Miracle-dz/UniFAR-FTUs huggingface dataset:
The Need for Control Experiments in Local Helioseismology

The key to local helioseismology is the effective application of local seismic diagnostic techniques to determine the structure of the solar interior with the finest possible resolution. The extent and magnitude of the supergranular return flow and the nature of thermal anomalies, flows, and magnetic-field configurations in and near active regions are phenomena on which we hope local helioseismic analyses will shed clear light. However, current applications of local seismic methods produce ambiguous and inconsistent interpretations. It is clear that in order to make further progress, evaluation and refinement of local analysis techniques, and the development of procedures that can separate magnetic effects, subsurface flows, and sound-speed variations will prove critical. We believe substantial progress in this area can be made by conducting control experiments based on magnetoacoustic-gravity waves propagating through specified models of subphotospheric anomalies. In this paper we describe the need for such an effort and developments currently under way to produce the tools necessary to implement a validation and testing program.
Couple Attachment and Sexual Desire Discrepancy: A Longitudinal Study of Non-Clinical Married Couples at Mid-Life

Couple Attachment and Sexual Desire Discrepancy: A Longitudinal Study of Non-Clinical Married Couples at Mid-Life Anthony A. Hughes School of Family Life, BYU Doctor of Philosophy Using latent growth curve modeling, this longitudinal study examined the patterns of the discrepancy between desired and actual frequency of sexual intercourse for 331 married couples over a period of 5 years. In addition, couple insecure attachment and control variables such as age, length of relationship, income, race, and education were used to predict each partner’s sexual desire discrepancy (SDD) and its change over the 5 year time period. Participants were asked to report their actual frequency of sexual intercourse and their desired frequency in each wave of data collection. Discrepancy scores were created for each year by subtracting the reported actual frequency from the reported desired frequency separately for wives and for husbands. In terms of change over time, findings showed a significant change across time for wives with a trend toward less discrepancy over time. Husbands’ discrepancy scores were higher than wives and remained stable over the five years. Insecure attachment predicted the average SDD for husbands. Wife income predicted the change in SDD over the five years for husbands but not for wives. Wife race predicted the average SDD for husbands. Implications for research and clinical use are highlighted.
Adaptive Robust Optimization with Scenario-wise Ambiguity Sets

We present a tractable format for optimization under uncertainty based on the framework of adaptive robust optimization via a new class of scenario-wise ambiguity sets. The new format naturally unifies classical stochastic programming and robust optimization, and also incorporates the more recent distributionally robust optimization with ambiguity sets based on generalized moments, mixture distribution, Wasserstein (or Kantorovich-Rubinstein) metric, φ-divergence, and new ones such as k-means clustering, among others. We introduce a compatible scenario-wise affine recourse approximation, which is developed on the classical affine recourse approximation (a.k.a. linear decision rule or affine policy), to provide tractable solutions to adaptive robust optimization problems. To illustrate the modeling power of this new format, we develop a new algebraic modeling package, AROMA and demonstrate how it can be used to deliver tractable solutions to adaptive robust optimization problems.
Reasons for Variations in the Levels of Efficiency in Smallholder Dairy Milk Production in Sri Lanka: A Cross Sectional Data Analysis

In the light of poverty of dairy smallholders and the inability of the Sri Lankan dairy production sector to meet the national demand for dairy milk and milk products, this study looks into why there is a variation in the levels of efficiency achieved by farmers to highlight the policy measures to combat this issue. Using a production frontier, the average levels of efficiency was found to be very low at 52% relative to the most efficient farmer in the sample. This indicates that an efficiency gain of 48% can be achieved if this problem is properly addressed. Identified reasons for this high inefficiency is discussed in detail in this article. Findings suggest that a policy on development of smallholder dairy farming would essentially incorporate the development of veterinary services and knowledge transfer in the producing areas. Keywords: Efficiency; Dairy smallholders DOI: 10.4038/jfa.v1i2. 1797 Journal of Food and Agriculture Vol.1(2) 2008 pp.30-39
Model parameters of growth curves of three meat-type lines of Japanese quail

This study was focused on a comparison of the growth characteristics and parameters of three meat-type lines of Japanese quail. The body weight data of wild-type, dotted-white and extended-brown quail lines over time were collected and fitted to Richards equation. The relevant parameters were compared based on the Confidence Interval Test. Confidence Interval Test calculates the percentages of model predictions staying in the confidence intervals of the corresponding experimental data. Both sexes of brown quails showed lower weight gains than the other two lines. Behind the inflection point a decline in the absolute growth rate was slowest for brown females. In general, Richards model parameter values showed deviations of one line from the other lines to a varying extent. Shape parameter for males (0.335-0.618) and maturation index for females (0.067-0.077) tend to be the most critical parameters. When the overall models were used to predict the weight of other lines, the models of white and wild males showed great similarity. Overall model predictions for male brown and white quails, for female brown and wild-type quails showed the largest differences. Like in males, white and wild females were the closest lines but the likeliness percentage was lower than that for males. The proposed method of parameter comparison can be a useful tool for researchers working on biological modelling.
Natural Variability in a Stable, 1000-Yr Global Coupled Climate–Carbon Cycle Simulation

Abstract A new 3D global coupled carbon–climate model is presented in the framework of the Community Climate System Model (CSM-1.4). The biogeochemical module includes explicit land water–carbon coupling, dynamic carbon allocation to leaf, root, and wood, prognostic leaf phenology, multiple soil and detrital carbon pools, oceanic iron limitation, a full ocean iron cycle, and 3D atmospheric CO2 transport. A sequential spinup strategy is utilized to minimize the coupling shock and drifts in land and ocean carbon inventories. A stable, 1000-yr control simulation [global annual mean surface temperature ±0.10 K and atmospheric CO2 ± 1.2 ppm (1σ)] is presented with no flux adjustment in either physics or biogeochemistry. The control simulation compares reasonably well against observations for key annual mean and seasonal carbon cycle metrics; regional biases in coupled model physics, however, propagate clearly into biogeochemical error patterns. Simulated interannual-to-centennial variability in atmospheric CO2.
How Well Do ‘ Facts ’ Travel ? No . 01 / 05 Transferring Technical Knowledge and Innovating in Europe , c . 1200-1800

The role of technology in the transition from premodern to modern economies in late eighteenthand nineteenth-century Europe is among the major questions in economic history, but it is still poorly understood. A plausible explanation of premodern European technological development must account for why Europe industrialised in advance of the great Asian civilisations, despite still being a comparative backwater in the twelfth century. What appears to set Western Europe apart is not that technological progress occurred at a faster rate than elsewhere, but that progress was more persistent and uninterrupted. The technical knowledge of premodern craftsmen and engineers was largely experience-based; thus, virtually all premodern technical knowledge was, and had to be, transferred in the flesh. However, the implications for premodern economic history of the basic cognitive limitations to how technical knowledge can be expressed, processed, and transmitted have yet to be examined in any detail. This paper asks how premodern European societies were able to generate incremental technical innovation under three headings: How was premodern technical knowledge stored to avoid loss? How were tacit, visual, verbal, and written means of transmission used heuristically? How was established and new knowledge transmitted? 1 The research on which this paper is based was supported by a British Academy Research Readership, a Senior Fellowship at the Dibner Institute for the History of Science and Technology, an E.S. R.C. Research Award (no. RES-000-22-0031), and a Fellowship at the Wissenschaftskolleg ZU Berlin; I am very grateful to all these institutions. I must also thank those who have heard earlier versions of this paper at Harvard University, University of Colorado (Boulder), UCLA, UBC, London (IHR), Wissenschaftskolleg zu Berlin, University of Greifswald, Cambridge University, the Economic History Association Annual Congress (2004), and at the 4 Global Economic History Conference (GEHN), Leiden. Particular thanks go to Mary Morgan and Simon Schaffer.
EXPLOITATION OF THE FULL POTENTIAL OF PERSISTENT SCATTERER INTERFEROMETRY DATA

The potential of Persistent Scatterer Interferometry (PSI) for deformation monitoring has been increasing in the last years and it will continue to do so in the short future, especially with the advent of the Sentinel-1 mission. The full exploitation of this potential requires two important components. The first one is the improvement of the PSI processing tools, to achieve massive and systematic data processing capabilities. The second one is the need to increase the capabilities to correctly analyze and interpret the PSI results. The paper addresses both components. The key features of the PSI processing chain implemented by the authors, which is named PSIG chain, are described. This is followed by a brief discussion of the key elements needed to analyse and interpret the results of a given PSI processing. The paper concludes with a description of the results obtained by processing a full frame of very high resolution TerraSAR-X data that covers the metropolitan area of Barcelona (Spain).
Multi-task Learning for Macromolecule Classification , Segmentation and Structural Recovery in Cryo-Tomography – Supplemental Document S 1 Dataset S 1 . 1 Simulated

For a persuasive assessment of the approach, we generated realistically simulated tomograms with known structures of macromolecular complexes by simulating the actual tomographic image reconstruction process. It is similar to previous works [1]. Specifically, 22 distinct macromolecular complexes (Tab. Supplementary S1) are chosen from the Protein Databank (PDB) [2] for experiments. Each simulated tomograms of 600× 600× 300 voxels contains 10000 randomly distributed macromolecular complexes with a tilt angle range ±60◦. Given the true position of these macromolecules inside tomograms, we extracted the subvolumes of 40 voxels centering on these positions as input to our model. Removing those subtomograms outside the boundary of tomograms, we finally collected 3205 simulated subtomograms of 22 structural classes for each dataset. Datasets A, B have SNR of 0.06, and 0.01 respectively. Fig. 2a shows examples of 2D slices of subtomograms extracted from a simulated tomogram.
Information needs in the Dutch long-term care sector

This research contributes to the domain of long-term care by exploring representative information needs to better manage both quality of care and financial spendings, as a first step towards mature healthcare business intelligence in long-term care. This work describes the first step as part of our more elaborate exploratory research according to the CRoss Industry Standard Process for Data Mining, wherein we perform a single case study at a long-term care institution with five locations throughout the Netherlands. We interview twenty-two domain experts and stakeholders in order to determine the information needs in long-term care from which we, then, derive the Top 10 needs using weigthed valuation calculations.
Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process‐based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological‐climate‐induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest‐based mitigation strategies and should be carefully considered within a portfolio of mitigation options.
Industrial Flame Edge Detection Algorithm Based on Gray Dominant Filter

Industrial furnace flame detection is directly related to the safety and economic operation of boiler. The flame edge detection is one of the most key parts of the flame detection. At present, there are many edge detection algorithms for normal object but few for industrial flame edge detection which cannot provide fully support for furnace flame combustion stability, flame 3D reconstruction and flame temperature field reconstruction. One new industrial flame image edge detection algorithm based on industrial flame image characteristics is proposed in this paper. This algorithm can effectively remove noise level in flame image and well maintain flame image edge features, compute the gradients from multiple-directions for entirely detecting flame edge information. Moreover, this algorithm is verified by experiment in this paper to present high performance in resisting noise, and clearly see continuous flame edge curve, which reveals better effect in industrial flame edge detection than other edge detection algorithms.
Circulating 25-Hydroxyvitamin D and Insulin Resistance in Patients with Coronary Heart Disease

Background: Coronary heart disease (CHD) is a global epidemic, insulin resistance (IR) one of the predictors of coronary heart disease. Low concentration of vitamin 25-Hydroxyvitamin D(25(OH) D) associated with IR. The aim of our study was to explore the associations between 25(OH) Dand indexes of IRamong patients with CHD.Methods: This case–control study included 100 unrelated subjects. 60 patients with CHD and 40 healthy control group. Serum 25(OH) D levels were measured using a highperformance liquid chromatography (HPLC) according to. Results: Our results revealed that diabetic patient with CHD had significantly lower values of serum 25(OH) D compared to non-diabetic group as well as control group, there were significant negative correlations between serum 25 (OH) D levels and HOMA-IRas well as other studied parameters. Receiver operating characteristic analyses (ROC) revealed thatthe cut-off value of serum 25(OH) D levels was 31.1and the AUC was 0.996. The sensitivities and the specificities were 98.3%and 75%. Conclusion:25(OH) D levels are significant low in CHD patients as well as diabeticsubgroup compared to non-diabetic group. 25(OH) D levels are strongly correlated with insulin resistance thuslow25 (OH) D could be used asmarker of insulin resistance.
Competing magnetic interactions in a spin-1/2 square lattice: Hidden order in Sr 2 VO 4

With decreasing temperature, ${\mathrm{Sr}}_{2}{\mathrm{VO}}_{4}$ undergoes two structural phase transitions, tetragonal-to-orthorhombic-to-tetragonal, without long-range magnetic order. Recent experiments suggest that only at very low temperature, ${\mathrm{Sr}}_{2}{\mathrm{VO}}_{4}$ might enter a yet-unknown phase with long-range magnetic order, but without orthorhombic distortion. By combining relativistic density functional theory with an extended spin-1/2 compass-Heisenberg model, we find an antiferromagnetic single-stripe ground state with highly competing exchange interactions, involving a non-negligible interlayer coupling, which places the system at the crossover between the XY-model and Heisenberg-model regimes. Most strikingly, we find a strong two-site ``spin-compass'' exchange anisotropy which is relieved by the orthorhombic distortion induced by the spin stripe order. Based on these results, we discuss the origin of the hidden-order phase and the possible formation of a spin liquid at low temperatures.
RUNNING HEAD: THE IAT AND SOURCE ATTRACTIVENESS AND LIKEABILITY

In two studies, participants read persuasive messages introduced by an attractive (Study 1) or likeable (Study 2) source before completing measures of implicit and explicit evaluations. The persuasive messages were in favor of an unfamiliar brand of facial soap (Study 1) and the implementation of comprehensive examinations at the participants’ university (Study 2). Results showed that persuasive messages had a stronger impact on an Implicit Association Test when the source was high in attractiveness or likeability (Study 1 and Study 2); responses on an Affect Misattribution Procedure, though in the predicted direction, were not significantly impacted by a source high in likeability (Study 2). These findings parallel those of numerous studies that, however, have looked almost exclusively at persuasion of explicit evaluations. They confirm that implicit evaluations can be changed through direct persuasive appeals and provide new information about the conditions under which persuasion of implicit evaluations can be found.
Lepton asymmetries and primordial hypermagnetic helicity evolution

The hypermagnetic helicity density at the electroweak phase transition (EWPT) exceeds many orders of magnitude the galactic magnetic helicity density. Together with previous magnetic helicity evolution calculations after the EWPT and hypermagnetic helicity conversion to the magnetic one at the EWPT, the present calculation completes the description of the evolution of this important topological feature of cosmological magnetic fields. It suggests that if the magnetic field seeding the galactic dynamo has a primordial origin, it should be substantially helical. This should be taken into account in scenarios of galactic magnetic field evolution with a cosmological seed.
Strong robust generalized cross-validation for choosing the regularization parameter

Let fλ be the Tikhonov regularized solution of a linear inverse or smoothing problem with discrete noisy data yi, i = 1, …, n. To choose λ we propose a new strong robust GCV method denoted by R1GCV that is part of a family of such methods, including the basic RGCV method. R1GCV chooses λ to be the minimizer of γV(λ) + (1 − γ)F1(λ), where V(λ) is the GCV function, F1(λ) is a certain approximate total measure of the influence of each data point on fλ with respect to the regularizing norm or seminorm, and γ ∊ (0, 1) is a robustness parameter. We show that R1GCV is less likely to choose a very small value of λ than both GCV and RGCV. RGCV and R1GCV also have good asymptotic properties for general problems with independent errors. Strengthening previous results for RGCV, it is shown that the (shifted) RGCV and R1GCV functions are consistent estimates of ‘robust risk’ functions, which place extra weight on the variance of fλ. In addition RGCV is asymptotically equivalent to the modified GCV method. The results of numerical simulations for R1GCV are consistent with the asymptotic results, and, for suitable values of γ, R1GCV is more reliable and accurate than GCV.
Why is the effect of live fuel moisture content on fire rate of spread underestimated in field experiments in shrublands?

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behaviour in laboratory experiments. However, field evidence linking LFMC to fire behaviour are very limited, despite numerous field experiments. In this study, we reanalyse a shrubland fire dataset with a special focus on LFMC to investigate this counterintuitive outcome. We found that this controversy might result from three causes. First, the range of experimental LFMC data was too moist to reveal a significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the number of fire experiments was smaller than 40. Finally, an analysis suggested that 10 to 15% measurement error – arising from the estimation of environmental variables from field measurements – could lead to an underestimation by 30% of the LFMC effect. The LFMC effect in field experiments is thus stronger than previously reported in the range of LFMC occurring during the French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behaviour to refine fire-danger predictions.
Institutional Environments and Resource Dependence: Sources of Administrative Structure in Institutions of Higher Education.

Pamela S. Tolbert Two theoretical perspectives are combined to explain the pattern of administrative offices in public and private institutions of higher education. The first perspective, resource dependence, is used to show that the need to ensure a stable flow of resources from external sources of support partially determines administrative differentiation. The second perspective, institutionalization, emphasizes the common understandings and social definitions of organizational behavior and structure considered appropriate and nonproblematic and suggests conditions under which dependency will and will not predict the number of administrative offices that manage funding relations. The results of the analyses indicate that dependence on nontraditional sources of support is a strong predictor of administrative differentiation and demonstrate the validity of integrating these two theoretical perspectives.