Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving Structural Influences on Water‐Retention Properties of Alluvial Deposits

With the goal of improving property‐transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory‐measured water retention (water content vs. potential [θ(ψ)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris‐flow structure based on observed stratification and measured spread of particle‐size distribution. The θ(ψ) data were fit with the Rossi–Nimmo junction model, representing water retention with three parameters: the maximum water content (θmax), the ψ‐scaling parameter (ψo), and the shape parameter (λ). We examined trends between these hydraulic parameters and bulk physical properties, both textural—geometric mean, Mg, and geometric standard deviation, σg, of particle diameter—and structural—bulk density, ρb, the fraction of unfilled pore space at natural saturation, Ae, and porosity‐based randomness index, Φs, defined as the excess of total porosity over 0.3. Structural parameters Φs and Ae were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore‐size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for θmax, including Ae, Φs, and σg, and for both ψo and λ, including only textural parameters, although use of Ae can somewhat improve ψo predictions. Textural properties can explain most of the sample‐to‐sample variation in θ(ψ) independent of deposit type, but inclusion of the simple structural indicators Ae and Φs can improve PTM predictions, especially for the wettest part of the θ(ψ) curve.
Convex Combination Based Reinforcement Learning Algorithm for Dynamic Pricing Demand Response

Demand response (DR) is an effective strategy to correct supply-demand mismatches and achieve energy savings by adjusting the supply side flexible loads promptly. This study balances the profit of service provider (SP) and the cost of expenditure of customers (CUs) after participating in a DR strategy, and formulates the sequential decision problem of dynamic pricing in a hierarchical electricity market (HEM) as a Markov Decision Process. A convex combination based reinforcement learning algorithm is proposed to effectively overcome the overestimation problem and pessimistic underexploration of traditional algorithms and achieve an economical dynamic pricing DR strategy for the HEM.
OPT: Optimal Proposal Transfer for Efficient Yield Optimization for Analog and SRAM Circuits

Yield optimization is one of the central challenges in submicrometer integrated circuit manufacture. However, yield optimization is computationally expensive due to intensive yield estimation and intractable optimization processes. In this work, we first reinvent the state-of-the-art all sensitivity adversarial importance sampling (ASAIS) yield optimization from a Laplace approximation perspective, which also reveals its limitations and suggests improvements. We then generalize it with infinite components and discover the key ingredient in yield optimization to be an effective proposal distribution transfer (OPT) procedure, which is captured using conditional normalizing flow (CNF). To deliver a reliable yield optimization pipeline that accounts for the uncertainty due to the lack of data, we propose sequential ensemble, the first empirical uncertainty estimation that enables tractable Bayesian yield optimization without introducing an extra surrogate for the first time. We conduct extensive experiments against five state-of-the-art baselines and show that the proposed method delivers superior performance: a speedup of 1.01x-11.94x (5.57x on average) with higher yield designs, and most importantly, excellent robustness and consistency in all our experiments on analog and SRAM circuits.
Adaptive Command Filtered Backstepping Control of Connected Vehicles with Nonlinear Disturbances

This paper investigates the problem of adaptive control of connected vehicles subject to uncertain nonlinearity. A third-order nonlinear error model is established, which considers the effect of nonlinear vehicle dynamics and unknown acceleration disturbances. To deal with the nonlinear dynamics and uncertainty, the command filtering technique is used to design the controller, where the radial basis function neural networks (RBFNNs) is introduced to estimate and compensate for the uncertainty. It is evident that the problem of "explosion of complexity" is solved when the backstepping method is involved. Both the individual vehicle stability and the disturbance string stability can be guaranteed by the designed controller. The effectiveness of the proposed method is illustrated by the numerical simulations.
A3Track: Achieving Precise Target Tracking in Aerial Images With Receptive Field Alignment

Tracking arbitrary objects in aerial images presents formidable challenges to existing trackers. Among these challenges, the large-scale variation and arbitrary geometry shape of visual targets are pronounced, resulting in twofold mismatch issues between the feature receptive field and the tracking target. For one, there is a mismatch between the prior receptive field center and arbitrary-shaped targets. For another, the single receptive field mismatches the significantly scale-varied targets in the aerial imagery. To handle these challenges, we propose to achieve precise aerial tracking with receptive field alignment (RFA), dubbed A3Track. The proposed A3Track is comprised of two modules: an RFA module and a pyramid receptive field (PRF) module. First of all, we transform and update the receptive field center progressively, which drives the feature sampling location onto the targets’ main body, thus gradually yielding precise feature representation for arbitrary-shaped targets. We term this progressively updating process as the RFA. Moreover, the PRF module constructs a set of pyramid features for the target, providing a multiscale receptive field to handle the large-scale variation of tracking objects. On four benchmarks, the new tracker A3Track achieves leading performance compared with existing methods and shows consistent improvements over baselines. The project is available at: https://chnleixu.github. io/A3Track-web/.
Persistent Suppression of Hepatic CYP2A1 Expression and Serum Triiodothyronine Levels by Tamoxifen in Intact Female Rats: Dose-Response Analysis and Comparison with 4-Hydroxytamoxifen, Fulvestrant (ICI 182,780), and 17 (cid:1) -Estradiol-3-benzoate

Tamoxifen, a nonsteroidal antiestrogen, is used widely in the treatment of breast cancer and is undergoing evaluation as a chemopreventive agent. In this study, we investigated several long-term effects of tamoxifen in intact adult female rats following acute treatment at various dosages. The effects of ta- moxifen on somatic growth, growth hormone (GH) levels, thyroid hormone levels, and on hepatic cytochrome P450 (P450) expression were compared with those of fulvestrant (ICI 182,780), 17 (cid:1) -estradiol-3-benzoate, and 4-hydroxytamoxifen under the same experimental conditions. Each compound was injected s.c. for two consecutive days, and rats were killed 37 days after treatment. Tamoxifen decreased body weight and serum triiodothyronine (T3) levels at dosages ranging from 0.5 to 200 mg/kg. Ovary weight, uterus weight, peak plasma GH concentration, and hepatic CYP2A1 content were decreased 37 days after treatment with tamoxifen at a dosage of 20 mg/kg, but expression of other P450 enzymes was not affected. However, tamoxifen and 4-hydroxytamoxifen could not be detected in plasma by high performance liquid chromatog-raphy analysis at this time, which suggests that the effects of tamoxifen were mediated indirectly. 4-Hydroxytamoxifen ex-hibited effects similar to those of tamoxifen, indicating that this metabolite contributes to the in vivo activity of tamoxifen.
Enhancing the Reliability of Wearable Cardiac Monitoring using Accelerometer Activity Data

We developed a system for monitoring both activity and electrocardiogram for improved reliability of cardiac monitoring. Additionally, the link between activity information and recorded cardiac information can be used to better incorporate physiological state in analysis in free-living conditions. Our approach uses a machine learning model to predict the activity based on accelerometer data that is subsequently used to estimate cardiac monitoring reliability and linking the heart rate data in to a physical activity. We collected proof-of-concept data from eight healthy volunteers using accelerometers on wrist and on thigh and an electrocardiogram (ECG). The measurement protocol included eight activities (lying, sitting, standing, walking, jogging, walking stairs up and down and cycling). Each measurement was one minute long and the set was repeated 5-10 times per research participant. In addition, three individuals conducted outdoor "free-living" measurements which were used for testing. Time- and frequency-domain features were extracted and XGBoost model was trained. The model was able to recognize correct activity with a mean accuracy of 84 % and 87 % with leave-one-subject-out and leave-half-subject-out cross validation, respectively. The MA-AUC was 0.97 for both cross validations. From the "free-living" test measurements the activities were correctly predicted with a mean accuracy of 81 %. Quality of the ECG varied between activities and was the highest for lying and the lowest for jogging and the quality metric had a strong correlation with heart rate estimation error.
Investigation of a Proposed Four Storey Building Sites Using Geophysical and Laboratory Engineering Testing Methods in Lagos, Nigeria

The spate of engineering structures collapse in Lagos metropolis with its attendant loss of lives and properties has assumed an alarming proportion in recent times. Efforts to mitigate such incidence has necessitated an integrated geophysical and geotechnical investigation of a proposed four storey building sites with a view to determine the suitability of the site for the proposed project. Resistivity investigation, un-drained multi-stage triaxial compression and oedometer consolidation tests were carried out to determine the engineering properties of the subsurface. The results revealed peaty clay to silty sand materials characterized by 35kN/m 2 75kN/m 2 cohesion values, (5°-13°) internal friction, 29.3% 64.5% natural water content and 1.652 – 1.972 Mg/m 3 bulk density. The allowable bearing capacity of 50 kN/m 2 , volume compressibility from 0.115 m 2 /MN to 0.666 m 2 /MN, initial void ratio and consolidation coefficient of 0.779 1.381 and 2.7 m 2 /year 8.3 m 2 /year respectively on the pressure range of 0 to 400 kN/m 2 and estimated settlement values of 114 to 273 mm were obtained for the site materials. These results are indicative of soft to stiff clays and presence of sands and silts in the essentially clayey deposit. The study area is thus underlain by extensive zone of ductile and low strength founding materials having medium to high compressibility and settlement value that exceeds the tolerable limit suitable for founding a four storey building and should therefore be avoided. These characteristics preclude the use of conventional shallow foundations, piles or vibro-replacement up
Making sense of the link between tiller density and pasture production

Interpretation of tiller or shoot density data requires resolution of two independent, confounding effects, namely size/density compensation and what is here called the “leaf area effect”. Size/density compensation implies that at higher herbage mass, individual tillers or shoots are larger, but the population density is correspondingly decreased. The leaf area effect represents difference in sward leaf area for two tiller populations. Such leaf area differences may be environmentally or genetically determined, but must of necessity be expressed through change in tiller size and/or tiller density as “yield components” of leaf area. The theoretical basis for distinguishing between size/density compensation and the leaf area effect is to consider tiller or shoot density and herbage yield, respectively, as X,Y co-ordinates in a size/density plot. When such a plot is drawn on a logarithmic scale, points along a line of -l/2 slope show size/ density compensation with respect to each other. Movement of points to the right or left of the size/ density compensation line is evidence of a leaf area effect. It is shown that when the size/density effects are removed from a data set in this way, rankings of experimental treatments for the leaf area effect can often be reversed compared with the ranking of uncorrected tiller density. Tiller density data corrected for size/density compen-. sation in this way appear to be a useful indicator of sward productivity.
Behavioral characteristics of phosphorus in sediments according to the forms of phosphorus

This study investigates the behavioral characteristics and forms of phosphorus in the sediment according to the oxygen condition (aerobic/anaerobic). In the behavioral characteristics analysis, Al-P and Fe-P concentrations were the highest among the forms of inorganic phosphorus, and therefore had the strongest impact on sorption and release corresponding to environmental condition changes. In the experimental investigation of the inorganic forms of phosphorus in the sediment according to the oxygen condition, we determined that the forms of inorganic phosphorus did not greatly affect the sorption or release reaction because the distribution ratios of the inorganic forms remained constant corresponding to changes of dissolved oxygen (DO) conditions. In contrast, the forms of organic phosphorus in the sediments affected both sorption and release . Furthermore, labile-P and moderately labile-P forms were the major mechanisms of sorption in sediment . Moderately labile-P was the greatest contributor to phosphorus release action in sediment. As environmental changes are important for the behavioral characteristics of phosphorus in sediment, the forms of phosphorus should be considered to have a greater effect, especially in the organic phosphorus case . Therefore, based on the present study results, sediment evaluation aimed at controlling internal pollutants in reservoirs should include an examination of the forms of phosphorus present, as well as the release characteristics of environmental changes, which are influential factors of phosphorus control. Further research in this field is required. with sediments. From the experimental results, the phosphorus concentration increased from 344 mg/kg pre-experiment to 541 mg/kg post-experiment under aerobic condition and to 353.8 mg/kg under anaerobic condition at Site A, indicating that sorption action by sediments was superior, but decreased from 295.6 mg/kg to 152 mg/kg and 176 mg/kg, respectively, at Site B, indicating that release action was superior. This suggests that phosphorus are relatively significant impact factors on phosphorus behavioral characteristics between water body and sediments.
Magnetostratigraphic constraints on the age of the lower Beaufort Group, western Karoo basin, South Africa, and a critical analysis of existing U‐Pb geochronological data

We studied three partially overlapping sections with a composite thickness of ∼600 m in the upper Permian fluvial siltstones and fine‐grained sandstones of the Abrahamskraal Formation, the basal unit of the Beaufort Group, in the Karoo Basin of Western Cape Province, South Africa. Paleomagnetic analysis reveals three components of Natural Remanent Magnetization (NRM). Heating to ∼180°C removes a remanent magnetization parallel to the present‐day field, which is interpreted as a viscous overprint. An intermediate unblocking temperature component is removed by heating to 450°C; this direction is always of normal polarity and is identical to a regional overprint imparted during the Early Jurassic emplacement of the Karoo Large Igneous Province. A high‐temperature component isolated above 450°C is of dual polarity and is interpreted as primary on the basis of a positive reversals test. The virtual geomagnetic pole position for the Abrahamskraal Formation computed from the average high‐temperature characteristic remanent magnetization direction is in agreement with the late Permian directions for stable Gondwana and with previous results from the lowermost Abrahamskraal Formation and Waterford Formation at the Ouberg Pass section. The predominantly normal polarity of this magnetization is in agreement with either a middle‐late Lopingian age (ca. 254–256 Ma) or a late Guadalupian age (ca. 262 Ma) according to the global geomagnetic polarity time scale. We integrate these new results with existing magnetostratigraphic, biostratigraphic, and geochronological results from the Karoo Basin, with particular emphasis on the controversy over zircon age data reported from the underlying Ecca Group.
Event-triggered compensation control of networked control systems with threshold consideration

An ℋ∞ composite control strategy under the event-triggered framework is discussed in this paper. To treat the abrupt data jittering, the transmission of control signal is determined by a mean value based triggering structure. With this structure, composite controllers under three triggering modules are built on the mean value part, the nonlinear part, and the threshold dependent part, respectively. Resorting to Simpson’s rule, sufficient conditions are proposed to make the resultant closed-loop systems be uniformly ultimate boundedness (UUB). The validity of the proposed schemes is verified by an example.
Development in Eastern Europe and the South Caucasus

The publication, Development in Eastern and the South Caucasus, provides detailed country reviews of Armenia, Azerbaijan, Georgia,the republic of Moldova and Ukraine. It explores current economic performance and the challenges of economic performance and the challenges of economic development and competitiveness. Despite differences in economic structures and policy reforms, all these countries face similar challenges arising from the transition from a centralized to a market economy in a climate of rapid political and societal change.
Coupled Temporal Variation Information Estimation and Resolution Enhancement for Remote Sensing Spatial–Temporal–Spectral Fusion

Spatial–temporal–spectral fusion (STSF) of remote sensing imagery can produce data with the highest spatial and spectral resolution, only as well as fine temporal resolution, by integrating images with complementary information in both the temporal and spectral domains. Accuracy of temporal variation is an important guarantee for achieving fidelity fusion in STSF. However, current STSF methods estimate the temporal variation only by utilizing the temporal variation between the observed multispectral image (MSI) and the relationship between MSI and hyperspectral image (HSI), which is difficult to obtain accurate temporal variation. To address this problem, this article proposes a coupled temporal variation information estimation and resolution enhancement for remote sensing image STSF (CTVRE-STSF). The temporal variation information estimation model estimates the temporal variation of the target image, while the resolution enhancement model provides additional constraints for estimating the temporal variation. For the temporal variation information reconstruction model, we build a temporal variation information estimation based on a generalized linear mixed model and use the temporal variation between MSIs. In addition, a resolution enhancement model is constructed to estimate the temporal variation of the target image by incorporating relevant prior knowledge. The introduction of the resolution enhancement model in the prior provides additional constraints on the estimation of the temporal variation high-dimensional information, thus facilitating the resolution improvement. The experimental results on two real datasets demonstrate the effectiveness and superiority of our proposed method over current state-of-the-art methods, especially in terms of spectral fidelity.
Resource Estimation of Quantum Multiplication Algorithms

As quantum computers progress towards a larger scale, it is imperative that the “top” of the computing-technology stack is improved. This project investigates the quantum resources required to compute primitive arithmetic algorithms, particularly multiplication. By using various quantum resource estimators, like Microsoft's Azure Quantum Resource Estimator, one can determine the resources required for numerous quantum algorithms [8]. In this paper, we will provide a comprehensive resource analysis of numerous quantum multiplication algorithms such as Karatsuba, schoolbook, and windowed arithmetic for different qubit platforms (trapped ion, superconducting, and Majorana) using the new Azure Quantum Resource Estimator.
An Energy-Efficient 3D Point Cloud Neural Network Accelerator With Efficient Filter Pruning, MLP Fusion, and Dual-Stream Sampling

Three-dimensional (3D) point cloud has been employed in a wide range of applications recently. As a powerful weapon for point cloud analysis, point-based point cloud neural networks (PNNs) have demonstrated superior performance with less computation complexity and parameters, compared to sparse 3D convolution-based networks and graph-based convolutional neural networks. However, point-based PNNs still suffer from high computational redundancy, large off-chip memory access, and low parallelism in hardware implementation, thereby hindering the applications on edge devices. In this paper, to address these challenges, an energy-efficient 3D point cloud neural network accelerator is proposed for on-chip edge computing. An efficient filter pruning scheme is used to skip the redundant convolution of pruned filters and zero-value feature channels. A block-wise multi-layer perceptron (MLP) fusion method is proposed to increase the on-chip reuse of features, thereby reducing off-chip memory access. A dual-stream blocking technique is proposed for higher parallelism while maintaining inference accuracy. Implemented in an industrial 28-nm CMOS technology, the proposed accelerator achieves an effective energy efficiency of 12.65 TOPS/W and 0.13 mJ/frame energy consumption for PointNeXt-S at 100 MHz, 0.9 V supply voltage, and 8-bit data width. Compared to the state-of-the-art point cloud neural network accelerators, the proposed accelerator enhances the energy efficiency by up to 66.6× and reduces the energy consumption per frame by up to 70.2×.
Marine Debris in the Island of Santa Catarina, South Brazil: Spatial Patterns, Composition, and Biological Aspects

Abstract The prevalence of marine debris is a worldwide issue, especially in coastal areas. Half of the Brazilian population live within 200 km of the coast and generate large amounts of garbage, which is not always sent to an appropriate destination. This study aims to assess patterns of spatial variability and composition of marine debris in the beaches of Florianópolis, an important tourist destination in Brazil. Biological aspects were also assessed. Five beaches were sampled twice, and abundances of litter ranging from 12.8 to 498 items/100 m2 were found, depending on location and time of sampling. Plastic items accounted for almost 90% of the material collected. Only 5% of the items collected showed biological encrustations, suggesting that most items had a local origin. A weak negative correlation was found between the number of items and the number of ghost crab (Ocypode quadrata) open burrows. These results can be used for management purposes and to make comparisons with other coastal cities.