Miracle-dz/UniFAR-FTUs huggingface dataset:
Fracture analysis for materials by a stable generalized/extended finite element method

In this paper, a method is proposed for extracting fracture parameters in isotropic material cracking via a stable generalized/extended finite element method. The numerical results of the stress intensity factors and scaled condition number of the system matrix are presented and compared with different enrichment schemes or those reported in related references. The good agreement and convergence of the results obtained by the developed method with those obtained by other solutions or enrichment schemes proves the applicability of the proposed approach and confirms its capability of efficiently extracting fracture parameters in isotropic materials.
Hemoglobin, albumin, lymphocytes and platelets (HALP) score is a useful predictor of survival in patients with recurrent glioblastoma multiforme treated with bevacizumab plus irinotecan

Purpose: We aimed to investigate whether the HALP score is a predictive marker in patients with recurrent GBM who were given bevacizumab plus irinotecan.Methods: We compared the survival of patients followed up in our clinic with the diagnosis of recurrent GBM and treated with bevacizumab plus irinotecan, according to HALP score.Results: Median PFS and OS were 4.5 (0.9-14.9) and 8 (0.9-21.3) months, respectively. The median PFS of the low HALP score group was 1.85 (1.3-3.37) months, and of the high HALP score group was 4.96 (0.9-14.9) months (p=0.03). The OS of the high HALP score group (9.63 [7.28-11.9]) was statistically higher compared with low HALP score group (2.26 [0.88-3.65]) (p<0.001). In univariate analysis HALP score was a significant prognostic factor; patients with low HALP score had a poorer prognosis than high HALP score (HR: 0.063, p<0.001). The multivariate analysis showed that HALP score (p=0.003), and residual tumor (p=0.029) were significant prognostic factors. In multivariate Cox regression analysis, low HALP score was a significant poor prognostic factor for OS compared with high HALP score (HR: 0.063, p<0.001). Conclusion: We showed that the HALP score at the start of treatment is an independent prognostic factor for PFS and OS in patients with recurrent GBM treated with bevacizumab plus irinotecan. The HALP score, which can be easily calculated by routine tests before chemotherapy, can be used as a predictive marker for bevacizumab treatment decision.
Low Light Alters the Photosynthesis Process in Cigar Tobacco via Modulation of the Chlorophyll Content, Chlorophyll Fluorescence, and Gene Expression

Shading or low light (LL) conditions are a key and necessary cultivation technique in cigar wrapper tobacco production. However, the effect of low light on the photosynthesis in cigar tobacco is not clear. Therefore, this study is designed to know the photosynthesis of cigar tobacco under different light intensities (T200, T100, and T50 μmol m−2 s−1). The results reveal that under low light, T50 especially improved the light interception and increased carbon utilization, as witnessed by a higher specific leaf area and lower specific leaf weight. Low light intensity caused better light interception and carbon utilization in cigar tobacco leaves, and thus thinner leaves are more able to use low light efficiently. The chlorophyll content is related to the photosynthesis process; thus, LL affected the photosynthesis process by lowering the chlorophyll content. Similarly, LL also altered the photosynthetic efficiency by lowering the QY_Lss, qP_Lss, and Rfd_Lss. Additionally, higher expression of Lhcb4.2, Lhcb6, PsbA, PsbB, and PsbD under low light, especially T50, shows that the PSII and antenna proteins complex efficiently utilized the absorbed energy for photosynthesis. Finally, the lower photosynthesis, particularly in T50, is attributed to the downregulation of genes related to NADPH production (petH) and the rubisco enzyme synthesis-related gene (rbcs) for CO2 fixation in the Calvin cycle. Overall, the results show that the photosynthesis is decreased under LL intensities which might be related to lower chlorophyll content and downregulation of petH and rbcs genes.
Ready for Screening: Fast Assessable Hydraulic and Anatomical Proxies for Vulnerability to Cavitation of Young Conifer Sapwood

Research Highlights: novel fast and easily assessable proxies for vulnerability to cavitation of conifer sapwood are proposed that allow reliable estimation at the species level. Background and Objectives: global warming calls for fast and easily applicable methods to measure hydraulic vulnerability in conifers since they are one of the most sensitive plant groups regarding drought stress. Classical methods to determine P12, P50 and P88, i.e., the water potentials resulting in 12, 50 and 88% conductivity loss, respectively, are labour intensive, prone to errors and/or restricted to special facilities. Vulnerability proxies were established based on empirical relationships between hydraulic traits, basic density and sapwood anatomy. Materials and Methods: reference values for hydraulic traits were obtained by means of the air injection method on six conifer species. Datasets for potential P50 proxies comprised relative water loss (RWL), basic density, saturated water content as well as anatomical traits such as double wall thickness, tracheid lumen diameter and wall/lumen ratio. Results: our novel proxy P25W, defined as 25% RWL induced by air injection, was the most reliable estimate for P50 (r = 0.95) and P88 (r = 0.96). Basic wood density (r = −0.92), tangential lumen diameters in earlywood (r = 0.88), wall/lumen ratios measured in the tangential direction (r = −0.86) and the number of radial cell files/mm circumference (CF/mm, r = −0.85) were also strongly related to P50. Moreover, CF/mm was a very good predictor for P12 (r = −0.93). Conclusions: the proxy P25W is regarded a strong phenotyping tool for screening conifer species for vulnerability to cavitation assuming that the relationship between RWL and conductivity loss is robust in conifer sapwood. We also see a high potential for the fast and easily applicable proxy CF/mm as a screening tool for drought sensitivity and for application in dendroecological studies that investigate forest dieback.
High-Power Closed-Loop SMPC-Based Photovoltaic System Characterization under Varying Ambient Conditions

Photovoltaic energy generation potential can be tapped with maximum efficacy by characterizing the source behaviour. Characterization refers to the systematic terminal measurement-based PV modeling which can further facilitate output prediction and fault detection. Most of the existing PV characterization methods fail for high-power PV array due to increased thermal losses in electronic components. Here, we propose a switched-mode power converter-based PV characterization setup which is designed with input filter to limit switching ripple entering into PV array under test, thereby enhancing system life and efficiency. The high resonant frequency input filter ensures its compactness with high-speed characterization capability. To further enhance the system performance, a closed-loop current control of the system is designed for high bandwidth and stable phase margins. Variation of the controller parameters under varying ambient conditions of 200–1000 W/m2 irradiation and 25–70 °C temperature is documented and an adaptive PI controller is proposed. Experimental and simulation results validate the high performance of the closed loop operation of the PV characterization at 1.2 kW range power level in real-time field conditions. Compared to the open loop operation, the closed-loop operation eliminates the waveform ringing by 100% during characterization.
A circularly polarized, high aperture efficiency metasurface antenna

A circularly polarized, high aperture efficiency antenna based on metasurface (MTS), inexpensively fabricated using a standard printed circuit board (PCB) technology, is presented. An array of 8 × 8 cross‐shaped resonators was designed to operate at 3.1 GHz with a 12 cm × 12 cm (i.e., 1.24 λ0× 1.24 λ0 ) footprint size. Each resonator was double fed (by two lines) with appropriate phases to achieve circular polarization. Full characterization of the designed antenna was achieved using full‐wave simulations. The MTS antenna was fabricated using a multilayer PCB technology and experimentally tested. A good agreement between the simulation results and measurements was observed. According to the measurements, with a realized gain of 11.1 dBi, the antenna has an aperture efficiency of 66.7%, which is high compared to many other antennas.
Optimal Design Generation and Power Evaluation in R: The skpr Package

The R package skpr provides a suite of functions to generate and evaluate experimental designs. Package skpr generates D, I, Alias, A, E, T, and G-optimal designs, and supports custom user-defined optimality criteria, N-level split-plot designs, mixture designs, and design augmentation. Also included are a collection of analytic and Monte Carlo power evaluation functions for normal, non-normal, random effects, and survival models, as well as tools to plot fraction of design space plots and correlation maps. Additionally, skpr includes a flexible framework for the user to perform custom power analyses with external libraries and user-defined functions, as well as a graphical user interface that wraps most of the functionality of the package in a point-and-click web application.
Multi-Agent RL Enables Decentralized Spectrum Access in Vehicular Networks

In this paper, we investigate the joint sub-channel and power allocation problem for cellular vehicle-to-everything (V2X) communications, where multiple vehicle-to-infrastructure (V2I) users share the spectrum resources with vehicle-to-vehicle (V2V) users. In particular, a novel channel state information (CSI)-independent decentralized algorithm based on multi-agent reinforcement learning (MARL) is proposed to maximize the sum throughput of V2I links while meeting the latency and reliability requirements of V2V links. Specifically, we implement the individual double dueling deep recurrent Q-networks (D3RQN) and the carefully designed common reward to train the implicitly collaborative agents, through which, each agent optimizes the policy individually based solely on local CSI-independent observations. To handle the non-stationarity induced by multi-agent concurrent learning, we incorporate hysteretic Q-learning and concurrent experience replay trajectory (CERT) to stabilize the training process. Besides, we incorporate the approximate regretted reward (ARR) to alleviate the unstable reward estimation problem caused by shifting environment dynamics. Simulation results demonstrate that the proposed algorithm outperforms the baselines and can achieve close performance compared with the centralized Brute-force method. Furthermore, the proposed CSI-independent design exhibits comparable performance as the CSI-involved version, which sheds some light on the potential to further reduce the signalling overhead of machine learning-based vehicular communication systems.
Detection of the Benthic Dinoflagellates, Ostreopsis cf. ovata and Amphidinium massartii (Dinophyceae), Using Loop-Mediated Isothermal Amplification

For the in situ and sensitive detection of benthic dinoflagellates, we have established an integrated loop-mediated isothermal amplification (LAMP) assay based on Ostreopsis cf. ovata and Amphidinium massartii. To detect the two species, a set of species-specific primers was constructed between the ITS gene and D1–D6 LSU gene, and the reaction temperature, time, and buffer composition were optimized to establish this method. In addition, the specificity of the LAMP primers was verified both in strains established in the laboratory and in field samples collected from the Jeju coastal waters, Korea. With the LAMP assay, the analysing time was within 45 to 60 min, which may be shorter than that with the conventional PCR. The detection sensitivity of the LAMP assay for O. cf. ovata or A. massartii was comparable to other molecular assays (PCR and quantitative PCR (qPCR)) and microscopy examination. The detection limit of LAMP was 0.1 cell of O. cf. ovata and 1 cell of A. massartii. The optimized LAMP assay was successfully applied to detect O. cf. ovata and A. massartii in field samples. Thus, this study provides an effective method for detecting target benthic dinoflagellate species, and could be further implemented to monitor phytoplankton in field surveys as an altenative.
Taking the HIGHWAY to Save Lives on Lake Victoria

Up to one thousand drowning deaths occur every year on Lake Victoria in East Africa. Nocturnal thunderstorms are one of the main culprits for the high winds and waves that cause fishing boats to capsize. The HIGHWAY project was established to develop an Early Warning System for Lake Victoria. Prior to HIGHWAY, weather forecasts for the lake were overly general and not trusted. Under the HIGHWAY project, forecasters from weather service offices in East Africa worked with leaders of fishing communities and Beach Management Units to develop marine forecasts and hazardous-weather warnings that were meaningful to fishermen and other stakeholders. Forecasters used high-resolution satellite, radar, and lightning observations collected during a HIGHWAY field campaign, along with guidance from numerical weather prediction models and a 4.4-km resolution Tropical Africa model, to produce specific forecasts and warnings for 10 zones over the lake. Forecasts were communicated to thousands of people by radio broadcasters, local intermediaries, and via smartphones using the WhatsApp application. Fishermen, ferry-boat operators, and lakeside communities used the new marine forecasts to plan their daytime and nighttime activities on the lake. A socio-economic benefits study conducted by HIGHWAY found that ~75% of the people are now using the forecasts to decide if and when to travel on the lake. Significantly, a 30% reduction in drowning fatalities on the lake is likely to have occurred, which when combined with the reduction in other weather-related losses, generates estimated socio-economic benefits of $44M/year due to the HIGHWAY project activities; the new marine forecasts and warnings are helping to save lives and property.
Developing a new deep learning CNN model to detect and classify highway cracks

Purpose This paper aims to Test the capabilities/accuracies of four deep learning pre trained convolutional neural network (CNN) models to detect and classify types of highway cracks, as well as developing a new CNN model to maximize the accuracy at different learning rates. Design/methodology/approach A sample of 4,663 images of highway cracks were collected and classified into three categories of cracks, namely, “vertical cracks,” “horizontal and vertical cracks” and “diagonal cracks,” subsequently, using “Matlab” to classify the sample to training (70%) and testing (30%) to apply the four deep learning CNN models and compute their accuracies. After that, developing a new deep learning CNN model to maximize the accuracy of detecting and classifying highway cracks and testing the accuracy using three optimization algorithms at different learning rates. Findings The accuracies result of the four deep learning pre-trained models are above the averages between top-1 and top-5 and the accuracy of classifying and detecting the samples exceeded the top-5 accuracy for the pre-trained AlexNet model around 3% and by 0.2% for the GoogleNet model. The accurate model here is the GoogleNet model as the accuracy is 89.08% and it is higher than AlexNet by 1.26%. While the computed accuracy for the new created deep learning CNN model exceeded all pre-trained models by achieving 97.62% at a learning rate of 0.001 using Adam’s optimization algorithm. Practical implications The created deep learning CNN model will enable users (e.g. highway agencies) to scan a long highway and detect types of cracks accurately in a very short time compared to traditional approaches. Originality/value A new deep learning CNN-based highway cracks detection was developed based on testing four pre-trained CNN models and analyze the capabilities of each model to maximize the accuracy of the proposed CNN.
Influence of heating on the measured friction behavior of graphene evaluated under ultra-high vacuum conditions

Atomic scale friction measurements of exfoliated graphene on a silicon oxide substrate were conducted under ultra-high vacuum (UHV) conditions using an atomic force microscope. Two groups of samples were prepared: one that was heated for 3 h at 800 °C in the UHV chamber and one that was not heated in the UHV chamber. The heated sample showed much lower friction, a lower pull-off force during unloading, and no hysteresis between loading and unloading friction measurements on the heated sample compared with the unheated sample. Additionally, a significantly higher tilt of the friction loop was observed in the unheated sample compared with no or very little tilt of friction loops in the heated sample. Interpretation of lateral forces using the Prandtl–Tomlinson model showed a significantly higher energy corrugation on the unheated sample, but similar lateral contact stiffnesses. Furthermore, no hysteresis in either the energy corrugation or lateral contact stiffness was observed in either sample, suggesting that friction hysteresis is less likely correlated with the energy corrugation and lateral contact stiffness. These observations suggest that surface contamination was present on the unheated sample, which is removed or reduced to undetectable levels on the heated sample. Furthermore, the study distinguishes features in the friction behavior induced by surface contamination with those associated with graphene's intrinsic properties.
Enhancing Subseasonal Temperature Prediction by Bridging a Statistical Model With Dynamical Arctic Oscillation Forecasting

This study proposes a hybrid approach to improving subseasonal prediction skills by bridging a conventional statistical model and a dynamical ensemble forecast system. Based on the perfect prognosis method, the phase of the Arctic Oscillation (AO) from the European Centre for Medium‐range Weather Forecasts ensemble forecast system is used as a predictor in a composite based statistical model to predict the wintertime surface air temperature in the Northern Hemisphere. The hybrid model, which employs AO phases predicted by the dynamical model for weeks 1–4, generally outperforms the conventional statistical model for lead times of weeks 2–6. The improved skill score is due to the high accuracy of the AO forecast from the dynamical model and the strong lagged connection between the AO and temperature. This study thus lays the groundwork for the potential use of combining climate variability, statistical relation, and dynamical forecasting.
A broadband circularly polarized stacked microstrip patch antenna with parasitic elements

In this article, a wideband circularly polarized stacked microstrip patch antenna (CP SMPA) with continuous phase feed characteristics is presented. The designed antenna consists of a square‐loop feeding structure as driven element, four rectangular‐patches and four rotated square‐patches as parasitic elements. First, a square‐loop with arc‐shaped strip is designed to obtain 90° phase difference. Second, four rectangular‐patches are placed next to the square‐loop for generating a CP resonant mode through a capacitive coupling method. Third, four rotated square‐patches are arranged at the top of the rectangular‐patches to excite an additional CP resonant mode. Eventually, the designed CP SMPA features a wide −10‐dB impedance bandwidth (IBW) of 32% (5.93 GHz, 4.98–6.88 GHz), and a broad 3‐dB axial ratio bandwidth of 22.8% (6.15 GHz, 5.45–6.85 GHz).
Both diversity and functional composition affect productivity and water use efficiency in experimental temperate grasslands

Many experiments have shown that biodiversity promotes ecosystem functioning and stability and that this relationship varies with resource availability. However, we still have a poor understanding of the underlying physiological and ecological mechanisms driving diversity effects and how they may interact with soil nutrient availability. We collected data in a grassland experiment factorially manipulating fertilization, species richness (SR), functional composition (slow‐growing vs. fast‐growing species) and functional diversity in resource economic traits. We measured above‐ground productivity (AP), nitrogen (N) uptake, photosynthesis and water use efficiency by combining a 15N labelling approach with productivity, gas exchange and stable isotope measurements in 3 years differing in rainfall. We found that sown SR increased AP, N uptake and photosynthesis, suggesting that SR is the most important driver of ecosystem productivity and nutrient cycling. Similarly, photosynthesis was affected by functional composition but not by functional diversity. Water use efficiency was reduced by sown SR for communities dominated by slow‐growing species but not for communities dominated by fast‐growing species. Fertilization increased productivity, N uptake and water use efficiency. The positive effects of high SR on ecosystem functions were independent of fertility levels. Synthesis. Our results provide evidence that high species richness in temperate grasslands could enhance productivity and reduce the negative impacts of drought events. Multiple factors and community characteristics are important in driving enhanced ecosystem functioning in biodiverse grasslands and seem to affect functioning and stability through different mechanisms.
Energy Transfer and Cross-Relaxation Induced Efficient 2.78 μm Emission in Er3+/Tm3+: PbF2 mid-Infrared Laser Crystal

An efficient enhancement of 2.78 μm emission from the transition of Er3+: 4I11/2 → 4I13/2 by Tm3+ introduction in the Er/Tm: PbF2 crystal was grown by the Bridgman technique for the first time. The spectroscopic properties, energy transfer mechanism, and first-principles calculations of as-grown crystals were investigated in detail. The co-doped Tm3+ ion can offer an appropriate sensitization and deactivation effect for Er3+ ion at the same time in PbF2 crystal under the pump of conventional 800 nm laser diodes (LDs). With the introduction of Tm3+ ion into the Er3+: PbF2 crystal, the Er/Tm: PbF2 crystal exhibited an enhancing 2.78 μm mid-infrared (MIR) emission. Furthermore, the cyclic energy transfer mechanism that contains several energy transfer processes and cross-relaxation processes was proposed, which would well achieve the population inversion between the Er3+: 4I11/2 and Er3+: 4I13/2 levels. First-principles calculations were performed to find that good performance originates from the uniform distribution of Er3+ and Tm3+ ions in PbF2 crystal. This work will provide an avenue to design MIR laser materials with good performance.