Miracle-dz/UniFAR-FTUs huggingface dataset:
Catastrophic Failure: How and When? Insights From 4‐D In Situ X‐ray Microtomography

Catastrophic failure of brittle rocks is important in managing risk associated with system‐sized material failure. Such failure is caused by nucleation, growth, and coalescence of microcracks that spontaneously self‐organize along localized damage zones under compressive stress. Here we present X‐ray microtomography observations that elucidate the in situ micron‐scale processes, obtained from novel tri‐axial compression experiments conducted in a synchrotron. We examine the effect of microstructural heterogeneity in the starting material (Ailsa Craig microgranite; known for being virtually crack‐free) on crack network evolution and localization. To control for heterogeneity, we introduced a random nanoscale crack network into one sample by thermal stressing, leaving a second sample as‐received. By assessing the time‐dependent statistics of crack size and spatial distribution, we test the hypothesis that the degree of starting heterogeneity influences the order and predictability of the phase transition between intact and failed states. We show that this is indeed the case at the system‐scale. The initially more heterogeneous (heat‐treated) sample showed clear evidence for a second‐order transition: inverse power law acceleration in correlation length with a well‐defined singularity near failure and distinct changes in the scaling exponents. The more homogeneous (untreated) sample showed evidence for a first‐order transition: exponential increase in correlation length associated with distributed damage and unstable crack nucleation ahead of abrupt failure. In both cases, anisotropy in the initial porosity dictated the fault orientation, and system‐sized failure occurred when the correlation length approached the grain size. These results have significant implications for the predictability of catastrophic failure in different materials.
Biomass production and carbon sequestration of dense downy birch stands on cutaway peatlands

ABSTRACT The establishment of biomass plantations with short-rotation forestry principles is one of the after-use options for cutaway peatlands. We studied biomass production and carbon sequestration in the above- and below-ground biomass of 25 naturally afforested, 10–30 years old downy birch (Betula pubescens Ehrh.) stands located in peat cutaway areas in Finland. Self-thinning reduced the stand density from 122,000 trees ha−1 (stand age of 10 years) to 10,000 trees ha−1 (25–30 years), while the leafless above-ground biomass increased from 17 Mg ha−1 up to 79–116 Mg ha−1. The total leafless biomass (including stumps and roots) varied from 46 to 151 Mg ha−1. The mean annual increment (MAI) of the above-ground biomass increased up to the stand age of 15 years, after which the MAI was on the average 3.2 Mg ha−1a−1. With below-ground biomass, the MAI of the stands older than 15 years was 4.7 Mg ha−1. The organic matter accumulated in the O-layer on the top of the residual peat increased linearly with the stand age, reaching 29.3 Mg ha−1 in the oldest stand. The O-layer contributed significantly to the C sink, and the afforestation with downy birch converted most of sites into C sinks.
Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US

Incomplete representations of physical processes often lead to structural errors in process-based (PB) hydrologic models. Machine learning (ML) algorithms can reduce streamflow modeling errors but do not enforce physical consistency. As a result, ML algorithms may be unreliable if used to provide future hydroclimate projections where climates and land use patterns are outside the range of training data. Here we test hybrid models built by integrating PB model outputs with an ML algorithm known as long short-term memory (LSTM) network on their ability to simulate streamflow in 531 catchments representing diverse conditions across the Conterminous United States. Model performance of hybrid models as measured by Nash–Sutcliffe efficiency (NSE) improved relative to standalone PB and LSTM models. More importantly, hybrid models provide highest improvement in catchments where PB models fail completely (i.e. NSE < 0). However, all models performed poorly in catchments with extended low flow periods, suggesting need for additional research.
The Transformative Paradigm: Equipping Technical Communication Researchers for Socially Just Work

ABSTRACT This article provides an overview of robust social justice work already done in technical and professional communication (TPC) to introduce the transformative paradigm, an action research framework articulated by Donna Mertens. Research articles in TPC offer examples of the axiological, ontological, epistemological, and methodological tenets of the transformative paradigm. Together with a measured discussion of the paradigm, this Methodologies and Approaches article responds to calls in TPC scholarship to articulate and practice methodologies resonant with the social justice turn.
Invasive macrophytes induce context‐specific effects on oxygen, pH, and temperature in a hydropeaking reservoir

Dense macrophyte beds are known to produce extreme diurnal oxygen and temperature conditions in shallow lakes. However their influences in managed hydropeaking reservoirs has received limited attention. We measured dissolved oxygen, pH and water temperature in the Lake Karāpiro hydroreservoir, northern New Zealand, across a gradient of proportional water‐column height occupied by the invasive macrophytes Egeria densa and Ceratophyllum demersum, which dominated in the upper‐riverine (variable water inflow) and lower‐lacustrine (variable water level) sections, respectively. Hypoxia and anoxia events that occurred inside invasive macrophyte beds during their summer peak biomass accumulation period were more pronounced for C. demersum than for E. densa, and within the bottom 20% of the water column. In contrast, pH and temperature changed little in relation to proportional macrophyte height. Macrophyte species differences in the production of hypoxia and anoxia events increased when site‐specific hydropeaking management covariates (depth, inflows, water level) were accounted for. This association with hydropeaking likely resulted from contrasting hydrodynamics in the lower‐lacustrine and upper‐riverine lake sections, where oxygen can decrease with higher water levels and lower water inflow rates, respectively. During the course of our study, some macrophyte beds were treated with herbicide, enabling us to document prolonged and sustained hypoxic/anoxic conditions near the bottom following spraying. These results underscore the adverse effects of invasive macrophytes on water physicochemical attributes that sustain aquatic biota, and highlight the context‐dependent nature of these effects moderated by reservoir management for hydropeaking and macrophyte control.
Elements of disturbance that affect epiphyte vitality in a temperate rainforest: an experimental approach

Epiphytes are an abundant and diverse component of many wet temperate forests and have significant roles in ecosystem processes. Little is known about the processes and rates of their death and decomposition when they fall from the canopy, which limits our understanding of their role in forest carbon sequestration and nutrient cycling. In the temperate rainforest of the Quinault River Valley, Washington State, our aim was to test hypotheses regarding four elements of disturbance that might contribute to their decline. We established set of experiments in which we placed samples of canopy epiphytes and their branch segments: (i) in the canopy versus forest floor microenvironment (stratum); (ii) attached to live versus dead branch substrates; (iii) subjected to physical disruption and ‘jarring’; and (iv) in direct versus indirect contact with the forest floor. Over the 2-year study, we assigned a non-destructive ‘vitality index’ (based on color and apparent mortality and dryness) to each sample every 2–3 months to compare effects of the experimental treatments and analyzed with a statistical model and post hoc pairwise comparisons of treatments. The canopy versus ground stratum and live/dead branch status significantly affected epiphyte vitality. Effects of physical disruption and ground contact were not significant. There were seasonal effects (low vitality during the sampling times in the summer, revitalization upon sampling times in the winter) for all treatments except samples in contact with the ground. One implication of these results relates to effects of climate change, which is predicted to shift to hotter, drier summers and wetter winters. Climate change may affect forest dynamics and nutrient cycling in unpredictable ways. Results also point to future experiments to understand biotic and abiotic effects on epiphyte disturbance and dynamics.
The Effect Of Return On Assets (ROA), Net Profit Margin (NPM), Dividend Payout Ratio (DPR) And Dividend Yield (DY) On Stock Prices In The Subsectors Insurance Company Listed In Indonesia Stock Exchange Period 2015-2018

This study aims to examine the effect of Return on Assets (ROA), Net Profit Margin (NPM), Dividend Payout Ratio (DPR), Dividend Yield (DY) on Share Prices in Insurance sub-sector companies listed on the Indonesia Stock Exchange period 2015- 2018. This type of research is explanatory research. This study took a population of 16 companies with a sample of 10 companies selected through purposive sampling, so the number of sample observations over 4 years to 40 companies. The data used are secondary data, namely financial statement data in the form of ROA, NPM, DPR and DY ratios from 2015-2018. Secondary data was collected through documentation of research objects obtained by the IDX. Furthermore, the data were analyzed using multiple linear regression which had previously been fulfilled the classic assumption test as a prerequisite for conducting a regression test. The results of this study ROA and NPM significantly influence stock prices. DPR and DY have no effect on stock prices. The coefficient of determination (R2)worth of 0.29%, which means that the ROA, NPM, Parliament and DY explain the effect on stock prices by 29%, while the value of 71% is influenced by other variables not included in this study.
Factors Influencing Farmers’ Climate Change Adaptation in Northern Ghana: Evidence from Subsistence Farmers in Sissala West, Ghana

Most African countries are vulnerable to climate change as a result of poverty, weather extremes, and insufficient governmental agricultural support. Using the area of Sissala West District, factors influencing farmers’ adaptation to climate change and strategies used to avert climate change impact were determined. A total of 330 small-scale farmers were sampled and their views were determined Using logits regression model, weighted average index, and frequency table. Weighted average index was used to rank opinions of 150 key informants in focus group discussions. Using logits regression model, the study indicated irregular rainfall, high temperature, weather information, and high evaporation as the factors compelling farmers to adapt to climate change. Weighted Average Index used to measure weather extremes revealed that drought and temperature had the highest level of occurrence. Furthermore, climate change adaptation strategies assessed in the study showed that agroforestry practices, drought-resistant crops, and mulching were the most preferred methods. The study concluded that farmers’ ability to adapt to climate change can be improved if Environmental Protection Agency and Ministry of Food and Agriculture intensify climate adaptation campaigns, increase access to weather information, and training farmers on adaptable strategies including, but not limited to, alternative sources of livelihood.
Carbon Dioxide and Methane Emissions From A Temperate Salt Marsh Tidal Creek

Coastal salt marshes store large amounts of carbon but the magnitude and patterns of greenhouse gas (GHG; i.e., carbon dioxide (CO2) and methane (CH4)) fluxes are unclear. Information about GHG fluxes from these ecosystems comes from studies of sediments or at the ecosystem‐scale (eddy covariance) but fluxes from tidal creeks are unknown. We measured GHG concentrations in water, water quality, meteorological parameters, sediment CO2 efflux, ecosystem‐scale GHG fluxes, and plant phenology; all at half‐hour intervals over 1 year. Manual creek GHG flux measurements were used to calculate gas transfer velocity (k) and parameterize a model of water‐to‐atmosphere GHG fluxes. The creek was a source of GHGs to the atmosphere where tidal patterns controlled diel variability. Dissolved oxygen and wind speed were negatively correlated with creek CH4 efflux. Despite lacking a seasonal pattern, creek CO2 efflux was correlated with drivers such as turbidity across phenological phases. Overall, nighttime creek CO2 efflux (3.6 ± 0.63 μmol/m2/s) was at least 2 times higher than nighttime marsh sediment CO2 efflux (1.5 ± 1.23 μmol/m2/s). Creek CH4 efflux (17.5 ± 6.9 nmol/m2/s) was 4 times lower than ecosystem‐scale CH4 fluxes (68.1 ± 52.3 nmol/m2/s) across the year. These results suggest that tidal creeks are potential hotspots for CO2 emissions and could contribute to lateral transport of CH4 to the coastal ocean due to supersaturation of CH4 (>6,000 μmol/mol) in water. This study provides insights for modeling GHG efflux from tidal creeks and suggests that changes in tide stage overshadow water temperature in determining magnitudes of fluxes.
Slash Pile Burn Scar Restoration: Tradeoffs between Abundance of Non-Native and Native Species

The accumulation of live and dead trees and other vegetation in forests across the western United States is producing larger and more severe wildfires. To decrease wildfire severity and increase forest resilience, foresters regularly remove excess fuel by burning woody material in piles. This common practice could also cause persistent ecosystem changes such as the alteration of soil physical and chemical properties due to extreme soil heating, which can favor invasion by non-native plant species. The abundance and species richness of native plant communities may also remain depressed for many years after burning has removed vegetation and diminished propagules in the soil. This adds to the vulnerability of burned areas to the colonization and dominance by invasive species. Research into the use of revegetation techniques following pile burning to suppress invasion is limited. Studies conducted in various woodland types that investigated revegetation of pile burn scars have met with varying success. To assess the effectiveness of restoring pile burn scars in Rocky Mountain National Park, Colorado, we monitored vegetation in 26 scars, each about 5 m in diameter, the growing season after burning. Later that summer, we selected 14 scars for restoration that included soil scarification, seed addition, and pine duff mulch cover. We monitored the scars for four years, pre-restoration, and three years post-restoration and found that the cover of seeded species exceeded the surrounding unburned areas and unseeded controls. The restoration seeding suppressed cover of non-native species as well as native species that were not seeded during restoration. Our results suggest that restoration of pile burn scars could be a useful tool to retard the establishment of invasive plant species when there are pre-existing infestations near scars. However, this must be weighed against the simultaneous suppression of native species recruitment. Monitoring for periods more than three years will help us understand how long the suppression of native and non-native species by restoration species may persist.
Leveraging mist and fog for big data analytics in IoT environment

Internet of Things (IoT) emerged as one of the leading technological advancements of our days. IoT generates enormous quantities of valuable data that need on time processing, resulting in reliable, and accurate decisions based on the Internet of Things vision. The quality of the generated data is inadequate, incomplete, uncertain, and produced from multiple sources. Although cloud servers can analyze and store enormous data, they need a lot of time to send full‐size data for storage and analysis as well as the high overhead they have that not satisfactory in many applications. This article provides a systematic way to review the IoT environment according to big data analytics together with limitations and challenges. Moreover, a cloud‐fog‐mist combination for handling IoT data concerning centralized and distributed data mining is explained. A proposed hybrid real‐time remote patient monitoring framework introduced that consists of the integration among the mist, fog, and cloud for healthcare treatment, which remote‐monitors patients continuously. In addition, Reduced‐Error Pruning tree (REPtree), MultiLayer Perceptron, naïve Bayes, and Sequential Minimal Optimization algorithms have applied to “Gas sensors for home activity monitoring” dataset to demonstrate the feasibility of traditional data mining algorithms to IoT data. The results showed that the REPtree algorithm achieved better accuracy against others with accuracy ranged between 90.66% and 93.6% according to the size of the data used in the study. Still, for the time metric, naive Bayes outperformed them with the lowest time between 1 and 18 seconds for building the model.
The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards ‘untact’ tourism in South Korea during the first wave of the pandemic (March 2020)

ABSTRACT This study highlights ‘untact’ tourism as a health-protective behaviour stemming from individuals’ perceptions of COVID-19 risk. Based on the frameworks of the Health Belief Model and the extended Theory of Planned Behaviour, this study examines the effect of COVID-19 risk perception on behavioural intention towards untact tourism. The online survey was administered to South Korean citizens in March and April 2020. A total of 877 questionnaires were used for data analysis. The results indicate that affective risk perception is a significant antecedent of attitude, while cognitive risk perception was found to positively influence subjective norms. Despite the significant influence of both cognitive and affective risk perceptions on behavioural intention, affective risk perception exerts a negative influence on behavioural intention, which is in opposition to the original hypothesis. Attitude was found to be a significant mediator between affective risk perception and behavioural intention whereas subjective norms mediated the relationship between cognitive perception and behavioural intention. Gender and marital status partially moderated the hypothesized relationships among the constructs. This study provides timely and insightful implications for tourism practitioners who will be expected to prepare the post-corona field for a new normal after the experience of restricted living during an unprecedented pandemic.
Economic appraisal of fish cultre: A case study from Gomati District in Tripura

Fish cultivation has been recognised as an emerging enterprise in India particularly in North-eastern states like Tripura. It is considered to be an important economic activity for generating income and gainful employment of rural people in Tripura. The present study examined the economic viability of fish culture in Gomati District of Tripura and the results revealed that the enterprise is quite profitable which requires a huge investment. The study recommends extending more research and development in this sector to enhance the area and production for ensuring sustainable livelihood and income to the farmers of the state.
Calm Before the Storm: An Early Warning Approach Before and During the COVID-19 Crisis

This paper develops a means of visualising the vulnerability of complex systems of financial interactions resulting from the changing risk tolerance of investors. The investors’ risk behavior contributes to the buildup of vulnerability in crisis and in calm periods. We show how both time-varying risk tolerance and spillover indices can be translated into two-dimensional information transmission and crisis transmission maps, respectively. Taken together, the information transmission maps have the advantage of highlighting potential crisis transmission pathways in the crisis transmission maps. These maps provide clear visualization showing information transmission predates crisis transmission drawing from conditional signed spillover and risk tolerance indices computed from equity market data for 31 global markets between 1998 and 2020. We examine if investors’ risk preference induces a crisis and to what extent such a predictor may be related to a pandemic. Furthermore, we take a special look at the Covid-19 pandemic and its impact on the dynamics of systemic crisis transmission.
Human primary T cells: A practical guide

Human primary T cells are invaluable and feasible model systems to study the characteristics of the immune cells in various contexts, including but not limited to cancer immunotherapy. Following isolation of T cells from fresh human blood samples, it is possible to culture, expand, and manipulate these cells, which allows extensive investigation for research purposes. Techniques for isolation and handling of T cells are well-established but parts of the protocols can highly vary across different labs. These differences in the protocols are there due to historical reasons and are often only supported by anecdotal evidence. We systematically modified basic components of the T cell culturing protocols and collected data on how they altered the final yield. Here, based on these data, we provide practical hints and tips on basic cellular and molecular techniques for handling primary human T cells. We hope that this guide will serve as a reference point to allow evaluate, discuss, and improve current practices in T cell culturing and manipulation.
Ethnic Disparities in COVID-19 in the USA: An Update

Background: Available data suggest that minority groups are particularly impacted by coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Objective: To review the latest data that reflects the impact of COVID-19 in minority groups in the USA. Methods: Review of English literature by search of electronic databases: Pub/MEDLINE until July 22, 2020. Search terms included COVID-19, testing, admission, mortality, ethnicity, African Americans, Hispanics, and Asians. Retrospective studies, pertinent reviews and consensus guidelines are reviewed. Pre-print, not yet peer-reviewed studies are also carefully included. Results: African American patients and Hispanics are more likely than Whites to be tested for COVID-19, and to have positive results. African American patients get tested for COVID-19 more frequently in the emergency department or as inpatients rather than in the ambulatory setting. As of June 12, 2020, compared with Whites, hospitalization rates for COVID-19 among American Indians/ Alaska Natives was 5.5 times higher, and among non-Hispanic Blacks and Hispanics was 4.0 to 4.4 times higher. As of July 21st, 2020, compared with White patients, age-adjusted mortality rates for Blacks was 3.7 times higher, for Indigenous people was 3.5 times higher, for Pacific Islanders was 2.8 times higher, for Latinos 2.5 times higher, and Asians 1.4 times higher. A national internet survey suggests that knowledge regarding COVID-19 may be insufficient among African Americans and Hispanics. Conclusion: Covid-19 disproportionately affects minority groups, particularly African Americans, who had the highest mortality among all ethnic/racial groups.