Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable and efficient inference via CPE

Abstract Two primary concerns of inference for high-dimensional data are statistical accuracy and computational efficiency. Despite the appealing asymptotic properties of existing de-biasing methods, the de-biasing step is generally considered to be computationally intensive. In this article, we propose the constrained projection estimator (CPE) for deriving confidence intervals in a scalable and efficient way under high dimensions when the unknown parameters adopt an approximately sparse structure. The proposed method is implemented on the constrained projection spaces corresponding to the identifiable signals determined by a prescreening procedure, which significantly reduces the computational cost in comparison to the full de-biasing steps. Theoretically, we demonstrate that the proposed inference method enjoys equivalent asymptotic efficiency to the full de-biasing procedure in view of the lengths of confidence intervals. We demonstrate the scalability and effectiveness of the proposed method through simulation and real data studies.
These roots that bind us: using writing to process grief and reconstruct the self in chronic illness

ABSTRACT Chronic illness diagnoses frequently cause the shattering of personal assumptions about the self and the world, resulting in an experience of alienation and fragmentation of identity. Multiple studies on the effects of expressive writing have demonstrated physical, emotional, and psychological health benefits, yet little is known about how it might offer benefit in response to a chronic illness diagnosis. Combining the transformation-through-writing model with the dual process model for non-death loss and grief, I take an autoethnographic approach to explore how creative writing about Fibromyalgia (FM) allowed me to progress from a first story/loss orientation to a second story/restoration orientation as part of a dialogical process of self-reconstruction.
Adapting Literature Critique Engagement Activities for Online Learning Due to COVID-19: Use of Online Learning Groups to Promote Scientific Literacy Capabilities in Undergraduate Nutrition Education

Maintaining scientific literacy (SL) skill development in undergraduate science education while transitioning courses from the in-person to online learning environment due to the COVID-19 pandemic requires adaptation of some teaching practices. This study assessed the effectiveness of small online learning groups as the active engagement strategy (replacing in-person breakout groups) to promote SL skill development in fourth year undergraduate nutritional science students in the online learning environment (Fall 2020 semester). As a secondary outcome, SL skill development in the online learning environment (Fall 2020, n=178) was compared to that of the in-person course format (Fall 2019, n=144). Students were surveyed at the start and end of the semester to assess their i) scientific literature comprehension, ii) SL skill perceptions, and iii) practical SL skills. The use of online learning groups contributed to improvements in both literature comprehension and SL skill perceptions (P<0.05), however, practical SL skills remained unchanged (P>0.05). There was no difference in the magnitude of improvement in students’ SL skill perceptions or their practical SL skills between course formats (P>0.05). The ability to think critically about the scientific literature was increased in both course formats, with greater improvements observed in the online course format (P=0.02). Additionally, only students in the online course format had improved comprehension of scientific methods versus the in-person format (P=0.05). Collectively, these data demonstrate that the adaptations of an in-person course to an online learning environment using small online learning groups can similarly promote the development of SL in undergraduate nutrition education.
Low Temperature Characterization and Modeling of FDSOI Transistors for Cryo CMOS Applications

The wide range of cryogenic applications, such as spatial, high performance computing or high-energy physics, has boosted the investigation of CMOS technology performance down to cryogenic temperatures. In particular, the readout electronics of quantum computers operating at low temperature requires larger bandwidth than spatial applications, so that advanced CMOS node has to be considered. FDSOI technology appears as a valuable solution for co-integration between qubits and consistent engineering of control and read-out. However, there is still lack of reports on literature concerning advanced CMOS nodes behavior at deep cryogenic operation, from devices electrostatics to mismatch and self-heating, all requested for the development of robust design tools. For these reasons, this chapter presents a review of electrical characterization and modeling results recently obtained on ultra-thin film FDSOI MOSFETs down to 4.2 K.
Absorption and Translocation of Florpyrauxifen-Benzyl in Ten Aquatic Plant Species

Abstract Additional active ingredients are needed for use in aquatic systems to respond to new threats or treatment scenarios, enhance selectivity, reduce use rates, and mitigate the risk of herbicide resistance. Florpyrauxifen-benzyl is a new synthetic auxin developed for use as an aquatic herbicide. A study was conducted at North Carolina State University in which 10 µg L–1 of 25% radiolabeled florpyrauxifen-benzyl was applied to the isolated shoot tissue of 10 different aquatic plant species to elucidate absorption and translocation patterns in these species. Extremely high levels of shoot absorption were observed for all species, and uptake was rapid. Highest shoot absorptions were observed for crested floatingheart [Nymphoides cristata (Roxb.) Kuntze] (A192 = 20 µg g–1), dioecious hydrilla [Hydrilla verticillata (L. f.) Royle] (A192 = 25.3 µg g–1), variable watermilfoil (Myriophyllum heterophyllum Michx.) (A192 = 40.1 µg g–1), and Eurasian watermilfoil (Myriophyllum spicatum L.) (A192 = 25.3 µg g–1). Evidence of translocation was observed in all rooted species tested, with the greatest translocation observed in N. cristata (1.28 µg g–1 at 192 h after treatment). The results of this study add to the growing body of knowledge surrounding the behavior of this newly registered herbicide within aquatic plants.
Process Analysis of Main Organic Compounds Dissolved in Aqueous Phase by Hydrothermal Processing of açaí (Euterpe Oleraceae, Mart.) Seeds: Influence of Process Temperature, Biomass-to-Water Ratio, and Production Scales

This work aims to investigate systematically the influence of process temperature, bio-mass-to-water ratio, and production scales (laboratory and pilot) on the chemical composition of aqueous and gaseous phases and mass production of chemical by hydrothermal processing of Açaí (Euterpe Oleraceae, Mart.) seeds. The hydrothermal carbonization carried out at 175, 200, 225, and 250 °C, 2 °C/min, biomass-to-water ratio of 1:10, and at 250 °C, 2 °C/min, and biomass-to-water ratios of 1:10, 1:15, and 1:20, in technical scale, as well as at 200, 225, and 250 °C, 2 °C/min, bio-mass-to-water ratio of 1:10, in laboratory scale. The elemental composition (C, H, N, S) of solid phase determined to compute the HHV. The chemical composition of aqueous phase determined by GC and HPLC and the volumetric composition of gaseous phase by using an infrared gas an-alyzer. For the experiments in pilot scale with constant biomass-to-water ratio of 1:10, the yields of solid, liquid, and gaseous phases varied between 53.39 and 37.01% (wt.), 46.61 and 59.19% (wt.), and 0.00 and 3.80% (wt.), respectively. The yield of solids shows a smooth exponential de-cay with temperature, while that of liquid and gaseous phases a smooth growth. By varying the biomass-to-water ratios, the yields of solid, liquid, and gaseous reaction products varied be-tween 53.39 and 32.09% (wt.), 46.61 and 67.28% (wt.), and 0.00 and 0.634% (wt.), respectively. The yield of solids decreases exponentially with increasing water-to-biomass ratio and that of liquid phase increases in a sigmoid fashion. For constant biomass-to-water ratio, the concentrations of Furfural and HMF decrease drastically with increasing temperature, reaching a minimum at 250 °C, while that of phenols increases. In addition, the concentrations of CH3COOH and total car-boxylic acids increase, reaching a maximum at 250 °C. For constant process temperature, the concentrations of aromatics vary smoothly with the temperature. The concentrations of furfural, HMF, and cathecol decrease with temperature, while that of phenols increases. The concentra-tions of CH3COOH and total carboxylic acids decrease exponentially with temperature. Finally, for the experiments with varying water-to-biomass ratios, the productions of chemicals (furfu-ral, HMF, phenols, cathecol, and acetic acid) in the aqueous phase is highly dependent on the biomass-to-water ratio. For the experiments in laboratory scale with constant biomass-to-water ratio of 1:10, the yields of solid ranged between 55.9 and 51.1% (wt.), showing not only a linear decay with tem-perature, but also a lower degradation grade. The chemical composition of main organic compounds (furfu-ral, HMF, phenols, cathecol, and acetic acid) dissolved in the aqueous phase in laboratory scale shows the same behavior of those in obtained in pilot scale.
SPN: Stable Prototypical Network for Few-Shot Learning-Based Hyperspectral Image Classification

We tackle the problem of few-shot image classification in the context of remote sensing hyperspectral images (HSIs). Due to the difficulties in collecting a large number of labeled training samples, the few-shot classification techniques hold much prominence in remote sensing in general. One of the bottlenecks in designing few-shot learning (FSL) systems arises from the fact that the model is likely to overfit in the presence of few training samples and the complex spectral feature distributions of the land-cover classes. To this end, we introduce a stable prototypical network (SPN) for FSL by judiciously incorporating dropout and DropBlock-based regularizers jointly within the framework and averaging model parameters using the Monte Carlo approximation. Besides, a novel variance loss term to reduce the uncertainty of the network is considered together with the cross-entropy-based classification loss to train the model in an end-to-end manner. The experimental analysis on three benchmark HSI datasets confirms the SPN’s superior performance.
Subtropical Frontal Zone of the Southern Ocean

This paper combines a literature survey and data analysis. The literature on the Subtropical Front (STF) in the Southern Ocean is reviewed with a two-pronged emphasis on the double-front structure of the STF, hence the existence of a subtropical frontal zone (STFZ), and the circumpolar continuity of the STFZ. The data analysis is based on the World Ocean Circulation Experiment (WOCE) sections. The STFZ is detected along each section independently from other sections, while moving circum-polarly downstream (eastward). The literature survey and data analysis confirm the circumpolar continuity of the STFZ extending from the Brazil Current across the South Atlantic, South Indian, and South Pacific up to Chile, being bound by the North and South STF. The circumpolar continuity of the STFZ is partly interrupted by South Africa and Tasmania, where the North STF ceases, while the South STF continues eastward. The South Atlantic STFZ is the southern boundary of the well-defined Subtropical Mode Water (STMW) thermostad, which cools eastward from 15°C to 11°C between the Brazil Current and Greenwich Meridian. In the southeast Pacific, the STFZ is the southern boundary of the 17-to-19°C thermostad (South Pacific Eastern STMW). The STFZ’s vertical extent is at maximum in the South Atlantic (>1000 m), decreasing eastward to 300 m in the southeast Pacific off Chile. A special attention is given to the South Pacific and the STFZ’s role in the ecology of Chilean jack mackerel Trachurus murphyi that spawn at the STFZ and migrate along the STFZ from Chile up to New Zealand.
The Relationship between Risk Perception and Risk Definition and Risk-Addressing Behaviour during the Early COVID-19 Stages

The purpose of this article is to show the effect of Risk Perception RP and Risk Definition RD on the Risk-Addressing Behaviour RB. To carry out this study secondary data was used from a semi-structured survey administered between February and June 2020, a period during the early stages of the COVID-19 pandemic. The study identified six dimensions of risk perception and thus tested six structural models. Risk perception (ξ RP) is defined as an external latent variable in the study. It is also assumed that the risk perception variable may affect the risk definition variable (η RD). The application software SmartPLS was used to analyse data through exploratory factor analysis and partial least squares structural equation modelling on our research model. To achieve Convergent validity of the structural equation model of partial least squares, three criteria were met. In the study, Discriminant Validity was examined using the Fornell-Larcker criterion and Heterotrain-Monotrait Ratio (HTMT) coefficients. Results reveal that there is no direct relationship between the RB and “religion and beliefs”, the “fear level, the experience”, the “peer influences level” and the “openness”. However, we found a positive relationship between the agreement on “knowledge” and on RB and statistically significant relationships between the agreement on the RD and the agreement on the “religion and beliefs”, the “fear level”, the “experience”, the “knowledge”, the “peer influences level” and the RB. Moreover, there is an indirect relationship when controlling for the agreement on the RD between the agreement on the RB and the agreement on the “fear level”, the “experience”, the “knowledge” and the “peer influences level”. However, there is no relationship between the agreement on the “openness” and the agreement on the RB and a statistically significant but moderate relationship between the agreement on the RD and the agreement on the RB. Although, there seems to be abundant research on RP, so far we have found only a few studies on the influencing factors of RP, as effected by RB and RD, especially in distressed times such as during this current pandemic period of COVID-19. This study adds to body of literature and sheds new light on the interaction between RP, RB and RD in a time of distress. It provides important and original information that may be useful for government agencies, businesses, individuals, and the media when setting policies, governance structures, regulations, procedures and determining how to communicate.
Effect of Thermal Barrier Coating on the Performance and Emissions of Diesel Engine Operated with Conventional Diesel and Palm Oil Biodiesel

In this study, the performance and emission of a thermal barrier coating (TBC) engine which applied palm oil biodiesel and diesel as a fuel were evaluated. TBC was prepared by using a series of mixture consisting different blend ratio of yttria stabilized zirconia (Y2O3·ZrO2) and aluminum oxide-silicon oxide (Al2O3·SiO2) via plasma spray coating technique. The experimental results showed that mixture of TBC with 60% Y2O3·ZrO2 + 40% Al2O3·SiO2 had an excellent nitrogen oxide (NO), carbon monoxide (CO), carbon dioxide (CO2), and unburned hydrocarbon (HC) reductions compared to other blend-coated pistons. The finding also indicated that coating mixture 50% Y2O3·ZrO2 + 50% Al2O3·SiO2 had the highest brake thermal efficiency (BTE) and lowest of brake specific fuel consumption (BSFC) compared to all mixture coating. Reductions of HC and CO emissions were also recorded for 60% Y2O3·ZrO2 + 40% Al2O3·SiO2 and 50% Y2O3·ZrO2 + 50% Al2O3·SiO2 coatings. These encouraging findings had further proven the significance of TBC in enhancing the engine performance and emission reductions operated with different types of fuel.
The invisible hand of the shareholding state: the financialization of Italian real-estate investment funds for social housing

Abstract This article contributes to the emerging literature on the post-global-financial-crisis wave of financialization of housing 2.0 by furthering the understanding of how the national governments enable financialization and participate in financial intermediation to pursue statecraft objectives. The analysis stems from a mix-method research study combining longitudinal trans-scalar policy analysis with semi-structured interviews conducted in Lombardy since 2016. It focuses on the case of the Italian real-estate investment mutual funds dedicated to social housing as a key angle from which to observe the state-finance relation underlying the financialization of rental housing and the contextual rise of the shareholding state. While shedding light on the national government’s persistent role in favouring financial power concentrations, this research study framed financial infrastructures that connect local real estate to capital markets as contradictory condensations of power relations emerging from institutionally bounded conflicts and alliances. It thus exposed the hybrid assemblage of state and market forces behind financial market formation.
Water restriction in seeds of Cereus jamacaru DC.

: Mandacaru ( Cereus jamacaru DC.) is a cactus widely found in the Caatinga, with its seeds usually subjected to adverse conditions. Therefore, the objective of this study was to evaluate the effect of water restriction on germination and vigor of mandacaru seeds by using different salts and osmotic potentials. To that end, we used saline solutions of NaCl, KCl, CaCl 2 and MgCl 2 prepared at the osmotic potentials of 0.0; -0.2; -0.4; -0.6; -0.8; -1.0 and -1.2 MPa. Four replicates of 50 seeds per treatment were used, distributed in “gerbox” boxes between blotter paper and under temperature of 25 °C. Counts of the number of germinated seeds were performed daily for 21 days after root protrusion. The variables analyzed were the following: water content (%), germination (%), mean germination time and normal seedlings (%). A completely randomized following the factorial scheme 4 × 7 (salts × osmotic potentials) was employed. Results obtained suggest that mandacaru seeds show the ability to germinate in saline soils, a characteristic found in arid and semi-arid areas. Decreased osmotic potential promoted reductions in germination (%) and vigor of Cereus jamacaru DC seeds. The MgCl 2 salt was the one that most negatively affected the germination and initial seedling development.
Rate of convergence of the asymptotic normality of sample quantiles from a finite population

Abstract This study establishes the rate of convergence of the asymptotic normality of sample quantiles for simple random samples without replacement from a finite population. Using Hoeffding’s inequality for sampling without replacement and the Berry-Esseen inequality for hypergeometric random variables, the accuracy of the normal approximation of sample quantiles in survey sampling problems is presented.
Assessing the Relative Toxicity of Different Road Salts and Effect of Temperature on Salinity Toxicity: LCx Values vs. No Effect Concentration (NEC) Values

Freshwater biota are at risk globally from increasing salinity, including increases from deicing salts in cold regions. A variety of metrics of toxicity are used when estimating the toxicity of substances and comparing the toxicity between substances. However, the implications of using different metrics is not widely appreciated. Using the mayfly Colobruscoides giganteus (Ephemeroptera: Colobruscoidea) we compare the toxicity of seven different salts where toxicity was estimated using two metrics 1) the no effect concentrations (NEC) and 2) the lethal concentrations for 10, 25 and 50% of the test populations (LCx). The LCx values were estimated using two different models, the classic log-logistic model and the newer toxicokinetic-toxicodynamic (TKTD) model. We also compare the toxicity of two salts (NaCl and CaCl2) for C. giganteus at water temperatures of 4°C, 7°C and 15°C using the same metrics of toxicity. Our motivation for using a mayfly to assess salinity toxicity was because mayflies are generally salt sensitive, are ecologically important and are common in Australian (sub-)alpine streams. Considering 144-hour LCx values, we found toxicity differed between various salts, i.e., the lowest 144-hour LC50 (8 mS/cm) for a salt used by a ski resort was half that of the highest 144-hour LC50 from artificial marine salts and CaCl2 applied to roads (16mS/cm). 144-hour LC50 results at 7°C showed that analytical grade NaCl was significantly more toxic (7.3mS/cm) compared to analytical grade CaCl2 (12.5mS/cm). Yet for NEC values, there were comparably fewer differences in toxicity between salts and none between the same salts at different temperatures. We conclude that LCx values are better suited to compare difference in toxicity between substances or between the same substance at different test temperatures, while NEC values are better suited to estimating concentrations of substances that have no effect to the test species and endpoint measured under laboratory conditions.
Beyond User Control and Two-Way Communication: The Four-Factor Model of Interactivity of Wrist-Worn Smart Devices

ABSTRACT Wrist-worn smart devices such as smartwatches and smart health trackers have transformed the way we interact with technology. Whereas they share some commonalities with prior interactive media like smart phones, there are new interactivity elements of wrist-worn smart devices such as networking personal media and devices, adapting to personalized needs, and nudging healthy behavior. In order to investigate how these new factors can afford a unique interaction experience, the current study develops a user-driven conceptualization of interactivity in wearable technology. In Study 1, through an interview and a survey with wrist-worn smart device users, four factors that comprise interactivity of wrist-worn smart devices are identified: networking, adaptive, nudging, and multisensory. Exploratory and confirmatory factor analyses are conducted to examine the four-factor structure of interactivity and demonstrate strong reliability and convergent validity among the proposed factors. Study 2 revalidates the measurement structure of interactivity developed in Study 1 and further tests the theoretical value of the four-factor model by examining how the four factors predict usage intention mediated by hedonic and utilitarian benefits. Theoretical and practical implications are discussed.
Co-Shaping Smart Cities

This paper studies participation divides on civic crowdsourcing platforms in a smart city context, hybrid applications of distributed urban innovation management, and new modes of digital citizenship, often applied to co-shape future urban environments. However, the emergence of new participatory instruments also brings new digital inequalities, as their adoption is not distributed equally. Hence, from an explicitly interdisciplinary perspective, this article explores the role of civic engagement, digital inequalities, and opinion leadership in understanding differences in participatory behavior on such platforms. Using a regression model (N = 178), this study shows that participation differences on civic crowdsourcing platforms are explained by opinion leadership and political engagement, but not by community engagement, traditional digital inequalities. This reveals that such platforms are used most by those who were already participating and have high levels of expertise, which sheds a light on the potential empowerment of such platforms and its democratic implications.