked by using both monolingual and bilingual information and demonstrate that (1) unsegmented corpus is able to provide the nearly identical result compares to manually segmented corpus in PB-SMT task when a good heuristic character clustering algorithm is applied on it, (2) the performance of PB-SMT task has significantly increased when bilingual information are used on top of monolingual segmented result. Our technique, instead of focusing on word separation, mainly concentrate on character clustering. First, we cluster each character from the unsegmented monolingual corpus by employing character co-occurrence statistics and orthographic insight. Secondly, we enhance the segmented result by incorporating the bilingual information which are character cluster alignment, co-occurrence frequency and alignment confidence into that result. We evaluate the effectiveness of our method on PB-SMT task using English-Thai language pair and report the best improvement of 8.1% increase in BLEU score. There are two main advantages of our approach. First, our method requires less effort on developing the corpus and can be applied to unsegmented corpus or poor-quality manually segmented corpus. Second, this technique does not only limited to specific language pair but also capable of automatically adjust the character cluster boundaries to be suitable for other language pairs.
Thrust++: Extending Thrust Framework for Better Abstraction and Performance

A good design abstraction framework for high performance computing should provide a higher level programming abstraction that strikes a balance between the abstraction and visibility over the hardware so that the software developer can write a portable software without having to understand the hardware nuances, yet exploit the compute power optimally. In this paper we have analyzed a popular design abstraction framework called "Thrust" from NVIDIA, and proposed an extension called Thrust++ that provides abstraction over the memory hierarchy of an NVIDIA GPU. Thrust++ allows developers to make efficient use of shared memory and overall, provides better control over the GPU memory hierarchy while writing applications in Thrust style for the CUDA backend. We have shown that when applications are written for the CUDA backend using Thrust++, they have minimal performance degradation when compared to their equivalent CUDA versions. Further, Thrust++ provides almost 4x speedup when compared to Thrust, for certain compute intensive kernels that repeatedly use the reduce operation.
User association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations

Drone base stations (DBSs) can enhance network coverage and area capacity by moving supply towards demand when required. This degree of freedom could be especially useful for future applications with extreme demands, such as ultra reliable and low latency communications (uRLLC). However, deployment of DBSs can face several challenges. One issue is finding the 3D placement of such BSs to satisfy dynamic requirements of the system. Second, the availability of reliable wireless backhaul links and the related resource allocation are principal issues that should be considered. Finally, association of the users with BSs becomes an involved problem due to mobility of DBSs. In this paper, we consider a macro-BS (MBS) and several DBSs that rely on the wireless links to the MBS for backhauling. Considering regular and uRLLC users, we propose an algorithm to find efficient 3D locations of DBSs in addition to the user-BS associations and wireless backhaul bandwidth allocations to maximize the sum logarithmic rate of the users. To this end, a decomposition method is employed to first find the user-BS association and bandwidth allocations. Then DBS locations are updated using a heuristic particle swarm optimization algorithm. Simulation results show the effectiveness of the proposed method and provide useful insights on the effects of traffic distributions and antenna beamwidth.
The impact of social capitals on service quality of Chinese educational institutions: A multilevel analysis

Most of the existed researches of educational service quality are concentrated on the definition of service quality in education, measurement methods and the establishment of scales, or on student perception of service quality and its implication, while researches on the causes of educational service quality are quite scarce. In this study, the discussion on the causes of educational service quality was complemented from the perspective of social network, especially through analysis at the team level. A total of 478 copies of social network questionnaires were collected from 15 educational teams. Meanwhile, targeting at the educational institutions' customers, the service quality survey was conducted with 1,487 copies of valid samples in total. The results indicate that individual‐level social capital in the form of trust relations positively influences educational service quality. Among the group level factors, group centrality and number of cliques have a significant impact on group members' service quality, which also moderate the effect of trust on service quality.
Impact of Optimal Storage Allocation on Price Volatility in Energy-Only Electricity Markets

Recent studies show that the fast growing expansion of wind power generation may lead to extremely high levels of price volatility in wholesale electricity markets. Storage technologies, regardless of their specific forms, e.g., pump-storage hydro, large-scale, or distributed batteries, are capable of alleviating the extreme price volatility levels due to their energy usage time shifting, fast-ramping, and price arbitrage capabilities. In this paper, we propose a stochastic bilevel optimization model to find the optimal nodal storage capacities required to achieve a certain price volatility level in a highly volatile energy-only electricity market. The decision on storage capacities is made in the upper level problem and the operation of strategic/regulated generation, storage, and transmission players is modeled in the lower level problem using an extended stochastic (Bayesian) Cournot-based game. The South Australia (SA) electricity market, which has recently experienced high levels of price volatility, and a 30-bus IEEE system are considered as the case studies. Our numerical results indicate that 50% price volatility reduction in the SA electricity market can be achieved by installing either 430-MWh regulated storage or 530-MWh strategic storage. In other words, regulated storage firms are more efficient in reducing the price volatility than strategic storage firms.