Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing Collective Discursive User Interactions in Online Life Science Communities

This paper highlights the rationale for the development of BioViz, a tool to help visualize the existence of collective user interactions in online life science communities. The first community studied has approximately 22,750 unique users and the second has 35,000. Making sense of the number of interactions between actors in these networks in order to discern patterns of collective organization and intelligent behavior is challenging. One of the complications is that forums - our object of interest - can vary in their purpose and remit (e.g. the role of gender in the life sciences to forums of praxis such as one exploring the cell line culturing) and this shapes the structure of the forum organization itself. Our approach took a random sample of 53 forums which were manually analyzed by our research team and interactions between actors were recorded as arcs between nodes. The paper focuses on a discussion of the utility of our approach, but presents some brief results to highlight the forms of knowledge that can be gained in identifying collective group formations. Specifically, we found that by using a matrix-based visualization approach, we were able to see patterns of collective behavior which we believe is valuable both to the study of collective intelligence and the design of virtual organizations.
The space of rate monotonic schedulability

Feasibility analysis of fixed priority systems has been widely studied in the real-time literature and several acceptance tests have been proposed to guarantee a set of periodic tasks. They can be divided into two main classes: polynomial time tests and exact tests. Polynomial time tests are used for an online guarantee of dynamic systems, where tasks can be activated at runtime. These tests introduce negligible overhead when executed on a new task arrival, but provide only a sufficient schedulability condition, which may cause poor processor utilization. On the other hand, exact tests, which are based on response time analysis, provide a necessary and sufficient schedulability condition, but are too complex to be executed on line for large task sets. As a consequence, for large task sets, they are often executed offline. This paper proposes a novel approach for analyzing the schedulability of periodic task sets under rate monotonic priority assignment. Using this approach, we derive a new schedulability test which can be tuned through a parameter to balance the complexity vs. acceptance ratio, so that it can be used online to better exploit the processor based on available computational power. Extensive simulations show that our test, when used in its exact form, is significantly faster than current response time analysis methods. Moreover, the proposed approach, for its elegance and compactness, offers an explanation of known phenomena of fixed priority scheduling and could be helpful for further work on rate monotonic analysis.
Computing the Sparse Solution to Fourier Extension of Nonperiodic Function

For a given basis, the approximate solution to Fourier extension of Nonperiodic function computed with numerical least squares methods including projection methods and collocation methods are successful but not sparse. To solve the linear system equations built on projection methods by using Orthogonal Matching Pursuit algorithm, we extract some items from the original basis. We do optimization based on the low-dimensional basis generated by those items extracted from the original basis, thus we find the sparse solution to Fourier extension of Nonperiodic function without loss of approximation accuracy and unbounded Fourier coefficients.
NAFTA and Development: The Case of Mexico

This article examines, within the context of development theory, how the Mexican economy adapted to the period of liberalization which followed the external debt crisis of 1982 and the implementation of the North American Free Trade Agreement (NAFTA) in 1994. Integration of the Mexican economy under NAFTA had a modernizing effect on several manufacturing industries and strongly contributed to “trade creation” in the region. In general, however, the impact of neo-liberalism was negative, with neither sustained economic growth nor social progress in evidence, thus threatening the social stability and governance of Mexico. The neo-liberal model and its integration process have accentuated the structural heterogeneity of the productive system, which in turn hampered an endogenous base of capital accumulation needed to sustain dynamic economic growth. It also deepened social inequalities between and within the member countries of NAFTA. Because the neo-liberal economic model has not been able to solve the problem of exterior disequilibrium, the economic system remains very dependent on external capital flows. TRAVAIL, capital et societe 36:1 (avril 2003) pp. 40-70
Workload characteristics for process migration and load balancing

Is process migration useful for load balancing? We present experimental results indicating that the answer to this question depends largely on the characteristics of the applied workload. Experiments with our Shiva system, which supports remote execution and process migration, show that only those CPU bound workloads which were generated using an unrealistic exponential distribution for execution times show improvements for dynamic load balancing. (We use the term 'dynamic' to indicate remote execution determined at and not prior to run time. The latter is known as 'static' load balancing.) Using a more realistic workload distribution and adding a number of short lived tasks prevents dynamic algorithms from working. Migration is only useful with heterogeneous workloads. We find the migration of executing tasks to remote data to be effective for balancing I/O bound workloads, and indicate the region of 'workload variable space' for which this migrate-to-data approach is useful.
Open string diagrams I: topological type

An arbitrary Feynman graph for string field theory interactions is analyzed and the homeomorphism type of the corresponding world sheet surface is completely determined even in the nonorientable cases. Algorithms are found to mechanically compute the topological characteristics of the resulting surface from the structure of the signed oriented graph. Whitney’s permutation‐theoretic coding of graphs is utilized.
Robust synchronization technique for mobile DTV broadcasting system

Synchronization is considered an important design issue for the implementation of digital television (DTV) receiver, specially for proper reception of multipath distorted signal at low signal to noise ratio (SNR). This challenge is more pronounced in complex multipath channel scenarios and for high mobility applications in presence of carrier frequency offset (CFO). In this paper, time domain correlation technique based on multiple PN-511 sequences is proposed to improve the synchronization performance of DTV broadcasting system that is robust against multipath impairments and CFO. Due to self-resolving capability of the multipath components, proposed synchronization algorithm provides better performance than conventional single PN-511 based algorithm in complex multipath channel. Since only the received adjacent PN-511 sequences are considered in the correlation process, the proposed technique is robust against CFO as well. In addition, the proposed technique provides higher peak-to-noise ratio (PNR), therefore this technique can be effectively used at low SNR conditions. Further, maximum likelihood (ML) estimation for multiple PN-511 based algorithm is carried out to evaluate the feasibility of the proposed algorithm.
Calorie Anticipation Alters Food Intake After Low-Caloric but Not High-Caloric Preloads

Cognitive factors and anticipation are known to influence food intake. The current study examined the effect of anticipation and actual consumption of food on hormone (ghrelin, cortisol, and insulin) and glucose levels, appetite and ad libitum intake, to assess whether changes in hormone levels might explain the predicted differences in subsequent food intake.
Characterizing Comorbidity in Dialysis Patients: Principles of Measurement and Applications in Risk Adjustment and Patient Care

Comorbid conditions are highly prevalent in dialysis patients and are significant predictors of mortality and other adverse outcomes. Accordingly, it is important to account for differences in comorbid illness burden among groups of dialysis patients being compared. At present, there is no consensus on what conditions matter, how each should be defined, and what weights each carries when defining an individual's risk or case-mix severity. A number of comorbidity instruments, generic or disease specific, have been employed in dialysis populations. They differ by the representation and definition of conditions as well as instrument scoring. No instrument has been found to be superior to another in terms of predictive accuracy for mortality, and accuracy across the board is low. Further studies are needed to determine whether improvements would be found with the use of more specifically defined items and through assignment of item weights based on relationships for outcomes specifically in a dialysis population. The roles of other factors in risk prediction, such as markers of nutritional status, inflammation, or other physiological parameters, relative to comorbid conditions also need to be defined. Outcomes other than mortality are likely to identify different factors and/or different relationships than those noted for mortality, which also require study. Comorbidity is important for risk adjusting comparative analyses in nonrandomized trials and quality of care assessments and may, in future, influence payment for dialysis services. Efforts to improve the management of comorbid illnesses are needed. Comorbid conditions must be documented accurately and uniformly in all dialysis patients to enable these applications.
Modeling Connectivity of Inter-Vehicle Communication Systems with Road-Side Stations

In this letter, the authors discuss the improvement that roadside stations can bring to the multihop connectivity of intervehicle communication (IVC) in a traffic stream. With a recursive model of connectivity, they study impacts of different densities of roadside stations and different positions of roadside stations for uniform or non-uniform traffic streams. The rest of the article includes the introduction of an analytical model of an IVC system with roadside stations, the analysis of the connectivity of an IVC system under different conditions, and a summary and discussion of the findings. From the numerical studies, they find that, as expected, roadside stations can help relay information in an IVC system and have the following impacts on the performance of an IVC system: the larger the density of roadside stations, the more improvement in the connectivity; different locations of roadside stations relative to a traffic stream can yield different levels of improvement in connectivity; and it is better to deploy roadside stations along less congested traffic. This is consistent with the observation that sparse traffic is the communication bottleneck of an IVC system. For a particular road network, the best locations of roadside stations can be calculated with the proposed model. In addition to considerations in performance, economic constraints should also be considered when deploying roadside stations, since available budget would limit the number of roadside stations and may yield sub-optimal results.
Minimization of Dynamic Power using Pulsed Latch for Clock Tree

Nowadays power consumption is an important issue in high-performance digital circuits. Reducing the size of a clock tree is an effective approach to reduce dynamic power dissipation in digital circuit designs. Existing methods are based on reduction of the flip-flop power alone, which gives limited amount of power saving. To achieve the considerable power saving, this paper gives an analysis of the pulsedlatch utilization in a clock tree. This is the first step to propose a novel approach to efficiently construct a clock tree with both pulsed-latches and flip-flops. The proposed method is based on minimum-cost, maximum-flow formulation to determine the tree topology. It maintains load balance and considers the wire length between pulse generators and pulsed latches. Experimental results indicate that the proposed novel approach can reduce the power consumption by 25% to 30% . It is an average compared with the most recent paper on the industrial circuits and ISCAS-2012 benchmarks, respectively.
Robot motion planning with uncertainty

This thesis concerns robot motion planning with uncertainty in control and sensing. The problem can be formulated, with some approximations, as path-planning in the extended space of poses × covariances. The reduction of uncertainty due to data acquired by exteroceptive sensors is modelled with the use of Fisher’s information matrix. Many optimization problems can be defined in this framework; this thesis considers two problems: minimizing the execution time, and minimizing the final covariance, with an upper bound on the execution time. Two approaches are discussed. The first is the straight extension of classical graph-search algorithms to the extended space. In the second approach, in place of the forward propagation of states, uncertainty constraints are propagated backward from the goal to the start state. Much attention is given to the definition of dominance relations that allow to discard useless nodes during the search. Simulations show that motion planning with uncertainty is much more expensive to solve than classical path-planning. The backward algorithms are slightly more computationally expensive, but their search tree can be reused for multiple queries.
Monte-carlo driven stochastic optimization framework for handling fabrication variability

Increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. In this work, we propose a Monte-Carlo driven stochastic optimization framework that does not rely on the distribution of the varying parameters (unlike most other existing techniques). Stochastic techniques like successive sample mean optimization (SSMO) and stochastic decomposition present a strong framework for solving linear programming formulations in which the parameters behave as random variables. We consider binning-yield loss (BYL) as the optimization objective and show that we can get a provably optimal solution under a convex BYL function. We apply this framework for the MTCMOS sizing problem [Khandelwal, V. , et al., 2005] using SSMO and stochastic decomposition techniques. The experimental results show that the solution obtained from stochastic decomposition based framework had 0% yield-loss, while the deterministic solution [Khandelwal, V. , et al., 2005] had a 48% yield-loss.
Latency Performance Model of Direct and K-Access Reads in Distributed Storage Systems

Access latency is a crucial performance metric in distributed storage systems as it greatly impacts user experience, especially for hot data visitors. Existing papers argue that coding can reduce access latency compared with the replication method, and many dispatch schemes, such as those implementing redundant requests, dynamically changing code rates, and so on, are proposed and proved to work well in improving latency performance under certain conditions. However, some practical issues, such as direct reads, and the additional cost of redundant requests, are ignored and a general and practical model of latency performance is still lacking. Considering a more comprehensive set of practical issues in distributed storage systems, we propose a performance model that can be easily used to compare latency performance of different codes and replication methods under different conditions. We also use our performance model to evaluate many schemes and show their different impacts on the latency performance of different types of reads. To the best of our knowledge, we are the first to study the latency performance of direct reads under different codes or schemes, and the first to propose a model of latency performance including both direct and k-access reads.
Pain-Related Fear: A Critical Review of the Related Measures

Objectives: In regards to pain-related fear, this study aimed to: (1) identify existing measures and review their measurement properties, and (2) identify the optimum measure for specific constructs of fear-avoidance, pain-related fear, fear of movement, and kinesiophobia. Design: Systematic literature search for instruments designed to measure fear of pain in patients with persistent musculoskeletal pain. Psychometric properties were evaluated by adjusted Wind criteria. Results: Five questionnaires (Fear-Avoidance Beliefs Questionnaire (FABQ), Fear-Avoidance of Pain Scale (FAPS), Fear of Pain Questionnaire (FPQ), Pain and Anxiety Symptoms Scale (PASS), and the Tampa Scale for Kinesiophobia (TSK)) were included in the review. The main findings were that for most questionnaires, there was no underlying conceptual model to support the questionnaire's construct. Psychometric properties were evaluated by diverse methods, which complicated comparisons of different versions of the same questionnaires. Construct validity and responsiveness was generally not supported and/or untested. Conclusion: The weak construct validity implies that no measure can currently identify who is fearful. The lack of evidence for responsiveness restricts the current use of the instruments to identify clinically relevant change from treatment. Finally, more theoretically driven research is needed to support the construct and thus the measurement of pain-related fear.
Short-term sustainability of drainage water reuse: spatio-temporal impacts on soil chemical properties.

Greater urban demand for finite water resources, increased frequency of drought resulting from erratic weather, and increased pressure to reduce drainage water volumes have intensified the need to reuse drainage water. A study was initiated in 1999 on a 32.4-ha saline-sodic field (Lethent clay loam series; fine, montmorillonitic, thermic, Typic Natrargid) located on the west side of California's San Joaquin Valley (WSJV) with the objective of evaluating the sustainability of drainage water reuse with respect to impact on soil quality. An evaluation after 5 yr of irrigation with drainage water is presented. Geo-referenced measurements of apparent soil electrical conductivity (EC(a)) were used to direct soil sampling at 40 sites to characterize the spatial variability of soil properties (i.e., salinity, Se, Na, B, and Mo) crucial to the soil's intended use of growing Bermuda grass (Cynodon dactylon (l.) Pers. ) for livestock consumption. Soil samples were taken at 0.3-m increments to a depth of 1.2 m at each site in August 1999, April 2002, and November 2004. Drainage water varying in salinity (0.8-16.2 dS m(-1)), SAR (5.4-52.4), Mo (80-400 microg L(-1)), and Se (<1-700 microg L(-1)) was applied to the field since July 2000. An analysis of the general temporal trend shows that overall soil quality has improved due to leaching of B from the top 0.6 m of soil; salinity and Na from the top 1.2 m, but primarily from 0 to 0.6 m; and Mo from the top 1.2 m. Short-term sustainability of drainage water reuse is supported by the results.
Evaluating Hybrid Music Recommender Systems

Taste in music is of highly subjective nature, making the recommending of music tracks a challenging research task. With TRecS, our live prototype system, we present a weighted hybrid recommender approach that amalgamates three diverse recommender techniques into one comprehensive score. Moreover, our system peppers the generated result list with recommendations based on a simple serendipity heuristic. This way, users can benefit from recommendations aligned with their current taste in music while gaining some exploratory diversification. An explanation feature helps the user understand the rationale behind each of the tracks being recommended to him. Empirical evaluations of the live system, based on an online evaluation, assess the overall recommendation quality as well as the impact of each of the three sub-recommenders.
Fisher-ratio-separability boosted binary tree of posterior probability SVMs with application to action recognition

Based on fisher ratio class separability measure, we propose two types of posterior probability support vector machines (PPSVMs) using binary tree structure. The first one is a some-against-rest binary tree of PPSVM classifiers (SBT), for which some classes as a cluster are divided from the rest classes at each non-leaf node. To determine the two clusters, we use the Fisher ratio separability measure. Accordingly, the second proposed method termed one-against-rest binary tree of PPSVMs (OBT), we separate only one class with the largest separability measure from the rest classes at each non-leaf node. Then, the procedures of both SBT and OBT are provided. Finally, we consider the problem of human action recognition based on depth maps adopting both proposed approaches. Simulation results indicate both methods gain higher classifying accuracy than those of canonical multi-class SVMs and PPSVMs. Besides, the decision complexity of the proposed SBT and OBT are reduced because they use the posterior probability and the Fisher ratio separability measure.
Botnet Statistical Analysis Tool for Limited Resource Computer Emergency Response Team

Botnet is recognized as one of the fastest growing threat to the Internet and most users do not aware that they were victimized. ThaiCERT is one of many computer emergency response teams that have limited resources in term of budget to monitor and handle this kind of threat. An interim solution for teams with limited resource is to subscribe to the Shadowserver Foundation’s mailing list instead of deploying their own capturing and monitoring tools. The valuable information from the Shadowserver Foundation in form of plaintext e-mails may be difficult to manage and analyze. However, there is a need to analyze information provided by the Shadowserver Foundation to be able to efficiently handle botnet’s incidents for our own constituency. In this manuscript, we present our approach to handle the botnet threat using available information from the Shadowserver Foundation and describe our automate tool using by our incident handling team. Finally, we present our statistical data on botnet’s threat in our constituency over the last two years.
Integrated Technologies Like Noninvasive Brain Stimulation (NIBS) for Stroke Rehabilitation New Hopes for Patients, Neuroscientists, and Clinicians in Iran

1. Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA 2. Neurovascular Department, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran 3. Neurocognitive Laboratory, Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran 4. Tabas’som Stroke Rehabilitation Centre, Tehran, Iran 5. Physical and Rehabilitation Medicine Department, Research Center for Rehabilitation, Iran University of Medical Sciences, Iran