Miracle-dz/UniFAR-FTUs huggingface dataset:
The support vector regression based on the chaos particle swarm optimization algorithm for the prediction of silicon content in hot metal

An optimal selection approach of support vector regression parameters is proposed based on the chaos particle swarm optimization(CPSO) algorithm; A model based on the support vector regression to predict the silicon content in hot metal is established; and the optimal parameters of which is searched by CPSO. The data of the model are also collected from the No.3 BF in Panzhihua Iron and Steel Group Co. The results show that the proposed prediction model has better prediction results than the neural network trained by particle swarm optimization and least squares support vector regression algorithm; the percentage of samples with absolute prediction error less than 0.03 is higher than 90%, when predicting the silicon content by the proposed model. This indicates that the prediction precision can meet the requirement of practical production and demonstrates that the CPSO is an effective approach for parameter optimization of support-vector regression.
Shear Creep Properties and Creep Model of Gravel Sliding Zone: A Case Study of the Zhoujia Landslide in China

Creep behavior of landslide sliding zones is closely related to the long-term stability and safety of landslides. In this paper, shear creep tests are carried out on undisturbed samples of the gravel sliding zone in the Zhoujia landslide. Creep properties, such as creep rate and long-term strength, of the sliding zone are studied. The result shows that the sliding zone has typical time-dependent behavior. The relationship between the steady strain rate and shear stress can be described by an exponential equation. The long-term strengths of the sliding zone under different normal stresses are determined by using the isochronous curve cluster method. A nonlinear viscoelastic-plastic creep model is developed based on the Nishihara model. The model is shown to be suitable for describing the accelerated creep deformation of the sliding zone. The results obtained are of practical significance for understanding the deformations of the Zhoujia landslide.
Fabrication of an Anti-Icing Aluminum Alloy Surface by Combining Wet Etching and Laser Machining

The phenomenon of icing on the surface of the fuselage while aircraft pass through clouds has an impact on flight safety. This aircraft icing may adversely affect metrological conditions and cause aerodynamic mechanical effects, resulting in a threat to flight safety. This research aims to fabricate an anti-icing surface on a 2524 aluminum alloy material by combining laser machining and wet etching. The microstructure surfaces were obtained by laser, the nanostructured surfaces were obtained by wet etching, and the hierarchical structures were prepared through a combination of these two processes. The contact angle, icing delay performance, icing adhesion, and dynamic water repellency of three kinds of textured surfaces and smooth surface were tested and compared comprehensively through experiments. The experimental findings have shown that the hierarchical surface has the best superhydrophobic properties, and the freezing time of droplets on the hierarchical surface can be extended 10 times. In addition, the ice adhesion on the surface of the hierarchical structure decreased by approximately 75% compared to the untreated samples. The surface of the hierarchical structure showed the best dynamic water repellency. The proposed hybrid laser machining–wet etching fabricating method has the potential to avoid aircraft icing.
Design Methodology of Wire-Driven Parallel Support Systems in the Low Speed Wind Tunnels and Attitude Control Scheme of the Scale Model

Firstly,the wire-driven parallel support system is presented.Secondly,the designing principle of the support systems in a low speed wind tunnel is investigated according to the experimental requirement of a vehicle model.Under the principle,the detail of the design about a new kind of redundantly restrained positioning mechanisms with 8 wires,WDPSS-8,is presented to suspend the 1∶40 scale model of F-15E.By this design,the ranges of pitch,roll and yaw angles of the model at the home pose respectively are-79°～71°,(-90°)～90°,-38°～39°. Finally,based on the systematic dynamics model,a position control scheme in wire length coordinates applying an actuator torque controller is proposed to implement the attitude control of the model.Moreover,the motion stability is proven by a Lyapunov function.
Effects of defacing whole head MRI on neuroanalysis

Recent advances in magnetic resonance (MR) scanner quality and the rapidly improving nature of facial recognition software have necessitated the introduction of MR defacing algorithms to protect patient privacy. As a result, there are a number of MR defacing algorithms available to the neuroimaging community, with several appearing in just the last five years. These various approaches have qualities that have been explored with respect to skull stripping masks or identifiability of the patient in previous works. However, to our knowledge there has been no evaluation of the subsequent impact of these defacing algorithms on a neuroimaging pipeline. In this work, we use six MR defacing algorithms on 179 subjects from the OASIS-3 cohort and 21 subjects from the Kirby 21 dataset, then apply a neuroimaging pipeline to the resultant defaced images. We compare the consistency of the output from the pipeline using the defaced images with the output of the same pipeline without defacing the MR data.
Assessing the replication landscape in experimental linguistics

Replications are an integral part of cumulative experimental science. Yet many scientific disciplines do not replicate enough because novel confirmatory findings are valued over direct replications. To provide a systematic assessment of the replication landscape in experimental linguistics, the present study estimated replication rates for over 50.000 articles across 98 journals. We used automatic string matching using the Web of Science combined with in-depth manual inspections of 210 papers. The median rate of mentioning the search string "replicat*" was as low as 1.6%. Subsequent manual analyses revealed that only eight of these were direct replications, i.e. studies that arrive at the same scientific conclusions as an initial study by using exactly the same methodology. Moreover, only 1 in 1600 experimental linguistic studies reports a direct replication performed by independent researchers. We conclude that, similar to neighboring disciplines, experimental linguistics does not replicate enough.
Experimental Analysis of Wax Micro-Droplet 3D Printing Based on a High-Voltage Electric Field-Driven Jet Deposition Technology

High-voltage electric field-driven jet deposition technology is a novel high resolution micro scale 3D printing method. In this paper, a novel micro 3D printing method is proposed to fabricate wax micro-structures. The mechanism of the Taylor cone generation and droplet eject deposition was analyzed, and a high-voltage electric field-driven jet printing experimental system was developed based on the principle of forming. The effects of process parameters, such as pulse voltages, gas pressures, pulse width, pulse frequency, and movement velocity, on wax printing were investigated. The experimental results show that the increasing of pulse width and duration of pulse high voltage increased at the same pulse frequency, resulting in the micro-droplet diameter being increased. The deposited droplet underwent a process of spreading, shrinking, and solidifying. The local remelting and bonding were acquired between the contact surfaces of the adjacent deposited droplets. According to the experiment results, a horizontal line and a vertical micro-column were fabricated by adjusting the process parameters; their size deviation was controlled within 2%. This research shows that it is feasible to fabricate the micro-scale wax structure using high-voltage electric field-driven jet deposition technology.
Chiral Switch: Between Therapeutical Benefit and Marketing Strategy

Chirality of pharmaceutical substances is an important aspect in drug research because it determines how enantiomers will interact with chiral biological targets. Enantiomers of a chiral drug can have different pharmacokinetic and pharmacological profiles; consequently, using a single pure enantiomer instead of a racemate can enhance the effectiveness and/or safety of the treatment. The tendencies of modern pharmaceutical industry regarding the current market of chiral drugs are divided between the chiral switch of previously used racemates and the development of new enantiopure drugs. The term chiral switch refers to the replacement on the market of a previously approved racemate with its single enantiomer version. The potential advantages of chiral switch can be related to a higher therapeutic index due to better potency, selectivity and fewer adverse effects, faster onset of action and exposure of the patient to lower drug dosages. However, chiral switch is also a strategy that permits manufacturers to keep market exclusivity for chiral pharmaceuticals that have lost their patent protection, even if the pure enantiomers have not demonstrated higher effectiveness or safety profile compared with the racemates.
Laccase activities from three white-rot fungal species isolated from their native habitat in North China using solid-state fermentation with lignocellulosic biomass

Laccase has huge potential application in all aspects of biotechnology due to the ability of laccase to oxidize a wide range of phenolic and non-phenolic compounds. The future success of such applications requires large amounts of laccase with low costs. White-rot fungi are important groups of laccase production. In this study, three white-rot fungi, Phlebia acerina Han 618, Trametes hirsuta Han 726, and Coriolopsis trogii Han 751, isolated from a native North China habitat, were identified by the method of molecular biology and preliminary screening of the ability of laccase-production by guaiacol selection medium. Then they were fermented on different lignocellulosic biomass. Three species showed consistency in preference of lignocellulosic biomass, and the presence of stalk of Sorghum bicolor was more suitable for secreting laccase. The capacity of laccase secretion from different species was significantly different. The capacity of secreting laccase of C. trogii Han 751 was superior to that of P. acerina Han 618 and T. hirsuta Han 726. The discovery of a new strain with superior capacity of secreting laccase and suitable lignocellulosic biomass were helpful for laying a foundation for the optimization of the fermentation conditions for the highest laccase production, the isolation and purification of laccase, and the industrial application of laccase.
Eddy Covariance Data Reveal That a Small Freshwater Reservoir Emits a Substantial Amount of Carbon Dioxide and Methane

Small freshwater reservoirs are ubiquitous and likely play an important role in global greenhouse gas (GHG) budgets relative to their limited water surface area. However, constraining annual GHG fluxes in small freshwater reservoirs is challenging given their footprint area and spatially and temporally variable emissions. To quantify the GHG budget of a small (0.1 km2) reservoir, we deployed an Eddy covariance (EC) system in a small reservoir located in southwestern Virginia, USA over 2 years to measure carbon dioxide (CO2) and methane (CH4) fluxes near‐continuously. Fluxes were coupled with in situ sensors measuring multiple environmental parameters. Over both years, we found the reservoir to be a large source of CO2 (633–731 g CO2‐C m−2 yr−1) and CH4 (1.02–1.29 g CH4‐C m−2 yr−1) to the atmosphere, with substantial sub‐daily, daily, weekly, and seasonal timescales of variability. For example, fluxes were substantially greater during the summer thermally stratified season as compared to the winter. In addition, we observed significantly greater GHG fluxes during winter intermittent ice‐on conditions as compared to continuous ice‐on conditions, suggesting GHG emissions from lakes and reservoirs may increase with predicted decreases in winter ice‐cover. Finally, we identified several key environmental variables that may be driving reservoir GHG fluxes at multiple timescales, including, surface water temperature and thermocline depth followed by fluorescent dissolved organic matter. Overall, our novel year‐round EC data from a small reservoir indicate that these freshwater ecosystems likely contribute a substantial amount of CO2 and CH4 to global GHG budgets, relative to their surface area.
Detection of Soil Freeze/Thaw States at a High Spatial Resolution in Qinghai-Tibet Engineering Corridor

The freeze/thaw (F/T) state of the soil is an essential indicator for permafrost monitoring. However, current soil F/T products with a coarse spatial resolution (>1 km) have limited their use on a fine scale. In this letter, a new approach integrating two microwave sensors [i.e., Sentinel-1 and advanced microwave scanning radiometer 2 (AMSR-2)] is developed to identify the soil F/T state at a spatial resolution of 10 m in the Qinghai-Tibet engineering corridor (QTEC). Using a linear regression model to integrate the coarse AMSR-2 data with the finer Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST), the frozen frequency product at a 1-km resolution can be obtained. Then, the high-spatial-resolution F/T map based on Sentinel-1 synthetic aperture radar (SAR) time-series images can be produced using the threshold extracted from each pixel of frozen-frequency products. We tested soil F/T results via both visual and quantitative evaluations. The overall accuracy of the 10-m soil F/T map achieves 84.63% and 77.09% for ascending and descending orbits based on four meteorological stations, respectively.
Large-Scale G Protein-Coupled Olfactory Receptor–Ligand Pairing

G protein-coupled receptors (GPCRs) conserve common structural folds and activation mechanisms, yet their ligand spectra and functions are highly diverse. This work investigated how the amino-acid sequences of olfactory receptors (ORs)—the largest GPCR family—encode diversified responses to various ligands. We established a proteochemometric (PCM) model based on OR sequence similarities and ligand physicochemical features to predict OR responses to odorants using supervised machine learning. The PCM model was constructed with the aid of site-directed mutagenesis, in vitro functional assays, and molecular simulations. We found that the ligand selectivity of the ORs is mostly encoded in the residues up to 8 Å around the orthosteric pocket. Subsequent predictions using Random Forest (RF) showed a hit rate of up to 58%, as assessed by in vitro functional assays of 111 ORs and 7 odorants of distinct scaffolds. Sixty-four new OR–odorant pairs were discovered, and 25 ORs were deorphanized here. The best model demonstrated a 56% deorphanization rate. The PCM-RF approach will accelerate OR–odorant mapping and OR deorphanization.
GAN–argcPredNet v1.0: a generative adversarial model for radar echo extrapolation based on convolutional recurrent units

Abstract. Precipitation nowcasting plays a vital role in preventing meteorological disasters, and Doppler radar data act as an important input for nowcasting models. When using the traditional extrapolation method it is difficult to model highly nonlinear echo movements. The key challenge of the nowcasting mission lies in achieving high-precision radar echo extrapolation. In recent years, machine learning has made great progress in the extrapolation of weather radar echoes. However, most of models neglect the multi-modal characteristics of radar echo data, resulting in blurred and unrealistic prediction images. This paper aims to solve this problem by utilizing the features of a generative adversarial network (GAN), which can enhance multi-modal distribution modeling, and design the radar echo extrapolation model GAN–argcPredNet v1.0. The model is composed of an argcPredNet generator and a convolutional neural network discriminator. In the generator, a gate controlling the memory and output is designed in the rgcLSTM component, thereby reducing the loss of spatiotemporal information. In the discriminator, the model uses a dual-channel input method, which enables it to strictly score according to the true echo distribution, and it thus has a more powerful discrimination ability. Through experiments on a radar dataset from Shenzhen, China, the results show that the radar echo hit rate (probability of detection; POD) and critical success index (CSI) have an average increase of 21.4 % and 19 %, respectively, compared with rgcPredNet under different intensity rainfall thresholds, and the false alarm rate (FAR) has decreased by an average of 17.9 %. We also found a problem during the comparison of the result graph and the evaluation index. The recursive prediction method will produce the phenomenon that the prediction result will gradually deviate from the true value over time. In addition, the accuracy of high-intensity echo extrapolation is relatively low. This is a question worthy of further investigation. In the future, we will continue to conduct research from these two directions.
The Spatiotemporal Evolution of Rainfall Extremes in a Changing Climate: A CONUS‐Wide Assessment Based on Multifractal Scaling Arguments

Given the rapidly changing climate, accurate spatiotemporal information on the evolution of extreme rainfall events is required for flood risk assessment and the design of resilient infrastructure. Consequently, various research efforts have focused on investigating the appropriateness of various parametric and non‐parametric approaches in modeling the observed changes in the frequency of extreme rainfall over time. Yet, the assumption of stationarity, or the change of model parameters when accounting for nonstationary rainfall, may magnify estimation uncertainty of rain rates associated with low exceedance probabilities. Moreover, the use of climate model results may yield inconclusive outcomes, given the existence of epistemic uncertainties in the frequency of extreme events developing on smaller spatial scales or over complex terrain. Herein, we employ a parametric approach based on multifractal scaling arguments, along with high‐resolution (4‐km) hourly precipitation estimates covering a 40‐year period over CONUS, to derive Intensity‐Duration‐Frequency curves and investigate the spatiotemporal evolution of extreme rainfall over a wide range of characteristic temporal scales and exceedance probability levels. Considering the robustness of the multifractal models even when fitted to short rainfall records, we uniquely apply the framework to sequential 10‐year segments of data, where the rainfall process can be reasonably assumed stationary. The obtained results reveal that existing infrastructure may be severely impacted by the intensification of precipitation extremes due to climate change, with the observed trends being significantly influenced by the topography and rainfall climatology of each region, while depending on the averaging durations and return periods of interest.
95 Incidence of Hypertrophic Scar Diagnosis in Burn Patients Prescribed Glucocorticoids

Abstract Introduction Despite advancements in burn care, the optimal treatment to prevent or treat hypertrophic scars is still elusive. Therefore, the objective of this study is to compare the efficacy of five glucocorticoid medications commonly used in the treatment of hypertrophic scarring in burned patients using a large patient database. Methods Patients diagnosed with hypertrophic scarring, hypertrophic disorders of the skin, or scar conditions and fibrosis of skin at least one day after burn injury were identified in the TriNetX database. Hydrocortisone, methylprednisolone, dexamethasone, triamcinolone, and prednisone were the glucocorticoids investigated. Those who received a glucocorticoid on the same day or any time after the incidence of burn injury were compared to those who did not take glucocorticoids in the previous five years. Patients were stratified into four groups based on percent total body surface area (TBSA) burned: 0-9%, 10-19%, 20-39%, and 40-100%. A total of 165,041 burned patients were found who did not receive glucocorticoids, and 66,652 burn patients who received glucocorticoids after injury. Statistical analysis for comparison included a risk ratio with a significance defined as a p-value < 0.05. Results In all burn patients identified, the risk of hypertrophic scarring diagnosis was reduced with methylprednisolone (RR=0.60, p< 0.001) and prednisone (RR=0.37, p< 0.001), while it was increased with dexamethasone (RR=2.48, p< 0.001). Stratification based on %TBSA burned showed that diagnosis of hypertrophic scarring was reduced in the < 10% TBSA group with methylprednisolone (RR=0.49, p< 0.001) and prednisone (RR=0.33, p< 0.001), while it was increased with dexamethasone (RR=3.6, p< 0.001). Similarly, in the 10-19% TBSA group, the risk was reduced with prednisone (RR=0.57, p=0.024) while increased with dexamethasone (RR=2.2, p< 0.001). No significant effect was observed with hydrocortisone or triamcinolone with any of the %TBSA groups examined. Patients treated with dexamethasone continued to show increased risk for hypertrophic scar diagnosis with 20-39% TBSA (RR=1.69, p< 0.001) and 40-100% TBSA (RR=1.87, p< 0.001). Conclusions While methylprednisolone and prednisone decreased the risk of hypertrophic scarring diagnosis among all burn patients identified, dexamethasone showed an increased risk of hypertrophic scarring diagnosis in all burn patients and in each %TBSA stratified group.
Chemical Composition, Antibacterial and Anti-Quorum Sensing Activities of Pimenta dioica L. Essential Oil and Its Major Compound (Eugenol) against Foodborne Pathogenic Bacteria

The Pimenta dioica essential oil and its main compound (eugenol) were tested for their antibacterial potency against eight Gram-negative and Gram-positive bacteria implicated in food intoxication. This essential oil and its main component were evaluated for their ability in inhibiting Quorum sensing (QS)-dependent mechanisms such as motility in Pseudomonas aeruginosa PAO1, production of violacein by Chromobacterium violaceum and biofilm formation on stainless steel and glass surfaces. Our results demonstrated that P. dioica essential oil and eugenol were active against all tested strains with a maximum of inhibition against Listeria monocytogenes CECT 933 (26.66 ± 0.57 mm). The minimal inhibitory concentration (MIC) value of the tested essential oil and eugenol was about 0.048 mg/mL for all strains. The obtained results demonstrated that 4CMI eugenol inhibited foodborne strains biofilm formation on the glass strips by 73.79% and by 75.90% on polystyrene. Moreover, 0.048 mg/mL (MIC) of P. dioica essential oil inhibited the violacein production by 69.30%. At 100 µg/mL, P. dioica oil and eugenol affected the motility of PAO1 by 42.00% and 29.17%, respectively. Low concentrations of P. dioica essential oil are active against the quorum sensing phenomena and biofilm potency. Thus, this essential oil could be further investigated for new molecules useful for the treatment of toxi-alimentary infections.