Miracle-dz/UniFAR-FTUs huggingface dataset:
Frost matters: incorporating late-spring frost into a dynamic vegetation model regulates regional productivity dynamics in European beech forests

Abstract. Late-spring frost (LSF) is a critical factor influencing the functioning of temperate forest ecosystems. Frost damage in the form of canopy defoliation impedes the ability of trees to effectively photosynthesize, thereby reducing tree productivity. In recent decades, LSF frequency has increased across Europe, likely intensified by the effects of climate change. With increasing warming, many deciduous tree species have shifted towards earlier budburst and leaf development. The earlier start of the growing season not only facilitates forest productivity but also lengthens the period during which trees are most susceptible to LSF. Moreover, recent forest transformation efforts in Europe intended to increase forest resilience to climate change have focused on increasing the share of deciduous species in forests. To assess the ability of forests to remain productive under climate change, dynamic vegetation models (DVMs) have proven to be useful tools. Currently, however, most state-of-the-art DVMs do not model processes related to LSF and the associated impacts. Here, we present a novel LSF module for integration with the dynamic vegetation model Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS). This new model implementation, termed LPJ-GUESS-FROST, provides the ability to directly attribute simulated impacts on forest productivity dynamics to LSF. We use the example of European beech, one of the dominant deciduous species in central Europe, to demonstrate the functioning of our novel LSF module. Using a network of tree-ring observations from past frost events, we show that LPJ-GUESS-FROST can reproduce productivity reductions caused by LSF. Further, to exemplify the effects of including LSF dynamics in DVMs, we run LPJ-GUESS-FROST for a study region in southern Germany for which high-resolution climate observations are available. Here, we show that modeled LSF plays a substantial role in regulating regional net primary production (NPP) and biomass dynamics, emphasizing the need for LSF to be more widely accounted for in DVMs.
WIDER Working Paper 2014/078 Savings by and for the poor A

: The poor can and do save, but often use formal or informal instruments that have high risk, high cost, and limited functionality. This could lead to undersaving compared to a world without market or behavioural frictions. Undersaving can have important welfare consequences: variable consumption, low resilience to shocks, and foregone profitable investments. We lay out five sets of constraints that may hinder the adoption and effective usage of savings products and services by the poor: transaction costs, lack of trust and regulatory barriers, information and knowledge gaps, social constraints, and behavioural biases. We discuss each in theory, and then summarize related empirical evidence, with a focus on recent field experiments. We then put forward key open areas for research and practice.
A Time-Consistent Video Segmentation Algorithm designed for Real-Time Implementation

In this paper, we propose a time consistent video segmentation algorithm designed for real-time implementa tion. Our algorithm is based on a region merging process that combines both spatial and motion information. The spatial segmentation takes benefit of an adaptive decision rule and a specific order of merging. Our method has proven to be efficien t for the segmentation of natural images with few parameters t o be set. Temporal consistency of the segmentation is ensured by incorporating motion information through the use of an improved change detection mask. This mask is designed using both illu mination differences between frames, and region segmentat ion of the previous frame. By considering both pixel and region levels, we obtain a particularly efficient algorithm at a low computational cost, allowing its implementation in real-time on the TriMedia processor for CIF image sequences.
SIMULATION OF DRIFTING SNOW.

Abstract : Scale factors which are based on geometric, kinematic and dynamic similarity requirements are derived in order to simulate drifting snow in a wind tunnel. The scale factors related to threshold characteristics involve unknown functions that should be determined if a proper simulation of drifting is desired. The scale factors derived from the equation of motion of the particles apply to the conditions where low frequency turbulence with large eddies occurs. Further research is necessary to extend knowledge of the motion of particles in a medium where high frequency turbulence with small eddies exists. (Author)
U.S. Department of Agriculture Agricultural Research Service Mahantango Creek Watershed, Pennsylvania, United States: Physiography and history

The 420 km2 Mahantango Creek Watershed, within the Northern Appalachian Ridges and Valleys Province, is a subwatershed of the Susquehanna River, which flows to the Chesapeake Bay. Research on agricultural management and hydrologic processes controlling nonpoint source nutrient loss is conducted within a 7.3 km2 subwatershed designated WE‐38. The physical watershed description and history of monitoring and research activities contained herein and the data discussed in three companion papers are intended to facilitate the use and interpretation of archived databases on the U.S. Department of Agriculture Agricultural Research Service's Sustaining the Earth's Watersheds—Agricultural Research Data System (STEWARDS) Web site. Sources for regional geospatial data not maintained on STEWARDS are also identified.
Incorporating the Impact of Climate and Weather Variables in Impact Assessments: An Application to an IFAD Climate Change Adaptation Project in Viet Nam

The authors integrate climate variables into an IFAD project impact assessment, discussing in detail the steps taken to determine which climate variables to collect, and from which sources. The impact assessment is based on cross-section data collected ex post, and the impact assessment team carefully selected control areas to implement a propensity score matching procedure to isolate the causal impacts of the project on household-level production and livelihood outcomes. The authors show that incorporating climate variables provides important relevant information in its own right; in particular, findings show that severe saline intrusion – caused by both climate change and land and water use taking place up-and downstream – had significant effects on crop choices, as well as significant negative impacts on a wide range of production and livelihood outcomes. Thus, not including climate variables would lead to a downward bias in the impact assessment estimates, particularly for crop production. Additionally, results show that rice yields for treated households are lower than those for control households, when there is no severe saline intrusion, but are actually significantly higher under severe saline intrusion. This reveals that the project was able to increase “resilience” in the face of an extreme weather-related shock; however, previous research suggests that practices are often disadopted if yields are not also higher in “normal” years, with implications for future programme design. Finally, the paper notes that a very high proportion of the project budget was spent on supra-household-level activities to increase the performance of women’s credit cooperatives and to invest in community-level infrastructure designed to build resilience to climate change. However, the authors were unable to assess resilience benefits at those levels, as relevant data were not collected. Collecting those data will be particularly important to inform future projects that explicitly attempt to scale promising pilot projects.
A M ULTIMODAL A UTOENCODER A RCHITECTURE FOR I MAGE AND T EXT D IMENSION R EDUCTION

Analyzing video content includes processing information from both visual and audio aspects. Previous works by the research team have shown the effectiveness and efficiency of using Convolutional Variational Autoencoders (CVAE) with fully connected layers to reduce the dimension of video frames. In this report, we further extend the modality of the model by incorporating image frames and text captions of news videos. We propose another Convolutional-Recurrent Variational Autoencoder (CRVAE) structure that combines CVAE and LSTM to encode integrated video contents. We evaluate its result by clustering and analyzing the vector in lower dimensions to provide cultural affinity insights
Entorhinal cortex EWAS meta-analysis highlights four novel loci showing differential methylation in Alzheimer’s disease

Affiliations: 1. Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany 2. Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany 3. Nuffield Department of Clinical Neurosciences, Oxford Parkinson’s Disease Centre, University of Oxford, UK 4. Ageing Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK 5. Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
Empirical Spectral Acceleration Amplification in the Iwate–Miyagi and Niigata Regions, Japan, Inferred by a Spectral Ratio Method Using Ground‐Motion Prediction Equations

Abstract Using the strong ground motion dataset of M w 4.0–6.0 earthquakes in Japan from K‐NET and KiK‐net, we studied empirically the 5% damped spectral acceleration amplification for periods from 0.05 to 5 s at 75 seismic stations located in the Iwate–Miyagi and Niigata regions. The method of study is based on estimating the empirical site effect from the spectral ratio of observed and predicted ground motions based on the ground‐motion prediction equations (GMPEs). Our results show a large amplification at most analyzed stations at periods of 0.1 s and shorter; at periods of 0.3 s and longer, large amplifications generally dominate at basin stations, but deamplifications generally dominate at mountain stations. Empirical amplification factors of spectral acceleration were used to correct the observed strong ground motion data of two crustal earthquakes: the 2008 Iwate–Miyagi Nairiku earthquake ( M w 6.9) and the 2004 Chuetsu earthquake ( M w 6.6). The site‐corrected data fit better with GMPEs inferred by less standard error. We took advantage of a large body of empirical data to develop a mean empirical site‐response model for each region. These empirical models are superior to models predicted from GMPEs using only V S 30 site corrections. Those relations have shown a low correlation at short periods such as 0.1 s. We also found the relations are different for the mountain and basin stations. The method is efficient for calculating site effects at observation stations where insufficient velocity structure information and a history of earthquake recordings are available.
Plant sterols/stanols as cholesterol lowering agents: A meta-analysis of randomized controlled trials

Background Consumption of plant sterols has been reported to reduce low density lipoprotein (LDL) cholesterol concentrations by 5–15%. Factors that affect plant sterol efficacy are still to be determined. Objectives To more precisely quantify the effect of plant sterol enriched products on LDL cholesterol concentrations than what is reported previously, and to identify and quantify the effects of subjects’ characteristics, food carrier, frequency and time of intake on efficacy of plant sterols as cholesterol lowering agents. Design Fifty-nine eligible randomized clinical trials published from 1992 to 2006 were identified from five databases. Weighted mean effect sizes were calculated for net differences in LDL levels using a random effect model. Results Plant sterol containing products decreased LDL levels by 0.31 mmol/L (95% CI, –0.35 to –0.27, P= < 0.0001) compared with placebo. Between trial heterogeneity was evident (Chi-square test, P = <0.0001) indicating that the observed differences between trial results were unlikely to have been caused by chance. Reductions in LDL levels were greater in individuals with high baseline LDL levels compared with those with normal to borderline baseline LDL levels. Reductions in LDL were greater when plant sterols were incorporated into fat spreads, mayonnaise and salad dressing, milk and yoghurt comparing with other food products such as croissants and muffins, orange juice, non-fat beverages, cereal bars, and chocolate. Plant sterols consumed as a single morning dose did not have a significant effect on LDL cholesterol levels. Conclusion Plant sterol containing products reduced LDL concentrations but the reduction was related to individuals’ baseline LDL levels, food carrier, and frequency and time of intake.
Modular design of a gas mixing apparatus for complex trace gas mixtures

Volatile organic compounds (VOCs) found in our environment can lead to reduced cognitive functions or serious health problems at elevated concentrations [1]. Their sources are manifold and range from the human metabolism to human activities such as cooking, heating, and cleaning, to emissions from furnishings, hygiene articles and building materials [2]. With the gold standard gas chromatography–mass spectrometry (GC-MS) being too expensive for consumer applications and not real-time capable, cost effective real-time measurement of these substances is possible by using metal oxide semiconductor (MOS) gas sensors combined with dynamic operation [3]. However, to make full use of the increased selectivity, the MOS sensor systems must be calibrated with application-specific complex gas mixtures. For this calibration, a gas mixing apparatus (GMA) is needed to produce well-defined, adjustable, and reproducible gas mixtures. Since more than 300 different VOCs are found in indoor air [4], creating an exact replicate of indoor air or similar complex atmospheres is not feasible. This contribution describes the design and realization of a GMA being able to provide sufficiently complex and representative, yet still manageable VOCs mixtures also with realistic atmospheric background of humidity and inorganic gases.
Further Observations upon Hyperodapedon Gordoni.

It is now twenty-nine years since, in describing those remains of Stagonolepis Robertsoni from the Elgin Sandstones which enabled me to determine the reptilian nature and the crocodilian affinities of that supposed fish, I indicated the occurrence in the same beds of a Lacertilian reptile, to which I gave the name of Hyperodapedon Gordoni. I laid stress upon the “marked affinity with certain Triassic reptiles” (e. g. Rhynchosaurus) of Hyperodapedon, and I said that these, “when taken together with the resemblance of Stagonolepis to Mesozoic Crocodilia,” led me “to require the strongest stratigraphical proof before admitting the Palæozoic age of the beds in which it occurs”. Many Fellows of the Society will remember the prolonged discussions which took place, in the course of the ensuing ten or twelve years, before the Mesozoic age of the reptiliferous sandstones of Elgin was universally admitted. Hyperodapedon was destined to play no inconsiderable part in the controversy. Some ten years after the discovery of the original specimen, remains referable to the same genus were found in strata of unquestionably Triassic age in Central and Southern England; and, about the same time, I received abundant evidence of the occurrence of Hyperodapedon, associated with Dicynodonts, Crocodilia, and Labyrinthodonts, in certain Indian rocks which, on other grounds, were strongly suspected to belong to the oldest Mesozoic series. An account of these new materials, together with a full description of the original specimen of Hyperodapedon, was read before the Society and published in the ‘Quarterly Journal’ for 1869.
Does Equity Finance Improve Entrepreneurship Potency of Financial Sector Development?

Purpose: This study is exploring the holistic quadratic financial market development effect on entrepreneurship at the macroeconomic level and assesses the contrast of patterns because of the increase in the share of Islamic equity financing as a risk-sharing instrument. Method: An unbalanced panel data is acquired for selected Islamic banks of 21 nations to estimate Panel Quantile Regression (PQR) measuring the curvilinear financial market development effect and moderating role of Islamic equity financing in explaining the macroeconomic entrepreneurship index. Results: The results show that higher equity financing dissipates the debt burden of financing by sharing risks, thus motivating entrepreneurship at a macroeconomic level. Implications: Central Banks and Islamic advisory boards regulating banking systems innovate to integrate and increase equity based financial instruments as a financial inclusion policy in promoting a risk-sharing entrepreneurial ecosystem.
Laboratory reproduction of arecibo experimental results: HF wave‐enhanced Langmuir waves

Laboratory experiments at MIT using the Versatile Toroidal Facility (VTF) have produced “cascading” and “frequency‐upshifted” spectra of HF wave‐enhanced Langmuir waves resembling the spectra observed in Arecibo experiments. The VTF experiments are well‐explained using the source mechanism proposed by Kuo and Lee [1992] to interpret observed Langmuir wave spectra at Arecibo, Puerto Rico. This mechanism is referred to as a nonlinear scattering of parametric decay instability (PDI)‐excited Langmuir waves by “pre‐existing” lower hybrid waves to preferentially produce anti‐Stokes (i.e., frequency‐upshifted) Langmuir waves. Recent radar spectral observations of anti‐Stokes Langmuir waves at Arecibo with improved range and time resolution [Sulzer and Fejer, 1994] can be reasonably understood in terms of this mechanism.
Machine Learning For Credit Card Fraud Detection System

The quick growth of the e-commerce industry led to an exponential growth in credit card online purchases, resulting in an increase in fraud. Banks have become increasingly important in recent years. Fraud in the credit card system is difficult to identify. In order to detect credit card fraud, machine learning is used for the business transactions. Banks utilise various machine learning approaches to forecast these transactions; historical data has been collected, and new characteristics have been added to improve accuracy. The ability to predict the detection of fraud performance in the sampling has a significant impact on credit card transactions. Using this method we can data-set, variable selection, and detection utilised techniques. To balance the data set, we have used oversampling, which resulted in 60% of fraudulent transactions and 40% of legitimate transactions. These three are techniques that are used for the dataset, and to complete the work. Implementation is done using the R programming language. The effectiveness of the methods is evaluated on the basis of sensitivity, specificity, precision and error rate for different variables. The logistic regression, decision tree and random forestry classifications are respectively 90.0, 94.3 and 95.5. The Random forest outperforms the logistic regression and decision tree procedures, according to the results.
Numerical solutions for dispersion in porous mediums

A numerical method is presented for the solution of problems of dispersion in steady three-dimensional potential flow fields in porous mediums, in which the miscible fluids have the same density and viscosity. The method is developed and tested for two-dimensional problems, and the extension to three dimensions is presented. Emphasis is put on the efficiency of the numerical scheme and on its generality. It is shown to be independent of the geometry of the flow field. The computer program for carrying out the computations as described is tested with simple problems, for which exact or approximate analytical solutions exist. It is also used to obtain solutions to a few problems for which no other solution is known. (Key words: Dispersion; porous mediums; groundwater; pollution)
Shifted-elliptical nonstretch moveout correction of wide-angle seismic data in the τ-p domain, using an example from the Faeroe-Shetland Basin

ABSTRACTWe developed a method of moveout correction in the τ-p domain to tackle some of the problems associated with processing wide-angle seismic reflection data, including residual moveout and normal-moveout stretching. We evaluated the concept of the shifted ellipse in the τ-p domain as an alternative to the well-known concept of the shifted hyperbola in the t-x domain. We used this shifted-ellipse concept to address the problem of residual moveout caused by vertical heterogeneity in the subsurface. We also addressed the stretching problem associated with dynamic corrections by combining selected strips from a set of constant-moveout stacks generated using a shifted-ellipse equation. Application of this method to a wide-angle data set from the Faeroe-Shetland Basin provided an enhanced image of the subbasalt structure.
Metabolik Sendrom ve İnflamatuar İndikatörler

Objective: The combination of a number of metabolic abnormalities such as high body mass index (BMI), central obesity, low high-density lipoprotein (HDL), high triglycerides, high blood pressure, and hyperglycemia is defined as metabolic syndrome (MetS). This study aimed to clarify the effect of metabolic syndrome components on joint degeneration and investigate the relationship between systemic inflammatory response and end-stage osteoarthritis clinical course. Material and Methods: Fifty-seven patients, who underwent total knee arthroplasty due to primary knee osteoarthritis, were classified according to metabolic syndrome diagnosis criteria. Their medial and lateral tibial plateau specimens were graded histopathologically according to Osteoarthritis Research Society International scoring system (OARSI). Results: 33 patients were performed right total arthroplasty (57.9%), 24 were performed left (42.1%). The mean age was 68.46 ± 6.88 (range 57 to 85). The mean BMI value was 30.31 ± 5.26 (range 20.2 to 48). According to the International Diabetes Foundation (IDF) 2005 metabolic syndrome (MetS) diagnostic criteria; 31.5% (n = 18) of the patients did not have MetS, while 68.4% (n = 39) had. There was no statistically significant relationship between tibial plateau OARSI scores and metabolic syndrome (p> 0.05). Besides, these OARSI scores and the operation side, hypertension, and BMI had no statistically significant relationship (p> 0.05). Conclusions: Metabolic syndrome components may play a role in initiating the osteoarthritic process via adipokines, but we could not identify certain effects of pro-inflammatory mediator components on tibial plateau cartilage degeneration with histopathological scores till end-stage arthritic progress.
Estimating China’s Capital Flows-at-risk: The Case of Potential US Financial Sanctions †

The arena of strategic competition between the US and China is expandable from international politics, trade and commerce to finance. What would happen if financial sanctions against China are imposed by the US? Would US financial sanctions lead to a sudden outflow of foreign capital and a liquidity crisis in China? We try to address these questions by estimating China’s capital flows-at-risk with the CDS premium on Chinese sovereign funds. We follow Gelos et al. (2019) in setting up a quantile regression model from which China’s foreign capital flow-at-risks are estimated. Based on our analysis of China’s monthly capital flow data, we find that a rise in the CDS premium has statistically significant negative impacts on China’s foreign capital flows-at-risk, mainly in banking flows. However, the analysis also found that due to favorable global conditions, an increase in the CDS premium is unlikely to trigger a shift to a sudden outflow of foreign capital at the moment. Meanwhile, this study found no statistically significant correlation between Korea’s capital flows-at-risk and the CDS premium, suggesting that the negative impact of US financial sanctions on China would not increase the probability of capital flight from Korea in a significant manner.