Miracle-dz/UniFAR-FTUs huggingface dataset:
Work-Related Practices: An Analysis of Their Effect on the Emergence of Stable Practices in Daily Activity Schedules

Despite its ‘wordless’ and hidden characteristics, it is within the everyday tasks, routines, and rhythms that consumption takes place, from getting up every morning, having breakfast, going to work or school, having lunch, going home, having dinner, reading a book, surfing the Internet, watching TV, and probably doing similar things again and again. This study examines this routinized daily use of time of employed individuals based on the 2014–2015 UK Time-Use Survey data. In doing this, we focus on individual’s day-to-day activities and how they are routinized or how they are formed into stabilized practices. Starting from the definition of stable practices, we apply a relatively new method of social network analysis to visualize stable practices during workdays. We then analyse the cohesion between practices based on work hours and connections and coordination between practices. Our results suggest that work arrangements create stable practices that by themselves are stone pillars of daily routines. This implies that the removal (or ‘unlocking’) of stable practices during these time periods could produce some – albeit marginal – decongestion of routinized activities.
Climate impact on hypersalinity in an Australian coastal bay

Recent work on episodes of hypersalinity in a subtropical east Australian coastal bay is reviewed. Hypersalinity is a response of coastal bays and estuaries to the local freshwater balance which fluctuates due to variable rainfall, river run-off, and evaporation. Longer lasting episodes of hypersaline conditions are a likely consequence of a drying and warming climate. The response of the coastal ocean to changes in the hydrological cycle has been observed in several Australian coastal systems, including the response to persistent drought conditions resulting in increased salinity and more frequent hypersaline conditions. In addition to observing hypersaline conditions in Hervey Bay off the central Queensland coast, first modelling experiments indicate that the frequency of hypersaline conditions has increased during the last twenty years. Coastal regions are important nurseries for Australian fisheries and the likely impact of persistent below average rainfall upon marine environmental conditions is yet to be assessed. This work indicates that routine monitoring of coastal salinity is essential in order to evaluate future impacts of climate change.
Modelling human brain-wide pigmentation in rodents recapitulates age-related multisystem neurodegenerative deficits

One key limitation in developing effective treatments for neurodegenerative diseases is the lack of models that accurately mimic the complex physiopathology of the human disease. Humans accumulate with age the pigment neuromelanin inside catecholaminergic neurons. Neurons reaching the highest neuromelanin levels preferentially degenerate in Parkinson’s, Alzheimer’s and apparently healthy aging individuals. However, this brain pigment is not taken into consideration in current animal models because, in contrast to humans, common laboratory species such as rodents do not produce neuromelanin. Here we generated a tissue-specific transgenic mouse that mimics the human age-dependent brain-wide distribution of neuromelanin within catecholaminergic regions, based on the constitutive catecholamine-specific expression of human melanin-producing enzyme tyrosinase. In parallel to progressive human-like neuromelanin pigmentation, these animals display age-related neuronal dysfunction and degeneration affecting numerous brain circuits and body tissues, linked to motor and non-motor deficits, reminiscent of early neurodegenerative stages. This model may open new research avenues in the field of brain aging and neurodegeneration.
Auditory cortical error signals retune during songbird courtship

Auditory feedback is important for vocal learning and control, but it remains unclear how the presence of an audience affects neural representations of self-produced sounds. Here we recorded neural activity in a primary auditory cortical area, Field L, in zebra finches practicing singing alone and directing courtship songs to females. We first discovered that many Field L neurons changed their singing-related discharge patterns during courtship singing, even though the auditory feedback from the bird’s own song was similar. We next used syllable-targeted distorted auditory feedback (DAF) to test how auditory error signals depend on courtship context. Though past work showed that dopamine neurons uniformly reduce error signaling during courtship, Field L neurons exhibited heterogeneous error signal re-tuning in the presence of the female. Thus, single neurons in a primary sensory area process feedback from self-produced actions differently during practice and performance.
Vascularized tumor on a microfluidic chip to study mechanisms promoting tumor neovascularization and vascular targeted therapies

The cascade of events leading to tumor formation includes induction of a tumor supporting neovasculature as a primary hallmark of cancer. Developing vasculature is difficult to evaluate in vivo but can be captured using microfluidic chip technology and patient derived cells. Herein, we established an on chip approach to investigate the mechanisms promoting tumor vascularization and vascular targeted therapies via co-culture of metastatic renal cell carcinoma spheroids and endothelial cells in a 3D environment. Our model permitted real-time, high-resolution observation and assessment of tumor-induced angiogenesis, where endothelial cells sprout towards the tumor and mimic a vascular network. Bevacizumab, an angiogenic inhibitor, disrupted interactions between vessels and tumors, destroying the vascular network. The on chip approach enabled assessment of endothelial cell biology, vessel’s functionality, drug delivery, and molecular expression of PSMA. Finally, observations in the vascularized tumor on chip permitted direct and conclusive quantification of this therapy in weeks as opposed to months in a comparable animal model. Teaser Vascularized tumor on microfluidic chip provides opportunity to study targeted therapies and improves preclinical drug discovery.
Three dimensional fibrotic extracellular matrix directs microenvironment fiber remodeling by fibroblasts

Idiopathic pulmonary fibrosis (IPF), for which effective treatments are limited, results in excessive and disorganized deposition of an aberrant extracellular matrix (ECM). An altered ECM microenvironment is postulated to contribute to disease perpetuation in a feed-forward manner through inducing profibrotic behavior by lung fibroblasts, the main producers and regulators of ECM. Here, we examined this hypothesis in a 3D in vitro model system by growing primary human lung fibroblasts in ECM-derived hydrogels from non-fibrotic (control) or IPF lung tissue. Culture of fibroblasts in fibrotic hydrogels did not trigger a change in the overall amount of collagen or glycosaminoglycans but did cause a drastic change in fiber organization compared to culture in control hydrogels. Mechanical properties of fibrotic hydrogels were modified by fibroblasts while control hydrogels were not. These results illustrate how the 3D microenvironment plays a crucial role in directing cells to exhibit pro-fibrotic responses by providing biochemical and/or biomechanical cues.
A strict requirement in proteasome substrates for spacing between ubiquitin tag and degradation initiation elements

Proteins are typically targeted to the proteasome for degradation through the attachment of ubiquitin chains and the proteasome initiates degradation at a disordered region within the target protein. Yet some proteins with ubiquitin chains and disordered regions escape degradation. Here we investigate how the position of the ubiquitin chain on the target protein relative to the disordered region modulates degradation and show that the distance between the two determines whether a protein is degraded efficiently. This distance depends on the type of the degradation tag and is likely a result of the separation on the proteasome between the receptor that binds the tag and the site that engages the disordered region.
Inhibitory subpopulations in preBötzinger Complex play distinct roles in modulating inspiratory rhythm and pattern

Inhibitory neurons embedded within mammalian neural circuits shape breathing, walking, chewing, and other rhythmic motor behaviors. At the core of the neural circuit controlling breathing is the preBötzinger Complex (preBötC), a nucleus in the ventrolateral medulla necessary for generation of inspiratory rhythm. In the preBötC, a recurrently connected network of glutamatergic Dbx1-derived (Dbx1+) neurons generates rhythmic inspiratory drive. Functionally and anatomically intercalated among preBötC Dbx1+ neurons are GABAergic (GAD1/2+) and glycinergic (GlyT2+) neurons, whose roles in breathing remain unclear. To elucidate the inhibitory microcircuits within preBötC, we first characterized the spatial distribution of molecularly-defined preBötC inhibitory subpopulations in double reporter mice expressing either the red fluorescent protein tdTomato or EGFP in GlyT2+, GAD1+, or GAD2+ neurons. We found that, in neonatal mice, the majority of preBötC inhibitory neurons expressed a combination of GlyT2 and GAD2 while a much smaller subpopulation also expressed GAD1. To determine the functional role of these subpopulations, we used holographic photostimulation, a patterned illumination technique with high spatiotemporal resolution, in rhythmically active medullary slices from neonatal Dbx1tdTomato;GlyT2EGFP and Dbx1tdTomato;GAD1EGFP double reporter mice. Stimulation of 4 or 8 preBötC GlyT2+ neurons during endogenous rhythm prolonged the interburst interval in a phase-dependent manner and increased the latency to burst initiation when bursts were evoked by stimulation of Dbx1+ neurons. In contrast, stimulation of 4 or 8 preBötC GAD1+ neurons did not affect interburst interval or latency to burst initiation. Instead, photoactivation of GAD1+ neurons during the inspiratory burst prolonged endogenous and evoked burst duration and decreased evoked burst amplitude. We conclude that the majority of preBötC inhibitory neurons express both GlyT2 and GAD2 and modulate breathing rhythm by delaying burst initiation while a smaller GAD1+ subpopulation shapes inspiratory patterning by altering burst duration and amplitude.
Haplotype Function Score improves biological interpretation and cross-ancestry polygenic prediction of human complex traits

We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3,619 independent HFS-trait associations with a significance of p<5×10−8. Fine-mapping revealed 2,699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with SNP-based analysis. HFS-based enrichment analysis uncovered 727 pathway-trait associations and 153 tissue-trait associations with strong biological interpretability, including “circadian pathway-chronotype” and “arachidonic acid-intelligence”. Lastly, we applied LASSO regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1% to 39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.
Socio-demographic Influence on Rider Type Self Classification with respect to Bicycling

Cyclists differ widely in their perceptions of safety and comfort and hence, possibly in their preference for infrastructure. The difference in perception is further complicated by lack of data on individuals who are not cycling at present because of safety issues, but who may otherwise choose bicycling as a mode choice if proper infrastructure and environment are provided. One possible way of predicting choices of future cyclists based on present data is to classify cyclists based on attributes that are readily observable. Although several cyclist type classification systems have been proposed in the literature, the most commonly used classification system was developed in Portland based on experience rather than empirical analysis. In this paper, a five category classification system is proposed, including the categories strong and fearless, enthused and confident, comfortable but cautious, interested but concerned and no way no how. These rider type categories are then related to the socio-demographic information of cyclists collected through the Cycle Atlanta app to identify relationships to the variables such as age, gender, income, frequency of cycling and rider history. A survey of cyclists was also conducted to obtain stated preferences for infrastructure by cyclist types. Results show that age and gender and in some cases, income have significant influence on rider type categorization. Riders across all cyclist types prefer dedicated cycling facilities and are opposed to high speed traffic and high volume traffic, with little variation based on the classification of the cyclist.
Bayesian updating for self-assessment explains social dominance and the winner effect

Dominance interactions determine access to scarce resources and are thus major contributors to fitness in many social species. Although in some systems, dominance is a direct reflection of intrinsic resource holding potential, often there can be mismatches between an animal’s expected dominance (based on body condition, fighting ability, social connections, etc.) and the actual results of dominance contests and their position in a hierarchy. This can be driven in part by the winner/loser effect, in which prior results bias the outcome of future contests. In many systems, the winner/loser effect is driven not by a measurable change in relative resource holding potential, but by the aggressiveness of experienced individuals, suggesting a shift in self-assessment based on newly gained information. This updating of a prior estimate is ideally described by Bayesian updating, which predicts animal behavior in other contexts, such as foraging and mate selection. Despite the obvious relevance, the winner effect has never been modeled as a Bayesian process. Here we show that Bayesian updating provides a mechanism to explain why winner effects form and makes clear predictions for the behavior of individuals and social groups. We implement an agent-based model to compare Bayesian updating to other possible strategies. We first show that Bayesian updating reproduces empirical results of the behavior of individuals and groups in dominance interactions. We then provide a series of testable predictions that can be used in empirical work to distinguish Bayesian updating from other potential mechanisms. Our work demonstrates the utility of Bayesian updating as a mechanism to explain how changes in self-assessment can determine the outcome of repeated social interactions.
WORK ENGAGEMENT: A META-ANALYTIC REVIEW AND DIRECTIONS FOR RESEARCH IN AN EMERGING AREA.

This study reviews the engagement construct using a meta-analytic framework. Meta-analytic results show that the three factors of engagement (i.e. vigor, dedication, and absorption) are strongly intercorrelated. Also, engagement is more strongly related to job resources than job demands. Finally, we found that the dimensions of engagement predict organizational commitment and individual health outcomes in a manner consistent with predictions.
Opleiding Informatica A New Way of Learning English: Integration of Computational Thinking Through Digital Storytelling

Computational thinking (CT) is a problem solving method that can be used for any kind of problem that needs to be solved. The focus of the thesis is to find out what the influences of the integration of CT through digital storytelling are for the implementation of it within the Dutch school curriculum for the subject English. The study was focused on the second year high school students’ English lessons. The aim of the study is to find out what kind of influence the making of a digital story has on the students’ English learning skills, and CT learning skills, as well as to find out what the students’ and the teacher’s attitude are concerning digital storytelling as a method of integrating CT. The influence of the CT integrated lessons were investigated by analysing the students’ digital stories, the filled in surveys, and the semi-structured interviews wherewith the students and the teacher were interviewed. The results shows that the students, through creating a digital story, enjoyed the lessons more. The teachers mentioned that because of the way the learning objectives have been taught, that the students understood it better as well as that it will stick longer with them. The students were also able to practice with their pronunciation and writing skills and were allowed to be very creative.
Static Class-Level Approach For Test Impact Analysis

The objective of this paper is to examine the efficacy of test impact analysis in a setting of continuous testing, where automated test cases are routinely run to guarantee the integration of high-quality codes. While continuous testing can enhance code quality and minimize maintenance workload, it may also lead to a notable rise in overhead for test execution. Building on previous research, we introduce a new static class-level technique by constructing test cases to class dependency graphs from abstract syntax trees using JavaParser and applying it to seven Java systems. Like prior findings, we observe that, despite a small number of changed files in code changes, roughly 40 percent of test cases are impacted and require execution on average. Nonetheless, we conclude that test impact analysis can serve as a powerful tool for reducing test overhead. Moreover, we compare our proposed technique with a state-of-the-art static class-level method and find that our approach outperforms by achieving roughly a 13 percent reduction in selecting impacted tests on the commonly evaluated systems.
Controller Design, Analysis, and Experimental Validation of a Robotic Serpentine Tail to Maneuver and Stabilize a Quadrupedal Robot

This paper analyzes how a multisegment, articulated serpentine tail can enhance the maneuvering and stability of a quadrupedal robot. A persistent challenge in legged robots is the need to account for propulsion, maneuvering, and stabilization considerations when generating control inputs for multidegree-of-freedom spatial legs. Looking to nature, many animals offset some of this required functionality to their tails to reduce the required action by their legs. By including a robotic tail on-board a legged robot, the gravitational and inertial loading of the tail can be utilized to provide for the robot's maneuverability and stability, while the legs primarily provide the robot's propulsion. System designs for the articulated serpentine tail and quadrupedal platform are presented, along with the dynamic models used to represent these systems. Outer-loop controllers that implement the desired maneuvering and stabilizing behaviors are discussed, along with an inner-loop controller that maps the desired tail trajectory into motor torque commands for the tail. Case studies showing the tail's ability to modify yaw-angle heading during locomotion (maneuvering) and to reject a destabilizing external disturbance in the roll direction (stabilization) are considered. Simulation results utilizing the tail's dynamic model and experimental results utilizing the tail prototype, in conjunction with the simulated quadrupedal platform, are generated. Successful maneuvering and stabilization are demonstrated by the simulated results and validated through experimentation.
Parameters extraction and Suppression of Interrupted Sampling Periodic Repeater Jammer in LFM Pulse Compression Radar

Linear frequency modulation (LFM) pulse compression radar is one of the modern radars, it has high processing gain, and high immunity against conventional jamming techniques. However, it is severely affected by coherent jamming techniques. Interrupted sampling periodic repeater jamming technique can produce multiple false targets in range at the matched filter output. This study aims to suppress the effect of this jamming technique, the published literature presented many techniques to suppress the jamming signal through various jamming signal parameters extraction methods. In this paper a suppression process is proposed to effectively extract the jamming signal parameters, These parameters are the number of interrupter sampling slices, the jamming forwarding times, and the slice width, they are extracted using a proposed robust statistics threshold crossing, the intercepting slice number is extracted from the discrete cosine transform of the deconvolution process. The parameter extraction leads to jamming signal reconstruction, and then the jamming signal is suppressed from the received signal. The proposed method performance is verified using Monte Carlo simulations to estimate the relative error in measuring the slice width with respect to JNR, this performance was estimated in realistic radar environment that includes Gaussian noise and non-Gaussian clutter model (K-distributed clutter). The results demonstrates an improvement in slice width error estimation for the favor of the proposed method by 2.6%, which, in turn enhances jamming signal suppression to be 28.29 dB.
Analysis of the Resonance Characteristics of the Six-Tooth-Shaped Monopole Microstrip Antenna

The monopole microstrip antenna with the six-tooth-shaped radiator is considered. The influence of the depth of symmetrical rectangular cutouts, the length and width of the radiator on the resonance frequencies of the antenna is studied. The analysis of the changing in the values of the first, second, and third resonance frequencies is made when varying the dimensions of these radiator geometric parameters. Based on the analysis for the studied characteristics, nonlinear regression models are constructed with high accuracy from three radiator parameters (the relative errors of the models are 2.56%, 3.39%, and 0.36% for the first, second, and third resonance frequencies, respectively).
Is the Minimal Erythema Dose Achievable at Optical Spectroscopy of Skin in Vivo?

Since UV radiation is capable to cause skin erythema, there is a damage risk at in-vivo UV spectroscopy of skin. An optical fiber delivery of UV radiation to the skin is potentially dangerous because of its small aperture, and, consequently, the high output power density of radiation. In this paper, to investigate this issue, an analysis of the distribution of energy absorbed in skin was conducted using Monte Carlo simulations of light transport. On the example of two types of light sources - an optical fiber and an extended large-area source, which usually applied at UV phototherapy, it was shown that the approach calculating the UV radiation dose as a radiant exposure is not quite correct for the optical-fiber illumination.