Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of non-linear models to describe the growth in the Andalusian turkey breed

Abstract Seven non-linear growth models were compared in the Andalusian turkey, an endangered native breed. To this aim, turkeys were weekly weighted until they reached 35 weeks. The goodness-of-fit and flexibility criteria of Brody, Von Bertalanffy, Verhulst, Logistic, Gompertz, Richards, and Sinusoidal growth models were evaluated to quantify their ability to describe the biological growth curve. Goodness-of-fit criteria were assessed comparing the mean squared error (MSE) and adjusted determination coefficient (Pseudo-R2), while the flexibility criteria of Akaike (AIC) and Bayesian information criteria (BIC) were evaluated to quantify the explanatory and predictive ability of the models tested. Afterward, all criteria were considered in a combined index to determine the most efficient model to describe and predict growth patterns. The best-fitting model for males growth was Logistic (MSE: 250,349.87; Pseudo-R2: 0.97) which also reported the best explanatory and predictive properties (AIC: 18,949.25; BIC: 18,963.24), while best goodness-of-fit criteria, explanatory and predictive capacity in females were reported for the Richards model (MSE: 144,432.45; Pseudo-R2: 0.95; AIC: 17,529.83; BIC: 17,549.02, respectively). Von Bertalanffy and Richards models underestimated the weight at early age stages, contrary to Logistic and Verhulst models. The asymptotic weight was higher in males than in females at all evaluated models, being 11,085.37 g for Logistic and 5,706.38 g for Richards, respectively. In conclusion, a marked sexual dimorphism is evident, with females reaching maturity earlier than males. The higher inflection point in males may enable their relatively easier commercial standardisation than in turkey hens. Highlights Logistic was the best fitting model for males' growth and Richards for females. Females reach maturity earlier than males with higher rates of maturity. Andalusian turkey breed shows an intense sexual dimorphism.
Mother-Son Communication about Sex: Exploring Associations with Emerging Adult Sons’ Sexual Self-Esteem, Anxiety, and Satisfaction

Abstract Parent-child communication about sex and sexuality during adolescence may have long-lasting effects on children’s sexual self-concept and sexual health. As such, the present study explored the connection between mother-son communication about sex and sexuality while growing up and emerging adult sons’ sexual well-being. The sample consisted of 137 sexually active men between the ages of 18 and 23. The findings revealed that open mother-son communication was negatively associated with sons’ sexual anxiety and positively associated with sons’ sexual satisfaction, but that sons’ sexual self-esteem and anxiety did not account for the association between mother-son communication and sons’ sexual satisfaction. These findings provide preliminary evidence that sons’ perception that their mother provided an open and non-judgmental communication environment for discussing sex during adolescence is associated with positive sexual outcomes for emerging adult sons later in life. These findings and their implications are explored through the lens of communication privacy management theory.
School as a site of transformative adult learning: parents’ experiences of Polish democratic schools

ABSTRACT This paper aims to explore transformative learning processes of parents involved in informal, parent-established democratic schools, which are novel educational initiatives in Poland. The author argues that the distinctive educational ideology and the practice of such schools expose parents to new understandings of education, the child and the parent, which prompts their transformative learning. Drawing on the conceptual framework of transformative learning and practice-based learning theories, the author analyses interviews with parents to identify the trajectory of parental learning, the scope of their transformation and the factors that enhance or hinder it. Primarily concerning the respondents’ personal identities and part-identities as parents, the transformation entails changes in their value systems, definitions of a good life, perceptions of the child and parenting practices. While its potential to instigate broader social change currently appears limited, parental transformative learning exemplifies significant emancipatory biographical praxis.
Child Support in Shared Care Cases: Do Child Support Policies in Thirteen Countries Reflect Family Policy Models?

Increasingly, parents in separated families equally share care of their children post-separation. In this article we extend a well-known family policy model to generate hypotheses about the level of child support to be paid by separated parents when children live primarily with their mother (‘sole custody’) in contrast to when children spend equal time with both parents (‘shared care’). We test these hypotheses with data collected from thirteen countries. In sole custody cases, countries with an earner-carer policy model do have lower child support expectations than countries with a traditional family policy model or a market-oriented model, as predicted. Countries with a traditional family policy model do have the highest orders in the shared case, as predicted. However, there is as much variation within models as there is between, suggesting new analytic frameworks for considering child support in family policy need to be developed.
Phenotyping and Validation of Root Morphological Traits in Barley (Hordeum vulgare L.)

Barley (Hordeum vulgare L.) is an important cereal crop, but its sustainable production is significantly hampered due to the presence of various edaphic stresses. Understanding the variability in root morphological traits among diverse barley genotypes is critical for selecting those with suitable root traits for breeding new cultivars better adapted to stress environments. Root morphological traits in an early growth stage (30 days after transplanting) in a panel of 189 barley genotypes (mostly advanced breeding lines) were assessed using a semi-hydroponic phenotyping platform followed by a validation experiment of eight genotypes with contrasting root systems in two soils. The phenotyping experiment showed large variation (coefficient of variation values ≥ 0.25) in 16 of 26 measured root and shoot traits. A strong correlation among most of the selected traits was identified. Principal component analysis indicated four principal components (eigenvalues >1) captured 79.5% of the total variation. Root traits, including total root length, root length at various depths, root diameter and root length ratio (top 20 cm vs. lower section), could be considered in the barley breeding programs. Consistent ranking of the selected eight genotypes based on root biomass and root length in both the semi-hydroponic system and the columns with two different soils confirmed root trait performance in different growth environments as well as the reliability of the phenotyping method. This study identified phenotypic variability in root morphological traits in barley genotypes in the early growth stage. The genotypic variability in root traits represents a basis for mapping quantitative trait loci (QTLs) and molecular markers, particularly focused on breeding lines with optimal root properties for the efficient acquisition of soil resources and adaptation to drought and other abiotic stresses.
5G and 6G Broadband Cellular Network Technologies as Enablers of New Avenues for Behavioral Influence with Examples from Reduced Rural-Urban Digital Divide

Two of the key information technologies with very high expectations to change our contemporary society are the fifth generation broadband cellular network technologies, which are already emerging to markets, and the foreseen sixth generation broadband cellular network technologies currently under research and development. The core promise of these next generation technologies lies especially in lower latency for providing users feedback on their behavior; thus, growing opportunities for influencing users in their everyday contexts. This viewpoint article seeks to discuss how these opportunities may impact future information technology in general and especially persuasive design and research before 2030. In addition, we will address challenges regarding the promise of 5G and 6G technologies. Information and communication technology can support individuals’ behavioral change only if they can access the technology. In this article, we will exemplify this by presenting possible ways to minimize the digital divide between rural and urban areas, wherein lies a general danger that the divide would increase further.
Vision-Cloud Data Fusion for ADAS: A Lane Change Prediction Case Study

With the rapid development of intelligent vehicles and Advanced Driver-Assistance Systems (ADAS), a new trend is that mixed levels of human driver engagements will be involved in the transportation system. Therefore, necessary visual guidance for drivers is vitally important under this situation to prevent potential risks. To advance the development of visual guidance systems, we introduce a novel vision-cloud data fusion methodology, integrating camera image and Digital Twin information from the cloud to help intelligent vehicles make better decisions. Target vehicle bounding box is drawn and matched with the help of the object detector (running on the ego-vehicle) and position information (received from the cloud). The best matching result, a 79.2% accuracy under 0.7 intersection over union threshold, is obtained with depth images served as an additional feature source. A case study on lane change prediction is conducted to show the effectiveness of the proposed data fusion methodology. In the case study, a multi-layer perceptron algorithm is proposed with modified lane change prediction approaches. Human-in-the-loop simulation results obtained from the Unity game engine reveal that the proposed model can improve highway driving performance significantly in terms of safety, comfort, and environmental sustainability.
The rigid adsorbent lattice fluid model for pure and mixed gas adsorption

The ability of macroscopic models to predict correctly multicomponent systems from pure component isotherms alone remains a major challenge in adsorption engineering. A new fundamental thermodynamic model for multicomponent adsorption of molecules of different size in nanoporous materials is derived from a modified lattice fluid model. Expressions for the fugacity coefficients are derived and the resulting equilibrium relationships are shown to be consistent with a type I adsorption isotherm. Expressions are obtained for the saturation capacity, the Henry law constant and the adsorption energy. The model is applied to silicalite and the parameters for the adsorbent are obtained from crystal properties, the adsorption energy of n-alkanes and Henry law constants for 6 gases. Model predictions for gas adsorption up to 20 bar are shown to be comparable to empirical adsorption isotherm equations. Extension to binary and quaternary systems shows good a priori predictive capability when compared to experimental data.
Preplant Soil Incorporation of Compost to Mitigate Replant Disease: Soil Biological Factors Associated with Plant Growth Promotion in Orchard Soil

Abstract Preplant soil incorporation of compost has previously shown potential to suppress Pratylenchus penetrans populations and improve replant establishment of newly planted fruit trees at old orchard sites. Using a greenhouse experiment, we evaluated the effects of preplant incorporation of three compost amendments (agricultural waste compost, yard trimmings compost, and municipal waste compost) on growth of apple seedlings, P. penetrans populations, microbial populations associated with soil suppressiveness, and microbial activity using soil collected from three orchard sites. We also aimed to identify the biological factors that were most strongly associated with enhanced plant growth in compost-amended soil. In four out of nine compost type × soil combinations, compost improved apple seedling growth relative to the control. In four out of nine compost type × soil combinations, compost reduced P. penetrans root infestation relative to the control, and in one compost type × soil combination, compost amendment increased P. penetrans root infestation. Composts stimulated soil microbial activity and abundance, resulting in greater populations of Pseudomonas spp. in soil in seven of the nine compost type × soil combinations. In a step-wise multiple linear regression, P. penetrans root infestation and the total abundance of fungi in soil accounted for the most variance in plant biomass, with increases in both variables correlated with reduced seedling biomass. Overall, composts show variability in the capacity to promote the establishment of fruit trees in orchard soil. Future research should be directed toward understanding variability in compost-induced plant growth promotion among different orchard soils and compost types.
Active Exploration for Obstacle Detection on a Mobile Humanoid Robot

Conventional approaches to robot navigation in unstructured environments rely on information acquired from the LiDAR mounted on the robot base to detect and avoid obstacles. This approach fails to detect obstacles that are too small, or that are invisible because they are outside the LiDAR’s field of view. A possible strategy is to integrate information from other sensors. In this paper, we explore the possibility of using depth information from a movable RGB-D camera mounted on the head of the robot, and investigate, in particular, active control strategies to effectively scan the environment. Existing works combine RGBD-D and 2D LiDAR data passively by fusing the current point-cloud from the RGB-D camera with the occupancy grid computed from the 2D LiDAR data, while the robot follows a given path. In contrast, we propose an optimization strategy that actively changes the position of the robot’s head, where the camera is mounted, at each point of the given navigation path; thus, we can fully exploit the RGB-D camera to detect, and hence avoid, obstacles undetected by the 2D LiDAR, such as overhanging obstacles or obstacles in blind spots. We validate our approach in both simulation environments to gather statistically significant data and real environments to show the applicability of our method to real robots. The platform used is the humanoid robot R1.
Effect of nitrogen regulation on berry quality and flavonoids during veraison stage

Abstract Nitrogen regulation can effectively promote the improvement of berry components and the formation of flavor compounds in wine grapes. In order to understand the effects of foliar nitrogen spraying on grape quality and flavonoid substance, took Cabernet Sauvignon as the test subject, grape leaves were sprayed by ammonium sulfate, calcium ammonium nitrate, urea, phenylalanine, and glutamate during veraison, and clear water was used as the control. The results showed that spraying ammonium sulfate could improve the contents of soluble solids, anthocyanins, and total phenols of grape berries; spraying phenylalanine significantly increased the content of titratable acid and tannin and decreased the ratio of sugar to acid in grape berries; compared with the control group, spraying glutamate could significantly upregulate some flavonol monomers; spraying calcium ammonium nitrate can adjust the monomer content of some flavanols; urea spraying significantly increased the contents of most anthocyanins, flavanols, and flavonol and increased the contents of total anthocyanins, total flavanols, and total flavonol in grape skins, laying a foundation for the improvement of the nutritional value of grapes and wine in the future.
Precision force control of an underactuated stance leg exoskeleton for human performance augmentation

Lower limb exoskeleton which augments the human performance is a wearable human–machine integrated system used to assist people carrying heavy loads. Recently, underactuated lower limb exoskeleton systems with some passive joints become more and more attractive due to the advantages of smaller weight, lower system energy consumption and lower cost. However, because of the less of control inputs, the existed control methods of fully actuated exoskeletons cannot be extended to underactuated systems, which makes the robust controller design of underactuated lower limb exoskeletons becomes more challenged. This article focuses on the high-performance human–machine interaction force control design of underactuated lower limb exoskeletons with passive ankle joint. In order to solve the reduction of control inputs, the holonomic constraint from the wearer is considered, which help transform the dynamics of 3-degree-of-freedom underactuated exoskeleton in joint space into a 2-degree-of-freedom fully actuated system in Cartesian space. A two-level interaction force controller using adaptive robust control algorithm is proposed to effectively address the negative effect of various model uncertainties and external disturbances. In order to facilitate the control parameter selection, a gain tuning method is also presented. Comparative simulations are carried out, which indicate that the proposed two-level interaction force controller achieves smaller interaction force and better robust performance to various modeling errors and disturbances.
Magmatic Underplating Thickening of the Crust of the Southern Tibetan Plateau Inferred From Receiver Function Analysis

How the crust thickens to double the normal continental crust is a key issue in the formation of the Tibetan Plateau. Using data recorded by a new 2‐D broadband seismic array, we extracted the crustal thicknesses and average VP/VS ratios in central Tibet from receiver functions. In our results, the crustal thicknesses increase southward, while the crustal average VP/VS ratios generally decrease southward. The lower VP/VS ratios in the crust seem to be produced by higher silica contents. We suggest that upper mantle magmas induced by the subduction of Indian lithospheric and Tethyan oceanic slabs underplating the overriding crust differentiate into felsic melts and mafic residues. Mafic residues delaminate into the mantle due to their high density, while felsic magmas are retained in the crust. As a result, crustal thickening in southern Tibet is accompanied by increasing silica contents.
Fast And Accurate Homography Estimation Using Extendable Compression Network

Fast and accurate homography estimation between images is crucial for relative pose estimation in autonomous exploration. Recently, learning-based methods have been proposed to use semantic information to solve challenging cases like large displacements, dynamic scenes, and illumination changes, where traditional methods may degrade. However, most existing methods have large model sizes and low inference speed, which make them infeasible in terminal devices and real-time scenarios. In this paper, we build a basic network based on the ShuffleNetV2 compressed units, which can extremely accelerate the homography estimation process. To further deal with the large displacements, we extend the basic network to a multiscale weight-shared form to additionally process the half-scale input. In the case of sufficient computational resources, this basic network can also be extended to a recurrent coarse-to-fine form to achieve the most accurate results. Experimental results show that our extendable networks can well balance the accuracy and inference speed, and the sizes of all models are less than 9MB.
Four practices for conducting feminist participatory action research with young women

While there has been an increase in action research explicitly defined as feminist in orientation, there has not been sufficient discussion on the actual translation of feminist theory into research practices. The aim of this article is to contribute to the growing body of knowledge labelled Feminist Participatory Action Research (FPAR) by articulating specific research practices for conducting research with young women who are negotiating social injustice and marginalization. We define and describe four research practices: 1. coalescing into a group; 2. encouraging the shared ownership of the research process and its outcomes; 3. developing multiple centres of power; and 4. promoting interdependency. We illustrate these principles with specific examples from an FPAR study that explored how social workers in Israel can best support girls and young women in situations of distress. We explored this question with a group of young women who were active partners in the research process. We conclude the article by underscoring the linkage between these four practices and feminist theory.
Mobile Registration Number Plate Recognition Using Artificial Intelligence

Automatic License Plate Recognition (ALPR) for years has remained a persistent topic of research due to numerous practicable applications, especially in the Intelligent Transportation system (ITS). Many currently available solutions are still not robust in various real-world circumstances and often impose constraints like fixed backgrounds and constant distance and camera angles. This paper presents an efficient multi-language repudiate ALPR system based on machine learning. Convolutional Neural Network (CNN) is trained and fine-tuned for the recognition stage to become more dynamic, plaint to diversification of backgrounds. For license plate (LP) detection, a newly released YOLOv5 object detecting framework is used. Data augmentation techniques such as gray scale and rotatation are also used to generate an augmented dataset for the training purpose. This proposed methodology achieved a recognition rate of 92.2%, producing better results than commercially available systems, PlateRecognizer (67%) and OpenALPR (77%). Our experiments validated that the proposed methodology can meet the pressing requirement of real-time analysis in Intelligent Transportation System (ITS).
A New Off-Board Electrical Vehicle Battery Charger: Topology, Analysis and Design

The extensive use of electric vehicles (EVs) can reduce concerns about climate change and fossil fuel shortages. One of the main obstacles to accepting EVs is the limitation of charging stations, which consists of high-charge batteries and high-energy charging infrastructure. A new transformer-less topology for boost dc-dc converters with higher power density and lower switch stress is proposed in this paper, which may be a suitable candidate for high-power fast-charging battery chargers of EVs. Throughout this paper, two operating modes of the proposed converter, continuous current mode (CCM) and discontinuous current mode (DCM), are analyzed in detail. Additionally, critical inductances and design considerations for the proposed converter are calculated. Finally, real-time verifications based on hardware-in-loop (HiL) simulation are carried out to assess the correctness of the proposed theoretical concepts.