Miracle-dz/UniFAR-FTUs huggingface dataset:
Mite fauna associated with different environments in the Southern Pampa, Brazil

ABSTRACT The Brazilian Pampa is predominantly composed of native grasslands with riparian forest formations. It preserves a rich biodiversity and provides vast biological resources for economic uses. The objectives of this study were to compare the mite fauna composition on plants in three environments i.e. grassland, grazing exclusions, and riparian forest; to relate mites with microclimatic factors, and to evaluate interactions between mites and vascular plants. Data analysis was based mainly on the relationship between mite and plant species. A total of 117 mite species were collected, most of which were phytophagous (57%). Our studies revealed that mite communities from riparian forest differ from grazing exclusions and grasslands. Grassland and grazing exclusions were dominated by two species i.e. Brevipalpus sp2 and Tydeus californicus (Banks). In the riparian forest, the most abundant species was Lorryia formosa (Cooreman). In conclusion, mites represent environmental indicators of microclimatic factors and landscape. All the sampling sites had high interaction between mites and plants.
Parental Stress and Home Activities for Young Children during the Stay-at-home Quarantine Time in China

ABSTRACT Research Findings: Hierarchical regression analyses were conducted to examine the associations among the family pandemic experience, home activities during the stay-at-home quarantine, and level of parental stress. The results showed that, Chinese parents perceived only significantly higher stress related to children’s behavioral and emotional difficulties during the pandemic. Parents’ educational level and teacher remote support were significantly associated with the frequency of different home activities for young children. Although family direct exposure of COVID-19 was a critical risk factor predicting parent-perceived stress, parents’ education, family income, and teachers’ support were important protective factors for parents’ stress. Some learning-focused home activities showed an inverse association with parental stress. Practices or Policy: The findings of this study point to the importance of supporting parents to provide quality home-based learning for their young children during the COVID-19 pandemic. Professional support should also focus on the quality of parent-child interaction in addition to the promotion of children’s learning experience at home.
Development and characterization of electrosprayed microcaspules of poly ε-caprolactone with citronella oil for mosquito-repellent application

Abstract Several life-threatening diseases such as malaria, dengue or zika are transmitted by mosquito bites. Although there are several products available for personal protection against mosquitoes, the adequate efficacy of natural insect repellents (NIR) or the adverse effects of synthetic ones are problems that need to be solved. The encapsulation of NIR in low-cost, nontoxic and biodegradable polymers has emerged as a promising method for the development of eco-friendly repellent systems. In this work, the encapsulation of citronella oil (CO) into microcapsules of poly (ε-caprolactone) (PCL) was made by electrospraying technique to obtain a system that shows a sustained release of the high volatile oil. Characterizations of the capsules were performed by NMR, FTIR, SEM and DSC techniques. CO encapsulation efficiency (EE) and release studies were also determined by using HPLC technique. Results demonstrated that a 3/1 PCL-CO ratio and 10 kV were the best conditions to obtain regular and well-formed microcapsules. Characterization techniques showed the presence of CO in the microcapsules with an EE higher than 80%. Release studies in water solution indicated a sustained CO liberation for at least forty days. The present study shows the strong potential of the PCL-CO microcapsules as an effective and sustained release system with potential application in protection against mosquitoes. These microcapsules are not considered microplastics due to their biodegradable character and therefore their use is not restricted by the different legislations.
Developing a New Segmentation Typology for Telecom Service Users With the Motivated Consumer Innovativeness (MCI) Scale

Abstract What motivates consumers to become innovative is an important phenomenon in consumer behavior and is gaining special attention through the concept of motivated consumer innovativeness. The present study is an attempt to create a new segmentation typology for telecom services incorporating social, functional, hedonic, and cognitive motives for classifying a target population into more meaningful homogenous groups through cluster (K-means) analysis. Results of a single cross-sectional survey indicate creation of three distinct consumer segments: logical thinkers, experiencers, and value-driven users in mobile telecom services. The study offers useful implications on developing telecom service marketing mix for successful diffusion and adoption of innovation.
Perspectives of using machine learning in laser powder bed fusion for metal additive manufacturing

ABSTRACT The adoption of laser powder bed fusion (L-PBF) for metals by the industry has been limited despite the significant progress made in the development of the process chain. One of the key obstacles is the inconsistency of the parts obtained from L-PBF. Due to its complexity, there are many potential fluctuations that can occur within the process chain which can lead to quality inconsistency in L-PBF parts. Machine learning (ML) has the possibility to overcome this obstacle by utilising datasets obtained at various stages of the L-PBF process chain. In this perspective article, the integration of ML into the different stages of L-PBF process chain, which potentially lead to better quality control, is explored. Prior to L-PBF, ML can be used for part designs and file preparation. Then, ML algorithms can be applied in the process parameter optimisation and in situ monitoring. Finally, ML can also be integrated into the post-processing.
The research-practice nexus in doctoral education: the voices of social and health sciences PhD candidates and graduates

ABSTRACT The recent shift towards more practice-oriented doctoral training programmes relevant for non-academic settings raises the important, but still largely unexplored, question regarding how the relationships between research and professional practice are understood, experienced, and developed in contemporary doctoral education. Drawing on a mixed-methods study, combining a survey (n = 188) and individual interviews (n = 14), this paper explores the nature of the research-practice nexus in doctoral education from the perspective of PhD candidates and graduates with different professional backgrounds in social and health sciences in Poland and Portugal. Overall, the study findings suggest that this nexus is viewed as a dynamic, multidimensional relationship imbued with both connections and tensions. While the majority of the participants reported that their doctoral research influenced their professional practice positively and vice versa, there were also some respondents who identified negative impacts of their research on their practice and vice versa. The paper ends with some implications, thus providing a basis for reappraisal of current doctoral education provision in terms of deepening the relationship between research and professional practice.
Creative wellbeing. Prototyping an arts-health practice program for mental health recovery

Abstract Collaborations between designers and healthcare professionals are at the core of design for health, with calls in this journal for partnerships between designers and occupational therapists. This article follows these calls. It discusses a research project where designers, occupational therapists and inpatients of a mental health unit collaborated to prototype an ‘arts-health practice’ program for mental health recovery. During the development of this project, we constituted a ‘lo-fi living lab’, a collaborative platform that resulted from combining participatory design and autonomous design frameworks. As we show, this platform enables collaborative design processes that give priority to the creative practices and co-creative projects that healthcare communities have in their everyday life. It also reframes the role of designers and allows them to learn from those practices and become participants in those projects. The ‘lo-fi living lab’ format, we argue, makes it possible to run collaborative design projects that empower health staff to do their work in creative ways; allow designers to learn from the ‘everyday design’ practices of healthcare professionals; and creates non-disruptive platforms for user participation in the design of health services.
How does feeding on different diets affect the life history traits of Neoseiulus californicus?

ABSTRACT We examined how feeding on different diets affects the life-history traits of Neoseiulus californicus using seven pollen grains (pistachio, walnut, date palm, wild almond, pomegranate, oak, and peach) as well as a natural prey (two-spotted spider mites (TSSM)). The pre-adult duration of individuals reared on TSSM was significantly longer, whereas duration on oak and peach pollen was shorter than all the others. Females fed on peach, wild almond, and walnut pollen showed low fecundity. The highest number of eggs was laid by the females reared on TSSM. When the mites were reared on pistachio pollen, the fecundity was higher compared with other pollen grains. The net reproductive rate (R 0) varied from 1.77 (on peach pollen) to 26.28 offspring (on TSSM). The cohort reared on pistachio pollen had the highest intrinsic rate of increase (r) as well as the finite rate of increase (λ); however they were insignificant to the values obtained for the cohort reared on the date palm, oak, and pomegranate pollen. Pistachio and date palm pollen provide commensurate nutritional effects on survivorship, development, and fecundity of N. californicus. Knowledge about the profitability of different pollens can be used to optimize rearing systems for phytoseiid predators.
Travelling to Bundesliga matches: the carbon footprint of football fans

ABSTRACT The purposes of this study were to estimate the carbon footprint caused by football fans travelling to Bundesliga matches (first division) in Germany in the 2018/19 season, to analyse determinants of seasonal carbon footprint, and to identify fan clusters based on travel behaviour. A nationwide online survey of football fans was conducted (n = 539) asking respondents to report their match-related travel behaviour. The average seasonal carbon footprint of a Bundesliga fan amounted 311.1 kg of carbon dioxide equivalent emissions (CO2-e), with car travel accounting for 70% of the emissions. The aggregate carbon footprint of all fans for the whole Bundesliga season was 369,765.2 t CO2-e. Buying out of these carbon emissions would cost over €9.2 million in total. The regression results revealed that club membership and commitment to favourite club significantly increased fans’ carbon footprint. The choice of favourite Bundesliga club also predicted carbon footprint, with fans of FC Bayern Munich and RB Leipzig producing a significantly higher carbon footprint than fans of Borussia Dortmund. The segmentation of Bundesliga fans by their travel behaviour identified three distinct clusters: Devoted travellers (19%), home fans (30%) and casual visitors (51%). These clusters differed significantly in terms of emissions per kilometre travelled, car use versus public transport, club membership, fan commitment, environmental consciousness, education and age. The findings have practical implications for policy makers, Bundesliga officials and club authorities, and can serve as a basis for initiatives to reduce carbon dioxide emissions in professional team sports.
Habitat use by Long-tailed Weasels in a Fragmented Agricultural Landscape

Abstract. Long-tailed weasels (Mustela frenata) have an extensive North American geographic range and tolerate a wide range of life zones, excluding some desert ecosystems. However, little is known of their habitat use in landscapes fragmented by agriculture, despite the fact that long-tailed weasel populations may be declining in these landscapes. During late winter-spring and late summer-autumn 1998–2000, we monitored 11 long-tailed weasels (seven males, four females) via radio telemetry to examine patterns of habitat use in an Indiana landscape fragmented by agriculture. Long-tailed weasels exhibited scale-dependent patterns of habitat selection (i.e., habitat selection within a landscape and selection of habitats within home ranges). Weasels selected forest patches, fencerows, and drainage ditches, whereas agricultural fields were avoided. Forest patches and fencerows provided suitable den sites and refuge cover from other predators and exhibited an abundant and diverse prey community. Drainage ditches provided movement corridors and access to free-standing, drinking water. The resource selection patterns and limited dispersal ability of long-tailed weasels compared to other carnivores are consistent with the notion that long-tailed weasels appear sensitive to agriculturally induced fragmentation of habitat.
Electrical, Mechanical, and Structural Characterization of Self-Assembly in Poly(3-hexylthiophene) Organogel Networks

An electrically percolated network structure of conjugated polymers is critical to the development of organic electronics. Herein, we investigate the potential to rationally design an interconnected network of conjugated polymers using the gelation of poly(3-hexylthiophene) (P3HT) as a model system. The three-dimensional network structure is evaluated through small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS). The analytical models used for data fitting provide relevant structural parameters over multiple length scales. Structural parameters include the fiber cross section (height and width), the specific surface area, and the network density (i.e., fractal dimension). Simultaneous rheological and conductivity measurements also provide insight into the development of the mechanical and electrical properties of organogels and allow us to propose a detailed gelation mechanism for P3HT. The fiber shape is found to be relatively independent of the solvent type, but P3HT orga.
Towards the Possibility of Additive Manufacturing of XNA-Based Devices Using Molecular Engineering Principles

This paper considers a novel approach for integration between molecular engineering of XNA-based structures and additive manufacturing of XNA-based devices based on multiparametric characterization of XNAs by different functional descriptors (such as physical properties of XNA-based materials and precursors of XNA-based molecular devices) and the possibility of thermal or electron-beam processing as a prerequisite of the industrial technical process development for such device implementation. This can be performed in the framework of additive manufacturing by connecting the output of the XNA synthesizer or nucleic acid synthesizer with 3D-printer nozzles in such a way that oligos / AGCTX products are supported into the nozzles separately.
Relaxation of turbulent pipe flow downstream of a square bar roughness element

Abstract The relaxation of turbulent pipe flow downstream of a single square bar roughness element is studied at distances up to $120R$ ($R$ is the pipe radius). Three bar heights, $h/R = 0.04$, 0.1 and 0.2, are investigated. The data suggest three stages for the relaxing flow. Immediately following the square bar is the development of a separated shear layer, where we find that the peak Reynolds stress scales linearly with $h/R$ and the disturbance profile is characterised by $h$. The bulk shear stress and turbulence intensity in this stage scale as $(h/R)^{2}$ and reach their maximum near the reattachment point. The second stage features the redistribution of turbulence towards the pipe centre and a power law in the decay of turbulence. The extent of this region is characterised by a streamwise length scale, ${x_c}$, which measures the extent of the redistribution process. The final stage of recovery is found to be long-lasting and oscillatory owing to asynchronous recovery between the mean velocity and the Reynolds stress. The oscillation wavelength scales with ${x_c}$ and decreases with increasing $h/R$. In contrast, the deficits in the mean shear and the bulk shear stress increase with $h/R$. For all three bar sizes, the flow recovery is not complete until the streamwise distance exceeds 500$h$–1000$h$.
Genomic data support management of anadromous Arctic Char fisheries in Nunavik by highlighting neutral and putatively adaptive genetic variation

Distinguishing neutral and adaptive genetic variation is one of the main challenges in investigating processes shaping population structure in the wild, and landscape genomics can help identify signatures of adaptation to contrasting environments. Arctic Char (Salvelinus alpinus) is an anadromous salmonid and the most harvested fish species by Inuit people, including in Nunavik (Québec, Canada), one of the most recently deglaciated regions in the world. Unlike many other anadromous salmonids, Arctic Char occupy coastal habitats near their natal rivers during their short marine phase restricted to the summer ice‐free period. Our main objective was to document putatively neutral and adaptive genomic variation in anadromous Arctic Char populations from Nunavik and bordering regions to inform local fisheries management. We used genotyping by sequencing (GBS) to genotype 18,112 filtered single nucleotide polymorphisms (SNP) in 650 individuals from 23 sampling locations along >2000 km of coastline. Our results reveal a hierarchical genetic structure, whereby neighboring hydrographic systems harbor distinct populations grouped by major oceanographic basins: Hudson Bay, Hudson Strait, Ungava Bay, and Labrador Sea. We found genetic diversity and differentiation to be consistent both with the expected postglacial recolonization history and with patterns of isolation‐by‐distance reflecting contemporary gene flow. Results from three gene–environment association methods supported the hypothesis of local adaptation to both freshwater and marine environments (strongest associations with sea surface and air temperatures during summer and salinity). Our results support a fisheries management strategy at a regional scale, and other implications for hatchery projects and adaptation to climate change are discussed.
A gradient-based framework for 3D print appearance optimization

In full-color inkjet 3D printing, a key problem is determining the material configuration for the millions of voxels that a printed object is made of. The goal is a configuration that minimises the difference between desired target appearance and the result of the printing process. So far, the techniques used to find such a configuration have relied on domain-specific methods or heuristic optimization, which allowed only a limited level of control over the resulting appearance. We propose to use differentiable volume rendering in a continuous material-mixture space, which leads to a framework that can be used as a general tool for optimising inkjet 3D printouts. We demonstrate the technical feasibility of this approach, and use it to attain fine control over the fabricated appearance, and high levels of faithfulness to the specified target.
End-to-end complex lens design with differentiate ray tracing

Imaging systems have long been designed in separated steps: experience-driven optical design followed by sophisticated image processing. Although recent advances in computational imaging aim to bridge the gap in an end-to-end fashion, the image formation models used in these approaches have been quite simplistic, built either on simple wave optics models such as Fourier transform, or on similar paraxial models. Such models only support the optimization of a single lens surface, which limits the achievable image quality. To overcome these challenges, we propose a general end-to-end complex lens design framework enabled by a differentiable ray tracing image formation model. Specifically, our model relies on the differentiable ray tracing rendering engine to render optical images in the full field by taking into account all on/off-axis aberrations governed by the theory of geometric optics. Our design pipeline can jointly optimize the lens module and the image reconstruction network for a specific imaging task. We demonstrate the effectiveness of the proposed method on two typical applications, including large field-of-view imaging and extended depth-of-field imaging. Both simulation and experimental results show superior image quality compared with conventional lens designs. Our framework offers a competitive alternative for the design of modern imaging systems.
Control strategies for physically simulated characters performing two-player competitive sports

In two-player competitive sports, such as boxing and fencing, athletes often demonstrate efficient and tactical movements during a competition. In this paper, we develop a learning framework that generates control policies for physically simulated athletes who have many degrees-of-freedom. Our framework uses a two step-approach, learning basic skills and learning bout-level strategies, with deep reinforcement learning, which is inspired by the way that people how to learn competitive sports. We develop a policy model based on an encoder-decoder structure that incorporates an autoregressive latent variable, and a mixture-of-experts decoder. To show the effectiveness of our framework, we implemented two competitive sports, boxing and fencing, and demonstrate control policies learned by our framework that can generate both tactical and natural-looking behaviors. We also evaluate the control policies with comparisons to other learning configurations and with ablation studies.
Learning an animatable detailed 3D face model from in-the-wild images

While current monocular 3D face reconstruction methods can recover fine geometric details, they suffer several limitations. Some methods produce faces that cannot be realistically animated because they do not model how wrinkles vary with expression. Other methods are trained on high-quality face scans and do not generalize well to in-the-wild images. We present the first approach that regresses 3D face shape and animatable details that are specific to an individual but change with expression. Our model, DECA (Detailed Expression Capture and Animation), is trained to robustly produce a UV displacement map from a low-dimensional latent representation that consists of person-specific detail parameters and generic expression parameters, while a regressor is trained to predict detail, shape, albedo, expression, pose and illumination parameters from a single image. To enable this, we introduce a novel detail-consistency loss that disentangles person-specific details from expression-dependent wrinkles. This disentanglement allows us to synthesize realistic person-specific wrinkles by controlling expression parameters while keeping person-specific details unchanged. DECA is learned from in-the-wild images with no paired 3D supervision and achieves state-of-the-art shape reconstruction accuracy on two benchmarks. Qualitative results on in-the-wild data demonstrate DECA's robustness and its ability to disentangle identity- and expression-dependent details enabling animation of reconstructed faces. The model and code are publicly available at https://deca.is. tue.mpg. de.