Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Ecosystem Service Function of Baiyangdian Wetland in Anxin County

Wetland has multi-functions of unique ecosystem.Its importance is to provide foods and other raw materials for industrial and agricultural production to the human.The most importance is that it has supported and kept the life support system of the earth.The evaluation on its ecological service function can provide scientific basis for management and wetland protection.Taking Baiyangdian Wetland in Anxin County of Hebei Province as a study object,the paper conducts value estimation of the ecological service function of the wetland.The results show that water conservation,flood and waterlog retarding,diversion and regulation are the most important functions of the wetland.It should be deliberation during the development and utilization and reasonably planned,otherwise the exertion of ecological service function of the wetland would be effected.
Estimating saturated hydraulic conductivity for southeastern soils using decision tree analysis

Pedotransfer functions (PTFs) are used to predict saturated hydraulic conductivity (Ks) from more easily measured soil properties. Our objective was to determine if soil morphology was an important factor in predicting Ks using PTFs. We used soil profile descriptions for nine soils from the S-124 regional project dataset describing soils of the southeastern United States. Our best decision-tree model predicted log10 Ks (cm day -1 ) with an average log10 root mean square residual (RMSR) of 0.8017. The best models used bulk density and texture but not soil morphological descriptors. Sand textural class predicted the highest Ks. For the finer textured soils, the splits were based on bulk density. The NRCS method predicted Ks with a RMSR of 0.9562. Morphological descriptors of soil structure may not have been important because bulk density acted as a surrogate for structure. INDEX WORDS: Regression tees, saturated hydraulic conductivity, soil structure ESTIMATING SATURATED HYDRAULIC CONDUCTIVITY FOR SOUTHEASTERN SOILS USING DECISION TREE ANALYSIS
Phytoremediation of vaname shrimp (Litopenaeus vannamei) wastewater using vetiver grass system (Chrysopogon zizanioides, L) in flow water surface-constructed wetland

One of the negative impacts of vaname shrimp (Litopenaeus vannamei) cultivation activities is the deterioration of water quality in rivers and coastal waters that functioned as a source of water for L. vannamei cultivation and other activities. This condition brings the need to treat the wastewater to restore the water quality. The study was focused on the evaluation of the ability of phytoremediation of vetiver grass (Chrysopogon zizanioides, L) in removing pollutants (NH4+, NO3and PO43-) from the wastewater of L. vannamei. The results show that the vetiver grass can grow in mesohaline conditions and can perform phytoremediation for NH4, NO3, and PO43pollutants. The planting treatment of emergent and hidrophonic do not show significant difference in their ability of reducing pollutants. The growth of vetiver grass is determined more by the increasing age of the grass and is not affected by mesohaline’s salinity.
Watershed flow paths and stream water nitrogen‐to‐phosphorus ratios under simulated precipitation regimes

Stream water nitrogen‐to‐phosphorus (N:P) ratios influence algal community composition and nutrient limitation in lotic ecosystems. N:P ratios trend across climates, with low stream water N:P ratios more common in arid climates, yet little is known about mechanisms that cause this spatial and temporal variation. This study evaluates the relationship between precipitation regime (mean annual precipitation and its frequency), watershed flow pathways, and stream water total N‐to‐total P (TN:TP) ratios, using a model based on a central Minnesota watershed. The purpose of the study was to examine hydrologic mechanisms that control stream water TN:TP ratios. We constructed a model that accounted for hydrological and biogeochemical processes, followed by 161 simulations under a wide range of precipitation frequency and intensity scenarios. Precipitation regime controlled total runoff and subsurface hydrologic connectivity, which had implications for TN and TP concentrations and TN:TP ratios. Results supported the hypothesis that watershed hydrology is an important control on stream water TN:TP ratios and suggested that variation of flow pathways can lead to fundamental changes of N:P ratios.
Temporality foundations impacting the speed of change in digital transformation

Digital transformation (DT) refers to changes to organizational properties that are shaped by the application of digital technologies. Extant studies on DT have largely focused on which properties are changed and the extent of the changes. Not much attention has been paid to the temporality dimensions of DT. This paper suggests that the number of properties impacted, the level of an organization’s digital technology capability, and the order in which changes are implemented may influence the speed of DT. Additionally, this paper also points out that the strength of the interdependencies among organization properties can also affect the duration of DT. The implications of the study are also discussed.
A Study on Co-movements and Information Spillover Effects Between the International Commodity Futures Markets and the South Korean Stock Markets: Comparison of the COVID-19 and 2008 Financial Crises

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co- movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.
Rethinking Object Saliency Ranking: A Novel Whole-Flow Processing Paradigm

Existing salient object detection methods are capable of predicting binary maps that highlight visually salient regions. However, these methods are limited in their ability to differentiate the relative importance of multiple objects and the relationships among them, which can lead to errors and reduced accuracy in downstream tasks that depend on the relative importance of multiple objects. To conquer, this paper proposes a new paradigm for saliency ranking, which aims to completely focus on ranking salient objects by their “importance order”. While previous works have shown promising performance, they still face ill-posed problems. First, the saliency ranking ground truth (GT) orders generation methods are unreasonable since determining the correct ranking order is not well-defined, resulting in false alarms. Second, training a ranking model remains challenging because most saliency ranking methods follow the multi-task paradigm, leading to conflicts and trade-offs among different tasks. Third, existing regression-based saliency ranking methods are complex for saliency ranking models due to their reliance on instance mask-based saliency ranking orders. These methods require a significant amount of data to perform accurately and can be challenging to implement effectively. To solve these problems, this paper conducts an in-depth analysis of the causes and proposes a whole-flow processing paradigm of saliency ranking task from the perspective of “GT data generation”, “network structure design” and “training protocol”. The proposed approach outperforms existing state-of-the-art methods on the widely-used SALICON set, as demonstrated by extensive experiments with fair and reasonable comparisons. The saliency ranking task is still in its infancy, and our proposed unified framework can serve as a fundamental strategy to guide future work. The code and data will be available at https://github.com/MengkeSong/Saliency-Ranking-Paradigm.
A Comprehensive Analysis and the Popularity Prediction for Wordle Game Based on Attentoin_LSTM

Wordle, an elegant word-guessing game, has become immensely popular from the December of 2021. Its goal is to discover a latent five letter word within six chances. Several literature have proved that it is NP-hard. Therefore, how to find an optimal policy to predict the word in limited attempts is challenging. To address this issue, this work mainly explore to find the optimal human strategy for winning the game. First, we propose to use the Attention_LSTM to predict the development trend of the number of game users. Then, we establish the enhanced VAE model to predict the probability distribution sequence of guessing attempts. To enhance the accuracy of attempts during playing the game, we analyze all the employed models’ performance, which can be utilized as an important information during making a winning strategy. Extensive experiments have proved the performance of our models in analyzing the game’s history data and predicting the popularity of the game and the probability distribution sequence of guessing attempts for the game.
Revision of the scombroid fishes from the Cenozoic of England

ABSTRACT Since 1966, when the last major work on fossil scombroid fishes (Scombroidei, Perciformes) from England appeared, our knowledge of the taxonomy and systematics of Recent scombroids has been thoroughly updated, improved and studied in the context of cladistic methods. In comparison, our knowledge of the fossil taxa has lagged much behind. As part of a revision of all fossil and Recent scombroid fishes, the present paper describes an updated systematic palaeontology of the English fossil taxa. These are a subset of taxa subject to a cladistic analysis of Recent and fossil genera combined, the results of which will appear in future papers. Three new genera are erected, two species transferred to other, already existing, ones and a new species is described (in a new genus). The author follows the opinion that Eothynnus Woodward, 1901 is a carangid. Several individual specimens are re-identified. The systematic affinities of Tamesichthys Casier, 1966, Eocoelopoma Woodward, 1901, Scombramphodon Woodward, 1901, Sphyraenodus Agassiz, 1844, Wetherellus Casier, 1966 and Woodwardella Casier, 1966, and a few new taxa, are here considered unknown. Aglyptorhynchus Casier, 1966 is probably a billfish, and Cylindracanthus Leidy, 1856, is possibly one as well, even though there are serious objections to this.
"Add more config detail": A Taxonomy of Installation Instruction Changes

README files play an important role in providing installation-related instructions to software users and are widely used in open source software systems on platforms such as GitHub. However, these files often suffer from various documentation issues, leading to challenges in comprehension and potential errors in content. Despite their significance, there is a lack of systematic understanding regarding the documentation efforts invested in README files, especially in the context of installation-related instructions, which are crucial for users to start with a software project. To fill the research gap, we conducted a qualitative study, investigating 400 GitHub repositories with 1,163 README commits that focused on updates in installation-related sections. Our research revealed six major categories of changes in the README commits, namely pre-installation instructions, installation instructions, post-installation instructions, help information updates, document presentation, and external resource management. We further provide detailed insights into modification behaviours and offer examples of these updates. Based on our findings, we provide recommendations to practitioners for maintaining their README files, as well as motivations for future research directions. These recommendations and research directions encompass completeness, correctness and up-to-dateness, and information presentation consideration. The proposed research directions span the development of automated documentation tools and empirical studies to enhance comprehension of the needs of documentation users. Furthermore, we provide a comprehensive README template tailored to cover the installation-related sections for document maintainers, serving as a practical starting point for their efforts.
Evaluation of Historical Diurnal Temperature Range Trends in CMIP5 Models

AbstractDiurnal temperature range (DTR) is a useful index of climatic change in addition to mean temperature changes. Observational records indicate that DTR has decreased over the last 50 yr because of differential changes in minimum and maximum temperatures. However, modeled changes in DTR in previous climate model simulations of this period are smaller than those observed, primarily because of an overestimate of changes in maximum temperatures. This present study examines DTR trends using the latest generation of global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and utilizes the novel CMIP5 detection and attribution experimental design of variously forced historical simulations (natural-only, greenhouse gas–only, and all anthropogenic and natural forcings). Comparison of observed and modeled changes in DTR over the period of 1951–2005 again reveals that global DTR trends are lower in model simulations than observed across the 27-member multimodel ensemb.
Cropland soil organic matter content change inNortheast China, 1985-2005

Abstract Soil organic matter (SOM) content is one of themost important indicators of soil quality and hence theproductive capacity of soils. Northeast China (NEC) is themost important region in grain production in China. Inthis study,we assessed the spatiotemporal change of croplandSOM content in NEC using sampling data of 2005 andsurvey data of 1985. We also analysed the driving forcesbehind the SOM content change. Our results showed thatSOM content decreased in 39% of all the cropland in NEC,while increase in SOM content was only detected on 16%of the cropland. SOM remained unchanged in nearly half(i.e. 45%) of the cropland. Our results also revealed thatcropping intensity and fertilizer application were the twomost important factors driving SOM change. Overall, resultsfrom this research provided novel details of the spatiotemporalpatterns of cropland SOM content change inNEC which was not revealed in earlier assessments. Thedatasets presented here can be used not only as baselinesfor the calibration of process-based carbon budget models,but also to identify regional soil quality hotspots andto guide spatial-explicit soil management practices.
Leaf Mustard (Brassica juncea) Germplasm Resources Showed Diverse Characteristics in Agro-Morphological Traits and Glucosinolate Levels

Leaf mustard, characterized by its purple/red/green leaves with a green/white midrib, is known for its thick, tender, and spicy leaves with a unique taste and flavor. There were only a few studies reported on leaf mustard for its morphological and biochemical traits from Korea. A total of 355 leaf mustard accessions stored at the GenBank of the National Agrobiodiversity Center were evaluated for 25 agro-morphological traits and seven intact glucosinolates (GSLs). The accessions showed a wide variation in terms of most of the traits. The quantitative agro-morphological traits varied from 16.0 (leaf length) to 48.7% (petiole width) of the coefficient of variation (CV). The highest variation was observed in glucoiberin (299.5%, CV), while the total GSL showed a CV of 66.1%. Sinigrin, followed by gluconapin and gluconasturtiin, was the most abundant GSL, accounting for as high as 75% of the total GSLs, while glucobrassicanapin and glucoiberin were the least abundant, contributing 0.7% and 0.1% on average, respectively. Sinigrin had a positive significant correlation with all GSLs but gluconasturtiin, while glucobarbarin and gluconasturtiin were highly positively correlated to each other, but least correlated with other GSLs. The leaf length was negatively correlated with sinigrin and glucoiberin. The width of the petiole showed a positive correlation with gluconapin, glucobrassicanapin, and glucobrassicin, while the length of the petiole had a negative correlation with sinigrin, glucobrassicanapin, glucoiberin, glucobrassicin, and the total GSLs. A higher width of the midrib was associated with higher contents of gluconapin, glucobrassicanapin, and glucobrassicin. A PCA analysis based on the agro-morphological traits showed that the first and second principal components accounted for 65.2% of the overall variability. Accessions that form a head tend to exhibit a longer leaf length, a larger plant weight, a thicker midrib, and higher widths of the midrib, petiole, and leaf. The GSLs showed inconsistent inter-and intra-leaf variation. Accessions that identified for various traits in their performance, such as, for example, Yeosu66 and IT259487 (highest total glucosinolates) and IT228984 (highest plant weight), would be promising lines for developing new varieties.
Palaeoecological change in middle to low latitude calcareous nannoplankton at the Cretaceous/Tertiary boundary

Calcareous nannofossil assemblages in four middle to low latitude Cretaceous/Tertiary boundary sections in different paleogeographic settings have been analysed. Correlation between the sections is based on the first occurrence of Neobiscutum romeinii, N. parvulum. Cruciplacolithus primus and Futyania petalosa and planktonic foraminiferal zones. Latest Maastrichtian assemblages are abundant and diverse, coccolithophores did not seem to be in decline in the latest Maastrichtian, though periods of stress are indicated by peaks in relative abundance of Micula decussata and increase in abundance of the genera Cribrosphaerella and Prediscosphaera. At the K/T boundary there was a drastic decrease in almost all Cretaceous species, blooms of Thoracosphaera, followed by acmes of few opportunistic survivors including Braarudosphaera bigelowii, Cyclagelosphaera reinhardtii, Markalius inversus, Octolithus multiplus and new Tertiary, dwarf species (Neobiscutum romeinii, N. Parvulum). The blooms are different in the studied sections probably as a result of their different paleogeography, paleodepth and consequent distribution of nutrients at the different sites. A significant change in the stratification of surface waters may have occurred in the earliest Tertiary : an influx of continental, runoff led to eutrophycation of the uppermost photic zone, triggering Braarudosphaera blooms at El Kef, Caravaca and Petriccio. Dwarf, early Tertiary coccoliths may indicate the ecosystem adjustment to unfavourable environmental conditions, increased primary productivity, poor stratification of surface water and anomalous nutrient availability. During the earliest Tertiary, nannoplankton are not the major producer of carbonate as they were in the late Cretaceous. Conditions not favourable to calcification of coccoliths are also invoked to explain the long-lasting calcareous nannofossil low-production and diversity in the earliest Danian. In this work, the rebuilding of the calcareous nannofossil community has been informally fixed by the entry of the first, "complex" Tertiary taxon Cruciplacolithus primus (<5mu ), indicating the long return to more stable conditions. The complete return of the nannoplankton community to equilibrium conditions occurred later than other planktonic organisms, above the studied interval. Cretaceous species occurring after the K/T boundary are mainly considered as reworked though survival of some taxa in the earliest Danian cannot be completely ruled out.
Viscosity Distribution within the Earth

Summary There are three sets of data (L= wavelength, t r = relaxation time) by using which we can determine the viscosity distribution within the Earth. They are the Fennoscandian uplift, Earth oblateness and a Pleistocene lake uplift. It is shown in the present paper that these are compatible only with a thin viscous channel in the upper mantle. The result seems to preclude lower mantle convection.
Adaptive spectral graph wavelets for collaborative filtering

Collaborative filtering is a popular approach in recommender systems, whose objective is to provide personalized item suggestions to potential users based on their purchase or browsing history. However, personalized recommendations require considerable amount of behavioral data on users, which is usually unavailable for new users, giving rise to the cold-start problem. To help alleviate this challenging problem, we introduce a spectral graph wavelet collaborative filtering framework for implicit feedback data, where users, items and their interactions are represented as a bipartite graph. Specifically, we first propose an adaptive transfer function by leveraging a power transform with the goal of stabilizing the variance of graph frequencies in the spectral domain. Then, we design a deep recommendation model for efficient learning of low-dimensional embeddings of users and items using spectral graph wavelets in an end-to-end fashion. In addition to capturing the graph’s local and global structures, our approach yields localization of graph signals in both spatial and spectral domains and hence not only learns discriminative representations of users and items, but also promotes the recommendation quality. The effectiveness of our proposed model is demonstrated through extensive experiments on real-world benchmark datasets, achieving better recommendation performance compared with strong baseline methods.