Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of the gut microbiome in red deer (Cervus elaphus) and fallow deer (Dama dama) by high-throughput sequencing of the V3-V4 region of the 16S rRNA gene

The gut microbiome is a complex ecosystem that plays an essential role in maintaining the host’s gut homeostasis and health. The available sequencing data for the Cervidae gut microbiome, especially for red deer and fallow deer in China, are limited. To improve the health of the two species in captivity, we characterized the gut microbiome of red deer and fallow deer via high-throughput Illumina sequencing of the 16S rRNA genes V3–V4 hypervariable regions. We found that the gut microbiome community of red deer included 20 phyla, 89 families and 193 genera, while the gut microbiome community of fallow deer included 18 phyla, 102 families and 227 genera. Firmicutes (red deer: 37.46–44.98%; fallow deer: 32.67–49.54%) was the most abundant phylum, followed by Bacteroidetes (red deer: 28.09–39.02%; fallow deer: 27.45–38.71%). The observed species and Shannon indices in red deer were higher than in fallow deer (p = 0.002, 0.016, respectively). Hence compared with fallow deer, red deer had higher diversity and species richness in their gut microbiome. The MRPP results showed that significant differences did occur in their microbiome compositions (A= 0.037, significance level α = 0.001). This study provides an initial understanding of the gut microbiome composition of red deer and fallow deer. The results may benefit captive management and future reintroduction programs.
Neural arbitration between social and individual learning systems

Decision making often requires integrating self-gathered information with information acquired from observing others. Depending on the situation, it may be beneficial to rely more on one than the other source, taking into account that either information may be imprecise or deceiving. The process by which one source is selected over the other based on perceived reliability, here defined as arbitration, has not been fully elucidated. In this study, we formalised arbitration as the relative reliability (precision) of predictions afforded by each learning system using hierarchical Bayesian models. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and self-sampled outcomes. The number of points participants wagered on their predictions reflected arbitration: The higher the relative precision of one learning system over the other and the lower the intention volatility, the more points participants wagered on a given trial. Functional neuroimaging demonstrated that the arbitration signal was independent of decision confidence and involved modalityspecific brain regions. Arbitrating in favour of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain whereas arbitrating in favour of social information engaged ventromedial prefrontal cortex and the temporoparietal junction. These findings are in line with domain specificity and indicate that relative precision captures arbitration between social and individual learning systems at both the behavioural and neural level.
Time varying connectivity across the brain changes as a function of nicotine abstinence state

Background The Nicotine Withdrawal Syndrome (NWS) includes affective and cognitive disruptions whose incidence and severity vary across time during acute abstinence. However, most network-level neuroimaging employs static measures of resting state functional connectivity (rsFC), assuming time-invariance, and unable to capture dynamic brain-behavior relationships. Recent advances in rsFC signal processing allow characterization of “time varying connectivity” (TVC), which characterizes network communication between sub-networks that reconfigure over the course of data collection. As such, TVC may more fully describe network dysfunction related to the NWS. Methods To isolate alterations in the frequency and diversity of communication across network boundaries as a function of acute nicotine abstinence we scanned cigarette smokers in the nicotine sated and abstinent states and applied a previously-validated method to characterize TVC at a network and nodal level within the brain. Results During abstinence, we found brain wide decreases in the frequency of interactions between network nodes in different modular communities (i.e. temporal flexibility; TF). In addition, within a subset of the networks examined the variability of these interactions across community boundaries (i.e. spatiotemporal diversity; STD) also decreased. Finally, within two of these networks the decrease in STD was significantly related to NWS clinical symptoms. Conclusions Employing multiple measures of TVC in a within subjects’ design, we characterized a novel set of changes in network communication and link these changes to specific behavioral symptoms of the NWS. These reductions in TVC provide a meso-scale network description of the relative inflexibility of specific large-scale brain networks as a result of acute abstinence.
What influences social entrepreneurs to adopt particular social enterprise structures and why

Despite the founders of social enterprises being faced with a proliferation of structural forms to pursue their interests, social enterprise is often portrayed as a homogenous organisational category. This domain is increasingly rendered a governable terrain (Nickel & Eikenberry, 2016) through the development of Kitemarks, funder/investor requirements and government policy initiatives which shape and control what it means to be a ‘good’ social enterprise. Such mechanisms have been shown to strengthen institutional coherence and drive structural isomorphism (i.e. Similarity) (DiMaggio & Powell, 1983; Boxenbaum, & Jonsson, 2017). As yet, however, scant attention has been given to the ways in which Kitemarks, standards and funding criteria serve to prioritise and marginalise particular forms of social enterprise by bestowing or denying access to material (e.g. financial) and symbolic (e.g. legitimacy) resources. Further, the implications of such disciplining affects and how individual entrepreneurs respond to them has likewise received little attention from scholars. This thesis seeks to explicate this issue, positioning Kitemarks, standards and funding criteria as political artefacts that serve to discipline the structure choices of social entrepreneurs through prescribing desirable characteristics, behaviours and structures for social enterprises. This prescription becomes problematic in situations when adherence to such prescriptions is at odds with social entrepreneur’s own constructions of legitimate organising principles, which are perceived by them to be as socially and materially efficacious but prevent access to physical and symbolic resources. The qualitative data set for this thesis comprises fifteen in-depth interviews with social entrepreneurs and their advisors regarding structure choice. The analysis presented offers new insights into the dynamics of structure choice by social entrepreneurs, including the potential nodes of conflict between exogenous prescriptions and social entrepreneur’s own orientation to certain aspects of organisation and what social entrepreneurs actually do in the face of such conflict. I find that conflict is particularly prevalent in respect of ownership and decision-making. In order to resolve the tensions that they experience, social 4 entrepreneurs often ‘decouple’ their governance and/or organising practices from those prescribed in external standards or begin to create new structures and ways of organising on the margins of the social enterprise domain through a process of institutional entrepreneurship (Battilana, Leca, & Boxenbaum, 2009). This thesis places such structures within an extended structural typology, extending the work of Bull (2015, 2018), and culminates in the development of a practice model for social enterprise structure selection.
Genome-Wide Association Study of Weaning Traits in Lori-Bakhtiari Sheep

Abstract Weaning traits, including preweaning daily gain (PWDG) and weaning weight (WW) are important economic traits, especially for meat type mammals, with high impacts on growth performance and survival rate in higher ages. This study was conducted to perform a genome-wide association study (GWAS) on weaning traits in a meat type breed of sheep. Body weight records of 7557 Lori-Bakhtiari sheep with PWDG and WW records were used to estimate breeding values (EBVs) using an animal mixed model. A total of 132 animals were selected by two-tailed selection strategy, based on EBVs for body weight and then were genotyped using Illumina 50k Ovine SNP chip. After quality control, a total of 130 animals and 41323 SNPs were remained for further analyses. De-regressed estimates of breeding values were used as a pseudo-phenotype in GWAS analysis. Based on Bonferroni-adjusted p-values, five SNPs, located on chromosomes 2, 3, 4, 12 and 22 were significantly (p < 0.05) associated with weaning traits and accounted for 5.06% and 0.37% of total genetic variations of PWDG and WW, respectively. Two SNPs on chromosomes 2 and 3 were located near to previously reported QTLs for weaning traits. Three genes, including ANGPTL7, mTOR and WDR11, were found within 50 kbp distances from the significant SNPs and thus could be considered as candidate genes for weaning traits. The detected QTLs and candidate genes could be studied for construction of breeding programs for genetic improvement of growth performance in meat type sheep.
Modeling the carbon footprint of fresh produce: effects of transportation, localness, and seasonality on US orange markets

Agriculture is one of the most impactful ways that we interact with the environment. Food demand is expected to increase 70% by 2050 as a result of population growth and the emergence of the global middle class. Meeting the expected demand in a sustainable manner will require an integrated systems-level approach to food production and supply. We present a conceptual framework for estimating the cradle-to-market life-cycle seasonal greenhouse gas emissions impact of fresh produce commodities, including the production, post-harvest processing, packaging, and transportation stages. Using oranges as a case study, we estimate the carbon footprint per kilogram of fruit delivered to wholesale market in New York City, Los Angeles, Chicago, and Atlanta and assess the relative importance of transportation mode, transportation distance (i.e. localness), and seasonality. We find that the cradle-to-market carbon footprint of oranges delivered to US cities can vary by more than a factor of two, depending on the production origin (e.g. 0.3 kgCO2e/kg for Californian oranges delivered to New York City versus 0.7 kgCO2e/kg for Mexican oranges delivered to New York City). The transportation mode was found to have a significant impact on the results; transportation-related greenhouse gas emissions associated with oranges trucked from Mexico to New York City were found to be six times higher than those transported by containership from Chile, in spite of traveling less than half the distance. Seasonality had a moderate impact on the results and varied depending on the destination city; based on our cradle-to-market analysis, the average carbon footprint of ‘out-of-season’ oranges relative to ‘in-season’ oranges increased by 51%, 46%, 14%, and 24% for Atlanta, Chicago, Los Angeles, and New York City, respectively. This study highlights the value of regionally-specific carbon footprinting for fresh produce and the need for a consistent and standardized data reporting framework for agricultural systems.
Gnana Laryngeal Airway in Clinical Practice: A Prospective Observational Study

Objective The Gnana Laryngeal Airway (GLA) device, a novel supraglottic airway device, is similar to the LMA-Classic in basic design, but with an additional suction port on the convex portion of the laryngeal mask to remove the saliva. We evaluated the GLA device in terms of ease and time to insertion, the number of attempts, oropharyngeal leak pressure (OLP), correct placement, and complications in adult patients undergoing elective surgical procedures. Methods After general anaesthesia, the GLA device was inserted in ASA Class I–II consecutive patients aged 18–60 years, who were scheduled for elective surgeries lasting <2h. An independent observer noted (1) 10 consecutive successful GLA device insertions, all on the first attempt; (2) 10 consecutive device insertions, each <20 second in duration; and (3) 10 consecutive patients with the mean leak <10%. The criteria were fulfilled in 50 consecutive patients. Results In 72% of patients, the GLA device was successfully placed on the first attempt and was effortless in 64%. Between the first 10 and last 10 consecutive patients of the total 50, the ease-of-insertion grade progressively decreased (mean±standard deviation [SD]: 2.80±0.25 to 1.30±0.15, p<0.0001) and so did insertion time in seconds (28.70±1.87 to 14.20±0.79, p<0.0001). The post-insertion, OLP and airway compliance progressively increased, while the cuff inflation volume, peak airway pressure and airway resistance progressively decreased, along with minimal side effects and malposition. Conclusion The GLA device insertion became progressively easier and faster; thus, such a device is promising and warrants further clinical evaluation.
What can tripartite semantic network analysis do for media framing research?

This study primarily aims to demonstrate how tripartite semantic network analysis can help us with media framing analysis. Predominant quantitative framing research has tended to focus on identifying salient frames and/or assessing their influences on public opinions. Also, semantic network analysis has been used to display relationships among frames, which complements conventional quantitative frame analysis for frequency and salience of frames. However, it needs to be advanced in the way that it can assess the dynamical relationships among actors, frames, and the actors’ stances on an issue. In this vein, it is encouraging to find that Robert Entman has demonstrated the dynamics in framing and the complicated relationships between frames and actors in different social realms through his cascading activation model. Tripartite semantic network analysis is expected to contribute to systematically depicting the complicated framing relationships in the form of network. This research attempts to showcase how tripartite semantic analysis can complement framing analysis through a case study on a controversial local housing policy in Madison, Wisconsin, USA. While the descriptive statistical analyses show the overall differences in framing across the newspapers and the changes in framings over time, the tripartite semantic network analyses display delicate and significant differences and changes in framing, which is hard to be captured in quantitative framing analysis. It might also be valuable for not only research but also more effective engagement in public discourses.
Emergency volunteering 2030: Views from managers in volunteerism (Environmental Scan Report No. 1)

What is emergency volunteering going to look like in 2030? How (and by whom) is it going to be organised? How can the emergency management sector best enable the value of volunteering for communities - before, during and after an emergency - into the future? This report provides answers to these questions from the perspectives of 34 managers that have responsibilities for volunteerism in Australian emergency management organisations (EMOs) working across preparedness, response, relief, and recovery. The report is one of a series of Environmental Scan reports that will be synthesised and presented to an expert panel to assist researchers in developing alternative scenarios for the future of emergency volunteering to inform todays decision making.
Student performance and loss aversion

In this paper, we match data on student performance in a multiple-choice exam with data on student risk preferences that are extracted from a classroom experiment. We find that more-loss-averse students leave more questions unanswered and perform worse in the multiple-choice exam when giving an incorrect answer is penalized compared to not answering. We provide evidence that loss aversion parameters extracted from lottery choices in a controlled experiment have predictive power in a field environment of decision making under uncertainty. Furthermore, the degree of loss aversion appears to be persistent over time, as the experiment was conducted three months prior to the exam. We also find important differences across genders; they are partly explained by differences in loss aversion.
VLSI Implementation of Seed Transistor for Super Gate Design based on Grid based Transistor Network Generation

In VLSI digital design, the Propagation Delay, Power Dissipation and Area of circuits are strongly related to the number of transistors which are present on an IC. Hence transistor optimization is special interest when designing digital integrated circuits. Therefore, efficient algorithms are used to generate optimized transistor networks, which are quite useful for designing digital integrated circuits (ICs). Several methods have been proposed for generating and optimizing transistor networks. Most Traditional solutions are based on factoring Boolean expressions in which only Chain - Parallel (CP) arrangement of transistors can be obtained from factored forms. Whereas grid-based methods are able to find CP and also non - CP (NCP) arrangements with potential reduction of transistor count. This method is an effective way of improvising VLSI circuits. In this an efficient algorithm is proposed i.e. Novel (Seed) method. It is automatically generates networks with minimal transistor count starting with irredundant sum of products (ISOPs) as inputs. Novel method is able to deliver both CP switching networks and NCP switching network arrangements, which improves VLSI circuit’s performance in terms of area, power and delay. All the network circuits are implemented in ASIC Cadence by using 45nm and 90nm technology with GPDK libraries. By using Cadence Virtuoso tool, it can obtain schematics of design and its test bench, power analysis, SPICE simulation and its simulation waveform.
Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems

Given the magnitude of soil carbon stocks in northern ecosystems, and the vulnerability of these stocks to climate warming, land surface models must accurately represent soil carbon dynamics in these regions. We evaluate soil carbon stocks and turnover rates, and the relationship between soil carbon loss with soil temperature and moisture, from an ensemble of eleven global land surface models. We focus on the region of NASA’s Arctic-Boreal vulnerability experiment (ABoVE) in North America to inform data collection and model development efforts. Models exhibit an order of magnitude difference in estimates of current total soil carbon stocks, generally under- or overestimating the size of current soil carbon stocks by greater than 50 PgC. We find that a model’s soil carbon stock at steady-state in 1901 is the prime driver of its soil carbon stock a hundred years later—overwhelming the effect of environmental forcing factors like climate. The greatest divergence between modeled and observed soil carbon stocks is in regions dominated by peat and permafrost soils, suggesting that models are failing to capture the frozen soil carbon dynamics of permafrost regions. Using a set of functional benchmarks to test the simulated relationship of soil respiration to both soil temperature and moisture, we find that although models capture the observed shape of the soil moisture response of respiration, almost half of the models examined show temperature sensitivities, or Q10 values, that are half of observed. Significantly, models that perform better against observational constraints of respiration or carbon stock size do not necessarily perform well in terms of their functional response to key climatic factors like changing temperature. This suggests that models may be arriving at the right result, but for the wrong reason. The results of this work can help to bridge the gap between data and models by both pointing to the need to constrain initial carbon pool sizes, as well as highlighting the importance of incorporating functional benchmarks into ongoing, mechanistic modeling activities such as those included in ABoVE.
La Niña's Diminishing Fingerprint on the Central Indian Summer Monsoon

La Niña years tend to provide increased Indian summer monsoon (ISM) rainfall. However, observations show 6–8% reduction in ISM rainfall during post‐1980 La Niñas relative to pre‐1980. Using a suite of atmospheric general circulation model experiments, we replicate this observed phenomenon and attribute it to a combination of weakening La Niña events themselves plus strongly warming tropical Indian Ocean. We demonstrate that half of the ISM rainfall reduction during post‐1980 La Niñas can be attributed to changes in the spatial pattern and intensity of La Niña within the tropical Pacific Ocean. Warmer eastern‐equatorial Pacific Ocean temperatures during post‐1980 La Niñas weaken the Walker circulation, resulting in large‐scale anomalous subsidence over the Indian subcontinent, thereby inhibiting the deep convection that drives ISM rainfall. Further, we demonstrate the declining central ISM rainfall during La Niña years with increasing tropical Indian Ocean warming, which has several serious concerns for regional water resources and stability.
Evaluation of anxiety sensitivity, depression, and personality characteristics in chronic subjective dizziness patients

Aim: Dizziness and vertigo are among the most common symptoms in otolaryngology, neurology and psychiatry clinics. In this study, it was aimed to evaluate anxiety sensitivity, depression and personality traits in patients who were followed up with chronic subjective dizziness. Methods: Fifty-one patients with dizziness complaints for at least 3 months and no history of peripheral vestibular disease were enrolled to the patient group, and 51 healthy controls were enrolled to the control group of this case-control study. Anxiety Sensitivity Index-3 (ASI-3), Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI) and Eysenck Personality Questionnaire (EPQ) scale forms were applied to the patient and control groups by a psychiatrist. Results: There was no statistically significant difference in ASI-3 between the groups (P=0.119). In the patient group, the BAI values were found higher than the control group (P<0.001). While BDI values between the patient and control groups were similar, there was a trend for higher depression scores in the patients compared with the healthy individuals (P=0.052). Conclusion: As a result, the presence of anxiety symptoms and neurotic personality characteristics may worsen dizziness development or disease progression. In the treatment of dizziness patients without neurological and otologic problems, a multidisciplinary approach will provide positive contributions to the course of the disease and to the quality of life of the patients.
Development of a Thulium Fiber Laser for an Atomic Spectroscopy Experiment

A convenient thulium fiber laser source is described with 3 W of output power operating at a wavelength of 2059 nm with a slope efficiency of 49% with respect to input pump power and 60% with respect to absorbed pump power. The laser was applied in an atomic helium spectroscopy experiment to quench 3He (2058.63 nm) and 4He (2058.69 nm) meta-stable singlets (21S0), allowing for further investigation of the helium fine structure. The customized laser effectively eliminates the singlet counts to well below a background level (1%). A simplified analysis describes the basic laser performance with fitted constants in reasonable agreement with previous work.