Miracle-dz/UniFAR-FTUs huggingface dataset:
Relating salt marsh pore water geochemistry patterns to vegetation zones and hydrologic influences

Physical, chemical, and biological factors influence vegetation zonation in salt marshes and other wetlands, but connections among these factors could be better understood. If salt marsh vegetation and marsh pore water geochemistry coorganize, e.g., via continuous plant water uptake and persistently unsaturated sediments controlling vegetation zone‐specific pore water geochemistry, this could complement known physical mechanisms of marsh self‐organization. A high‐resolution survey of pore water geochemistry was conducted among five salt marsh vegetation zones at the same intertidal elevation. Sampling transects were arrayed both parallel and perpendicular to tidal channels. Pore water geochemistry patterns were both horizontally differentiated, corresponding to vegetation zonation, and vertically differentiated, relating to root influences. The geochemical patterns across the site were less broadly related to marsh hydrology than to vegetation zonation. Mechanisms contributing to geochemical differentiation included: root‐induced oxidation and nutrient (P) depletion, surface and creek‐bank sediment flushing by rainfall or tides, evapotranspiration creating aerated pore space for partial sediment flushing in some areas while persistently saturated conditions hindered pore water renewal in others, and evapoconcentration of pore water solutes overall. The concentrated pore waters draining to the tidal creeks accounted for 41% of ebb tide solutes (median of 14 elements), including being a potentially toxic source of Ni but a slight sink for Zn, at least during the short, winter study period in southern San Francisco Bay. Heterogeneous vegetation effects on pore water geochemistry are not only significant locally within the marsh but may broadly influence marsh‐estuary solute exchange and ecology.
Camera Calibration Based on Free-Placed Single Right Cylindrical Target

Camera calibration is critical for vision sensors. In a scene where the target is easily occluded, it is usually difficult for traditional calibration methods to obtain satisfactory calibration results. This article proposes a novel camera calibration method based on a freely placed right cylinder (RC), which has strong adaptability to scenes where the target is easily occluded. First, the distortion coefficients of the camera are obtained by using the projection lines of the cylindrical quadric. Second, the intrinsic and extrinsic parameters of the camera are calibrated by using the geometric properties of the RC target and the properties of the vanishing point. Then, nonlinear optimization algorithms can be employed to obtain the optimal solution for internal and external parameters. Finally, the effectiveness and adaptability of this method to space-constrained scenes have been demonstrated by simulations and actual experiments. The mean reprojection error of this method is 0.169 pixels in actual experiments. In addition, even when the target is occluded and the projection contour is incomplete, the mean reprojection error of this method is 0.172 pixels, which indicates that the method has great potential for widespread application to space-constrained scenarios.
Enhanced watershed modeling and data analysis with a fully coupled hydrologic model and cloud-based flow analysis

ii ACKNOWLEDGEMENTS . v LIST OF TABLES . xii LIST OF FIGURES . xiii CHAPTER 1: INTRODUCTION . 1 CHAPTER 2: COUPLING SWAT AND MODFLOW MODELS FOR ENHANCED ASSESSMENT OF HYDROLOGIC PROCESSES AT THE WATERSHED SCALE . 5 2.1: INTRODUCTION . 5 2.1. 1: SWAT . 8 2.1. 2: SWAT GROUNDWATER DISCHARGE TO RIVERS . 11 2.1. 3: MODFLOW . 12 2.1. 4: SURFACE-SUBSURFACE WATERSHED MODELING . 14 2.2: METHODS AND MODELS . 19 2.2.1 OVERVIEW . 19 2.2.2 MODEL COUPLING . 20 2.2.3: APPLICATION . 27 2.3: RESULTS AND DISCUSSION . 30 2.3. 1: NORTH FORK OF THE SPRAGUE RIVER . 31
SEA SURFACE-WATER TEMPERATURE AND ISOTOPIC RECONSTRUCTIONS FROM NANNOPLANKTON DATA USING ARTIFICIAL NEURAL NETWORKS

Artificial neural networks (ANN) are computer systems that differ from other pattern recognition methods in their ability to ‘learn’ one or more target variables from a set of input variables. These systems learn by self-adjusting a set of parameters to minimize the error between the desired output and network output. To explore the potential of artificial neural networks for predictions of paleo-oceanographic parameters from relative abundances of calcareous nannoplankton species we analysed observations taken from the literature for (1) the prediction of sea surfacewater temperature (SST) in samples from offshore southern California, and (2) the prediction of oxygen isotopic values in a Quaternary core from the eastern Mediterranean. We employed a back propagation (BP) neural network to assess the ability of the network to predict SST and oxygen isotopic values. Each of the data sets was divided into five random training and test sets to assess the stability of the error rate estimates. For the California Bight samples we obtained an average Root-Mean-Square-Error of Prediction (RMSEP) in the test sets of 0.68, implying that an unknown SST can be predicted with a precision of ± 0.68°C. In the Mediterranean samples the average RMSEP in the test sets was 0.64; hence an unknown oxygen isotope value can be predicted with a precision of ± 0.64 δ18O‰ vs. PDB. ANN techniques can be seen as a complementary tool to more conventional approaches to paleoceanographic data analysis. Such techniques hold great potential for making predictions of various types of variables from paleontological data.
Sub-nanosecond coherent optical manipulation of a single aromatic molecule at cryogenic temperature

Single molecules trapped in the solid state at liquid helium temperatures are promising quantum emitters for the development of quantum technologies owing to their remarkable photostability and their lifetime-limited optical coherence time of the order of 10 ns. The coherent preparation of their electronic state requires resonant excitation with a Rabi period much shorter than their optical coherence time. Sculpting the optical excitation with sharp edges and a high on–off intensity ratio (∼3 × 105) from a single-frequency laser beam, we demonstrate sub-nanosecond drive of a single dibenzanthanthrene molecule embedded in a naphthalene matrix at 3.2 K, over more than 17 Rabi periods. With pulses tailored for a half-Rabi period, the electronic excited state is prepared with fidelity as high as 0.97. Using single-molecule Ramsey spectroscopy, we prove up to 5 K that the optical coherence lifetime remains at its fundamental upper limit set by twice the excited-state lifetime, making single molecules suitable for quantum bit manipulations under standard cryogen-free cooling technologies.
Benchmarking Continual Learning from Cognitive Perspectives

Continual learning addresses the problem of continuously acquiring and transferring knowledge without catastrophic forgetting of old concepts. While humans achieve continual learning via diverse neurocognitive mechanisms, there is a mismatch between cognitive properties and evaluation methods of continual learning models. First, the measurement of continual learning models mostly relies on evaluation metrics at a micro-level, which cannot characterize cognitive capacities of the model. Second, the measurement is method-specific, emphasizing model strengths in one aspect while obscuring potential weaknesses in other respects. To address these issues, we propose to integrate model cognitive capacities and evaluation metrics into a unified evaluation paradigm. We first characterize model capacities via desiderata derived from cognitive properties supporting human continual learning. The desiderata concern (1) adaptability in varying lengths of task sequence; (2) sensitivity to dynamic task variations; and (3) efficiency in memory usage and training time consumption. Then we design evaluation protocols for each desideratum to assess cognitive capacities of recent continual learning models. Experimental results show that no method we consider has satisfied all the desiderata and is still far away from realizing truly continual learning. Although some methods exhibit some degree of adaptability and efficiency, no method is able to identify task relationships when encountering dynamic task variations, or achieve a trade-off in learning similarities and differences between tasks. Inspired by these results, we discuss possible factors that influence model performance in these desiderata and provide guidance for the improvement of continual learning models.
Biotechnology and Solutions: Insect-Pest-Resistance Management for Improvement and Development of Bt Cotton (Gossypium hirsutum L.)

Cotton (Gossypium spp. L.) is a major origin of natural fiber, and is projected at 117 million bales worldwide for 2021/22. A variety of biotic and abiotic stresses have considerable negative impacts on cotton. The significantly decreased applications of chemical insecticidal sprays in the agro-ecosystem have greatly affected the biodiversity and dynamics of primary and secondary insects. Various control measures were taken around the globe to increase production costs. Temperature, drought, and salinity, and biotic stresses such as bacteria, viruses, fungi, nematodes, insects, and mites cause substantial losses to cotton crops. Here, we summarize a number of biotic and abiotic stresses upsetting Bt cotton crop with present and future biotechnology solution strategies that include a refuge strategy, multi-gene pyramiding, the release of sterile insects, seed mixing, RNAi, CRISPR/Cas9, biotic signaling, and the use of bioagents. Surveillance of insect resistance, monitoring of grower compliance, and implementation of remedial actions can lead to the sustainable use of cotton across the globe.
Relationship between Quality of Life and Adult Attachment Factors in Mothers of Children with and without Type 1 Diabetes

The mothers of children with a specific clinical situation such as type 1 diabetes mellitus may have a higher level of stress, causing a worse perception of their quality of life, greater anxiety, and greater avoidance (adult attachment factors). The objective of this research was to verify if there is a relationship between the adult attachment factors of mothers of children with and without type 1 diabetes mellitus and the perception of the quality of life of these mothers. This survey was carried out from July to September 2022, with mothers of children aged 5 to 10 years, with and without diabetes. The data were collected through an online questionnaire, with socioeconomic data from the attachment scale Experience in Close Relationship—(Reduced), and the questionnaire on the quality of life, the WHOQOL-abbreviated questionnaire. For statistical analysis, the Statistical Package for Social Science 24 was used. A total of 45 mothers of children with DM1 and 55 mothers of healthy children were evaluated. The mothers of children with DM1 had a worse perception of their quality of life when compared to the mothers of healthy children (p < 0.05), with no difference in terms of the attachment style. Therefore, it is understood that actions aimed at improving the quality of life of these mothers are necessary.
Building a Digital Twin for British Cities

Ever faster computers are enabling us to extend our standard land use transportation interaction (LUTI) models to systems of cities within which individual cities compete for resources within the wider environment in which they interact.As we scale up in this way, we are able to simulate and measure the impacts of large-scale infrastructures at different spatial levels.Here we build a platform, which is essentially a digital twin, for over 8000 urban places in Great Britain where we can rapidly model all flows between these locations using multi-modal spatial interaction models.We first present the structure of the model and then apply it to population, employment and trip flow data for three modes of travel (road, bus and rail) between small spatial units defining the three countries, England, Scotland and Wales.We then tune and train the model to reproduce a baseline, and follow this with a demonstration of the web-based interface used to run and interact with the model and its predictions.Once we have developed the platform, we are able to explore variants of the twin, partitioning the country in different ways, showing how different forms of spatial representation change the performance of the model.We are developing the model at a much finer scale making comparisons of performance while adding an active travel layer that elaborates the twin.We finally illustrate how the model can be used to measure the impacts of new scenarios for rail, simulating the Integrated Rail Plan and the High Speed 2 proposal
Improved YOLOv5 Detection Algorithm of Road Disease Image

With the rapid development of China's urban roads, the traffic road network is increasingly improved, and the road mileage has reached a new height. Faced with such a large-scale traffic road network, fast and efficient pavement disease detection becomes an urgent problem to be solved. The existing models are weak in detecting defects related to the proximal and distal ends of the actual roads, and the detection performance is insufficient. Therefore, the YOLOv5 network model containing RepLKDeXt module, SOCA module, and Mixup hybrid data enhancement is modified for the YOLOv5 model, which is designed to use RepLKDeXt module to replace some of the C3 layers of the trunk and neck to enrich the feature extraction capability and improve the feature expression capability of the network, use Mixup data enhancement at the input side technique to improve the learning ability of the network to extract features from complex images and further enhance the detection accuracy of the network model. Experiments were conducted on the Japanese road disease dataset, and the experimental results showed that the improved YOLOv5 model reduced the number of parameters by about 10% and improved the detection accuracy by 3.1%.
Analyzing Role Overload, Mental Health, and Quality of Life Among Jordanian Female Healthcare Professionals: A Cross-Sectional Study

Purpose To identify the role overload, mental health distress, and quality of life among Jordanian female healthcare professionals and explore their interrelationships. Patients and Methods This cross-sectional correlational research involved 412 female participants (physicians, nurses, and pharmacists) from the government and private sectors in Jordan. The Role Overload, Depression, Anxiety, and Stress Scale-21 (DASS-21) and the World Health Organization Quality of Life-Brief Version were used for data collection. Statistical analyses included descriptive statistics, Pearson correlation, multiple linear regression, multivariate analysis of variance, Tukey’s post hoc test, Spearman rho, and linear regression tests (p=0.05). Results Results indicate that 83.2% of participants experienced moderate to high role overload, with 72.9% displaying signs of moderate to extreme depression. Professionals working >40 hours/week experienced elevated stress levels, while those with chronic illnesses exhibited higher mean scores for depressive symptoms (M= 16.91 vs M= 14.49, p=0.002) and stress (M= 20.55 vs M= 18.57, p=0.033). Professionals attending older individuals reported increased role overload (M= 3.66 vs M= 3.14, p<0.001), higher stress (M=19.99 vs M=18.14, p=0.027), and lower physical (M=51.79 vs 55.41, p =0.025) and psychological (M=50.04 vs M=53.57, p=0.045) quality of life. Simple regression analysis revealed that role overload significantly predicted stress, depression, and anxiety. Role overload’s impact on depression scores (β = 2.108, t=5.234, p<0.001), as well as anxiety (β =1.933, t=5.014, p<0.001), was associated with an inverse correlation with both physical (β =1.671, R2= 3.4, p<0.001) and psychological (β =1.914, R2= 1.4%, p=0.018) quality of life of healthcare professionals. Mental distress and role overload significantly predicted participants’ physical and psychological quality of life. Conclusion This study established a significant association between role overload, quality of life, and psychological health of female healthcare professionals in Jordan, with implications for enhancing their well-being.
Visual Characteristics of Elderly Drivers – Aging Effects on Visual Acuity and Glare Feeling

The objective of the study was to investigate age related effects on visual acuity and reflected-glare associated with daytime and nighttime driving conditions. Fifty-six participants (28 young, 28 old) recruited from Virginia Tech student population and Blacksburg Community were tested in the study. Landolt's Circle Method was adopted to assess visual acuity under simulated daytime and nighttime conditions. Although, the age and distance main effects were found to be significant, no differences were reported among all the distances within the young group. The study also examined the effects of reflected headlamp glare on age and mirror types on the basis of angle of incidence, illumination-front-of-eyes and rating scores. The results indicated that with the same glare level (as measured by angle and illumination in front of the eye), elderly adults reported lower glare rating scores (i.e. worse feelings of glare). Furthermore, the young and elderly both reported lower De Boer's rating scores for planar driver-side mirrors than non-planar driver-side mirrors. This result can have practical implications in reducing nighttime discomfort glare for both young and elderly.
Vertical plate motions in the West Siberian Basin

The West Siberian Basin is one of the world’s largest sedimentary basins representing an important source of oil and gas. The Basin’s history includes long periods of very slow subsidence coupled with periods of erosion and uplift. Despite that the Basin has been broadly explored the causes of these vertical motions are not yet understood. In this study we analyse the vertical motions by the means of backstripping. The new backstripping results refined by the paleo-water depth data give estimates of the subsidence and uplift rate. These results show a peculiar character of the vertical motions where the region of maximum subsidence migrated from the north to the south several times during the Basin’s history. Such southward propagation of subsidence happened in the Late Jurassic, Aptian and in the Paleogene periods. The newly constrained local eustatic curve indicates that the Basin’s vertical motions do not reflect the global sea level changes, but the more complicated tectonic processes. We put different data sets of the Basin’s sediments and crust structure together with the new backstripping results in order to understand better the vertical motions and the processes underlying the irregular subsidence and uplift pattern of the West Siberian Basin
Fairness and Deception in Human Interactions with Artificial Agents

Online information ecosystems are now central to our everyday social interactions. Of the many opportunities and challenges this presents, the capacity for artificial agents to shape individual and collective human decision-making in such environments is of particular importance. In order to assess and manage the impact of artificial agents on human well-being, we must consider not only the technical capabilities of such agents, but the impact they have on human social dynamics at the individual and population level. We approach this problem by modelling the potential for artificial agents to"nudge"attitudes to fairness and cooperation in populations of human agents, who update their behavior according to a process of social learning. We show that the presence of artificial agents in a population playing the ultimatum game generates highly divergent, multi-stable outcomes in the learning dynamics of human agents' behaviour. These outcomes correspond to universal fairness (successful nudging), universal selfishness (failed nudging), and a strategy of fairness towards artificial agents and selfishness towards other human agents (unintended consequences of nudging). We then consider the consequences of human agents shifting their behavior when they are aware that they are interacting with an artificial agent. We show that under a wide range of circumstances artificial agents can achieve optimal outcomes in their interactions with human agents while avoiding deception. However we also find that, in the donation game, deception tends to make nudging easier to achieve.
THREE-DIMENSIONAL SHEAR WAVE VELOCITY STRUCTURE AND DISTRIBUTION IMAGE OF Vp/Vs BENEATH THE WEIHE FAULT DEPRESSION

Using the seismic data observed by the seismic networks in Shanxi province and neighbor regions, we studied seismic tomographic imaging of the crustal S wave velocity in the Weihe fault basin by overlapping-shear iterative reconstruction method with the two-points fast ray tracing technique. On the basis of the velocity ratio Vp/ Vs in the same region is calculated. The results show that (1) there are two strong lateral no homogenous regions of S wave velocity distribution, one of which is Heyang-Yongji region on the boundary between Shanxi and Shanxi provinces and the other is Tongchuan-Jingyang zone. Those two areas are located in a region where different tectonic units meet, and differential movement is significant and different rock strata are interceded, (2) the historical strong earthquakes occurred mainly in S wave high-velocity regions on their boundaries; (3) a region with high Vp / Vs value (highest of 2.1) is enclosed by the areas of Chunhua, Yaoxian and Jingyang.
Outdoor Mass Gatherings in Kansas: An Examination of Local Health Department awareness and Involvement

3 BACKGROUND 4 1. JULY 1987: RAINBOW FAMILY OF LIVING LIGHT ANNUAL GATHERING — NANTAHALA NATIONAL FOREST, NORTH CAROLINA . 4 2. OCTOBER 2004: NORTH CAROLINA STATE FAIR — RALEIGH, NORTH CAROLINA 4 3. JUNE 2006: BIKING ACROSS KANSAS — KANSAS 5 4. JULY 2007: TASTE OF CHICAGO — CHICAGO, ILLINOIS 5 5. MAY 2010: SASQUATCH MUSIC FESTIVAL — GORGE AMPHITHEATER IN GEORGE, WASHINGTON 5 METHODS 7 RESULTS 8 DISCUSSION 11 ACKNOWLEDGEMENTS 13 REFERENCES 14
Disturbance and Recovery of Sooty Tern Nesting Colony in Dry Tortugas National Park

The sooty tern (Onychoprion fuscatus), an abundant pelagic seabird common throughout tropical waters, is an important ecological indicator for the health of the world’s oceans due to its widespread distribution and long life history. The nesting colony on Bush Key, Dry Tortugas National Park has been the subject of a 16-year monitoring effort to track changes in nesting population and plant community present on the island. A devastating hurricane season in 2005 reduced available nesting habitat by over 70%. By 2013, available habitat had recovered to 92% of pre-disturbance levels. Recovery of nesting pairs continues to lag with an estimated 16,000 in 2016, compared to 40,000 in 2001. Plant community composition remains significantly altered. This analysis is vital to park managers charged with protecting the natural resources of our National Parks. Continued monitoring will be necessary to assess emerging threats to marine resources, such as climate change and increased anthropogenic pressures.