Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYSIS OF STREAMFLOW TRENDS AND THE EFFECTS OF CLIMATE IN PENNSYLVANIA, 1971 TO 2001 1

An understanding of temporal trends in total stream‐flow (TSF), base flow (BF), and storm runoff (RO) can help in the development of water management plans for watersheds and local communities. In this study, 47 streams across Pennsylvania that were unregulated and unaffected by karst environments or coal mining were studied for flow trends and their relationships to selected climate parameters for the period 1971 to 2001. LOWESS curves for annual flow showed that almost all of the selected streams in Pennsylvania had downward trends in total TSF, BF, and RO. Using a seasonal Mann‐Kendall analysis, downward trends were significant at an α= 0.05 level for 68, percent 70 percent, and 62 percent of the streams and at an α= 0.10 level for another 19, 17, and 13 percent of the streams for TSF, BF, and RO, respectively. The ratio of BF to TSF (RBS) had significant upward trends for 34 percent of the streams at an α= 0.05 level and for another 9 percent of the streams at an α= 0.10 level, indicating that TSF decreased relative to BF for more than 40 percent of the streams during the previous 30 years. Downward trends in TSF, BF, and RO were most common for the months of June, July, and December. Trend analyses using monthly and annual total precipitation and mean temperature showed some association between climate and the streamflow trends, but Spearman's correlation and partial Mann‐Kendall analyses revealed that the trends in TSF, BF, and RO could not be explained by trends in precipitation and temperature alone, and thus urbanization and development may have played a role.
FlexGen: An Adaptive Pipeline Generator for Programmable Data Planes

In recent years, the programmability of data planes has been extensively investigated. However, users still face challenges in conveniently expressing their data plane algorithms due to the tight coupling between compiler back-ends and chip-specific architectures on data planes. Even Lyra, a compiler that allows programmers to achieve portability, extensibility, and composition in data plane programming, does not support mapping instructions for additional capabilities, such as computing, storage, and security, in intermediate representations to P4 or NPL. In this paper, we introduce FlexGen, a flexible pipeline generator that generates configurable or executable code for multiple heterogeneous targets, incorporating additional platform capabilities such as computing, storage, and security on data planes. We compile benchmarks from real production networks to three different programmable switch architectures, and our experiments demonstrate that FlexGen generated code runs at line-rate across all packet sizes, achieving latencies comparable to those of commercial ASICs.
Preparation of bio-based heat storage microcapsules of cellulose acetate butyrate/ polymethylmethacrylate composite by micro-suspension polymerization

ABSTRACT Because of environmental concerns, the utilization of bio-based, renewable resource materials has attracted great attention for a wide range of applications. In this research, green cellulose-based microcapsules containing capric acid (CA) as a bio-heat storage material were prepared. Cellulose acetate butyrate (CAB)/methacrylate polymer composite particles were produced by microsuspension iodine transfer polymerization to encapsulate CA. The influences of methacrylate polymer type and amount on microcapsule morphology, encapsulation efficiency (EE) and thermal properties were investigated. Using methyl methacrylate (MMA) monomer, the colloidal stable spherical microcapsules with smooth surfaces and core-shell morphology were obtained. Although high percentages of EE, ≥70%, were obtained at all CAB:MMA weight ratios, the latent heats of the encapsulated CA were lower than those of the original ones which may be due to the incomplete phase separation of the CAB/PMMA shell and CA core. The increase of CA content up to 60% provided stable spherical microcapsules with a maximum loading of 59% and 97% EE. After thermal cycling for 100 cycles, stable microcapsules still remained with stable thermal properties. The obtained bio-based microcapsules would be well applied for heat storage and temperature control applications. GRAPHICAL ABSTRACT
When are multiobjective calibration trade‐offs in hydrologic models meaningful?

This paper applies a four‐objective calibration strategy focusing on peak flows, low flows, water balance, and flashiness to 392 model parameter estimation experiment (MOPEX) watersheds across the United States. Our analysis explores the influence of model structure by analyzing how the multiobjective calibration trade‐offs for two conceptual hydrologic models, the Hydrology Model (HYMOD) and the Hydrologiska Byråns Vattenbalansavdelning (HBV) model, compare for each of the 392 catchments. Our results demonstrate that for modern multiobjective calibration frameworks to identify any meaningful measure of model structural failure, users must be able to carefully control the precision by which they evaluate their trade‐offs. Our study demonstrates that the concept of epsilon‐dominance provides an effective means of attaining bounded and meaningful hydrologic model calibration trade‐offs. When analyzed at an appropriate precision, we found that meaningful multiobjective trade‐offs are far less frequent than prior literature has suggested. However, when trade‐offs do exist at a meaningful precision, they have significant value for supporting hydrologic model selection, distinguishing core model deficiencies, and identifying hydroclimatic regions where hydrologic model prediction is highly challenging.
The national biodiversity network in the UK

The national biodiversity network in the UK The National Biodiversity Network (NBN) has been developed in the United Kingdom over a period of about five years, forming the NBN Trust in March 2000. The NBN Trust brings together those with shared interests in the collection, management and use of data and information about species, biotopes and sites in the UK. These include volunteers and specialist societies, non-governmental wildlife organisations and the statutory nature conservation agencies and other governmental organisations. By working to common standards, agreeing priorities and sharing data, greater use can be made of the work of the specialists and skilled volunteers that collect biodiversity data in the field. NBN is still developing, but it is beginning to create new opportunities in surveying and monitoring species, managing data and particularly in disseminating data. Central to the development of NBN is a system for providing access to remotely held data sets using internet technology – the NBN Gateway. From a European perspective the most important aspects of the NBN are freedom of access to biodiversity data via the internet Gateway and agreed standards for data and their management and dissemination.
Spatial distribution of soil organic carbon in northwest Greenland and underestimates of high Arctic carbon stores

The amount of soil organic carbon (SOC) in the high Arctic is generally poorly constrained. Because of periglacial processes such as frost churning and sequestration in frozen soils, a substantial amount of SOC is typically not inventoried. This study provides a detailed study of SOC content by depth in 55 soil pits in a high Arctic ecosystem of northwest Greenland. Sampling sites spanned ecosystems from mires to polar deserts, from sea level to the margins of the Greenland Ice Sheet, and across various periglacial features. The amount of SOC in the various ecosystems was mapped using a correlation of SOC with high‐resolution ASTER satellite imagery and the normalized difference vegetation index (NDVI) classes from the Circumpolar Arctic Vegetation Map. On the basis of this correlation, the total carbon was extrapolated to greater areas of the high Arctic. Our study found the amount of SOC in the high Arctic has typically been grossly underestimated, remarkably by the greatest amount in the most barren environments of the polar desert. We estimate that the high Arctic contains about 12 Pg SOC, a factor of over 5 times greater the most cited values previously reported. Since our estimate was only assessed in seasonally frozen ground, additional carbon frozen in the permafrost is likely present and potentially available in the event of permafrost thawing due to warming of the Arctic.
Magnitude −7 level earthquakes: A new lower limit of self‐similarity in seismic scaling relationships

Microfractures occurring in a rock sample that are called acoustic emission (AE) events show some similar features to earthquakes. However, it remains to be shown whether or not AE equate to ultramicroearthquakes. In this study, we show the existence of magnitude −7 level earthquakes based on seismological analyses of AE source parameters. Advances in multichannel, broadband, high‐speed continuous recording of AE under seismogenic pressure conditions has facilitated increasingly robust measurement. Source parameters of AE show that AE events satisfy the same scaling relationship as natural earthquakes in which seismic moment is inversely proportional to the cube of corner frequency. This result suggests that both millimeter scale fractures and natural earthquakes of kilometer scale ruptures are highly similar as physical processes. Hence, AE events can be interpreted as ultramicroearthquakes having a magnitude of about −7. These results demonstrate that laboratory observation is an effective approach in studying natural earthquake generation process.
Testing the applicability of correlations between topographic slope and VS30 for Europe

In the past few years a series of articles have been published concerning the use of topographic slope from digital elevation models (DEMs) constructed through remote sensing (satellite imaging) to give first-order estimates of National Earthquake Hazards Reduction Program (NEHRP) site classes based on the average shear-wave velocity in the top 30 m, VS30 (Wald and Allen, 2007). We evaluate the potential applicability of these methods taking advantage of a large (706 sites) new database of measured and estimated VS30 values and their topographic slopes for locations in Europe and the Middle East. Novel statistical tests are performed to evaluate the predictive power of the procedure in this region. We evaluate the percentage of sites correctly classified/misclassified for each site class for active and stable regimes. We also analyze the marginal distributions of the input VS30 and slope values and their impact on the VS30-slope correlations and we evaluate whether the method performs better than does chance. We also consider the surface geology of sites and investigate whether differences in geology can help explain why certain sites are poorly classified by the method. Finally, we use the city of Thessaloniki, Greece, as a test case for comparison between the results of a recent microzonation and the site classes predicted by VS30-slope correlations. Our results show that the method does a better job than blind chance for all site classes in active regions, but only for class B (rock) and to a lesser extent class C (stiff soil) sites located in stable areas, although the conclusions for stable areas are based on limited data. We recommend that site classifications based on the VS30-slope correlations proposed by Wald and Allen (2007) be used only for regional or national (and not local or site-specific) first-order studies in active parts of Europe and only in the absence of other more detailed information, excluding sites inside small basins or those with special geological conditions that may affect results (e.g., flat-lying volcanic plateaus, carbonate rocks, continental glaciated terrain, or a coastal location if slope is not calculated using bathymetric data).
An EKF-Based Multi-Object Tracking Framework for a Mobile Robot in a Precision Agriculture Scenario

Many robotic applications require the ability to locate multiple objects in the environment, but the use of instant-by-instant identification techniques may be unreliable in variable and poorly structured contexts, such as for the majority of precision agriculture settings. Inspired by the needs of the H2020 CANOPIES projects, where robotic platforms are required to perform harvesting operations in table-grape vineyards, in this paper, we propose a framework for tracking objects of interest over time using a mobile robotic platform equipped with RGB-D camera. Specifically, we design a multi-object tracking module based on an Extended Kalman Filter (EKF) which takes into account the motion of the robot to update the estimate of the localization of the objects. We validate the approach in a realistic Unity-based simulator, where a mobile robot is tasked with tracking table-grape bunches within a vineyard environment. Additionally, we conduct preliminary tests in a laboratory setup.
New horizons in soil fertility management

As the 21st century dawns, we can reflect on the progress made during the 20th century in the fields broadly covered by soil fertility and its management and see that progress has been truly amazing. When we consider the many aspects of soil fertility measurement, the management practices, the changes in productivity, the awareness of the off-site effects of management practices, and the speed with which changes can be implemented, we can but wonder what advances the next 100 years will bring. We can cast our minds back to where the science of soil fertility and its management was at the turn of the 20th century, track the progress since then, and finally discuss where the major advances in the next 10 years are likely to occur.
Gait Attribute Recognition: A New Benchmark for Learning Richer Attributes From Human Gait Patterns

Compared to gait recognition, Gait Attribute Recognition (GAR) is a seldom-investigated problem. However, since gait attribute recognition can provide richer and finer semantic descriptions, it is an indispensable part of building intelligent gait analysis systems. Nonetheless, the types of attributes considered in the existing datasets are very limited. This paper contributes a new benchmark dataset for gait attribute recognition named Multi-Attribute Gait (MA-Gait). Our MA-Gait contains 95 subjects recorded from 12 camera views, resulting in more than 13000 sequences, with 16 attributes labeled, including six attributes that have never been considered in the literature. Moreover, we propose a Multi-Scale Motion Encoder (MSME) to extract robust motion features, and an Attribute-Guided Feature Selection Module (AGFSM) to adaptively capture the most discriminative attribute features from static appearance features and dynamic motion features for different attributes. Our method achieves the best GAR accuracy on the new dataset. Comprehensive experiments show the effectiveness of the proposed method through both quantitative and qualitative evaluations.
A Furrow Irrigation Automation System Utilizing Adaptive Control

A furrow irrigation automation system utilizing an adaptive control algorithm (FAAC) was developed to estimate infiltration and vary inflow to control outflow at a desired rate. Field tests were completed on a Warden, very fine, sandy loam soil to evaluate the ability of the FAAC system to accurately calculate infiltration rates and control runoff on a soil with highly varying infiltration characteristics. Outflow was controlled at the desired outflow rate with a mean absolute error of 4% (0.19 L/min) and standard deviation of 3% (0.13 L/min). The FAAC system, compared with furrow irrigating at a constant flowrate, produced an average 95% reduction in sediment discharge, 74% reduction in tailwater, and 39% increase in application efficiency while decreasing cumulative infiltration by 28%.
CSLog: Anomaly Detection for Syslog Based on Contrastive Self-Supervised Representation Learning

In recent years, as the scale of computer clusters has expanded, maintaining stable system operation and timely detection of system anomalies have become significant challenges. System logs play an essential role in anomaly detection, and numerous methods have been proposed for detecting system anomalies using logs. However, these methods face challenges such as extreme data class imbalance, lack of labeled data, and low detection performance. In this paper, we present a contrastive self-supervised representation learning-based system log anomaly detection method, CSLog. This novel approach employs contrastive self-supervised representation learning to directly learn high-quality log sequence representations from easily obtainable normal log data, enabling downstream unsupervised detection methods to achieve state-of-the-art (SOTA) log anomaly detection performance. Furthermore, our method utilizes a distance-based anomaly modeling approach, avoiding parsing errors caused by the log parsing step required in traditional unsupervised log anomaly detection methods and simplifying the detection process. Experimental results demonstrate that our method achieves an f1-score of 96.7% on the HDFS dataset, surpassing the 95.3% achieved by supervised learning-based methods. Additionally, CSLog’s performance outperforms other unsupervised learning methods in comparative experiments.
Prevalence and Risk Factors of Metabolic Syndrome: A Prospective Study on Cardiovascular Health

Background and objectives: This article highlights the relationship between metabolic syndrome and cardiovascular disease, providing a comprehensive overview of its risk factors and prevalence. Metabolic syndrome, characterized by a cluster of interconnected risk factors, significantly increases the risk of developing cardiovascular disease and type II diabetes. Materials and methods: This study, conducted over a one-year period, involved 117 patients aged between 30 and 79 years old. Various parameters were analyzed, such as gender, age, education level, provenance from urban or rural environment, smoking, alcohol consumption, dietary aspects, physical activity, and their contribution to the appearance of metabolic syndrome. Central adiposity and high blood pressure emerged as prominent elements of the condition. Results: The findings underscore the importance of a healthy lifestyle in the prevention and management of metabolic syndrome. Encouraging regular physical activity, maintaining a balanced diet, rich in fresh vegetables and fruits, and avoiding harmful behaviors, such as smoking or alcohol consumption, are essential in reducing the risk of metabolic syndrome and its associated cardiovascular complications. Conclusions: The study highlights the need for public health initiatives, as well as individualized preventive strategies to combat the rising prevalence of metabolic syndrome. Through promoting awareness of its risk factors and implementing effective interventions, healthcare professionals can contribute to better cardiovascular health worldwide. Further research in this area will continue to enhance our understanding of metabolic syndrome and refine preventive and therapeutic approaches for its management.
Probabilistic earthquake relocation in three-dimensional velocity models for the Yellowstone National Park region, Wyoming

Recorded seismicity for the Yellowstone National Park region, comprising 25,267 earthquakes from November 1972 to December 2002, has been relocated using three-dimensional velocity models and probabilistic earthquake location. In addition, new coda magnitudes for earthquakes between 1984 and 2002 were computed by using an improved coda magnitude equation. Three-dimensional velocity models for earthquake location were computed by inverting subsets of high quality data of three different periods, 1973-1981, 1984-1994, and 1995-2002, for hypocenter locations and seismic velocities. Earthquakes were relocated by using a nonlinear, probabilistic solution to the earthquake location problem. Fully nonlinear location uncertainties included in the probabilistic solution allow a better and more reliable classification of earthquake locations into four quality classes. Earthquake locations show an improvement in location accuracy with time, which we attribute to improved network geometry and more precise timing of arrival times. No large systematic shifts of the relocated earthquake locations are observed, except a systematic shift of _2 km to greater depth. The new relocated earthquake locations show tighter clustering of epicenters and focal depths when compared with original earthquake locations. The most intense seismicity in terms of number of earthquakes and cumulative seismic moment release in the Yellowstone National Park region occurs northwest of the Yellowstone caldera between Hebgen Lake and the northern rim of the caldera. Seismicity within the Yellowstone caldera is diffuse, and shallow individual clusters of earthquakes can be associated with major hydrothermal areas.
Evidence of partial melting beneath a continental margin: case of Dhofar, in the Northeast Gulf of Aden (Sultanate of Oman)

SUMMARY Gravity data and P-wave teleseismic traveltime residuals from 29 temporary broad-band stations spread over the northern margin of the Gulf of Aden (Dhofar region, Oman) were used to image lithospheric structure. We apply a linear relationship between density and velocity to provide consistent density and velocity models from mid-crust down to about 250 km depth. The accuracy of the resulting models is investigated through a series of synthetic tests. The analysis of our resulting models shows: (1) crustal heterogeneities that match the main geological features at the surface; (2) the gravity edge effect and disparity in anomaly depth locations for layers at 20 and 50 km; (3) two low-velocity anomalies along the continuation of Socotra-Hadbeen and Alula-Fartak fracture zones between 60 and 200 km depth; and (4) evidence for partial melting (3–6 per cent) within these two negative anomalies. We discuss the presence of partial melting in terms of interaction between the Sheba ridge melts and its along-axis segmentation.
Stated Preferences and Length of Residency in Rural Communities: Are Development and Conservation Values Heterogeneous?

Newer residents of rural, urban-fringe communities are often assumed to have preferences for the development and conservation of rural lands that differ from those of longer-term residents. The existing literature offers little to verify or quantify presumed preference shifts. This paper provides a systematic, quantitative examination of whether stated preferences for development and conservation tradeoffs differ according to length of residency in a rural community, and explores implications of these findings for assumptions regarding development and conservation preferences. Results are based on stated preferences estimated from a multi-attribute contingent choice survey of Rhode Island rural residents. Heterogeneity-according to length of town residency-is incorporated using Lagrangian Interpolation Polynomials. This approach models the influence of policy attributes as a polynomial function of residence time, thereby allowing estimated coefficient values to vary as a continuous function of residence duration.