Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiscale Interactions betweenWater and Carbon Fluxes and Environmental Variables in A Central U.S. Grassland

The temporal interactions between water and carbon cycling and the controlling environmental variables are investigated using wavelets and information theory. We used 3.5 years of eddy covariance station observations from an abandoned agricultural field in the central U.S. Time-series of the entropy of water and carbon fluxes exhibit pronounced annual cycles, primarily explained by the modulation of the diurnal flux amplitude by other variables, such as the net radiation. Entropies of soil moisture and precipitation show almost no annual cycle, but the data were collected during above average precipitation years, which limits the role of moisture stress on the resultant fluxes. We also investigated the information contribution to resultant fluxes from selected environmental variables as a function of time-scale using relative entropy. The relative entropy of latent heat flux and ecosystem respiration show that the radiation terms contribute the most information to these fluxes at scales up to the diurnal scale. Vapor pressure deficit and air temperature contribute to the most information for the gross primary productivity and net ecosystem exchange at the daily time-scale. The relative entropy between the fluxes and soil moisture illustrates that soil moisture contributes information at approximately weekly time-scales, while the relative entropy with precipitation contributes information predominantly at the monthly time-scale. The use of information theory metrics is a relatively new technique for assessing biosphere-atmosphere interactions, and this study illustrates the utility of the approach for assessing the dominant time-scales of these interactions.
Data manipulation API in ERP systems

Efficiency in data manipulation is of vital importance to ERP systems. Flexible data manipulation API helps to address a number of acute needs of end users and application developers. To be efficient the API must meet a number of requirements: (i) allow data operations at any granularity level, (ii) guarantee data integrity, (iii) be scalable, (iv) allow cross-platform invocations, (v) be convenient to use. None of the ERP systems exposes an API like that. Building on the notions of business objects and Web services, this paper contributes with the concept of a business object query language (BOQL). Essentially, BOQL is a query-like service invocation, which provides on-the-fly orchestration of CRUD-operations of business objects. BOQL allows to achieve the desired level of data manipulation efficiency at a reasonable price. To demonstrate the efficiency of the suggested approach the paper presents a use case showing how BOQL enables the development of composite
ECHA J0843.3-7905: Discovery of an ‘old’ classical T Tauri star in the ζ Chamaeleontis cluster

A limited-area survey of the η Chamaeleontis cluster has identified two new late-type members. The more significant of these is ECHA (=IRAS , a slowly rotating M2 classical T Tauri (CTT) star with a spectrum dominated by Balmer emission. At a distance of 97 pc and cluster age of ≈9 Myr, the star is a nearby rare example of an ‘old’ CTT star and promises to be a rewarding laboratory for the study of disc structure and evolution in pre-main sequence (PMS) stars. The other new member is the M4 weak-lined T Tauri (WTT) star ECHA , which is the lowest mass primary known in the cluster.
Combining Partial Redundancy and Checkpointing for HPC

Today's largest High Performance Computing (HPC) systems exceed one Petaflops (1015 floating point operations per second) and exascale systems are projected within seven years. But reliability is becoming one of the major challenges faced by exascale computing. With billion-core parallelism, the mean time to failure is projected to be in the range of minutes or hours instead of days. Failures are becoming the norm rather than the exception during execution of HPC applications. Current fault tolerance techniques in HPC focus on reactive ways to mitigate faults, namely via checkpoint and restart (C/R). Apart from storage overheads, C/R-based fault recovery comes at an additional cost in terms of application performance because normal execution is disrupted when checkpoints are taken. Studies have shown that applications running at a large scale spend more than 50% of their total time saving checkpoints, restarting and redoing lost work. Redundancy is another fault tolerance technique, which employs redundant processes performing the same task. If a process fails, a replica of it can take over its execution. Thus, redundant copies can decrease the overall failure rate. The downside of redundancy is that extra resources are required and there is an additional overhead on communication and synchronization. This work contributes a model and analyzes the benefit of C/R in coordination with redundancy at different degrees to minimize the total wallclock time and resources utilization of HPC applications. We further conduct experiments with an implementation of redundancy within the MPI layer on a cluster. Our experimental results confirm the benefit of dual and triple redundancy - but not for partial redundancy - and show a close fit to the model. At ≈ 80, 000 processes, dual redundancy requires twice the number of processing resources for an application but allows two jobs of 128 hours wallclock time to finish within the time of just one job without redundancy. For narrow ranges of processor counts, partial redundancy results in the lowest time. Once the count exceeds ≈ 770, 000, triple redundancy has the lowest overall cost. Thus, redundancy allows one to trade-off additional resource requirements against wallclock time, which provides a tuning knob for users to adapt to resource availabilities.
Cancer Stage, Comorbidity, and Socioeconomic Differences in the Effect of Cancer on Labour Market Participation: A Danish Register-Based Follow-Up Study

Purpose Socioeconomic inequality in return to work after cancer treatment and rehabilitation have been documented, but less is known about its causes. This paper investigates the role played by breast cancer stage at diagnosis and comorbidity. Methods We used the comprehensive Danish Cancer Registry to follow 7372 women aged 30-60, who were in the labour force when diagnosed with breast cancer in 2000-06 and survived at least three years. Controls were 213,276 women without breast cancer. Inequalities in employment outlook were estimated as interaction effects in linear regression between educational attainment and disease on employment. Results There is significant interaction between education and breast cancer, but it is only marginally affected by including stage and comorbidity in the regression models. Education, breast cancer stage, and comorbidity all have strong effects on later employment, and a considerable amount of the educational effect is mediated by comorbidity and pre-cancer labour market participation and income. Conclusion The result of the study is negative in the sense that the stronger effect of breast cancer on employment among low-educated compared to highly educated individuals is not explained by cancer stage or comorbidity. The fact that comorbidity has little impact on inequality may be due to a different social patterning of most comorbidity compared to breast cancer.
Combining Global Features within a Nearest Neighbor Classifier for Content-based Retrieval of Medical Images

A combination of several classifiers using global features for the content description of medical images is proposed. Beside two texture features, downscaled representations of the original images are used, which preserve spatial information and utilize distance measures which are robust regarding common variations in radiation dose, translation, and local deformation. No query refinement mechanisms are used. The single classifiers are used within a parallel combination scheme, with the optimization set being used to obtain the best weighing parameters. For the medical automatic annotation task, a categorization rate of 78.6% is obtained, which ranks 12th among 28 submissions. When applied in the medical retrieval task, this combination of classifiers yields a mean average precision (MAP) of 0.0172, which is rank 11 of 11 submitted runs for automatic, visual only systems.
An almost optimal MAC protocol for all-optical WDM multi-rings with tunable transmitters and fixed receivers

This paper considers SRR (synchronous round robin), an almost optimal collision-free access scheme for all-optical packet networks based on WDM multi-channel ring topologies providing slotted channels for transmissions to disjoint subsets of destination nodes. Only a channel inspection capability and local status information are required at nodes in order to implement the access protocol. Since SRR is not able to enforce fairness by itself, MMR (multi MetaRing), a fairness control algorithm derived from those adopted in the MetaRing high-speed metropolitan area network, is superimposed to SRR. Our analysis proves that the considered access scheme, in spite of its simplicity, allows an almost optimal exploitation of the available resources while guaranteeing a fair access to all nodes.
Accelerating sketch-based network flow processing using Graphics Processing Unit

Sketch-based methods are widely used in highspeed network monitoring applications. In this paper, we present a parallel implementation of sketch computations using Open Computing Language (OpenCL) on Graphics Processing Unit (GPU) for network traffic change detection. The parallel nature of the computation on sketch data structure makes it suitable for implementation on GPU. Comparing to the implementation on CPU, the experiment results show the speed up of 2.8 times and 4 times in average for sketch table size of 1024 up to 32768 using two different forecasting methods.
A Mindfulness Workshop for Health Science Graduate Students: Preliminary Evidence for Lasting Impact on Clinical Performance

Introduction. Health science graduate students take high stakes examinations and experience stress and burnout, which can negatively influence performance in clinical courses. e intent of this study was to pilot a curriculum in mindful practice for graduate health science students under high levels of perceived stress. e purpose of this study was to determine the effectiveness of an abbreviated mindfulness workshop to determine if it would provide lasting benefit for students during clinical experiences 9 months later. Methods. Twenty-three graduate students across 4 health professions participated in a 6-week workshop for stress management in March 2017. Students were executed to practice mindfulness activities for 15 minutes daily over the 6 weeks. Weekly meetings included meditation, mindful movement, and small group discussion. A mixed methods approach incorporated preand postworkshopmeasures exploring students’ levels of worry, perceived stress, feelings of isolation, self-judgment, selfkindness, overidentification, and mindfulness. Additional survey data were collected 9 months later to determine if the tools learned in the workshop influenced clinical performance. Qualitative comments were coded using generic qualitative analysis, and member checking confirmed themes. Results. Overall, students demonstrated improvements in all measures of stress over the 6-week workshop. Additionally, they reported positive influences on clinical performance in the affective and cognitive domains 9 months later. Four main themes were extracted from the data. ese were I Have Tools; ink, Pause, Allow; Silence the Critic; and, I Am Not Alone. Overall, the participants experienced significant improvements in mindfulness scores and self-compassion, and showed improvements in perceived stress and worry (Cognitive-Affective Mindfulness Scale-revised). Discussion and Conclusion. Altogether, these data suggest that (1) graduate students can learn to manage worry, feelings of isolation, and self-judgment using tools and strategies from mindful practices; (2) students who practice mindfulness in a 6week workshop report lasting effects during clinical performance 9 months later; and (3) students benefit from a community of peers and a shared space to share their thoughts and feelings as emerging health professionals. Suggestions are made for integrating mindful practices into graduate health science education.
ENL and the DNA Binding Motifs of HRX the Transcriptional Transactivation Activity of The Oncogenic Capacity of HRX-ENL Requires

induce myeloid leukemias in mice as demonstrated by retroviral gene transfer and knock-inexperiments, respectively. In the present study, a structure-function analysis was performed to determine themolecular requirements for in vitro immortalization of murine myeloid cells by HRX-ENL. Deletions of eitherthe AT hook motifs or the methyltransferase homology domain of HRX substantially impaired the transform-ing effects of HRX-ENL. The methyltransferase homology domain was shown to bind non-sequence speciﬁcallyto DNA in vitro, providing evidence that the full transforming activity of HRX-ENL requires multiple DNAbinding structures in HRX. The carboxy-terminal 84 amino acids of ENL, which encode two predicted helicalstructures highly conserved in AF9, were necessary and sufﬁcient for transformation when they were fused toHRX. Similarly, mutations that deleted one or both of these conserved helices completely abrogated thetranscriptional activation properties of ENL. This ﬁnding correlates, for the ﬁrst time, a biological function ofan HRX fusion partner with the transforming activity of the chimeric proteins. Our studies support a modelin which HRX-ENL induces myeloid transformation by deregulating subordinate genes through a gain offunction contributed by the transcriptional effector properties of ENL.
Smart irrigation system for outdoor environment using Tiny OS

In recent years wireless sensor networks are widely used in many automated system like vehicle monitoring, heavy duty plants, robotic control etc. one of the best automated systems is the smart irrigation system. In this paper we have proposed a simple and cost effective smart irrigation system. Our system deploys wireless sensor motes from a wireless sensor network. The system is modelled in outdoor environment using TINY OS based IRIS motes to measure the moisture level of the paddy field and to set the threshold value. MDA100CB sensor motes can measure up to -40°c to 80°c and operate at a range between 1.6 to 2.7 volts. The proposed scheme uses data visualization and monitoring tool MOTEVIEW 2.0f developed by crossbow technology. Proposed scheme is easy to implement and requires less number of IRIS sensor motes as compared to other manual operating people.
A face recognition method robust to pose variation

In this paper, a face recognition method robust to pose variation is proposed. First, Cascade-MR-ASM is utilized to locate feature points in face image, then the location results are mapped into the public parameter space and the shape parameters are obtained. Then the frontal ASM model is obtained by setting zero to parameters related to pose. Then frontal face image is obtained by texture mapping. Finally, face recognition based on eigenface is finished using the K-Nearest Neighbor classifier. The experimental results in CMU_PIE show that the algorithm is robustness to variation of pose.
How donors choose charities: Findings of a study of donor perceptions of thenature and distribution of charitable benefit

This paper is concerned with the question of how donors select charitable beneficiaries, and the extent to which assessments of need are a factor in giving decisions. The study is based on interviews with 60 committed donors, representing a spread of gender, age and income levels. There is a widespread belief that charities exist primarily to help needy people and that the desire to meet needs is a key criterion in the selection of charitable beneficiaries. However, this study finds that people do not give to the most urgent needs, but rather they support causes that mean something to them. In particular, the study finds four non? needs? based criteria that commonly influence donors’ decision? making: Donors’ tastes, preferences and passions, acquired ? as a result of an individual’s social experiences. These motivate many giving decisions, even among donors who perceive themselves to be motivated by meeting needs. Donors’ personal and professional backgrounds, which shape their ‘philanthropic autobiographies’ and influence their choice of beneficiaries. Donors’ perceptions of charity competence, notably the efficiency with which they are believed to use their money, often judged on the basis of the quality and quantity of direct mail. Donors’ desire to have a personal impact, such that their contribution makes a difference and is not ‘drowned out’ by other donors and government funding. Given the voluntary nature of charitable activity, these are not surprising conclusions. Giving and philanthropy have always been supply-led rather than demand-driven: the freedom to distribute as much as one wants, to whom one chooses, is what distinguishes giving from paying tax. Yet the methods used to encourage donations tend to assume that philanthropy depends on objective assessments of need rather than on donors’ enthusiasms. The tendency to overestimate the extent to which people act as rational agents results in fundraising literature that often focuses on the dimensions and urgency of the problem for which funding is sought. The assumption underlying this approach is that donations are distributed in relation to evidence of neediness, when in fact much giving could be described as ‘taste-based’ rather than ‘needs-based’.
A multiprocessor system design

Parallel processing is not so mysterious a concept as the dearth of algorithms which explicitly use it might suggest. As a rule of thumb, if N processes are performed and the outcome is independent of the order in which their steps are executed, provided that within each process the order of steps is preserved, then any or all of the processes can be performed simultaneously, if conflicts arising from multiple access to common storage can be resolved. All the elements of a matrix sum may be evaluated in parallel. The ith summand of all elements of a matrix product may be computed simultaneously. In an internal merge sort all strings in any pass may be created at the same time. All the coroutines of a separable program may be run concurrently.
European and International Asymmetry in the Volatility Transmission Mechanism: The 'German Dominance Hypothesis' Revisited

This paper re-examines the volatility transmission mechanism within EMS and revisits the 'German Dominance Hypothesis' using short-term interest rates. The results, basically, support the idea of a German predominance within the European Monetary System, but not in a strict sense, since Germany's short-term rates are also affected by actions from its partners. When including the US short-term interest rate, neither the German nor the US rate surface as predominant players in the volatility transmission mechanism. This is explained by the fact that during Germany's post-unification era, the EMS and US monetary policies were diverging. A final finding refers to the absence of asymmetric behavior within EMS after Germany's reunification due to the rapid convergence of the EMS countries as they prepare for the anticipated monetary union.
Joint rate and power adaptation for wireless local area networks in Nakagami fading channels

In this paper, we propose a fast channel-driven rate and power adaptation (CDRPA) algorithm for wireless local area networks (WLAN). The proposed algorithm jointly adjusts the rate and power for data frame transmission in a generalized Nakagami fading channel. Different from the previous works, the CDRPA algorithm bases on the channel quality observed from the previous ACK frames and makes the selection only from the limited combinations of rate and power, instead of exhausted searching. Thus, the CDRPA algorithm greatly reduces the complexity compared to the previous approaches. Furthermore, to meat the different performance requirements, we propose several alternatives based on the CDRPA algorithm. Prom the viewpoint of energy saving, the CDRPA algorithm determines the transmit power first to maximize energy efficiency; while achieving the maximum goodput performance, the CDRPA first selects the appropriate transmit rate to ensure the successful transmissions. The numerical results show that the CDRPA algorithm can approach to the optimum performance in terms of energy efficiency and goodput while keeping the low complexity
Remote gaze estimation with a single camera based on facial-feature tracking without special calibration actions

We propose a real-time gaze estimation method based on facial-feature tracking using a single video camera that does not require any special user action for calibration. Many gaze estimation methods have been already proposed; however, most conventional gaze tracking algorithms can only be applied to experimental environments due to their complex calibration procedures and lacking of usability. In this paper, we propose a gaze estimation method that can apply to daily-life situations. Gaze directions are determined as 3D vectors connecting both the eyeball and the iris centers. Since the eyeball center and radius cannot be directly observed from images, the geometrical relationship between the eyeball centers and the facial features and eyeball radius (face/eye model) are calculated in advance. Then, the 2D positions of the eyeball centers can be determined by tracking the facial features. While conventional methods require instructing users to perform such special actions as looking at several reference points in the calibration process, the proposed method does not require such special calibration action of users and can be realized by combining 3D eye-model-based gaze estimation and circle-based algorithms for eye-model calibration. Experimental results show that the gaze estimation accuracy of the proposed method is 5° horizontally and 7° vertically. With our proposed method, various application such as gaze-communication robots, gaze-based interactive signboards, etc. that require gaze information in daily-life situations are possible.
A single-path-oriented fault-effect propagation in digital circuits considering multiple-path sensitization

Various satisfiability problems in combinational logic blocks as, for example, test pattern generation, verification, and netlist optimization, can be solved efficiently by exploiting the fundamental concepts of propagation and justification. Therefore, fault effect propagation gains further importance. For the first time, we provide the theoretical background for a single path oriented fault effect propagation considering both single and multiple path sensitization. We call this approach SPOP. Furthermore, we formulate necessary and sufficient sensitization conditions for SPOP. From these conditions the best suited algebra for propagation can be derived. Experimental results for stuck-at test pattern generation demonstrate that the new approach is orthogonal to D-frontier based methods. We achieve substantial improvements with respect to test pattern generation time and quality.
Heavy quark initiated contributions to deep inelastic structure functions

We present O(alpha_s^1) corrections to deep inelastic scattering amplitudes on massive quarks obtained within the scheme of Aivazis, Collins, Olness and Tung (ACOT). After identifying the correct subtraction term the convergence of these contributions towards the analogous coefficient functions for massless quarks, obtained within the modified minimal subtraction scheme (MSbar), is demonstrated. Furthermore, the quantitative relevance of the contributions to neutral current (NC) and charged current (CC) structure functions is investigated for several choices of the factorization scale.