Miracle-dz/UniFAR-FTUs huggingface dataset:
Parentification in Deployed and Non-Deployed Military Families: A Preliminary Assessment

: The purpose of this study is to investigate the differences in parentification in military families with a deployed parent and without a deployed parent. Parentification has been defined as a parent-child relationship in which the child is given roles and responsibilities that are inappropriate for the child’s developmental level. Previous research has highlighted increased rates of parentification in situations involving parental absence or unavailability, such as divorce, parental illness, parental alcoholism, and domestic violence. This construct was assessed using the Parentification Questionnaire – Youth, a 20 item self-report survey for children and adolescents. Participants consisted of 22 children, ages 7-17, from military families with a deployed parent and military families without a deployed parent. After removing two statistical outliers from the intact military families group, an independent samples t-test was conducted. It was found that there was a significant difference between military families with a deployed parent and military families without a deployed parent. In summary, military families with a deployed parent had higher rates of parentification than military families without a deployed parent. Limitations of the present study include small sample size, external influences through the possible presence of one or both parents during the questionnaire, and the lack of control groups. Future research should expand the sample size, extend the study to more family groups (i.e. civilian, divorced, separated by work), and explore the possibility of positive or negative impacts of parentification on military children from families separated by deployment.
Reductions in Systemic and Skeletal Muscle Blood Flow and Oxygen Delivery Limit Maximal Aerobic Capacity in Humans

Background—A classic, unresolved physiological question is whether central cardiorespiratory and/or local skeletal muscle circulatory factors limit maximal aerobic capacity (&OV0312;o2max) in humans. Severe heat stress drastically reduces &OV0312;o2max, but the mechanisms have never been studied. Methods and Results—To determine the main contributing factor that limits &OV0312;o2max with and without heat stress, we measured hemodynamics in 8 healthy males performing intense upright cycling exercise until exhaustion starting with either high or normal skin and core temperatures (+10°C and +1°C). Heat stress reduced &OV0312;o2max, 2-legged &OV0312;o2, and time to fatigue by 0.4±0.1 L/min (8%), 0.5±0.2 L/min (11%), and 2.2±0.4 minutes (28%), respectively (all P <0.05), despite heart rate and core temperature reaching similar peak values. However, before exhaustion in both heat stress and normal conditions, cardiac output, leg blood flow, mean arterial pressure, and systemic and leg O2 delivery declined significantly (all 5% to 11%, P <0.05), yet arterial O2 content and leg vascular conductance remained unchanged. Despite increasing leg O2 extraction, leg &OV0312;o2 declined 5% to 6% before exhaustion in both heat stress and normal conditions, accompanied by enhanced muscle lactate accumulation and ATP and creatine phosphate hydrolysis. Conclusions—These results demonstrate that in trained humans, severe heat stress reduces &OV0312;o2max by accelerating the declines in cardiac output and mean arterial pressure that lead to decrements in exercising muscle blood flow, O2 delivery, and O2 uptake. Furthermore, the impaired systemic and skeletal muscle aerobic capacity that precedes fatigue with or without heat stress is largely related to the failure of the heart to maintain cardiac output and O2 delivery to locomotive muscle.
High-starch, coarse-grain, low-fiber diets maximize growth of weaned dairy calves less than 4 months of age

Starch concentration, fiber concentration and type, and diet form were evaluated using Holstein steer calves from 2 to 4 mo of age in four 56-d trials. In trial 1, 96 calves were fed a high-starch diet that had the same composition in meal, pelleted, and whole-grain textured forms that was blended with 5% chopped grass hay at the time of feeding. In trial 2, the same meal and textured diets were retested with 96 calves. Calves fed the meal form diet consumed less DM and had lower ADG than the calves fed the textured form diet in each trial (P < 0.05). In trial 3, 96 calves were fed either a high-starch, whole-grain textured or low-starch, high-fiber (wheat middlings, soyhulls, distillers grains) pelleted diet that was blended with either 4 or 12% chopped alfalfa-grass hay. Calves fed the high-starch, low-hay diet had greater (P < 0.05) ADG, intake, feed efficiency, and change in BCS than calves fed the other treatments. In trial 4, 48 calves were fed a high-starch, whole-grain textured or 0, 20, 40, and 60% of a low-starch, pelleted diet blended with the high-starch, textured diet for progressive 14-d intervals. There were no differences in calf performance. Coarse high-starch textured diets supported more intake and ADG than meal form diets. Fiber from fibrous concentrates and roughages reduced calf performance and need to be introduced slowly in moderate amounts to calves under 4 mo of age.
Dynamics and stability of directional jumps in the desert locust

Locusts are known for their ability to jump large distances to avoid predation. The jump also serves to launch the adult locust into the air in order to initiate flight. Various aspects of this important behavior have been studied extensively, from muscle physiology and biomechanics, to the energy storage systems involved in powering the jump, and more. Less well understood are the mechanisms participating in control of the jump trajectory. Here we utilise video monitoring and careful analysis of experimental directional jumps by adult desert locusts, together with dynamic computer simulation, in order to understand how the locusts control the direction and elevation of the jump, the residual angular velocities resulting from the jump and the timing of flapping-flight initiation. Our study confirms and expands early findings regarding the instrumental role of the initial body position and orientation. Both real-jump video analysis and simulations based on our expanded dynamical model demonstrate that the initial body coordinates of position (relative to the hind-legs ground-contact points) are dominant in predicting the jumps’ azimuth and elevation angles. We also report a strong linear correlation between the jumps’ pitch-angular-velocity and flight initiation timing, such that head downwards rotations lead to earlier wing opening. In addition to offering important insights into the bio-mechanical principles of locust jumping and flight initiation, the findings from this study will be used in designing future prototypes of a bio-inspired miniature jumping robot that will be employed in animal behaviour studies and environmental monitoring applications.
A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks

Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data. In this paper, we presented the artificial hydrocarbon networks (AHN) technique to the human activity recognition community. Our artificial hydrocarbon networks novel approach is suitable for physical activity recognition, noise tolerance of corrupted data sensors and robust in terms of different issues on data sensors. We proved that the AHN classifier is very competitive for physical activity recognition and is very robust in comparison with other well-known machine learning methods.
Interactive comment on “ Intercomparison of air ion spectrometers : a basis for data interpretation ”

Specific Comments: Line 156: Assuming that the corona charger is not 100% efficient there should still remain electrically neutral particles; therefore, it seems inappropriate to state "particle-free" air. Also, it is not clear how the offset measurements are done. Is the classifying voltage applied during the offset measurements? Is the offset current affected by the presence of the classifying voltage?
The draft genome sequence of forest musk deer (Moschus berezovskii)

Abstract Background The forest musk deer, Moschus berezovskii, is one of seven musk deer (Moschus spp.) and is distributed in Southwest China. Akin to other musk deer, the forest musk deer has been traditionally and is currently hunted for its musk (i.e., global perfume industry). Considerable hunting pressure and habitat loss have caused significant population declines. Consequently, the Chinese government commenced captive breeding programs for musk harvesting in the 1950s. However, the prevalence of fatal diseases is considerably restricting population increases. Disease severity and extent are exacerbated by inbreeding and genetic diversity declines in captive musk deer populations. It is essential that knowledge of captive and wild forest musk deer populations' immune system and genome be gained in order to improve their physical and genetic health. We have thus sequenced the whole genome of the forest musk deer, completed the genomic assembly and annotation, and performed preliminary bioinformatic analyses. Findings A total of 407 Gb raw reads from whole-genome sequencing were generated using the Illumina HiSeq 4000 platform. The final genome assembly is around 2.72 Gb, with a contig N50 length of 22.6 kb and a scaffold N50 length of 2.85 Mb. We identified 24,352 genes and found that 42.05% of the genome is composed of repetitive elements. We also detected 1,236 olfactory receptor genes. The genome-wide phylogenetic tree indicated that the forest musk deer was within the order Artiodactyla, and it appeared as the sister clade of four members of Bovidae. In total, 576 genes were under positive selection in the forest musk deer lineage. Conclusions We provide the first genome sequence and gene annotation for the forest musk deer. The availability of these resources will be very useful for the conservation and captive breeding of this endangered and economically important species and for reconstructing the evolutionary history of the order Artiodactyla.
Fabrication and Characterization of Li2O Excess (Na0.49K0.49Li0.02)(Nb0.8Ta0.2)O3 Piezoelectric Ceramics

Dense Li2O excess (Na0.49K0.49Li0.02)(Nb0.8Ta0.2)O3 [NKLNT] ceramics were developed by conventional sintering process without any special technique. The electrical properties of NKNLT ceramics were investigated as a function of Li2O concentration. When the sample sintered at 1050 oC for 4 h with the addition of 1 mol% Li2O, electro-mechanical coupling factor (kP) and piezoelectric coefficient (d33) were found to reach the highest values of 0.42 and 260 pC/N, respectively.
A Resource-Based View Of International Human Resources: Toward A Framework of Integrative and Creative Capabilities

Drawing on organizational learning and MNC perspectives, we extend the resource-based view to address how international human resource management provides sustainable competitive advantage. We develop a framework that emphasizes and extends traditional assumptions of the resource-based view by identifying the learning capabilities necessary for a complex and changing global environment. These capabilities address how MNCs might both create new HR practices in response to local environments and integrate existing HR practices from other parts of the firm (affiliates, regional headquarters, and global headquarters). In an effort to understand the nature of such capabilities, we discuss aspects of human capital, social capital, and organizational capital that might be linked to their development. Page 3
The indispensable role of the transversal spin fluctuations mechanism in laser-induced demagnetization of Co/Pt multilayers with nanoscale magnetic domains

The switching of magnetic domains induced by an ultrashort laser pulse has been demonstrated in nanostructured ferromagnetic films. This leads to the dawn of a new era in breaking the ultimate physical limit for the speed of magnetic switching and manipulation, which is relevant to current and future information storage. However, our understanding of the interactions between light and spins in magnetic heterostructures with nanoscale domain structures is still lacking. Here, both time-resolved magneto-optical Kerr effect experiments and atomistic simulations are carried out to investigate the dominant mechanism of laser-induced ultrafast demagnetization in [Co/Pt]20 multilayers with nanoscale magnetic domains. It is found that the ultrafast demagnetization time remains constant with various magnetic configurations, indicating that the domain structures play a minor role in laser-induced ultrafast demagnetization. In addition, both in experiment and atomistic simulations, we find a dependence of ultrafast demagnetization time τM on the laser fluence, which is in contrast to the observations of spin transport within magnetic domains. The remarkable agreement between experiment and atomistic simulations indicates that the local dissipation of spin angular momentum is the dominant demagnetization mechanism in this system. More interestingly, we made a comparison between the atomistic spin dynamic simulation and the longitudinal spin flip model, highlighting that the transversal spin fluctuations mechanism is responsible for the ultrafast demagnetization in the case of inhomogeneous magnetic structures. This is a significant advance in clarifying the microscopic mechanism underlying the process of ultrafast demagnetization in inhomogeneous magnetic structures.
Deep Models for Engagement Assessment With Scarce Label Information

Task engagement is defined as loadings on energetic arousal (affect), task motivation, and concentration (cognition) [1]. It is usually challenging and expensive to label cognitive state data, and traditional computational models trained with limited label information for engagement assessment do not perform well because of overfitting. In this paper, we proposed two deep models (i.e., a deep classifier and a deep autoencoder) for engagement assessment with scarce label information. We recruited 15 pilots to conduct a 4-h flight simulation from Seattle to Chicago and recorded their electroencephalograph (EEG) signals during the simulation. Experts carefully examined the EEG signals and labeled 20 min of the EEG data for each pilot. The EEG signals were preprocessed and power spectral features were extracted. The deep models were pretrained by the unlabeled data and were fine-tuned by a different proportion of the labeled data (top 1%, 3%, 5%, 10%, 15%, and 20%) to learn new representations for engagement assessment. The models were then tested on the remaining labeled data. We compared performances of the new data representations with the original EEG features for engagement assessment. Experimental results show that the representations learned by the deep models yielded better accuracies for the six scenarios (77.09%, 80.45%, 83.32%, 85.74%, 85.78%, and 86.52%), based on different proportions of the labeled data for training, as compared with the corresponding accuracies (62.73%, 67.19%, 73.38%, 79.18%, 81.47%, and 84.92%) achieved by the original EEG features. Deep models are effective for engagement assessment especially when less label information was used for training.
The ABCD of Usability Testing

We introduce a methodology for tracking and auditing feedback, errors and suggestions for software packages. This short paper describes how we innovate on the evaluation mechanism, introducing an (Antecedent, Barrier, Consequence and Development) ABCD form, embedded within a platform to enable end users to easily report on usability issues. The evaluation platform we use is the STEP cloud e-Participation platform (part of the STEP Horizon2020 project http://step4youth.eu/) and it will be tested and validated in real life contexts, with the participation of public authorities that will integrate the service in their regular decision-making practices, involving young people through engagement and motivation strategies. The pilot evaluation aims to demonstrate how open engagement needs to be embedded within public sector processes and identify the key barriers for wide scale deployment of the platform.
Rearing conditions of greylag geese affect habitat choice throughout life

Anthropogenic changes to the landscape such as fertilization and mowing schemes have been correlated with goslings obtaining a higher weight gain during the first weeks of their life, which in turn increases breeding success and survival at the adult stage. As goose numbers rise, conflicts with farmers become stronger as the birds use agricultural sites for foraging. In this study, habitat choice for individually marked greylag geese from four different rearing conditions, categorized by their temporal application of fertilizer, was documented over a seventeen-year period. Weekly observations took place on a resident population of wild greylag geese within the Ooijpolder, the Netherlands. The region comprises of areas dedicated to nature restoration as well as agricultural use. In essence, we infer the habitat choice of greylag geese from the frequency of sightings of individually marked geese in different habitat patches, and model habitat choice as a function of rearing conditions, age, and seasonality. Despite a general preference for agricultural grassland, about 40% of the habitat choice was determined by the rearing condition of geese. Interestingly, geese reared in restored meadows, a less favorable rearing habitat, exhibited strong habitat fidelity and preferred to forage in meadows in the spring. Habitat choice was furthermore influenced by age of adult geese and seasonal changes in plant availability. We discuss management implications of our results on habitat choice in an agricultural landscape for increasing resident goose populations. An efficient management measure would be the limitation of goose access to improved grassland during rearing period in the spring.
Subgroup identification in dose‐finding trials via model‐based recursive partitioning

An important task in early‐phase drug development is to identify patients, which respond better or worse to an experimental treatment. While a variety of different subgroup identification methods have been developed for the situation of randomized clinical trials that study an experimental treatment and control, much less work has been done in the situation when patients are randomized to different dose groups. In this article, we propose new strategies to perform subgroup analyses in dose‐finding trials and discuss the challenges, which arise in this new setting. We consider model‐based recursive partitioning, which has recently been applied to subgroup identification in 2‐arm trials, as a promising method to tackle these challenges and assess its viability using a real trial example and simulations. Our results show that model‐based recursive partitioning can be used to identify subgroups of patients with different dose‐response curves and improves estimation of treatment effects and minimum effective doses compared to models ignoring possible subgroups, when heterogeneity among patients is present.
Long‐term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro‐ecosystems across the globe

Long‐term elevated nitrogen (N) input from anthropogenic sources may cause soil acidification and decrease crop yield, yet the response of the belowground microbial community to long‐term N input alone or in combination with phosphorus (P) and potassium (K) is poorly understood. We explored the effect of long‐term N and NPK fertilization on soil bacterial diversity and community composition using meta‐analysis of a global dataset. Nitrogen fertilization decreased soil pH, and increased soil organic carbon (C) and available N contents. Bacterial taxonomic diversity was decreased by N fertilization alone, but was increased by NPK fertilization. The effect of N fertilization on bacterial diversity varied with soil texture and water management, but was independent of crop type or N application rate. Changes in bacterial diversity were positively related to both soil pH and organic C content under N fertilization alone, but only to soil organic C under NPK fertilization. Microbial biomass C decreased with decreasing bacterial diversity under long‐term N fertilization. Nitrogen fertilization increased the relative abundance of Proteobacteria and Actinobacteria, but reduced the abundance of Acidobacteria, consistent with the general life history strategy theory for bacteria. The positive correlation between N application rate and the relative abundance of Actinobacteria indicates that increased N availability favored the growth of Actinobacteria. This first global analysis of long‐term N and NPK fertilization that differentially affects bacterial diversity and community composition provides a reference for nutrient management strategies for maintaining belowground microbial diversity in agro‐ecosystems worldwide.
Repurposing drugs in oncology (ReDO)—selective PDE5 inhibitors as anti-cancer agents

Selective phosphodiesterase 5 inhibitors, including sildenafil, tadalafil and vardenafil, are widely-used in the treatment of erectile dysfunction and pulmonary arterial hypertension. They are also well-known as examples of successful drug repurposing in that they were initially developed for angina and only later developed for erectile dysfunction. However, these drugs may also be effective cancer treatments. A range of evidentiary sources are assessed in this paper and the case made that there is pre-clinical and clinical evidence that these drugs may offer clinical benefit in a range of cancers. In particular, evidence is presented that these drugs have potent immunomodulatory activity that warrants clinical study in combination with check-point inhibition.
Text2Colors: Guiding Image Colorization through Text-Driven Palette Generation

In this paper, we propose a novel approach to generate multiple color palettes that reflect the semantics of input text and then colorize a given grayscale image according to the generated color palette. In contrast to existing approaches, our model can understand rich text, whether it is a single word, a phrase, or a sentence, and generate multiple possible palettes from it. To achieve this task, we introduce our manually curated dataset called Palette-and-Text (PAT), which consists of 10,183 pairs of text and its corresponding color palette. Our proposed model consists of two conditional generative adversarial networks: the text-to-palette generation networks and the palette-based colorization networks. The former employs a sequence-to-sequence model with an attention module to capture the semantics of the text input and produce relevant color palettes. The latter utilizes a U-Net architecture to colorize a grayscale image using the generated color palette. Our evaluation results show that people preferred our generated palettes over ground truth palettes and that our model can effectively reflect the given palette when colorizing an image.