Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuel Loads and Plant Traits as Community‐Level Predictors of Emergent Properties of Vulnerability and Resilience to a Changing Fire Regime in Black Spruce Forests of Boreal Alaska

Black spruce forest communities in boreal Alaska have undergone self‐replacement succession following low‐to‐moderate severity fires for thousands of years. However, recent intensification of interior Alaska's fire regime, particularly deeper burning of the soil organic layer, is leading to shifts to deciduous‐dominated successional pathways, resulting in many socioecological consequences. Both fuel load quantity and quality (or “burnability”) influence black spruce plant communities' potential to burn. Even relatively low fuel loads, such as those seen in black spruce forest understory, can be highly influential drivers of fire behavior due to their high flammability. Additionally, black spruce community self‐replacement following fire can be largely attributed to the suite of functional and life history traits possessed by the species dominating these communities. We used fuel load (quantity and quality) and amount of within‐population plant trait variation (coefficient of variation; CV) as community‐level emergent properties to investigate black spruce forest vulnerability and resilience to a changing fire regime across the landscape. Our burn severity potential index (BSPI), calculated from fuel load quantity and quality measurements, indicates that drier, higher elevation stands with thicker active layers were the most vulnerable to fire‐induced vegetation shifts under a changing fire regime. Forest resilience to fire‐induced vegetation shift, represented by higher CV, was negatively associated with BSPI and greatest in ecoregions dominated by lowland black spruce forests. Together, these analyses provide critical information for determining the likelihood of stand‐replacing shifts in dominant vegetation following fire and for implementing appropriate ecosystem management practices.
Modelling Stochastic Context of Audio-Visual Expressive Behaviour With Affective Processes

Recognising apparent emotion from audio-visual signals in naturalistic conditions remains an open problem. Existing methods that build on recurrent models, or in the modelling of contextual dependencies at the feature level using self-attention fail to model the long-term dependencies that subtly occur at different levels of abstraction. Affective Processes have emerged as a novel paradigm to the modelling of temporal dynamics through a probabilistic global latent variable that captures context and induces dependencies in the outputs, showing superior performance with little complexity. Despite its impressive results on visual data, Affective Processes remain unexplored in the domain of audio data, known to crucially influence the perception of emotions. In this paper, we first revisit and extend Affective Processes to the speech domain, identifying the key components and learning procedures for their efficient training. We then extend Affective Processes to audio-visual affect recognition, using modality-specific context encoders. Finally, we propose a novel application of Affective Processes in the domain of Cooperative Machine Learning for propagating affect labels in videos using sparse human supervision. We conduct extensive ablation studies, identifying the main components behind the success of Affective Processes, as well as comparisons against existing works in a variety of datasets.
Prenylcysteine Oxidase 1 (PCYOX1), a New Player in Thrombosis

Prenylcysteine Oxidase 1 (PCYOX1) is an enzyme involved in the degradation of prenylated proteins. It is expressed in different tissues including vascular and blood cells. We recently showed that the secretome from Pcyox1-silenced cells reduced platelet adhesion both to fibrinogen and endothelial cells, suggesting a potential contribution of PCYOX1 into thrombus formation. Here, we show that in vivo thrombus formation after FeCl3 injury of the carotid artery was delayed in Pcyox1−/− mice, which were also protected from collagen/epinephrine induced thromboembolism. The Pcyox1−/− mice displayed normal blood cells count, vascular procoagulant activity and plasma fibrinogen levels. Deletion of Pcyox1 reduced the platelet/leukocyte aggregates in whole blood, as well as the platelet aggregation, the alpha granules release, and the αIIbβ3 integrin activation in platelet-rich plasma, in response to adenosine diphosphate (ADP) or thrombin receptor agonist peptide (TRAP). Washed platelets from the Pcyox1−/− and WT animals showed similar phosphorylation pathway activation, adhesion ability and aggregation. The presence of Pcyox1−/− plasma impaired agonist-induced WT platelet aggregation. Our findings show that the absence of PCYOX1 results in platelet hypo-reactivity and impaired arterial thrombosis, and indicates that PCYOX1 could be a novel target for antithrombotic drugs.
Stochastic Approach For Modeling Arcing Faults In Cables From Experimental Data

o This paper discusses stochastic arcing fault models developed based on examination of test data conducted at shipboard system voltage levels by the US Navy at KEMA-Power Test, Inc. The arc model resistance had a typical mean value based upon physical parameters of the particular class of test and a random variation around this mean value. Models were developed for arcing faults on both on AC and DC systems. The models were developed using ACSL (Advanced Continuous Simulation Language) and veried with the test data results so the arcing fault models could be included in simulations of shipboard power systems for conducting fault studies to set protective devices and rate apparatus. The main objective of the model development was to match the ratio of arc voltage to fault current between the test data and the simulation results. randomly variation around this value. This model was used develop simulation cases to match the results of experimental tests on several classes of ac and dc cables proposed for use in shipboard power systems. The project sponsors will insert the resulting arcing fault models into simulation models that include detailed representatiions of the shipboard power system and conduct fault studies. The results of these stud- ies will be used to determine magnitudes of fault currents and resulting voltages on system components to rate circuit breakers, rate insulation and overvoltage devices, and to set protective devices. The Advanced Continuous Simulation Lan- guage (ACSL) (6) was used for the detailed shipboard power system model, so the arcing fault models are developed in ACSL as well. The models have also been implemented in using FORTRAN statements in the control system modeling language in an emtp-type program as well. Section II of the paper provides background on the high voltage hardware testing. Section III describes other methods for modeling arcing faults. Section IV introduces the stochastic model. Sections V and VI describe the power system repre- sentation in the simulation model and show simulation results for several cases. Section VII describes the model verication.
Path integral method for stochastic equations of financial engineering

The integral path method was applied to determine certain stochastic variables which occur in problems of financial engineering. A stochastic variable was defined by a stochastic equation where drift and volatility are functions of a stochastic variable. As a result, for transition probability density, a path integral was built by substituting variables Wiener's path integral (Wiener's measure). For the stochastic equation, Ito rule was applied in order to interpret a stochastic integral. The path integral for transition probability density was also found as a result of the Fokker--Planck equation solution, corresponding to the stochastic equation. It was shown that these two approaches give equivalent results.
The alleviation of manganese toxicity by ammonium in sugarcane is related to pectin content, pectin methyl esterification, and nitric oxide

Coexistence of ammonium ( NH4+ ) with manganese (Mn) in acid soils may facilitate the alleviation of Mn toxicity to plants. However, the effect of NH4+ on Mn toxicity and the corresponding mechanisms are unclear. In this study, the effects of NH4+ and nitrate ( NO3‐ ) on Mn toxicity, cell wall properties, and nitric oxide (NO) signaling in sugarcane were compared. NH4+ alleviated Mn‐induced chlorosis in sugarcane seedlings and increased seedling biomass compared with NO3‐ . Exogenous application of NH4+ decreased the root cell wall pectin content and methyl esterase (PME) activity, but increased the degree of root pectin esterification (PMD). These changes were accompanied by reductions in the Mn content in roots, leaves, root cell wall, and cell wall pectin. An analysis of adsorption kinetic revealed less Mn‐adsorption capacity in cell walls extracted from NH4+ ‐fed than from NO3‐ ‐fed sugarcane. Mn induced NO accumulation in sugarcane roots, but NH4+ ‐fed seedlings accumulated less NO. Exogenous application of the NO donor sodium nitroprusside increased the Mn content of root cell wall pectin in NH4+ ‐fed sugarcane, while the NO scavenger 2‐(4‐carboxyphenyl)‐4,4,5,5‐tetramethylimidazoline‐1‐oxyl‐3‐oxid decreased the Mn content in NO3‐ ‐fed sugarcane. These treatments eliminated the difference in the pectin Mn content between NH4+ ‐fed and NO3‐ ‐fed sugarcane, as did a similar treatment with the nitrate reductase inhibitor tungstate, which decreased root cell wall pectin content and NO accumulation. These results suggest that (i) NH4+ alleviates Mn toxicity in sugarcane by reducing root pectin accumulation and root cell wall PME activity, thereby increasing cell wall PMD and decreasing both the Mn‐binding capacity of cell wall and Mn accumulation, and (ii) NO mediates the accumulation of both pectin and Mn in response to different forms of nitrogen. The physiological mechanisms underlying the alleviation of ammonium on Mn phytotoxicity were clarified, which provided important implication for agricultural production and ecosystem functioning in acid soil.
Cow’s Milk Intake and Risk of Coronary Heart Disease in Korean Postmenopausal Women

Numerous studies have reported conflicting results associated with cow’s milk intake and coronary heart disease (CHD). However, studies involving postmenopausal women are very limited. This study was therefore undertaken to identify the relationship between cow’s milk intake and CHD risk in postmenopausal women, using data from the 6th period of the Korea National Health and Nutrition Examination Survey (2013–2015). A total of 1825 postmenopausal women, aged 50–64 years old, were included in the final analysis. The frequency of cow’s milk consumption for each subject was determined using the semi-quantitative food frequency questionnaire, and was classified into four groups (Q1–Q4): Q1, group that did not drink milk (no milk, n = 666); Q2, 0 < frequency of milk intake per week ≤ 1 (n = 453); Q3, 1 < frequency of milk intake per week ≤ 3 (n = 319); and Q4, frequency of milk intake >3 times per week (n = 387). General characteristics, such as education, living area, household income, and obesity level, were compared between the four groups. Percentages of daily nutrient intake compared to the dietary reference intake for Koreans (KDRIs) were determined, and the Framingham Risk Score (FRS), atherogenic index (AI), and atherogenic index of plasma (AIP) were determined as the CHD risk indicators. Except household income, no significant difference was obtained among the four groups with respect to age, education, living area, or obesity. Compared to KDRIs, the intake ratio of calcium, phosphorus, and riboflavin were significantly higher in the Q4 group than in the Q1–Q3 groups. Blood HDL-cholesterol was significantly higher in Q4 than in Q1. The CHD risk factors FRS (%), AI, and AIP were significantly lower in the Q4 group as compared to the other groups (CHD risk (%): Q1 9.4, Q4 8.5; AI: Q1 3.06, Q4 2.83; API: Q1 0.37, Q2 0.31, Q4 0.32). FRS was determined to be significantly and positively correlated to AI or AIP, and negatively correlated with the cow’s milk intake frequency and calcium intake. In conclusion, compared to women who do not consume cow’s milk, postmenopausal women who consume cow’s milk frequently have a better nutritional status of calcium, phosphorus, and vitamin B12, higher HDL levels, and a lower level of CHD risk indicators, such as FRS, AI, and AIP, contributing to decreased CHD risk in a 10-year period. Therefore, to prevent the risk of CHD in postmenopausal women, there needs to be a greater emphasis for cow’s milk consumption four or more times per week.
Lane Departure Assessment via Enhanced Single Lane-Marking

Vision-based Lane departure warning system (LDWS) has been widely used in modern vehicles to improve drivability and safety. In this paper, a novel LDWS with precise positioning is proposed. Calibration strategy is first presented through a 3D camera imaging model with only three parallel and equally spaced lines, where the three angles of rotation for the transformation from the camera coordinate system to the world coordinate system are deduced. Then camera height is calculated compared to the previous works using a measured one with potential errors. A criterion for lane departure warning with only one of the two lane-markings is proposed to estimate both yaw angle and distance between the lane-markings and the vehicle. Experiments show that calibration strategy can be easily set up and achieve an average of 98.95% accuracy on the lane departure assessment.
Optimizing Data Center Energy Efficiency via Event-Driven Deep Reinforcement Learning

To reduce the skyrocketing energy consumption of data centers, the prevailing approaches adopt the time-driven manner to control IT and cooling subsystems. These methods suffer from highly dynamic system states, complex action spaces and the risk of instability caused by frequent and unnecessary control operations. To tackle these problems, we propose a novel event-driven control paradigm and an optimization algorithm, under the deep reinforcement learning (DRL) framework. The principle is to make decisions based on certain critical events (e.g., overheating), rather than fixed periodic control. Specifically, we design an event-driven optimization framework to trigger control operations. Then, we present several models to describe IT and cooling subsystems, and mathematically define events to capture four types of prior factors that impact system performance. Furthermore, we develop an event-driven DRL (E-DRL) optimization algorithm to dispatch jobs and regulate cooling facilities for energy efficiency. Using two different types of real workload traces, we conduct extensive experiments to demonstrate that: 1) E-DRL reduces the number of regulating decisions by 70%<inline-formula><tex-math notation="LaTeX">$\sim$</tex-math><alternatives><mml:math><mml:mo>∼</mml:mo></mml:math><inline-graphic xlink:href="hu-ieq1-3157145.gif"/></alternatives></inline-formula>95% while achieving a comparable or even better energy efficiency in comparison with the state-of-the-art algorithm; and 2) E-DRL can adapt the control frequency to the changing operational conditions and diverse workloads.
Água residuária gerada em tratamento de água de piscina e possibilidade de reúso agrícola

Este trabalho teve por objetivos caracterizar e discutir a possibilidade de reúso agrícola da água de lavagem de filtros (ALAF) da piscina de um campus universitário e avaliar sua clarificação com e sem condicionamento químico, utilizando sementes de Tamarindus indica e cal. A qualidade da ALAF foi verificada em termos de parâmetros físicos, químicos, microbiológicos e biológico. Foram realizados ensaios de clarificação por gravidade com dosagens 0 e 15 g/kg SST para os dois coagulantes. O software R foi utilizado para a análise de variância, com um nível de 5% de significância. Observou-se um potencial de reúso agrícola da ALAF após seu tratamento (para remoção de SST e alumínio total), desde que acompanhado de manejo da irrigação, para algumas culturas. Para as condições dos ensaios e requisitos da análise de variância, não houve diferença entre os coagulantes tamarindo e cal, bem como na interação destes com as dosagens, para turbidez e SST no sobrenadante e, SST e alumínio total do lodo. Palavras-chave: Coagulantes naturais. Água de lavagem de filtro. Condicionamento químico. Tamarindus indica. Cal hidratada. Ensaios em escala de bancada.
Predicting Perforating Depths with Logging Data

Perforating depth is not only the most basic data for production estimation and calculation of productivity ratio, but also the basic condition of optimizing perforation scheme. According to the perforation charge performance and strength parameter of the formation, calculated are the actual perforating depths with the borehole wall as the starting depth-computing point in the open holes while considering the energy consumption of the charges penetrating through casing pipes and cement mantles. There is annular space between the perforating gun body and the casing, and also between the charges and casing walls. So, the maximum and minimum perforating depths are figured out after the space correction. Calculated and analyzed are the perforating depths for a well having pollution radius data. Now, many wells don't have enough logging data to calculate the perforating depths. Using our newly proposed method allows us to correctly estimate the depths of most wells.
Evaluation of Knowledge Levels of Dentistry Students on the COVID-19 and its Effects on Depression

Objective: To determine the level of knowledge of dentistry students regarding the COVID-19 outbreak and to evaluate whether the risk factors of the outbreak cause depression. Material and Methods: This study was conducted with 516 dentistry students (3rd, 4th and 5th grades) who started clinical practice in their education. The first part of the questionnaires applied to the students includes questions about demographic information, while the second part contains questions to determine their knowledge levels on the COVID-19 pandemic and protection against it. In the third section, Beck Depression Inventory (BDI) was used to examine depression symptoms. The data were analyzed by frequency analyses and Chi-squared tests via the IBM SPSS 22.0 software. Results: Of the 516 students, 150 (29%) participants were in the 5th, 212 (41%) were in the 4th and 154 (30%) were in the 5th grade. 355 (69%) students stated that their knowledge level about COVID-19 was high. 30.9% were conscious of the importance of using masks. 29.6% were aware of the importance of using gloves, 50.5% of not shaking hands. According to BDI scores, 57.1% of the participants seemed to experience moderate to severe and very severe depression. Conclusion: It was observed that the students didn't have a sufficient level of knowledge about the factors affecting the spread of the pandemic. New stress factors such as COVID-19 may increase the incidence of depression.
A visual approach towards forward collision warning for autonomous vehicles on Malaysian public roads

Background: Autonomous vehicles are important in smart transportation. Although exciting progress has been made, it remains challenging to design a safety mechanism for autonomous vehicles despite uncertainties and obstacles that occur dynamically on the road. Collision detection and avoidance are indispensable for a reliable decision-making module in autonomous driving. Methods: This study presents a robust approach for forward collision warning using vision data for autonomous vehicles on Malaysian public roads. The proposed architecture combines environment perception and lane localization to define a safe driving region for the ego vehicle. If potential risks are detected in the safe driving region, a warning will be triggered. The early warning is important to help avoid rear-end collision. Besides, an adaptive lane localization method that considers geometrical structure of the road is presented to deal with different road types. Results: Precision scores of mean average precision (mAP) 0.5, mAP 0.95 and recall of 0.14, 0.06979 and 0.6356 were found in this study. Conclusions: Experimental results have validated the effectiveness of the proposed approach under different lighting and environmental conditions.
Who Cares? The Neoliberal Turn and Changes in the Articulations of Women’s Relation to the Swedish Welfare State

ABSTRACT This article aims to investigate how articulations of women’s relation to the welfare state and modes of political agency has changed in Sweden between 1977 and 2017; a period characterized by the introduction and implementation of a neoliberal political rationality. By way of discourse analysis, the article highlights the reciprocal relationship between the construction of the welfare state and women. To this end, it analyses the debates following two films that problematize women’s relation to the welfare state, Summer Paradise (1977) and Beyond Dreams (2017). The article argues that: (a) childcare as a structuring factor for women’s work is replaced by a focus on the responsibility of the individual to provide for herself; (b) gender as a structuring principle is replaced by gender as an attribute of the individual, and; (c) the relation between women and the state is individualized. As a result, the state becomes articulated as an individualized collectivity, which aims to serve the individual’s self-preservation as opposed to the state being an arena for solving societal and collective problems. We argue that the neoliberal turn has changed women’s political subjectivity from a focus on collective action to an atomization of agency against systemic gender inequalities.
DETERMINING THE INTERNAL STRUCTURE OF CEMENT-BASED MATERIALS BY USING MRI TECHNIQUES

The primary concerns of the internal structure of cement-based materials involve the distribution of pores, pore size, and the manner in which they are connected. Thoroughly understanding the distributive rules of pores and the approaches to breaking their links can contribute considerably to enhancing the durability of cement-based materials. Several methods are used to measure the pores of cement-based materials; however, they cannot determine the exact location of pores or structural links. Magnetic resonance imaging (MRI) has been widely applied in physical examinations and has matured to the level of being able to obtain 3D images of the organs of recipients without causing damage. In this study, MRI and mercury intrusion porosimetry (MIP) techniques were used to analyze the distribution of pores in mortar specimens with water-to-cement (w/c) ratios of 0.45, 0.55, and 0.65. The results indicate that MRI techniques can be used to determine the spatial distribution of pores and can obtain 3D images of pores in mortar.