Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating seasonal loading models and their impact on global and regional reference frame alignment

Seasonal variations are observed in GPS time series, but are not included in the International Terrestrial Reference Frame (ITRF) models. Unmodeled seasonal variations at sites used for reference frame alignment are aliased into the reference frame parameters and bias all coordinates in the transformed solution. We augment ITRF2008 with seasonal loading models based either on Gravity Recovery and Climate Experiment (GRACE) measurements or a suite of models for atmospheric pressure, continental hydrology, and nontidal ocean loading. We model the seasonal components using either annual and semiannual terms or a nonparametric approach. When we include a seasonal variation model, the weighted root‐mean‐square misfit after seven‐parameter transformation decreases for 70–90% of the daily GPS solutions depending on the network and seasonal model used, relative to a baseline case using ITRF2008. When seasonal variations are included in the reference frame solution, the observed seasonal variations are more consistent with the GRACE‐based model at 80–85% of the GPS sites that were not used in the frame alignment. The suite of forward models performs nearly as well as the GRACE‐based model for North America, but substantially worse for other parts of the world. We interpret these findings to mean that the use of ITRF2008 without seasonal terms causes the amplitude of seasonal variations in the coordinate time series to be damped down relative to the true loading deformation and that the observed GPS time series are more consistent with a TRF model that includes seasonal variations. At present, a seasonal model derived from GRACE captures seasonal variations more faithfully than one based on hydrologic models.
Bifurcation control of solid angle car-following model through a time-delay feedback method

In order to alleviate unstable factor-caused bifurcation and reduce oscillations in traffic flow, a feedback control with consideration of time delay is designed for the solid angle model (SAM). The stability and bifurcation condition of the new SAM is derived through linear analysis and bifurcation analysis, and then accurate range of stable region is obtained. In order to explore the mechanism of the influence of multiple parameter combinations on the stability of controlled systems, a definite integral stabilization method is provided to determine the stable interval of time delay and feedback gain. Numerical simulations are explored to verify the feasibility and effectiveness of the proposed model, which also demonstrate that feedback gain and delay are two key factors to alleviate traffic congestion in the SAM.
Pipelines Failure Prediction Modelling for Onshore Gas Transmission Pipelines Using Machine Learning

Transmission pipeline is the safest and most effective way to transport large amounts of natural gas over long distances. Although transportation using pipelines is the safest, transmission pipeline failures can cause damage, financial losses, and injuries. A good preventive maintenance schedule is desired, which aims to predict break pipes proactively. In this paper, we present a prediction model of onshore gas transmission pipeline failure using machine learning with R software. The model presented is developed based on historical failure that includes structured and unstructured from the onshore gas transmission pipelines from approximately 2010-2020 released by the US Department of Transportation. The applying process can be divided into various steps: data pre-processing, model training, model testing, performance measuring, and failure predicting. By using machine learning, we can conclude that it is an effective method to work with a complex dataset for predicting pipe failures. It can provide significant improvement for the safe economic operation of pipelines .
A parameter-conditional neural network framework for modelling parameterized auditory models

The use of auditory models is important for designing speech and audio processing algorithms for hearing assistive devices. These auditory models are often parameterized by a set of parameters relating to auditory function, e.g., hair cell loss or synaptopathy. In practice, the computational load of these auditory models can be very high thus limiting the feasibility of using the models as bio-inspired loss functions for deep learning based hearing loss compensation strategies or denoising strategies. Previous efforts have addressed this problem by training a neural network for each parameter configuration of the auditory model which greatly reduces the computation time of the auditory model but requires a new network to be trained whenever the parameterization changes. In this paper we propose an approach where a single neural network is trained, once and for all, to accurately simulate auditory models across their parameter spaces by conditioning the weights of the network on the parameters of the respective auditory models. This approach enables greater flexibility than training a single model for each parameter configuration, as any parameterization can be acquired on the fly. The accuracy of the neural network is shown to be robust across both unseen inputs and standard audiograms.
Facies Relationships and Systems Tracts in the Late Holocene Mississippi Delta Plain

ABSTRACT Facies relationships in abandoned Holocene Mississippi Delta complexes are characteristic of both retrogradational transgressive systems tracts (TST) and progradational highstand systems tracts (HST). In the Barataria interlobe basin, delta-plain facies of the early Holocene Maringouin/Teche delta complex (TST), which accumulated from 7500 to 6000 yr BP, are overlain by a lagoonal facies 1-2 m thick (MFS) that accumulated during the maximum flooding event from 6000 to 3500 yr BP. Wave reworking transformed the distributary sands of retrogradational delta complexes into stratigraphically backstepping shoreline sand bodies. The most landward of these shorelines, the Teche shoreline, overlies the MFS and is, by definition, the shoreline of maximum transgression (SMT) (Penland et al. 1987 , 1987b; Kosters 1989). Relatively thick peats of high organic content, dating from 2400 to 1100 yr BP, are located immediately landward of this shoreline. Younger delta lobes, rapidly prograding since 1100 yr BP, have shifted the coastline seaward of the Teche shoreline, and form the first progradational HST parasequence. Thin, organic-poor salt marsh sediments are accumulating within this parasequence landward of the present shoreline. Rising relative sea level provides increased accommodation space while fresh water may be held within the delta plain, creating conditions of both groundwater and nutrients favorable to accumulation of high-quality organic facies of this type. In a subsequent progradational setting, stable relative sea level results in less accommodation space landward of the shoreline, while fresh water and nutrients are discharged into the Gulf of Mexico, forcing formation of brackish and salt marsh environments, unfavorable to accumulation of high-quality organic facies. These hypotheses may help explain the variability of some littoral high-quality coals vs. carbonaceous shales in the rock record.
Engineering Degree Project Performance analysis: CNN model on smartphones versus on cloud

In the modern digital landscape, mobile devices serve as crucial data generators. Their usage spans from simple communication to various applications such as user behavior analysis and intelligent applications. However, privacy concerns associated with data collection are persistent. Deep learning technologies, specifically Convolutional Neural Networks, have been increasingly integrated into mobile applications as a promising solution. In this study, we evaluated the performance of a CNN implemented on iOS smartphones using the CIFAR-10 data set, comparing the model’s accuracy and execution time before and after conversion for on-device deployment. The overarching objective was not to design the most accurate model but to investigate the feasibility of deploying machine learning models on-device while retaining their accuracy. The results revealed that both on-cloud and on-device models yielded high accuracy (93.3% and 93.25%, respectively). However, a significant difference was observed in the total execution time, with the on-device model requiring a considerably longer duration (45.64 seconds) than the cloud-based model (4.55 seconds). This study provides insights into the performance of deep learning models on iOS smartphones, aiding in understanding their practical applications and limitations.
Survival bene�t of neoadjuvant hepatic arterial infusion chemotherapy followed by hepatectomy for hepatocellular carcinoma with portal vein tumor thrombus

background/purpose: The prognosis of hepatocellular carcinoma (HCC) patients with portal vein tumor thrombus (PVTT) is generally poor and hepatectomy is optional for these patients. This study aims to explore the survival bene�ts of neoadjuvant hepatic arterial infusion chemotherapy (HAIC) for resectable HCC with PVTT. Methods: This retrospective study included 120 consecutive HCC patients with PVTT who underwent hepatectomy, from January 2017 to January 2021 at Sun Yat-sen University Cancer Center. Of these patients, the overall survival (OS) and recurrence-free survival (RFS) of 55 patients who received hepatectomy alone (Surgery group) and 65 patients who received neoadjuvant HAIC followed by hepatectomy (HAIC-Surgery group) were compared. Logistic regression analysis was conducted to develop a model predicting the response to neoadjuvant HAIC. Results: The OS rates for the HAIC-Surgery group at 1, 3, and 5 years were 94.9%, 78% and 66.4%, respectively, compared with 84.6%, 47.6% and 37.2% in the Surgery group (P < 0.001). The RFS rates were 88.7%, 56.2% and 38.6% versus 84.9%, 38.3% and 22.6% (P = 0.002). The subgroup analysis revealed that the survival bene�t of neoadjuvant HAIC was limited to patients who responded to it. The logistic model, consisting of AFP and CRP, that predicted the response to neoadjuvant HAIC performed well, with an area under the ROC curve (AUC) of 0.756. Conclusion: Neoadjuvant HAIC followed by hepatectomy is associated with a longer survival outcome than hepatectomy alone for HCC patients with PVTT and the survival bene�t is limited to patients who respond to neoadjuvant FOLFOX-HAIC.
Quantifying the Errors Involved in Transferring Suspended Sediment Rating Equations Across Ablation Seasons

Bias-corrected suspended sediment rating equations are developed for the data from six separate ablation seasons in the Glacier de Tsidjiore Nouve basin. These equations differ significantly from one another. Suspended loads as predicted by equations used beyond their year of origin fall in the range of 34-278% of the true load. Mean absolute-percentage errors (MAPE) based on forecasts computed from each year’s model applied to the other 5 years of data range from 35 to 81%, with a mean of 52%. The equivalent MAPE for a lumped multi-year model is 38%, for an autocorrelation-correcting generalized least-squares (GLS) regression model, is 15%, and for a transfer function (TF) developed from a single 25 d period, only 5%. Simple structure-transfer functions appear to be more robust to temporal transfer than the usual type of rating equation, and offer the possibility of greatly improving upon the poor performance of OLS rating equations in providing estimates of suspended loads for periods beyond frames of origin.
Assessing the environmental status of the Zeya River by the state of aquatic communities at the construction site of the Amur Gas Chemical Complex

В ходе оценки состояния сообществ гидробионтов реки Зеи на участке строительства Амурского газохимического комплекса в 2018 г. выявлено 37 таксонов планктонных водорослей рангом ниже рода, 32 вида зоопланктона и 37 видов бентосных организмов. В мае фитопланктон представлен большей частью диатомовыми водорослями, в июле он был более разнообразен, существенную роль играли зеленые, золотистые водоросли и цианобактерии. Зоопланктон в мае включал в основном коловраток, в июле на ряде станций по биомассе доминировали ракообразные. Зообентос в мае представлен преимущественно олигохетами и двустворчатыми моллюсками, тогда как в июле доминировали насекомые. Показатели численности и биомассы фитопланктона, зоопланктона и бентоса невысоки. Индексы Гуднайта и Уитлея, Пареле, Вудивиса, Майера свидетельствуют об относительно благополучных экологических условиях на изученных участках реки. По показателям фито- и зоопланктона, зообентоса воды реки отнесены к олигосапробным. Environmental engineering survey performed at the construction site of the Amur Gas Chemical Complex in 2018 in order to assess the state of aquatic communities of the Zeya River revealed 37 taxa of planktonic algae (below genus rank), 32 species of zooplankton, and 37 species of benthic organisms. In May, phytoplankton was mainly represented by diatoms; in July, it was more diverse, when green algae, golden algae and cyanobacteria all played a significant role. In May, zooplankton included mainly rotifers; in July, crustaceans dominated by biomass at most stations. Zoobenthos was represented in May mainly by oligochaetes and bivalves, while insects dominated in July. The abundance and biomass of phytoplankton, zooplankton, and benthos were low. The Goodnight–Whitley, Parele, Woodiwiss, and Mayer indices testified to relatively favorable environmental conditions in the studied sections of the Zeya River. According to the indicators of phyto- and zooplankton, and zoobenthos, the waters of the river are classified as oligosaprobic.
Triereme: Speeding up hybrid fuzzing through efficient query scheduling

Hybrid fuzzing, the combination between fuzzing and concolic execution, holds great promise in theory, but has so far failed to deliver all the expected advantages in practice due to its high overhead. The cause is the large amount of time spent in the SMT solver. As a result, hybrid fuzzers often lose out to simpler, yet faster techniques. This issue remains despite novel query pruning techniques that reduce the number and complexity of solver queries as they preclude other crucial optimizations like incremental solving. We introduce Triereme, a method to speed up the hybrid fuzzer’s concolic engine by reducing the time spent in the SMT solver. Triereme uses a trie (or prefix tree) data structure to schedule and cache solver queries, exploiting common prefixes. This design is made possible by decoupling concolic tracing from concolic solving. As a result, Triereme manages to reconcile pruning with incremental solving, reaping their combined benefits. In our tests, Triereme speeds up concolic executions by 6.1x on average in FuzzBench [22] and improves coverage progress in 79% of the benchmarks.
CMENet: A Cross-Modal Enhancement Network for Tobacco Leaf Grading

Tobacco leaf grading plays a crucial role in ensuring the quality of tobacco production. For a very long period, the grading process is manually determined by experienced experts. In recent years, some methods have been introduced to automate the grading process by utilizing the reflection images of tobacco leaves. However, the high visual similarity among reflection images at different grades renders a single reflection image insufficient for achieving accurate grading. Besides, the tobacco leaves with an identical grade may have inconsistent visual appearances due to their different planting locations. It is known that an expert integrates multimodal information such as visual, tactile, and planting location cues when performing grading. Inspired by this, we propose an end-to-end Cross-modal Enhancement Network, named CMENet, for automatic tobacco leaf grading. In addition to the common reflection image, the network also adopts a transmission image to incorporate the thickness information in manual grading. CMENet comprises a difference-aware fusion module and a meta self-attention module, enabling the extraction of multimodal information from the transmission image and the planting location, respectively. Experimental results demonstrate that our CMENet achieves a high grading accuracy (80.15%) when incorporating multimodal information, surpassing the performance of existing methods that rely solely on reflection images.
. A conceptual framework for personal reflection in healthcare practice and education

Personal reflection is seen as an essential and trainable professional quality in doctors and other health care practitioners and is increasingly promoted in health care education. A more precise understanding of its nature and value for optimal patient care is needed for its purposeful use in practice and for effective encouragement in education. This article offers a conceptual framework to help recognize, use and encourage personal reflection. At the meta-level of reflective practice, ‘scientific reflection’ is distinguished from ‘personal reflection’, while at the operational level, ‘information processing’ and ‘determinative judgment’ are distinguished from ‘sense making’ and ‘reflective judgment’. The main difference between both modes of reflection is their focus on operational processes. Scientific reflection is mainly oriented towards testing the evidence of expert information processing, thereby aiming for the augmentation of determinative clinical judgment, while personal reflection is mainly oriented towards clarifying the process of sense making, which aims to augment reflective judgment. The article also describes the properties of ‘sense making’ and ‘reflection on sense making’ and examines the implications of this analysis for a more profound definition of reflection as a competence necessary for effective educational encouragement.
Polarization beam splitter in the silicon nitride platform for the 1 μm wavelength band

Efficient and broadband devices able to control the polarizations state are an essential building block of any photonic integration platform. Here, we present the design and the experimental demonstration of an integrated polarization beam splitter realized in silicon nitride platform for the 1 μm optical wavelength band. The device has an experimental insertion loss smaller than 1 dB and a polarization extinction ratio of about 24 dB and 11 dB for TE and TM polarization, respectively
Characterization of Fe 2 O 3 Nanopowder Synthesized by Sol-Gel Method for Energy Storage Applications

: Fe 2 O 3 nanopowder was synthesized by sol-gel method from the iron source material Fe(NO 3 ) 3 . 9H 2 O and citric acid C 6 H 8 O 7 . H 2 O without any refined process. The structure and particles size of the synthesized materials were determined by X-ray diffraction and scanning electron microscopy. The obtained product is α-Fe 2 O 3 with different shapes and sizes depending on the preparation conditions. α-Fe 2 O 3 was applied as anode of iron-air battery. The cyclic voltammetry measurements showed that the size and morphology of Fe 2 O 3 particles affect the electrochemical characteristics of the electrodes. Using K 2 S as an electrolyte additive improved the electrochemical properties of mixing of Fe 2 O 3 and carbon acetylene black (Fe 2 O 3 /AB) electrodes as evidenced by increased redox reaction rate of iron, increased capacity of Fe 2 O 3 /AB electrode and reduced H 2 evolution.
Fractured Smackover Limestone in Northeast Louisiana; Implications for Hydrocarbon Exploitation

ABSTRACT Highly fractured Jurassic Smackover carbonates are present in northeast Louisiana in an area covering more than 2,000 sq mi (5,120 sq km). Vertically, more than 1,000 feet (330 m) of fractured section has been recovered in continuous conventional cores through the Smackover Formation. The most extensively fractured section extends eastward from Union and Ouachita Parishes in Louisiana into west central Mississippi, and northward from the northern part of Richland and Madison Parishes into southeast Arkansas. Wrench faulting together with normal faulting are likely causes of the shear and extension fractures found in the Smackover. The intensity of the fracturing appears to be extremely high when compared to the level observed elsewhere in the Gulf Coast Basin's productive Smackover trend. Regionally, wrench faulting and its related fracturing also may have provided a process for generating vertical and long distance hydrocarbon migration pathways from Middle and Lower Smackover source beds. These source rocks combined with: 1) a subsequent favorable thermal history, 2) an overlying upper Smackover reservoir (developed by depositional, secondary and structural processes), and 3) an effective overlying seal, have yielded a favorable hydrocarbon system. The fractured Smackover has been sparsely drilled and currently the area has no production from these rocks.
Economic Resources, Mortality and Inequality

Using full-population register data from Denmark, this study shows that estimates of the economic gradient in mortality depends on the specific measure of economic resources used, where we investigate permanent income, annual income or financial and housing wealth. Our favorite measure is what we call ’Permanent income’, that is the average level of income over a long interval. We find that when using annual income or current wealth, the gradient is overestimated, unless one controls for a number of additional variables, such as education, civil status and initial health. In the last part of the paper, we compare the results from Denmark to results from the UK. Although the countries are very different in terms of inequality, the estimates of the gradient we find are very similar, suggesting that differential levels of resources (including information), rather than inequality itself, determine the gradient in survival and mortality.
Salt Geometry and Subsalt Trapping in the Enchilada Area, NE Garden Banks, Offshore Louisiana

ABSTRACT Significant discoveries have been made in the Flex Trend, northeastern Garden Banks, at Prospects Enchilada, GB 128 #1, Salsa, GB 172 #1, and Chimichanga, GB 127 #1. Hydrocarbons in Pliocene age, upper slope channelized turbidite sands are located adjacent to and below a major tabular salt mass. Increased confidence in subsalt trap definition relies heavily on integrating fundamental geologic observations into interpretation of a proprietary 3-D prestack depth migrated seismic data set. Key observations include: suprasalt faults that strike parallel to a base salt "keel", morphological differentiation of the salt body from updip tabular salt, approximately 50 m of inverted and repeated condensed section below tabular salt defined by biostratigraphic evaluation, a "faceted" base salt surface characterized by abrupt changes in dip direction, and a more deeply buried regionally extensive salt evacuation surface. Integration of data yields interpretations far more complex than initially proposed. Traps are primarily fault controlled with a significant stratigraphic overprint. These controlling faults are related to deeper salt evacuation and are not strongly expressed above the tabular salt level. The overlying salt body appears comprised of several independent and separately rooted salts. One of the salt roots and the associated base salt keel provide part of the updip trap for subsalt reserves.