Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology for Using a Non-Linear Parameter Estimation Technique for Reactive Multi-Component Solute Transport Modeling in Ground-Water Systems

For a numerical or analytical model to be useful it should be ensured that the model outcome matches the observations or field measurements during calibration. This process has been typically done by manual perturbation of the model input parameters. This research investigates a methodology for using non linear parameter estimation technique (the Marquardt-Levenberg technique) with the multi component reactive solute transport model SEAM3D. The reactive multi-component solutes considered in this study are chlorinated ethenes. Previous studies have shown that this class of compounds can be degraded by four different biodegradation mechanisms, and the degradation path is a function of the prevailing oxidation reduction conditions. Tests were performed in three levels; the first level utilized synthetic model-generated data. The idea was to develop a methodology and perform preliminary testing where “observations” can be generated as needed. The second level of testing involved performing the testing on a single redox zone model. The methodology was refined and tested using data from a chlorinated ethenes-contaminated site. The third level involved performing the tests on a multiple redox zone model. The methodology was tested, and statistical validation of the recommended methodology was performed. The results of the tests showed that there is a statistical advantage for choosing a subgroup of the available parameters to optimize instead of the optimizing the whole available group. Therefore, it is recommended to perform a parameter sensitivity study prior to the optimization process to identify the suitable parameters to be chosen. The methodology suggests optimizing the oxidation-reduction species parameters first then calibrating the chlorinated ethenes model. The results of the tests also proved the advantage of the sequential optimization of the model parameters, therefore the parameters of the parent compound are optimized, updated in the daughter compound model, for which the parameters are then optimized so on. The test results suggested considering the concentrations of the daughter compounds when optimizing the parameters of the parent compounds. As for the observation weights, the tests suggest starting the applied observation weights during the optimization process at values of one and changing them if needed. Overall the proposed methodology proved to be very efficient. The optimization methodology yielded sets of model parameters capable of generating concentration profiles with great resemblance to the observed concentration profiles in the two chlorinated ethenes site models considered.
Photo‐Induced Self‐Cleaning and Wettability in TiO2 Nanocolumn Arrays Obtained by Glancing‐Angle Deposition with Sputtering

In this work, the preparation of regular nanosized columnar structures of titanium dioxide by means of glancing angle deposition with magnetron sputtering (MS‐GLAD) followed by thermal annealing is reported. MS‐GLAD gives rise to metallic titanium columnar structures with regular width and length that after thermal treatment are fully oxidized to form TiO2 nanocolumns that maintain the morphological features of the original metallic ones. Further functionalization with gold by means of multiple ion cluster source results in well‐dispersed Au nanoparticles across the nanocolumns’ surface with a narrow size distribution centered at ca. 8.5 nm. The obtained nanostructures show photocatalytic self‐cleaning activity as shown by the elimination of an organic layer deposited on their surface and the detection of hydroxyl radicals. Photoelectrochemical measurements show a better charge separation at the Au/TiO2 interface. In addition, wettability studies show that the degree of hydrophobicity of the surface is increased by the presence of nanocolumns, both in the dark and under UV illumination. This behavior is not modified by the presence of Au nanoparticles on the surface. The obtained results open up interesting implications in the tunability of the properties of nanostructured thin films for this kind of photo‐activated application.
When the Land Surface Shifts Gears

The land surface provides essential ecosystem services for society. Soils and vegetation take up atmospheric CO2 (Heimann & Reichstein, 2008), their moisture can attenuate wildfires (Forkel et al., 2019, O.S., Hou, et al., 2020), and their evaporative cooling can mitigate hot temperatures (Seneviratne et al., 2012). These services depend on the meteorological conditions; high radiation and low rainfall can induce water stress in ecosystems and consequently limit their services (Figure 1). In semiarid regions experiencing dry seasons such as Central North America and Southern Europe, the lack of water supply limits evapotranspiration, a condition known as water limitation (Mueller & Seneviratne, 2012). This is usually not the case for northern Europe, where normally wet and cloudy weather creates conditions where evaporation rates are limited by energy supply.
Trauma-Informed Parenting Education Support Groups for Mothers in Substance Abuse Recovery

Purpose: A trauma-informed educational support group pilot addressed traumatic stress, substance use disorders (SUDs), and child-rearing for clients who were pregnant and/or parenting young children. Methods: Seeking Safety was adapted with parenting content and delivered at two intensive residential rehabilitation facilities. An explanatory sequential mixed methods approach was used to evaluate the pilot. Forty-eight participants completed starting assessments (intention-to-treat) and 31 graduates completed postgroup surveys (per protocol). Focus group sessions were completed with 19 graduates. Results: Paired samples t tests of intention-to-treat data showed a statistically significant decrease in self-reported symptoms of stress and substance cravings and increases in positive behaviors and parenting self-efficacy. There were no statistically significant differences on lifestyle behaviors, parenting skill, and parenting confidence. Most participants found the intervention acceptable and felt supported to improve their parenting. Discussion: Trauma-informed parenting education support in inpatient rehabilitation settings may offer an important complement to existing SUD and parenting programming.
Crop-specific exposure to extreme temperature and moisture for the globe for the last half century

Global assessments of climate extremes typically do not account for the unique characteristics of individual crops. A consistent definition of the exposure of specific crops to extreme weather would enable agriculturally-relevant hazard quantification. To this end, we develop a database of both the temperature and moisture extremes facing individual crops by explicitly accounting for crop characteristics. To do this, we collate crop-specific temperature and moisture parameters from the agronomy literature, which are then combined with time-varying crop locations and high-resolution climate information to quantify crop-specific exposure to extreme weather. Specifically, we estimate crop-specific temperature and moisture shocks during the growing season for a 0.25∘ spatial grid and daily time scale from 1961 to 2014 globally. We call this the Agriculturally-Relevant Exposure to Shocks (ARES) model and make all ARES output available with this paper. Our crop-specific approach leads to a smaller average value of the exposure rate and spatial extent than does a crop-agnostic approach. Of the 17 crops included in this study, 13 had an increase in exposure to extreme heat, while 9 were more exposed to extreme cold over the past half century. All crops in this study show a statistically significant increase in exposure to both extreme wetness and dryness. Cassava, sunflowers, soybeans, and oats had the greatest increase in hot, cold, dry, and wet exposure, respectively. We compare ARES model results with the EM-DAT disaster database. Our results highlight the importance of crop-specific characteristics in defining weather shocks in agriculture.
Conspecific attraction for conservation and management of terrestrial breeding birds: Current knowledge and future research directions

ABSTRACT Conspecific presence can indicate the location or quality of resources, and animals settling near conspecifics often gain fitness benefits. This can result in adaptive conspecific attraction during breeding habitat selection as demonstrated in numerous terrestrial, territorial birds. There is growing interest in using simulated conspecific social cues (e.g., decoys, broadcasted vocalizations) to manage bird distributions, yet it remains unclear when this approach is likely to succeed. We reviewed published studies to evaluate whether the strength of conspecific attraction in terrestrial birds is mediated by characteristics of species (life history traits), simulated cues (e.g., timing and duration), sites (e.g., quality), and how conspecific attraction was measured. We identified 31 experiments that simulated social cues and compared conspecific settlement between treatment and control sites. We then used phylogenetically controlled meta-regression to assess the impacts of 19 moderators on settlement. Nearly all species included in these experiments were migratory passerines, and social cues generally had a strong, positive influence on their settlement decisions, as the odds of site occupancy were 3.12× (95% CI: 0.81–11.69) greater in treatment sites relative to control sites. Within this group, conspecific attraction was evolutionarily conserved with ≥25.5% (95% CI: 5.1%–65.4%) of the variance in treatment effects explained by phylogenetic relatedness. However, we found no evidence that any covariates influenced the response to social cues, and we posit this stems from limited research specifically designed to identify the mechanisms mediating conspecific attraction. We therefore developed a research agenda that provides a framework for testing mechanistic hypotheses regarding how cue characteristics, species traits, and spatial contexts may mediate attraction to conspecifics. Evaluating these hypotheses will greatly advance the field by helping managers understand when, where, and why simulating social cues can be used to enhance populations of species that are of conservation concern. LAY SUMMARY Simulating the presence of terrestrial birds often attracts breeders of the same species, though how this varies among species, simulated cues, or locations remains unknown. We reviewed 31 experiments that examined conspecific attraction to simulated social cues in terrestrial breeding birds and tested the effects of 19 variables on attraction. These experiments, which focused primarily on migratory songbirds, revealed strong effects of simulated presence on settlement rates, but no strong evidence that any other variables affected settlement rate. Simulating social cues such as vocalizations could be useful for managers interested in attracting migratory songbirds, although whether this extends to other terrestrial species remains unknown. A greater understanding of how and where to use this technique will improve its utility as a tool for enhancing populations of species of conservation concern.
Effect of Soil Nitrogen and Phosphorus on Early Development and Essential Oil Composition of Schinus terebinthifolius Raddi

Abstract Schinus terebinthifolius is a native Brazilian plant. It is wide-spread throughout Brazil and is popularly used as a medicinal plant. Research on this plant is encouraged by the Ministry of Health to investigate its therapeutic potential and to ensure its distribution in the National Health System. Thus, an experiment was carried out in Dourados-MS (22°11'53.8"S and 54°56'0.12"W) to evaluate the effects of nitrogen and phosphorus levels on early development, biomass yield and chemical composition of the essential oil of Schinus terebinthifolius. Five P2O5 rates (20, 120, 200, 280 and 380 kg ha−1) and five N rates (6, 36, 60, 84 and 114 kg ha−1) were used. Treatments were defined using the Plan Puebla III matrix, resulting in nine combinations of P2O5 and N levels, respectively (kg ha−1): 280 and 84; 280 and 36; 120 and 6; 120 and 36; 120 and 84; 200 and 60; 380 and 84, 20 and 36, and 280 and 114. The experimental design was a randomized block with four replications. Plants were harvested 105 and 213 days after transplanting. Phosphorus and nitrogen influenced plant height (174.65 cm), stem diameter (14.32 mm), fresh mass of leaves (169.67 g plant−1) and dry matter of leaves (51.01 g plant−1). Essential oil content (0.16 ml plant−1) was also influenced. The major constituents of the essential oil were α-pinene (15.20-15.56 %), limonene (13.58-14.12 %), sabinene (8.98-9.17 %), β-pinene (8.18-8.99 %), α-copaen (8.98-9.49 %) and z-zalvene (8.56-9.19 %). Thus, we recommend harvesting 213 days after transplanting and growing plants with 249.15 P2O5 and 98 N (kg ha−1).
Designs, Synthesis, Docking Studies, and Biological Evaluation of Novel Berberine Derivatives Targeting Zika Virus

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne flaviviral pathogen that was recently found to be responsible for a dramatically increased number of microcephaly cases and other congenital abnormalities in fetuses and newborns. There is neither a vaccine to prevent nor a drug to treat ZIKA virus infections, at the present time. Berberine (BBR) is a promising drug approved by FDA against flaviviral dengue virus, and BBR derivatives are of great interest in antiviral drug development. In this study, we synthesized eight BBR derivatives by introducing benzyl groups at the C-13 position of BBR and converting to respective 8-oxoberberine derivatives, performed molecular docking analysis, and evaluated their anti-Zika virus activity utilizing a cell‐based phenotypic assay. Binding mode analysis, absolute binding free energy calculation, and structure-activity relationship studies of these compounds with ZIKV NS3 receptor were collected. Amongst these studied compounds, compound 4d with a structure of 13-(2,6-difluoro)-benzylberberine showed high binding affinity (docking score of −7.31 kcal/mol) towards ZIKV NS2B-NS3 protease with critical binding formed within the active site. In the cell-based assay, compound 4d displayed the highest antiviral efficacy against ZIKV with a selective index (SI) of 15.3, with 3.7-fold greater than that of berberine. Together, our study suggests that the potential ZIKV NS2B-NS3 protease inhibitor, compound 4d, is the best alternative to BBR and, further, extends an assuring platform for developing antiviral competitive inhibitors against ZIKV infection.
Control Method of Flexible Manipulator Servo System Based on a Combination of RBF Neural Network and Pole Placement Strategy

Gravity and flexibility will cause fluctuations of the rotation angle in the servo system for flexible manipulators. The fluctuation will seriously affect the motion accuracy of end-effectors. Therefore, this paper adopts a control method combining the RBF (Radial Basis Function) neural network and pole placement strategy to suppress the rotation angle fluctuations. The RBF neural network is used to identify uncertain items caused by the manipulator’s flexibility and the time-varying characteristics of dynamic parameters. Besides, the pole placement strategy is used to optimize the PD (Proportional Differential) controller’s parameters to improve the response speed and stability. Firstly, a dynamic model of flexible manipulators considering gravity is established based on the assumed mode method and Lagrange’s principle. Then, the system’s control characteristics are analyzed, and the pole placement strategy optimizes the parameters of the PD controllers. Next, the control method based on the RBF neural network is proposed, and the Lyapunov stability theory demonstrates stability. Finally, numerical analysis and control experiments prove the effectiveness of the control method proposed in this paper. The means and standard deviations of rotation angle error are reduced by the control method. The results show that the control method can effectively reduce the rotation angle error and improve motion accuracy.
Identification of linear response functions from arbitrary
perturbation experiments in the presence of noise –
Part I. Method development and toy model demonstration

Abstract. Existent methods to identify linear response functions from data require tailored perturbation experiments, e.g. impulse or step experiments. And if the system is noisy, these experiments need to be repeated several times to obtain a good statistics. In contrast, for the method developed here, data from only a single perturbation experiment at arbitrary perturbation is sufficient if in addition data from an unperturbed (control) experiment is available. To identify the linear response function for this ill-posed problem we invoke regularization theory. The main novelty of our method lies in the determination of the level of background noise needed for a proper estimation of the regularization parameter: This is achieved by comparing the frequency spectrum of the perturbation experiment with that of the additional control experiment. The resulting noise level estimate can be further improved for linear response functions known to be monotonic. The robustness of our method and its advantages are investigated by means of a toy model. We discuss in detail the dependence of the identified response function on the quality of the data (signal-to-noise ratio) and on possible nonlinear contributions to the response. The method development presented here prepares in particular for the identification of carbon-cycle response functions in Part II of this study. But the core of our method, namely our new approach to obtain the noise level for a proper estimation of the regularization parameter, may find applications in solving also other types of linear ill-posed problems.
Shape sensing of optical fiber Bragg gratings based on deep learning

Continuum robots in robot-assisted minimally invasive surgeries provide adequate access to target anatomies that are not directly reachable through small incisions. Achieving precise and reliable shape estimation of such snake-like manipulators necessitates an accurate navigation system, that requires no line-of-sight and is immune to electromagnetic noise. Fiber Bragg grating (FBG) shape sensing, particularly eccentric FBG (eFBG), is a promising and cost-effective solution for this task. However, in eFBG sensors, the spectral intensity of the Bragg wavelengths that carries the strain information can be affected by undesired bending-induced phenomena, making standard characterization techniques less suitable for these sensors. We showed in our previous work that a deep learning model has the potential to extract the strain information from the eFBG sensor’s spectrum and accurately predict its shape. In this paper, we conducted a more thorough investigation to find a suitable architectural design of the deep learning model to further increase shape prediction accuracy. We used the Hyperband algorithm to search for optimal hyperparameters in two steps. First, we limited the search space to layer settings of the network, from which, the best-performing configuration was selected. Then, we modified the search space for tuning the training and loss calculation hyperparameters. We also analyzed various data transformations on the network’s input and output variables, as data rescaling can directly influence the model’s performance. Additionally, we performed discriminative training using the Siamese network architecture that employs two convolutional neural networks (CNN) with identical parameters to learn similarity metrics between the spectra of similar target values. The best-performing network architecture among all evaluated configurations can predict the shape of a 30 cm long sensor with a median tip error of 3.11 mm in a curvature range of 1.4 m−1 to 35.3 m−1.
Effect of tribochemical surface treatment technique on the push-out bond strength of novel CAD/CAM post restorations

Objectives: The purpose of this study was to investigate the effect of tribochemical surface treatment (TBC) on the push-out bond strength (PBS) of novel CAD/CAM post materials to root canal dentin. Materials and Methods: Fifty-two freshly extracted human maxillary central incisors were selected and endodontically treated. The teeth were randomly divided into 7 groups according to the post material used: fiber-reinforced composite post as control (FRC), zirconia (ZR), lithium disilicate (LDS), zirconia-reinforced lithium silicate (ZLS), nano-ceramic (RMC_CE), nanoparticle-filled (RMC_LU), and polymer-infiltrated-ceramic (RMC_EN). Then the posts, except FRC, were randomly assigned into two sub-groups according to the surface treatment technique used: Control (no treatment), TBC (CoJet). Following post space preparation, posts were cemented with dual-cure self-adhesive resin cement. A total of 156 sections were obtained (n=12), 3 sections on each root of the tooth. The PBS test was performed for each slice and the results were analyzed by using two-way ANOVA and Tukey HSD tests (α=0.05). The fracture modes were examined. Results: The lowest PBS values were obtained for ZR post groups that untreated (17.24±1.33 MPa) and tribochemical coated (23.09±2.16 MPa) ( p <0.05). The highest PBS values were obtained for untreated RMC_CE (42.45±2.42 MPa) and RMC_LU (45.22±2.32 MPa) groups ( p =0.215) and, tribochemical coated RMC_CE (43.55±2.63 MPa) and RMC_LU (45.38±2.59 MPa) groups ( p =0.821). Significant differences were observed between the remaining post groups ( p <0.05). Tbc has been significantly increased the PBS values of LDS, ZLS, and ZR post groups ( p <0.05). Adhesive failure was the most common failure mode. (n=78). Conclusion: The results of this study proved that the PBS values of the CAD/CAM RMC post groups were higher than the FRC, ZR, LDS, and ZLS post groups, and TBC increased the PBS values of all CAD/CAM post groups.
Towards a Global Entrepreneurial Culture: A Systematic Review of the Effectiveness of Entrepreneurship Education Programs

The number of entrepreneurship education programs (EEP) has increased exponentially over the past two decades. However, a systematic review has not yet been carried out to confirm the effectiveness of EEPs and their presence in the current global world. The main objective of this study was to provide a systematic synthesis of EEP, exploring their characteristics and effectiveness. The search was carried out in the following databases: Scopus, Web of Science, ProQuest and ERIC. Twenty-nine articles were included, with programs developed mainly in European (n=15), Asian (n=6) and American (n=5) countries. The programs were mainly aimed at higher education students (n=17), addressing the development of business plans and entrepreneurial skills. However, greater attention is paid to the entrepreneurial skills in both basic and secondary education. The development of the programs under analysis varied between one week and two years. The results of the studies showed the effectiveness of most of these programs in promoting entrepreneurial skills at all levels of education. In turn, there was not a verified increase in the intention to start a business, since this intention is determined by predisposition, namely socio-cultural and family aspects. This systematic review of the EEP points to the need for this type of program to be preferentially developed since the early school years, since it is at that time that predispositions are created for the development of entrepreneurial skills and intentions. This condition is corroborated by the global geography of the EEP, which demonstrates that, where there is currently an entrepreneurial culture, countries have made a long educational journey, with strategic options from the perspective of educational policies defending entrepreneurship among the younger generations.