Miracle-dz/UniFAR-FTUs huggingface dataset:
Diel cycles in dissolved metal concentrations in streams: Occurrence and possible causes

Substantial diel (24‐hour) cycles in dissolved (0.1‐μm filtration) metal concentrations were observed during low flow for 18 sampling episodes at 14 sites on 12 neutral and alkaline streams draining historical mining areas in Montana and Idaho. At some sites, concentrations of Cd, Mn, Ni, and Zn increased as much as 119, 306, 167, and 500%, respectively, from afternoon minimum values to maximum values shortly after sunrise. Arsenic concentrations exhibited the inverse temporal pattern with increases of up to 54%. Variations in Cu concentrations were small and inconsistent. Diel metal cycles are widespread and persistent, occur over a wide range of metal concentrations, and likely are caused primarily by instream geochemical processes. Adsorption is the only process that can explain the inverse temporal patterns of As and the divalent metals. Diel metal cycles have important implications for many types of water‐quality studies and for understanding trace‐metal mobility.
Results of the 1998 Ny‐Ålesund Ozone Monitoring Intercomparison

The Ny-Alesund Ozone Monitoring Intercomparison (NAOMI) took place at Ny-Alesund,Spitsbergen (78.92 degrees N, 11.95 degrees E), from January 20 to February 10, 1998.This paper focuses on comparing stratospheric ozone profiles measured by the Alfred WegenerInstitute differential absorption lidar (AWI DIAL), in routine Network for Detection ofStratospheric Change (NDSC) operation at Ny-Alesund, the mobile Goddard Space Flight CenterDIAL (GSFC DIAL), the University of Bremen microwave radiometer (mu Wave), andelectrochemical concentration cell (ECC) ozonesondes, flown routinely by AWI. Below 30 km thetwo DIALs and the ECC sondes give virtually the same results, with instrumental precision(repeatability) better than +/-5% and no detectable bias. When their coarser altitude resolution isnot accounted for, the mu Wave data show 15% low bias at 16 km and 15% high bias at 23 km,Considerably better agreement, better than +/-5% around 20 km and above 30 km, is found whenthe altitude resolution of the other data is degraded to match that of the mu Wave. During NAOMIthe mu Wave data show high bias of up to 10% in a mixing ratio plateau around 25 km. Such biashas not been seen in routine intercomparisons between mu Wave and ECC sonde data atNy-Alesund. It is likely caused by an a priori profile 40% higher than the true profile duringNAOMI, Above 30 km the mu Wave data show the best precision (repeatability), about +/-3 to+/-5%. Precision of the GSFC DIAL data decreases from better than +/-5% at 30 km to about+/-10% at 40 km, and the precision for the AWI DIAL data decreases from better than +/-5% at30 km to +/-30% at 40 km. From 34 to 38 km the AWI profile is 12% lower than the GSFCprofile. AWI DIAL measurements that are low at 35 km often end below 40 km of show highvalues at 40 or 45 km, This behavior seems related to the way in which the AWI processingalgorithm changes altitude resolution for data with poor signal-to-noise ratio.
Can Exchange Rates Forecast Commodity Prices

This paper studies the dynamic relationship between exchange rate fluctuations and world commodity price movements. Taking into account parameter instability, we demonstrate surprisingly robust evidence that exchange rates predict world commodity price movements, both in-sample and out-of-sample. Our results are consistent with a present value relationship in which the exchange rate depends on a present value of fundamentals including, for a core group of commodity exporters, the world price of their commodity exports. Because global commodity prices are essentially exogenous to these countries, we are able to avoid the endogeneity pitfalls that plague most of the related exchange rate literature. More directly, the analysis suggests that where commodity price forward markets are thin or non-existent, exchange rate-based forecasts may be a viable alternative for predicting future price movements.
Cognitive Multiple-Antenna Network with Outage and Rate Margins at the Primary System

This paper investigates the problem of spectrally efﬁcient operation of a multiuser uplink cognitive radio system in the presence of a single primary link. The secondary system applies opportunistic interference cancelation (OIC) and decode the primary signal when such an opportunity is created. We derive the achievable rate in the secondary system when OIC is used. This scheme has a practical signiﬁcance, since it enables rate adaptation without requiring any action from the primary system. The exact expressions for outage probability of the primary user are derived, when the primary system is exposed to interference from secondary users. Moreover, approximated formulas and tight lower and upper bounds for the ergodic sum-rate capacity of the secondary network are found. Next, the power allocation is investigated in the secondary system for maximizing the sum-rate under an outage constraint at the primary system. We formulate the power optimization problem in various scenarios depending on the availability of channel state information and the type of power constraints, and propose a set of simple solutions. Finally, the analytical results are conﬁrmed by simulations, indicating both the accuracy of the analysis
Physical controls on carbon dioxide transfer velocity and flux in low‐gradient river systems and implications for regional carbon budgets

[1] Outgassing of carbon dioxide (CO2) from rivers and streams to the atmosphere is a major loss term in the coupled terrestrial-aquatic carbon cycle of major low-gradient river systems (the term “river system” encompasses the rivers and streams of all sizes that compose the drainage network in a river basin). However, the magnitude and controls on this important carbon flux are not well quantified. We measured carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) in rivers and streams of the Amazon and Mekong river systems in South America and Southeast Asia, respectively. FCO2 and k values were significantly higher in small rivers and streams (channels 100 m wide). Small rivers and streams also had substantially higher variability in k values than large rivers. Observed FCO2 and k values suggest that previous estimates of basinwide CO2 evasion from tropical rivers and wetlands have been conservative and are likely to be revised upward substantially in the future. Data from the present study combined with data compiled from the literature collectively suggest that the physical control of gas exchange velocities and fluxes in low-gradient river systems makes a transition from the dominance of wind control at the largest spatial scales (in estuaries and river mainstems) toward increasing importance of water current velocity and depth at progressively smaller channel dimensions upstream. These results highlight the importance of incorporating scale-appropriate k values into basinwide models of whole ecosystem carbon balance.
UNIX Disk Access Patterns

Disk access patterns are becoming ever more important to understand as the gap between processor and disk performance increases. The study presented here is a detailed characterization of every lowlevel disk access generated by three quite different systems over a two month period. The contributions of this paper are the detailed information we provide about the disk accesses on these systems (many of our results are significantly different from those reported in the literature, which provide summary data only for file-level access on small-memory systems); and the analysis of a set of optimizations that could be applied at the disk level to improve performance. Our traces show that the majority of all operations are writes; disk accesses are rarely sequential; 25‐ 50% of all accesses are asynchronous; only 13‐41% of accesses are to user data (the rest result from swapping, metadata, and program execution); and I/O activity is very bursty: mean request queue lengths seen by an incoming request range from 1.7 to 8.9 (1.2‐1.9 for reads, 2.0‐14.8 for writes), while we saw 95th percentile queue lengths as large as 89 entries, and maxima of over 1000. Using a simulator to analyze the effect of write caching at the disk level, we found that using a small non-volatile cache at each disk allowed writes to be serviced considerably faster than with a regular disk. In particular, short bursts of writes go much faster ‐ and such bursts are common: writes rarely come singly. Adding even 8 KB of non-volatile memory per disk could reduce disk traffic by 10‐ 18%, and 90% of metadata write traffic can be absorbed with as little as 0.2 MB per disk of nonvolatile RAM. Even 128KB of NVRAM cache in each disk can improve write performance by as much as a factor of three. FCFS scheduling for the cached writes gave better performance than a more advanced technique at small cache sizes. Our results provide quantitative input to people investigating improved file system designs (such as log-based ones), as well as to I/O subsystem and disk controller designers.
TULIP 5

data visualization. The second package is a complete OpenGL rendering engine ( Tulip OGL ) tailored for information visualization techniques. The third package is a library of GUI components created using the Qt library ( Tulip GUI ). The fourth package is a complete binding of the C++ API to Python. It makes the usage of Tulip inside Python code straightforward. Finally, Tulip software is an application where users can embed their algorithm, visualization technique, or complete information visualization pipeline. Figure 2 summarized the connections between these diﬀerent libraries.
No boundaries for whales interacting with fishing activities targeting Patagonian toothfish ( Dissostichus eleginoides )

With the development of longlines targeting Patagonian toothfish (Dissostichus eleginoides), killer and sperm whale have adapted their preying behaviour by feeding on fish caught on the gear. Estimating depredation rates allows to correct catches and model the real impact of fishing activities on Patagonian toothfish stocks. Depredation has been documented as a severe issue in the fishery of Crozet EEZ since the late 90’s. The recent development of fishing activities in waters adjacent to the CCAMLR convention area such as in the Del Cano rise (Southern Indian Ocean Fisheries Agreement, SIOFA) might enhance the risk of spreading this feeding behavior to new pods. Photo-identification technique revealed movements of sperm whales and killer whales individuals across boundaries. Over the 2009 – 2019 period, depredation rates were estimated to be around 8% in the Del Cano – SIOFA area based on the available data from France and Spain.
Posibles huellas de crías de terópodo en el yacimiento de Valdehijuelos (Soria, España)

The Valdehijuelos tracksite (Soria, Spain) has provided, in several isolated plaques, a significant number of tiny theropod footprints, between others with bigger size. The associated morphometric characteristics and relationships make them different from those of Grallator, Anchisauripus and Eubrontes ichnogenus, whose morphology is relatively similar and whose size, in some cases (Grallator), is also small. However, they appear to be quite similar to the big tracks around so it could be supposed to be the baby of the big trackmakers.
Increasing the efficiency and accuracy of collective intelligence methods for image classification

Collective intelligence has emerged as a powerful methodology for annotating and classifying challenging data that pose difficulties for automated classifiers. It works by leveraging the concept of “wisdom of the crowds” which approximates a ground truth after aggregating experts’ feedback and filtering out noise. However, challenges arise when certain applications, such as medical image classification, security threat detection, and financial fraud detection, demand accurate and reliable data annotation. The unreliability of experts due to inconsistent expertise and competencies, coupled with the associated cost and time-consuming judgment extraction, presents additional challenges. Input aggregation is the process of consolidating and combining multiple individual judgments, feedback, or annotations obtained from a diverse group of experts to arrive at a single representative decision or prediction. In this dissertation, we introduce diverse deep learning techniques to enhance the accuracy of input aggregation methods and optimize task assignments among experts. We demonstrate that incorporating the outputs of an automated classifier as additional features improves traditional input aggregation methods. We also show that the accuracy of these methods can be further improved by adding meaningful image features learned by self-supervised models. The additional features reduce the requirements of collecting a large number of inputs from human labelers. We also investigate how task assignments can be optimized for groups of experts that possess varying degrees of expertise and diverse competency areas. We show that experts’ competencies and samples’ complexity can be modeled simultaneously and that optimization algorithms can leverage deep learning models to perform an optimal selection of experts. To train and evaluate the deep learning models, we propose a novel algorithm for generating a large dataset of synthetic X-ray images. The dataset works as a test bed for conducting comprehensive testing and validation of our proposed methodologies.
Mechanism of offshore nutrient supply in the western Arabian Sea

The mechanism to maintain the high surface chlorophyll in the western Arabian Sea during the southwest monsoon (SWM) season is studied with an eddy-permitting, biological-physical coupled model. Using a set of artificial tracers, it is revealed that horizontal transport of nutrient subsequent to the coastal upwelling is by far more important than the open ocean upwelling due to the Ekman pumping. The horizontal transport can be classified into three processes, the Ekman transport, transport by the large-scale circulation and that by the mesoscale currents. In the model, the first has only a minor effect within the area of high chlorophyll while the latter two have comparable contributions. Considering the fact that simulated eddy activity is still less than observed by satellites, it may be possible to make the model results more realistic by assimilating sea-surface height data or running a finer resolution model.
Fabricable Tile Decors

Recent advances in 3D printing have made it easier to manufacture customi- zed objects by ordinary users in an affordable manner, and therefore spurred high demand for more accessible methods for designing and fabricating 3D objects of various shapes and functionalities. In this paper we present a novel approach to model and fabricate surface-like objects composed of connected tiles, which can be used as objects in daily life, such as ornaments, covers, shades or handbags. Our method is designed to maximize the efficiency and ease of fabrication. Given a base surface and a set of tile elements as user input, our method generates a tight packing of connected tiles on the surface. We surfaces, such as a handbag and a teddy bear. Several user controls are available, to distribute different type of tiles over the surface and locally change their scales and orientations.
Methods for identification of isolated carbonate buildups from seismic reflection data

Isolated carbonate buildups (ICBs) are commonly attractive exploration targets. However, identifying ICBs based only on seismic data can be difficult for a variety of reasons. These include poor-quality two-dimensional data and a basic similarity between ICBs and other features such as volcanoes, erosional remnants, and tilted fault blocks. To address these difficulties and develop reliable methods to identify ICBs, 234 seismic images were analyzed. The images included proven ICBs and other features, such as folds, volcanoes, and basement highs, which may appear similar to ICBs when imaged in seismic data. From this analysis, 18 identification criteria were derived to distinguish ICBs from non-ICB features. These criteria can be grouped into four categories: regional constraints, analysis of basic seismic geometries, analysis of geophysical details, and finer-scale seismic geometries. Systematically assessing the criteria is useful because it requires critical evaluation of the evidence present in the available data, working from the large-scale regional geology to the fine details of seismic response. It is also useful to summarize the criteria as a numerical score to facilitate comparison between different examples and different classes of ICBs and non-ICBs. Our analysis of scores of different classes of features suggests that the criteria do have some discriminatory power, but significant challenges remain.
Development of a new laser triangulation system based on an optical frame of reference

In this paper a new triangulation‐based laser scanner is presented which has a simple, yet strong, flexible and low‐cost structure. A digital camera and three laser line projectors are the main components of the system. One of the laser projectors is positioned vertically, while the other two are horizontal. The former scans the object, whereas the latter two establish an optical frame which is used, in part, to define the plane containing the vertical laser projector at each step of scanning. At each step, an image is taken which includes the object along with the projected laser lines. By intersecting the vertical and horizontal lines a couple of points are formed which, along with the calibration information of the system, enable the extraction of the object coordinates. Results of the tests carried out show that by using an optical frame of this nature, the process of scanning is greatly facilitated. That is, the scanner can easily be used to scan objects of different size and dimensions. Within the current configuration, the system enables measurements with an accuracy of 1/1600. Also, as the system has a rigorous basis, its accuracy can be increased if improved hardware is provided.
Exploring Factors Relevant to the Benefit and Use of Retrieval Practice

iii Abbreviations . v Sammanfattning på svenska . vi List of papers . ix Introduction . 1 Background . 4 Memory and learning . 4 How are memories formed and stored? 5 Retrieval practice . 6 Overview of the research field . 6 Theoretical explanations for the testing effect . 9 Use of retrieval practice . 13 Individual differences and retrieval practice . 14 Cognitive factors and retrieval practice . 15 Non-cognitive factors and retrieval practice . 17 Aim of the thesis . 20 Study I . 20 Study II . 20 Study III . 20 Materials and Methods . 21 The measurement of psychological constructs. 21 Measures . 21 Working Memory Capacity (WMC) . 21 Fluid intelligence . 22 Need for Cognition . 22 Grit. 22 Conscientiousness and Openness to Experience . 23 Study design . 23 Studies I & II . 23 Study III . 26 Learning materials. 27 Studies I & II . 27
Genome-wide identi�cation of the 14-3-3 gene family and its participation in �oral transition by interacting with TFL1/FT in Apple

Background: Apple (Malus domestica Borkh.) is a popular cultivated fruit crop with high economic value in China. Apple �oral transition is an important process but liable to be affected by various environmental factors. The 14-3-3 proteins are involved in regulating diverse biological processes in plants, and some 14-3-3 members play vital roles in �owering. However, little information was available about the 14-3-3 members in apple. Results: In the current study, we identi�ed eighteen 14-3-3 gene family members from the apple genome database, designated MdGF14a to MdGF14r. The isoforms possess a conserved core region comprising nine antiparallel α-helices and divergent N and C termini. According to their structural and phylogenetic features, Md14-3-3 proteins could be classi�ed into two major evolutionary branches, the epsilon ((cid:0)) group and the non-epsilon (non-(cid:0)) group. Moreover, expression pro�les derived from transcriptome data and quantitative real-time reverse transcription PCR analysis showed diverse expression patterns of Md14-3-3 genes in various tissues and in response to different sugars and hormone treatments during the �oral transition phase. Four Md14 ‐ 3-3 isoforms (MdGF14a, MdGF14d, MdGF14i, and MdGF14j) exhibiting prominent transcriptional responses to sugars and hormones were selected for further investigation. Furthermore, yeast two-hybrid and bimolecular �uorescence complementation experiments showed that the four Md14-3-3 proteins interact with key �oral integrators, MdTFL1 (TERMINAL FLOWER1) and MdFT (FLOWERING LOCUS T). Subcellular localization of four selected Md14-3-3 proteins demonstrated their localization in both the cytoplasm and nucleus. Conclusion: We identi�ed the Md14-3-3s family in apple comprehensively. Certain Md14-3-3 genes are expressed predominantly during the apple �oral transition stage, and may participate in the regulation of �owering through association with �ower control genes. Our results provide a preliminary framework for further investigation into the roles of Md14-3-3s in �oral transition.
Predicting Stock Price Direction for Asian Small Caps with Machine Learning Methods

Portfolio managers have a great interest in detecting high-performing stocks early on. Detecting outperforming stocks has for long been of interest from a research as well as financial point of view. Quantitative methods to predict stock movements have been widely studied in diverse contexts, where some present promising results. The quantitative algorithms for such prediction models can be, to name a few, support vector machines, tree-based methods, and regression models, where each one can carry di↵erent predictive power. Most previous research focuses on indices such as S&P 500 or large-cap stocks, while smalland micro-cap stocks have been examined to a lesser extent. These types of stocks also commonly share the characteristic of high volatility, with prospects that can be di cult to assess. This study examines to which extent widely studied quantitative methods such as random forest, support vector machine, and logistic regression can produce accurate predictions of stock price directions on a quarterly and yearly basis. The problem is modeled as a binary classification task, where the aim is to predict whether a stock achieves a return above or below a benchmark index. The focus lies on Asian smalland micro-cap stocks. The study concludes that the random forest method for a binary yearly prediction produces the highest accuracy of 69.64%, where all three models produced higher accuracy than a binary quarterly prediction. Although the statistical power of the models can be ruled adequate, more extensive studies are desirable to examine whether other models or variables can increase the prediction accuracy for smalland micro-cap stocks.
Finite Element Heterogeneous Multiscale Methods with Near Optimal Computational Complexity

This paper is concerned with a numerical method for multiscale elliptic problems. Using the framework of the heterogeneous multiscale methods (HMM), we propose a micro-macro approach which combines the finite element method (FEM) for the macroscopic solver and the pseudospectral method for the microsolver. Unlike the micro-macro methods based on the standard FEM proposed so far, in the HMM we obtain, for periodic homogenization problems, a method that has almost-linear complexity in the number of degrees of freedom of the discretization of the macro- (slow) variable.