Miracle-dz/UniFAR-FTUs huggingface dataset:
01 12 19 1 v 2 2 1 D ec 2 00 1 Multi-trace quasi-primary fields of N = 4 SY M 4 from AdS n-point functions

We develop a recursive algorithm for the investigation of infinite sequences of quasi-primary fields obtained from chiral primary operators (CPOs) O I k (x) and eventually their derivatives by applying operator product expansions and singling out SO(6) representations, hereby proving Skiba's theorem. We show that normal products of O 2 operators can be expressed in terms of projection operators on representations of SO(20) and discuss intertwining operators for SO(6) representations. Furthermore we derive O(1 N 2) corrections to AdS/CFT 4-point functions by graphical combinatorics and finally extract anomalous dimensions by applying the method of conformal partial wave analysis.
Adaptive identification of Fuzzy Cognitive Networks

An adaptive methodology is introduced to identify the weights of a general Fuzzy Cognitive Network (FCN). The proposed scheme consists of two hierarchically structured individual identification tasks that are both implemented on-line. The inner task employs a robust integral of the sign error (RISE) observer to approximate the system's unknown nonlinearity. At the higher level, a nonlinear mapping of the observer's output provides an estimation of the linear parametrization of the FCN weights. Exploiting this fact, a standard gradient-based algorithm is proposed as an outer identification task to estimate the FCN weights under a persistence of excitation condition. Simulation results illustrate the effectiveness of the proposed approach.
Probabilistic Forecasts of Bike-Sharing Systems for Journey Planning

We study the problem of making forecasts about the future availability of bicycles in stations of a bike-sharing system (BSS). This is relevant in order to make recommendations guaranteeing that the probability that a user will be able to make a journey is sufficiently high. To do this we use probabilistic predictions obtained from a queuing theoretical time-inhomogeneous model of a BSS. The model is parametrized and successfully validated using historical data from the Vélib' BSS of the City of Paris. We develop a critique of the standard root-mean-square-error (RMSE), commonly adopted in the bike-sharing research as an index of the prediction accuracy, because it does not account for the stochasticity inherent in the real system. Instead we introduce a new metric based on scoring rules. We evaluate the average score of our model against classical predictors used in the literature. We show that these are outperformed by our model for prediction horizons of up to a few hours. We also discuss that, in general, measuring the current number of available bikes is only relevant for prediction horizons of up to few hours.
Successful high-level accumulation of fish oil omega-3 long-chain polyunsaturated fatty acids in a transgenic oilseed crop

Omega-3 (also called n-3) long-chain polyunsaturated fatty acids (≥C20; LC-PUFAs) are of considerable interest, based on clear evidence of dietary health benefits and the concurrent decline of global sources (fish oils). Generating alternative transgenic plant sources of omega-3 LC-PUFAs, i.e. eicosapentaenoic acid (20:5 n-3, EPA) and docosahexaenoic acid (22:6 n-3, DHA) has previously proved problematic. Here we describe a set of heterologous genes capable of efficiently directing synthesis of these fatty acids in the seed oil of the crop Camelina sativa, while simultaneously avoiding accumulation of undesirable intermediate fatty acids. We describe two iterations: RRes_EPA in which seeds contain EPA levels of up to 31% (mean 24%), and RRes_DHA, in which seeds accumulate up to 12% EPA and 14% DHA (mean 11% EPA and 8% DHA). These omega-3 LC-PUFA levels are equivalent to those in fish oils, and represent a sustainable, terrestrial source of these fatty acids. We also describe the distribution of these non-native fatty acids within C. sativa seed lipids, and consider these data in the context of our current understanding of acyl exchange during seed oil synthesis.
When less time is preferred: An analysis of the conceptualization and measurement of overemployment

Socioeconomic panel data indicate that numerous employees would prefer to work less, i.e. that they are overemployed. However, due to inconsistent definitions and divergent operationalizations of overemployment, integrating existing research results is challenging and implications for research and practice are difficult to draw. To advance research in this field, we present an analysis of the concept and measurement of overemployment. To analyze the concept, we proceed in two steps. In step 1, we present the range of overemployment definitions in the literature and systematize the similarities and differences in these previous conceptualizations with the aim of arriving at an adequate definition of “overemployment. ” In step 2, in view of the partial overlap between existing definitions of overemployment and other concepts used in past research, we demarcate overemployment from related concepts, identify conceptual distinctions between overemployment and other concepts and explore connections between concepts. To analyze the measurement of overemployment, we look at the bandwidth of content, measurement levels and question wording in overemployment measures and discuss the consequences of the different measures used for the overemployment rates found. We then present a consistent approach towards conceptualizing and measuring overemployment which aids future research on overemployment and similar concepts.
The Effects of Microsite (Logs versus Ground Surface) on the Presence of Forest Floor Biota in a Second-growth Hardwood Forest 1

A study conducted in forests at the University of Connecticut investigated the value of logs for biodiversity in second-growth hardwoods. Forest floor microsite (log versus featureless ground surface [soil and leaf litter only]) was significant (P < 0.001) for the frequency of occurrence of representatives of all seven broadly defined life form groups examined. Algae, non-vascular plants, and fungi were found on logs, but not on the ground. Small mammal and bird perching was noted on logs, but not on the ground. Seedlings and non-seedling vascular plants occurred on both microsites, but were found in significantly greater frequency on the ground surface.
Inhibitory Effect of the Hexane Fraction of the Ethanolic Extract of the Fruits of Pterodon pubescens Benth in Acute and Chronic Inflammation

Fruits of Pterodon pubescens Benth have been used traditionally for the treatment of rheumatism, sore throat, and respiratory disorders, and also as anti-inflammatory, analgesic, depurative, tonic, and hypoglycemic agent. The study was aimed at evaluating the anti-inflammatory activity of the hexane fraction of an ethanolic extract of P. pubescens fruits. The oil from P. pubescens fruits was extracted with ethanol and partitioned with hexane. The anti-inflammatory activity was measured with increasing doses of the hexane fraction (FHPp) by using a carrageenan-induced rat model of pleurisy and a rat model of complete Freund's adjuvant-induced arthritis by using an FHPp dose of 250 mg/kg for 21 days. Treatment with an FHPp resulted in anti-inflammatory activity in both models. The results of biochemical, hematological, and histological analyses indicated a significant decrease in glucose, cholesterol, and triglycerides levels (18.32%, 34.20%, and 41.70%, resp.) and reduction in the numbers of total leukocytes and mononuclear cells. The FHPp dose of 1000 mg/kg induced no changes in behavioral parameters, and no animal died. The results of this study extend the findings of previous reports that have shown that administration of extracts and fractions obtained from species of the genus Pterodon exhibits anti-inflammatory activity and lacks toxicity.
An Efficient BDD-Based Implementation of Gauss-Seidel for CTMC Analysis

Symbolic approaches to the analysis of Markov models, i.e. those that use BDDbased data structures, have proved to be an effective method of combating the state space explosion problem. One such example is the use of offset-labelled MTBDDs (multiterminal BDDs). However, a major disadvantage of this data structure is that it cannot be used with efficient iterative methods, in particular, Gauss-Seidel. In this paper, we propose a solution that permits the use of this numerical method by introducing a data structure derived from an offset-labelled MTBDD. This approach provides significant improvements in terms of both time and memory consumption. We present and analyse experimental results for both in-core and out-of-core versions of this implementation on a standard workstation, and successfully perform steady-state probability computation for CTMCs with as many as 600 million states and 7.7 billion transitions.
Mapping Forest Cover and Forest Cover Change with Airborne S-Band Radar

Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR) sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI) are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41) and 20 m (63% overall accuracy, κ = 0.27). The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its changes.
Use Your Powers Wisely: Resource Allocation in Parallel Channels

This study evaluates various resource allocation strategies for simultaneous estimation of two independent signals from noisy observations. We focus on strategies that make use of the underlying dynamics of each signal, exploiting the difference in estimation uncertainty between them. This evaluation is done empirically, by exploring the parameter space through computer simulations. Two cases are studied: one in which an initial allocation is maintained during estimation of the variables, and one in which allocation can be dynamically changed at each time step according to the uncertainty of the estimate from each channel. The results suggest that there are conditions in which it is advantageous to assign a high signal-to-noise ratio (SNR) to only one of the signals and guess the other one. Furthermore, comparison between the two allocation strategies shows that the dynamic strategy significantly improves estimation performance in low SNR scenarios when the signals have similar dynamics.
Assessing Workflow Ability of ERP and WfM Systems for Implementing Business Processes

Automation of a business process can be obtained by using a workflow management system or ERP system embedding workflow functionalities. The wider diffusion of ERP systems tends to favor the latter solution. There are several practical limitations of most ERP systems when automating business processes. To date, there is a lack of empirical studies aiming at achieving an evidence of these limitations. This chapter reports a study assessing the “workflow ability” of ERP systems and comparing this with that of Workflow Management Systems. Then, an empirical study was conducted regarding two different case studies. The correctness and completeness of the process models implemented using ERP and WfM systems were evaluated and analyzed
Nonlinear data assimilation in geosciences: an extremely efficient particle filter

Almost all research fields in geosciences use numerical models and observations and combine these using data‐assimilation techniques. With ever‐increasing resolution and complexity, the numerical models tend to be highly nonlinear and also observations become more complicated and their relation to the models more nonlinear. Standard data‐assimilation techniques like (ensemble) Kalman filters and variational methods like 4D‐Var rely on linearizations and are likely to fail in one way or another. Nonlinear data‐assimilation techniques are available, but are only efficient for small‐dimensional problems, hampered by the so‐called ‘curse of dimensionality’. Here we present a fully nonlinear particle filter that can be applied to higher dimensional problems by exploiting the freedom of the proposal density inherent in particle filtering. The method is illustrated for the three‐dimensional Lorenz model using three particles and the much more complex 40‐dimensional Lorenz model using 20 particles. By also applying the method to the 1000‐dimensional Lorenz model, again using only 20 particles, we demonstrate the strong scale‐invariance of the method, leading to the optimistic conjecture that the method is applicable to realistic geophysical problems. Copyright © 2010 Royal Meteorological Society
Induction of logical relations based on specific generalization of strings

Learning logical relations from examples expressed as first order facts has been studied extensively by the inductive logic programming research. Learning with positive-only data may cause over generalization of examples leading to inconsistent resulting hypotheses. A learning heuristic inferring specific generalization of strings based on unique match sequences is shown to be capable of learning predicates with string arguments. This paper describes an inductive learner based on the idea of specific generalization of strings, and the given clauses are generalized by considering the background knowledge.
Suggestions on informational teaching management construction

With the deepening teaching reform and development of informational management technology, the establishment and application of information systems management has become the inevitable requirement of vocational college teaching management. This article described the importance and necessity of informational teaching management in vocational college, analyzed the current situation and problems of informational teaching management and proposed corresponding countermeasures.
When Economic Reform is Faster than Statistical Reform: Measuring and Explaining Inequality in Rural China

Official tabulations from household survey data suggest rising income inequality in post-reform rural China, a trend of public concern. But the structural changes in China's rural economy have not been properly reflected in the methods used to process raw survey data. Using micro data from four provinces, the authors find that two-thirds of the conventionally measured increase in inequality in 1985-90 vanishes when market-based valuation methods are used and allowances are made for regional cost-of-living differences. The data revisions also suggest somewhat different explanations for rising inequality. Nonfarm income was secondary to grain production. While access to farm land was relatively equal, higher returns to land over time were inequality-increasing. But holding other factors constant, lower returns to physical capital reduced inequality over time, as did private transfers.
Neuropsychological Study of Resilience of School Graduates of the Region of Ecological Trouble

The article presents the data of neuropsychological research in the framework of a comprehensive study of the resilience of the youth population (secondary school graduates) of the region of ecological trouble – Zabajkal‘skij kraj. The authors consider resilience as a systemic characteristic of the system ‘man–life environment’. The model of resilience including psychophysiological, psychological and personal levels is offered. Standardized psychometric and neuropsychological methods are used to evaluate level’s indicators. School graduates residing in ecologically unfavorable territories identified drift of psychophysiological level in the direction of lower standards and regulatory intensity indicators of psychological and personal levels ofresilience. Using a neuropsychological approach with the aim of finding mechanisms to a reduction of the indicators of the psycho-physiological level of resilience allowed us to determine the presence of signs of deficiency of certain brain areas (posterior frontal and parietal). It was established that with the increase of degree of the ecology trouble territories of research, there is a reliable increase of mistakes ofaccomplishment by test subjects who live on them, the neuropsychological tests investigating visually spatial functions, and also functions of the serial organization of mental activity. Though there is the presence of correlations between indicators of different levels of resilience, but the rating and the explanation by virtue of their disparate data is difficult. The search for correlates, in this case, can be more aimed at proving the possibility of the existence of the proposed model of resilience, its consistency and productivity of the instruments that are used for its study. Keywords: neuropsychological study, resilience, level of resilience, ecological trouble, secondary school graduates
Intelligent decision support for road mapping a technology transfer case study with seimens corporate technology

In this paper, we describe a technology transfer case study with Siemens Corporate Technology, Systems and Engineering in Munich, Germany in which intelligent decision support was provided for road mapping of the services provided by this unit. The challenge was to provide roadmaps for optimal success in order to achieve maximum market competitiveness and customer satisfaction while simultaneously balancing the resources, business rules, risks, constraints and priorities of different stakeholders and customers around the world. The paper thus describes how ReleasePlanner, a cutting edge technology based on hybrid intelligence developed by the Laboratory for Software Engineering Decision Support at the University of Calgary was used to provide decision support. The technology transfer process and its impact at Siemens are reported.
Two Useful Bounds for Variational Inference

We review and derive two lower bounds on the expectation of the log-sum function in the context of variational inference. The first bound relies on the first-order Taylor expansion about an auxiliary parameter. The second bound relies on an auxiliary probability distribution. We show how these auxiliary parameters can be removed entirely from the model. We then discuss the advantage of keeping these parameters in certain cases, giving an example of a likelihood/prior pair for each case.
Incident Dysglycemia and Progression to Type 1 Diabetes Among Participants in the Diabetes Prevention Trial–Type 1

OBJECTIVE We studied the incidence of dysglycemia and its prediction of the development of type 1 diabetes in islet cell autoantibody (ICA)-positive individuals. In addition, we assessed whether dysglycemia was sustained. RESEARCH DESIGN AND METHODS Participants (n = 515) in the Diabetes Prevention Trial–Type 1 (DPT-1) with normal glucose tolerance who underwent periodic oral glucose tolerance tests (OGTTs) were followed for incident dysglycemia (impaired fasting glucose, impaired glucose tolerance, and/or high glucose levels at intermediate time points of OGTTs). Incident dysglycemia at the 6-month visit was assessed for type 1 diabetes prediction. RESULTS Of 515 participants with a normal baseline OGTT, 310 (60%) had at least one episode of dysglycemia over a maximum follow-up of 7 years. Dysglycemia at the 6-month visit was highly predictive of the development of type 1 diabetes, both in those aged <13 years (P < 0.001) and those aged ≥13 years (P < 0.01). Those aged <13 years with dysglycemia at the 6-month visit had a high cumulative incidence (94% estimate by 5 years). Among those who developed type 1 diabetes after a dysglycemic OGTT and who had at least two OGTTs after the dysglycemic OGTT, 33 of 64 (52%) reverted back to a normal OGTT. However, 26 (79%) of the 33 then had another dysglycemic OGTT before diagnosis. CONCLUSIONS ICA-positive individuals with normal glucose tolerance had a high incidence of dysglycemia. Incident dysglycemia in those who are ICA positive is strongly predictive of type 1 diabetes. Children with incident dysglycemia have an especially high risk. Fluctuations in and out of the dysglycemic state are not uncommon before the onset of type 1 diabetes.
Information Source Detection via Maximum A Posteriori Estimation

The problem of information source detection, whose goal is to identify the source of a piece of information from a diffusion process (e.g., computer virus, rumor, epidemic, and so on), has attracted ever-increasing attention from research community in recent years. Although various methods have been proposed, such as those based on centrality, spectral and belief propagation, the existing solutions still suffer from high time complexity and inadequate effectiveness. To this end, we revisit this problem in the paper and present a comprehensive study from the perspective of likelihood approximation. Different from many previous works, we consider both infected and uninfected nodes to estimate the likelihood for the detection. Specifically, we propose a Maximum A Posteriori (MAP) estimator to detect the information source for general graphs with rumor centrality as the prior. To further improve the efficiency, we design two approximate estimators, namely Brute Force Search Approximation (BFSA) and Greedy Search Bound Approximation (GSBA). BFSA tries to traverse the permitted permutations and directly computes the likelihood, while GSBA exploits a strategy of greedy search to find a surrogate upper bound of the probabilities of permitted permutations for a given node, and derives an approximate MAP estimator. Extensive experiments on several network data sets clearly demonstrate the effectiveness of our methods in detecting the single information source.
Calcium accumulations within the growing tips of pollen tubes

Pollen of L. longiflorum was grown in 45Ca-labeled medium and washed with nonradioactive medium. Whole, labeled pollen was then frozen and autoradiographed at -78 degrees C. The autoradiographs show striking accumulations of 45Ca in the growing tips of the pollen tubes. This result is obtained when the pollen is labeled for times as short as 1 min, or as long as 5 h. In most cases, the tip concentration is about two to four times greater than that in the bulk of the pollen tube, and extends for a length of about 20 mum. In autoradiographs of tubes longer than 1 mm, a small fraction of cells show a distinctly larger 45Ca accumulation, the tip containing more than 100 times that in the rest of the cell. The 1- to 5-h labeling experiments show that calcium is relatively concentrated within the cytoplasm of the growing tip. The 1- to 3-min labeling experiments suggest that calcium may enter the tip faster than it enters other regions. These patterns of calcium accumulation and flux may be related to the localized secretion of vesicles at the grow;ng tip.