Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparison study between CMAQ-simulated and OMI-retrieved NO 2 columns over East Asia for evaluation of NO x emission fluxes of INTEX-B, CAPSS, and REAS inventories

Abstract. Comparison between the CMAQ (Community Multi-scale Air Quality Model)-calculated and OMI (Ozone Monitoring Instrument)-retrieved tropospheric NO2 columns was carried out for 2006 over East Asia (100–150° E; 20–50° N) to evaluate the bottom-up NOx emission fluxes of INTEX-B, CAPSS, and REAS v1.11 inventories. The three emission inventories were applied to the CMAQ model simulations for the countries of China, South Korea, and Japan, respectively. For the direct comparison between the two NO2 columns, the averaging kernels (AKs) obtained from the Royal Netherlands Meteorological Institute (KNMI)/DOMINO v2.0 daily product were applied to the CMAQ-simulated data. The analysis showed that the two tropospheric NO2 columns from the CMAQ model simulations and OMI observations (ΩCMAQ,AK and ΩOMI) had good spatial and seasonal correlation, with correlation coefficients ranging from 0.71 to 0.96. In addition, the normalized mean errors (NMEs) between the ΩCMAQ,AK and ΩOMI were found to range from ~ 40 to ~ 63%. The ΩCMAQ,AK were, on annual average, ~ 28% smaller (in terms of the NMEs) than the ΩOMI, indicating that the NOx emissions used were possibly underestimated in East Asia. Large absolute differences between the ΩCMAQ,AK and ΩOMI were found, particularly over central eastern China (CEC) during winter (annual averaged mean error of ~ 4.51 × 1015 molecules cm−2). Although such differences between the ΩCMAQ,AK and ΩOMI are likely caused by the errors and biases in the NOx emissions used in the CMAQ model simulations, it can be rather difficult to quantitatively relate the differences to the accuracy of the NOx emissions, because there are also several uncertain factors in the CMAQ model, satellite-retrieved NO2 columns and AK products, and NOx and other trace gas emissions. In this context, three uncertain factors were selected and analyzed with sensitivity runs (monthly variations in NOx emissions; influences of different NOx emission fluxes; and reaction probability of N2O5 radicals). Other uncertain or possible influential factors were also discussed to suggest future direction of the study.
User-centric usability evaluation for enterprise 2.0 platforms: A complementary multi-method approach

Enterprise 2.0 projects offer a great potential for enabling the effective identification, generation and utilization of information and knowledge within complex organizational processes; and have a deep impact on organizational changes. This paper focuses on a usability methodology, whereby the critical success factors include (i) efficient organization, (ii) guided by organizational needs, (iii) dealing with organizational complexity, and (iv) providing end user requirements. We present a complementary multi-method approach of user-centric usability evaluation methods including eye tracking, heuristic evaluation and a feedback blog. This evaluation approach in combination with continuous user training allows comprehensive enhancement of ability and motivation of the users, which leads to excellent project performance.
Podemos and the Five-star Movement: populist, nationalist or what?

ABSTRACT The resounding electoral successes of the Italian Movimento Cinque Stelle (Five-star Movement, M5S) and the Spanish Podemos (We can) in recent years, have attracted the attention of many political scientists. The two parties can be considered a new kind of anti-establishment party with values incompatible with those of the radical-right parties. From a normative standpoint, two main allegations have been made against the two parties: both have been considered ‘populist’ and, in some ways, ‘nationalist’. Still, the academic literature so far lacks a detailed analysis of the nature of their alleged populism and nationalism. In this article, I argue that both parties share a populist stance, while the label ‘sovereigntists’ rather than ‘nationalists’ is more appropriate in both cases.
A non-deterministic adaptive inertia weight in PSO

Particle Swarm Optimization (PSO) is a relatively recent swarm intelligence algorithm inspired from social learning of animals. Successful implementation of PSO depends on many parameters. Inertia weight is one of them. The selection of an appropriate strategy for varying inertia weight w is one of the most effective ways of improving the performance of PSO. Most of the works done till date for investigating inertia weight have considered small values of w, generally in the range [0,1]. This paper presents some experiments with widely varying values of w which adapts itself according to improvement in fitness at each iteration. The same strategy has been implemented in two different ways giving rise to two inertia weight variants of PSO namely Globally Adaptive Inertia Weight (GAIW) PSO, and Locally Adaptive Inertia Weight (LAIW) PSO. The performance of the proposed variants has been compared with three existing inertia weight variants of PSO employing a test suite of 6 benchmark global optimization problems. The experiments show that the results obtained by the proposed variants are comparable with those obtained by the existing ones but with better convergence speed and less computational effort.
Recommending Tags for Pictures Based on Text, Visual Content and User Context

Imagine you are member of an online social system and want to upload a picture into the community pool. In current social software systems, you can probably tag your photo, share it or send it to a photo printing service and multiple other stuff. The system creates around you a space full of pictures, other interesting content (descriptions, comments) and full of users as well. The one thing current systems do not do, is understand what your pictures are about. We present here a collection of functionalities that make a step in that direction when put together to be consumed by a tag recommendation system for pictures. We use the data richness inherent in social online environments for recommending tags by analysing different aspects of the same data (text, visual content and user context). We also give an assessment of the quality of thus recommended tags.
Programming with Sociable Resources

We present a model for shared-memory parallel programming that makes shared objects (“resources”) the drivers of heap-manipulating parallel computations. The model aims to syntactically capture patterns of spatial locality in heap updates and to express the maximum amount of logical parallelism in computations. To achieve this, we take a “resources’-eye” view of parallel operations on the heap. Resources are now viewed as active entities arranged in a network that is the heap. While they actively change their data content and links to other resources, each change is local and restricted to a spatial “neighborhood”. Global computations are phrased as massively parallel compositions of these local operations. Our programming abstractions include operations that merge neighboring resources into larger resources and split complex resources into simpler ones. These abstractions are composable and directly encode heap-allocated data structures and spatial separation among resources. The model is data-race free even though it does not explicitly use locks. We demonstrate that the model allows easy, and easily parallelizable, programming of several important applications exhibiting irregular data-parallelism. In particular, it faithfully expresses the parallelism inherent in many natural processes and thus seems ideal for scientific and multimedia applications modeling them.
English Vocabulary Size as a Predictor of TOEIC Listening and Reading Achievement among EFL Students in Taiwan

This paper investigates the relationship between vocabulary size and performance on the reading and listening portions of the Test of English for International Communication (TOEIC). The participants were 973 English as a foreign language (EFL) learners from a technical college who had studied English for at least six years. The learners’ TOEIC listening and reading scores were found to be strongly associated with their receptive vocabulary size with no gender differences. These results indicate that vocabulary size could have a statistically significant effect on TOEIC listening and reading scores, reinforcing the value of vocabulary size for English proficiency. Additionally, English vocabulary size and the prediction of proficiency in the TOEIC listening and reading sections reached statistical significance. These findings demonstrate the importance of receptive vocabulary for EFL learners. Outcomes from the study have implications for EFL learners and teachers as well as future research.
i2Flex: Integrating a Large-Scale Technology Supported Educational Innovation in a K-12 International School Setting

In response to the global educational reform the American Community School of Athens (ACS Athens) Greece has developed its own education paradigm, Morfosis which is defined within the 21st century framework, as a holistic, meaningful, and harmonious educational experience, guided by ethos. The vehicle to implement Morfosis, is the i2Flex (isquareFlex), a non-traditional learning methodology, organically developed by the ACS Athens community of learners. I2Flex integrates face-to-face and internet-based instruction with faculty-guided, student independent learning, and aims aat developing higher order cognitive skills within a learning design framework that is flexible in terms of time, pace, place, and/or mode. Ultimately, i2Flex aims at developing students' 21st century skills, while also helping them successfully prepare for their higher education studies and their future careers.
An efficient hierarchical attribute set based encryption scheme with revocation for outsourcing personal health records in cloud computing

Enterprises will outsource their sensitive data in a cloud server due to the rapid development of cloud computing in the IT industry for last few years. It is attractive for the Personal Health Record (PHR) service providers to shift their PHR applications and storage into the cloud. Under encryption, it is excited to achieve fine-grained access control to PHR data in a scalable and efficient way. It also includes the problem of establishing access control for the encrypted data, and revoking or withdrawing the access rights from users when they are no longer authorized to access the encrypted data on cloud servers. But the use of one single Trusted Authority (TA) and Cipher text Policy (CP-ABE) are unable to manage multiple group owners for encryption process and access policy. In order to realize scalability, flexibility, and fine-grained access control of outsourced data in cloud computing, we leverage Hierarchical Attribute-Set-Based Encryption (HASBE). This HASBE extends the cipher text-policy Attribute-Set-Based Encryption (ASBE) with a hierarchical structure of users by means of compound attributes. The intended scheme achieves fine-grained, flexible and scalable data access control with the help of compound attributes of HASBE.
Exploring closed-loop feedback control using experiments in optics

We present two experiments in closed-loop feedback control. In the first experiment, students control the pointing angle of a laser to "lock" the laser onto a "target. " In the second, students stabilize the pathlength difference in two arms of a Michelson interferometer. These experiments are appropriate for electronics and optics laboratory classes for junior and senior level students.
Analysis of task feasibility for a home robot using prismatic joints

This paper evaluates the dynamic and kinematic properties of a prismatic mechanism and shows its capabilities in performing home manipulation tasks when integrated into a robotic arm. Our design is motivated from the observation that human hand motions often follow a linear trajectory when manipulating everyday objects. We present the mechanical design for a light-weight, energy-efficient robot named PRISM that emphasizes translational motion. By simulating the dynamics equations and comparing the structure of commonly used anthropomorphic arms and our proposed arm, we verify that translational motion is more energy efficient with PRISM, and the robot can maneuver itself in narrower places. Through simulation experiments using state of the art manipulation planning algorithms, we analyze the success rates of PRISM and an anthropomorphic robot arm in performing basic tasks. The simulation experiments center on pick-and-place tasks in cluttered kitchen scenes. We show a real-world prototype of PRISM and perform several manipulation experiments with it.
Osteopontin identified as lead marker of colon cancer progression, using pooled sample expression profiling.

BACKGROUND New tumor markers and markers of tumor progression are needed for improved staging and for better assessment of treatment of many cancers. Gene expression profiling techniques offer the opportunity to discover such markers. We investigated the feasibility of sample pooling strategy in combination with a novel analysis algorithm to identify markers. METHODS Total RNA from human colon tumors (n = 60) of multiple stages (adenomas; cancers with modified Astler Collier stages B, C, and D; and liver metastases) were pooled within stages and compared with pooled normal mucosal specimens (n = 10) by using oligonucleotide expression arrays. Genes that showed consistent increases or decreases in their expression through tumor progression were identified. Northern blot analysis was used to validate the findings. All statistical tests were two-sided. RESULTS More than 300 candidate tumor markers and more than 100 markers of tumor progression were identified. Northern analysis of 11 candidate tumor markers confirmed the gene expression changes. The gene for the secreted integrin-binding protein osteopontin was most consistently differentially expressed in conjunction with tumor progression. Its potential as a progression marker was validated (Spearman's rho = 0.903; P<.001) with northern blot analysis using RNA from an independent set of 10 normal and 43 tumor samples representing all stages. Moreover, a statistically significant correlation between osteopontin protein expression and advancing tumor stage was identified with the use of 303 additional specimens (human cancer = 185, adenomas = 67, and normal mucosal specimens = 51) (Spearman's rho = 0.667; P<.001). CONCLUSIONS Sample pooling can be a powerful, cost-effective, and rapid means of identifying the most common changes in a gene expression profile. We identified osteopontin as a clinically useful marker of tumor progression by use of gene expression profiling on pooled samples.
Ontology Search: Finding the Right Ontologies on the Web

With the recent growth of Linked Data on the Web, there is an increased need for knowledge engineers to find ontologies to describe their data. Only limited work exists that addresses the problem of searching and ranking ontologies based on keyword queries. In this proposal we introduce the main challenges to find appropriate ontologies, and preliminary solutions to address these challenges. Our evaluation shows that the proposed solution performs significantly better than existing solutions on a benchmark ontology collection for the majority of the sample queries defined in the benchmark.
Thermodynamics of spinning branes and their dual field theories

We present a general analysis of the thermodynamics of spinning black p-branes of string and M-theory. This is carried out both for the asymptotically-flat and near-horizon case, with emphasis on the latter. In particular, we use the conjectured correspondence between the near-horizon brane solutions and field theories with 16 supercharges in various dimensions to describe the thermodynamic behavior of these field theories in the presence of voltages under the R-symmetry. Boundaries of stability are computed for all spinning branes both in the grand canonical and canonical ensemble, and the effect of multiple angular momenta is considered. A recently proposed regularization of the field theory is used to compute the corresponding boundaries of stability at weak coupling. For the D2, D3, D4, M2 and M5-branes the critical values of Ω/T in the weak and strong coupling limit are remarkably close. Finally, we also show that for the spinning D3-brane the tree level R4 correction supports the conjecture of a smooth interpolating function between the free energy at weak and strong coupling.
Synthesis, activity, and docking study of phenylthiazole acids as potential agonists of PPARγ

Peroxisome proliferator-activated receptor gamma (PPARγ) is a ligand-mediated transcription factor playing key roles in glucose and lipid homeostasis, and PPARγ ligands possess therapeutic potential in these as well as other areas. In this study, a series of phenylthiazole acids have been synthesized and evaluated for agonistic activity by a convenient fluorescence polarization-based PPARγ ligand screening assay. Compound 4t, as a potential PPARγ agonist with half maximal effective concentration (EC50) 0.75±0.20 μM, exhibited in vitro potency comparable with a 0.83±0.14 μM of the positive control rosiglitazone. Molecular docking and molecular dynamics simulations indicated that phenylthiazole acid 4t interacted with the amino acid residues of the active site of the PPARγ complex in a stable manner, consistent with the result of the in vitro ligand assay.
A conditional random field for automatic photo editing

We introduce a method for fully automatic touch-up of face images by making inferences about the structure of the scene and undesirable textures in the image. A distribution over image segmentations and labelings is computed via a conditional random field; this distribution controls the application of various local image transforms to regions in the image. Parameters governing both the labeling and transforms are jointly optimized w.r. t. a training set of before-and-after example images. One major advantage of our formulation is the ability to approximately marginalize over all possible labelings and thus exploit much or most of the information in the distribution; this yields better results than MAP inference. We demonstrate with a system that is trained to correct red-eye, reduce specularities, and remove acne and other blemishes from faces, showing results with test images scavenged from acne-themed internet message boards.
Driver adaptation to haptic shared control of the steering wheel

Although the benefits of haptic shared control of the steering wheel have been repeatedly demonstrated, longitudinal studies of how drivers adapt to this kind of system are still lacking. The present study addressed this question by comparing two groups of participants in a driving simulator for an extended time period; one group drove with a shared control system and the other drove without. After the practice, all participants drove a final trial with shared control during which a failure of the system occurred. The results show that the evolution of driving performance and the way in which drivers monitored their performance was similar for the two groups. This suggests that the drivers quickly updated their internal model of the steering system dynamics at the sensorimotor level, without further behavioural adaptation afterwards. However, it appears that the internal model was consolidated with repeated use of the system, which translated as a difficulty to compensate for the system's failure. In addition, it appears that drivers did not attempt to maintain a level of task difficulty when steering was facilitated.
Symmetrizing Smoothing Filters

We study a general class of nonlinear and shift-varying smoothing filters that operate based on averaging. This important class of filters includes many well-known examples such as the bilateral filter, nonlocal means, general adaptive moving average filters, and more. (Many linear filters such as linear minimum mean-squared error smoothing filters, Savitzky--Golay filters, smoothing splines, and wavelet smoothers can be considered special cases.) They are frequently used in both signal and image processing as they are elegant, computationally simple, and high performing. The operators that implement such filters, however, are not symmetric in general. The main contribution of this paper is to provide a provably stable method for symmetrizing the smoothing operators. Specifically, we propose a novel approximation of smoothing operators by symmetric doubly stochastic matrices and show that this approximation is stable and accurate, even more so in higher dimensions. We demonstrate that there are several im.
Embedded Training Intelligent Tutoring Systems (ITS) for the Future Combat Systems (FCS) Command and Control (C2) Vehicle

Abstract : The FCS is a radical departure from the previous Army concept of operations. It is described primarily as a system of systems and is a new way to fight. The new concept of operations is network centric, with information from a large number of different types of sensors passing through the network to the C2 vehicle. This diverse information must be understood, situational awareness achieved, and, tactical decisions based on it must be made. Thus, the new soldier manning the FCS C2 platform is given much more information, more diverse in nature; and therefore has a much more cognitively challenging job. Embedded training (ET) seeks to provide effective training anytime, anywhere. "Embedded training must allow individual and collective training on a digital terrain representation of the mission area and permit mission planning and rehearsal in both stand-alone and networked modes while enroute. "FCS Mission Needs Statement (MNS) 2001 Instructors are required to perform several instructional tasks, including instructing the student on relevant information, presenting appropriate examples, debriefing the student, and assigning remedial instruction. However, an instructor will not usually be available in the field, anytime, anywhere.
Stochastic Implementation of LDPC Decoders

LDPC codes are found in many recent communications standards such as 10GBASE-T, DVB-S2 and IEEE 802.16 (WiMAX). We present a review of a new class of "stochastic" iterative decoding architectures. Stochastic decoders represent probabilistic messages by the frequency of ones in a binary stream. This results in a simple mapping of the factor graph of the code into silicon. An FPGA implementation of a LDPC decoder with 8 information bits and 8 coded bits is described. On an Altera Cyclone FPGA, the throughput is 5 Mbps when clocked at 100 MHz and is expected to increase nearly linearly with the code length. Simulations of the decoder on an Altera Stratix FPGA indicate a potential throughput of 8 Mbps
Stack Authority : Predicting Stack Overflow Post Helpfulness Using User Social Authoritativeness

Online Collaborative Questioning and Answering (CQA) websites have shown an explosive growth trend in recent years. Websites such as StackOverflow and Quora have become increasingly popular and relevant in today’s world, with people actively using these websites to ask questions about everything from mundane day-to-day tasks to highly specific details about specific subject matter. While these websites are incredibly useful, they also suffer from having extremely unhelpful, spam-like posts. Humans may be needed to properly classify posts as useful or not useful, but having a computer based model which predicts the usefulness of a post would greatly increase the efficiency of classifying posts. In this paper, we discuss two models which predict the ratio of upvotes to the sum of upvotes and downvotes on StackOverflow posts. Additionally, we study the effect of adding social information, specifically user hub and authority scores as a feature to our models. Overall, we are able to match and slightly outperform similar literature, and also conclude that hub and authority scores have little effect on predictive models.