Miracle-dz/UniFAR-FTUs huggingface dataset:
Histopathological Alterations in Gills, Liver and Kidney of African Catfish (Clarias gariepinus, Burchell 1822) Exposed to Melaleuca cajuputi Extract

This study evaluated the histopathological changes in the gill, liver and kidney of African catfish (Clarias gariepinus) intoxicated with a sub-lethal dose of Melaleuca cajuputi leaves extract (MCLE) for 96 h. The acute toxicity test has been determined previously with a value of 96-h LC50 = 127 mg/L, hence the selection of sub-lethal ranges from 60 mg/L to 160 mg/L of MCLE. Degenerative alterations were prominent in all tested organs, particularly after exposure to a high concentration of MCLE. Gill exhibited haemorrhage, epithelial lifting, lamellar disorganisation, and necrosis after exposure to a high MCLE concentration. Alterations in the liver include congestion, hydropic degeneration, and vacuolation, whereas lesions in the kidney were pyknosis, vacuolation, hydropic degeneration, and tubular necrosis. The obtained data showed that the organs experienced severe changes proportional to the increase in MCLE concentration. In addition, fish exposed to higher concentrations than the LC50 value experienced irreversible lesions. The present study suggests that the use of MCLE below the LC50 is recommended to avoid severe alterations to organs, particularly in African catfish. This study demonstrated that the use of MCLE above the LC50 promotes severe damage to the gills, liver and kidney of African catfish. However, further investigations are needed to define the causing-mechanisms underlying these effects.
The mediating role of psychological capital on organizational psychological ownership-organizational readiness for change relationship

The Covid 19 pandemic has accelerated the pace of change, especially in the hospital industry sector in Indonesia. The global Covid 19 pandemic in Indonesia has had an impact on the mental health of workers in the health sector which has caused work discomfort that must be faced so that Psychological Capital is needed, especially the ability of individuals to survive (resilience) in a work environment full of pressure during the global Covid 19 pandemic. The purpose of this research is to investigate the influence of organizational psychological ownership and the role of psychological capital on organizational readiness to change. This study was attended by 75 respondents from a satellite teaching hospital in the city of Surabaya, Indonesia by filling out an online questionnaire addressed to hospital employees. The results show that organizational psychological ownership influences organizational readiness for change directly and is mediated through psychological capital. This paper contributes to the theory of Conservation Resource Theory in the validated the mediated is needed to prove the relationship between organizational psychological ownership and organizational readiness for change. Psychological capital was proposed and found to have a full mediating role in the relationship between organizational psychological ownership and organizational readiness for change. Several practical implications of building psychological capital will be needed for organizations, especially in the hospital industry during and after the Covid 19 pandemic, which are change-oriented so that individual employees are ready for change initiatives.
Characterizing Image Sharing Behaviors in US Politically Engaged, Random, and Demographic Audience Segments

This work advances understandings of image-sharing behavior on Twitter, across race, gender, age, and political engagement. We infer account-level demographic measures via profile pictures of US Twitter accounts and characterize 20 types of images. Several of these types predict one’s demographics using account-level logistic regression models. Around half of the learned clusters (e.g., infographics, natural scenery, sports) are predictive of the user’s age, race, or gender, while several other clusters appear to be popular among politically engaged accounts (e.g., images of groups and images of single individuals, which often contain politicians). Our findings suggest it is possible to characterize certain audiences via different types of visual imagery, which has implications for information quality, online engagement, and communications.
Beyond the Headlines: Understanding Sentiments and Morals Impacting Female Employment in Spain

After decades of improvements in the employment conditions of females in Spain, this process came to a sudden stop with the Great Spanish Recession of 2008. In this contribution, we analyse a large longitudinal corpus of national and regional news outlets employing advanced Natural Language Processing techniques to capture the valence of mentions of gender inequality expressed in the Spanish press. The automatic analysis of the news articles does indeed capture the known hardships faced by females in the Spanish labour market. Our approach can be straightforwardly generalised to other topics of interest. Assessing the sentiment and moral values expressed in the articles, we notice that females are, in the majority of cases, concerned more than males when there is a deterioration in the overall labour market conditions, based on newspaper articles. This behaviour has been present in the entire period of study (2000--2022) and looked particularly pronounced during the economic crisis of 2008 and the recent COVID-19 pandemic. Most of the time, this phenomenon looks to be more pronounced at the regional level, perhaps caused by a significant focus on local labour markets rather than on aggregate statistics or because, in local contexts, females might suffer more from an isolation or discrimination condition. Our findings contribute to a deeper understanding of the gender inequalities in Spain using alternative data, informing policymakers and stakeholders.
Characterization and performance of a LWIR polarimetric imager

Polarimetric information has been shown to provide means for potentially enhancing the capacity of electro-optical sensors in areas such as target detection, recognition and identification. The potential benefit must be weighed against the added complexity of the sensor and the occurrence and robustness of polarimetric signatures. While progress in the design of novel systems for snapshot polarimetry may result in compact and lightweight polarimetric sensors, the aim of this work is to report on the design, characterization and performance of a polarimetric imager, primarily designed for polarimetric signature assessment of static scenes in the long wave thermal infrared. The system utilizes the division-of-time principle and is based on an uncooled microbolometer camera and a rotating polarizing filter. Methods for radiometric and polarimetric calibrations are discussed. A significant intrinsic polarization dependency of the microbolometer camera is demonstrated and it is shown that the ability to characterize, model and compensate for various instrument effects play a crucial role for polarimetric signature assessment.
Series solution of Painlev´e II in electrodiﬀusion: conjectured convergence

A perturbation series solution is constructed with the use of Airy functions, for a nonlinear two-point boundary-value problem arising in an established model of steady electrodiﬀusion in one dimension, with two ionic species carrying equal and opposite charges. The so-lution includes a formal determination of the associated electric ﬁeld, which is known to satisfy a form of the Painlev´e II diﬀerential equation. Comparisons with the numerical solution of the boundary-value problem show excellent agreement following termination of the series after a suﬃcient number of terms, for a much wider range of values of the parameters in the model than suggested by previously presented analysis, or admitted by previously presented approximation schemes. These surprising results suggest that for a wide variety of cases, a convergent series expansion for the Painlev´e transcendent describing the electric ﬁeld has been obtained. A suitable weighting of error measures for the approximations to the ﬁeld and its ﬁrst derivative provides a monotonically decreasing overall measure of the error in a subset of these cases. It is conjectured that the series does converge for this subset.
The End of the Rehydration Era The Problem of Sharing Harmful Twitter Research Data

Social media research is currently confronted with a data-sharing problem, as social media platforms prohibit full data distribution in their terms of service. Until recent changes to the platform, Twitter was an exception, allowing academics to legally share Tweet and user IDs with peers, which could then be re-collected using the Academic API endpoints. This work investigates how Twitter data is currently shared in two domains of harmful online communication — abusive language and social bot detection. We find that the currently frequently utilized intermediate strategy of sharing Twitter IDs suffers from substantial data loss, leading to the incompara-bility of computational results. Moreover, recent changes in the API result in additional expenses and an increased collection time that may have an impact on the feasibility of research projects. All of these aspects further fuel the reproducibility crisis that social media analytics currently faces. To improve the current situation, we propose several best practices for research projects utilizing ID-based datasets for their experiments and provide recommendations for researchers who want to share their Twitter data with peers.
Analysis of JT-60SA operational scenarios

Reference scenarios for the JT-60SA tokamak have been simulated with one-dimensional transport codes to assess the stationary state of the flat-top phase and provide a profile database for further physics studies (e.g. MHD stability, gyrokinetic analysis) and diagnostics design. The types of scenario considered vary from pulsed standard H-mode to advanced non-inductive steady-state plasmas. In this paper we present the results obtained with the ASTRA, CRONOS, JINTRAC and TOPICS codes equipped with the Bohm/gyro-Bohm, CDBM and GLF23 transport models. The scenarios analysed here are: a standard ELMy H-mode, a hybrid scenario and a non-inductive steady state plasma, with operational parameters from the JT-60SA research plan. Several simulations of the scenarios under consideration have been performed with the above mentioned codes and transport models. The results from the different codes are in broad agreement and the main plasma parameters generally agree well with the zero dimensional estimates reported previously. The sensitivity of the results to different transport models and, in some cases, to the ELM/pedestal model has been investigated.
The Real-World Insights of People Living with HIV Shared Through Electronic Devices (RISE) Study

As antiretroviral treatment (ART) has made viral suppression and survival less of a concern for individuals with the human immunodeficiency virus (HIV), the focus of research on treatment and care for people living with HIV (PLHIV) has shifted to normalizing living with HIV infection through improving their overall well-being and health-related quality of life (HRQoL). The RISE study aimed to implement an innovative method for gathering real-world data (RWD) on these topics through mobile application (app) surveys and subsequently, compare the outcomes to a normative population sample For this study, targeted recruiting methods through social media and other online sources were utilized. Participants were at least 21 years old with a self-reported diagnosis of HIV, living in the United States (US). Participants took mobile app surveys, detailing medical information on their personal mobile devices. From this data collection, it was concluded that White, non-Hispanic southern males who had private insurance, as well as other ethnicities and those who reported a greater general satisfaction, were significantly more likely to be adherent to their treatment and experienced less internalized stigma over HIV. Participants who were lower income or on Medicare or Medicaid were associated with a decrease HRQoL, as well as a higher internalized stigma over HIV.
The Effect of Visual Alcohol Cues on Risk Taking Behavior Based on Memory Primes and Individual Drinking Habits

Given the strong presence of alcohol cues in the media, this study aimed to investigate whether exposure to a visual alcohol cue versus a neutral cue would elicit memories about alcohol and increase the likelihood to engage in risk taking behavior, particularly for individuals who consume higher levels of alcohol or who report positive memories associated with alcohol. Through an online Qualtrics survey, 110 college student participants watched either two video advertisements for alcohol brands (alcohol cue), or two advertisements for soda brands (neutral cue), and then completed a memory cue task to assess if positive, neutral or negative memories involving alcohol became salient. Participants then completed the Domain Specific Risk Taking Scale, and a demographic survey assessing typical weekly alcohol consumption. The results from this study did not support any of the hypotheses about the proposed relationship between alcohol cues and risk taking, however results did find that heavy drinking behavior was associated with a higher risk taking score. It is possible that the lack of support for the hypotheses was due to the cue word task priming alcohol for a majority of participants, limited sample size, or the use of a more stable measurement of risk. Further research on the possibility of a relationship between alcohol cues and risk taking behavior would be beneficial.
Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

Assessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.
Supplementary Materials for “Dynamic Graph Learning with Content-guided Spatial-Frequency Relation Reasoning for Deepfake Detection”

Cross-testing Evaluation on FaceForensics++. As shown in Table 1, to further demonstrate the generalization ability of our proposed SFDG method among different manipulated types, we conduct additional experiments on FF++ (LQ) [10] benchmark dataset that contains counterfeit images from four manipulated techniques, i.e., Deepfakes (DF) [15], Face2Face (F2F) [14], FaceSwap (FS) [7], and NeuralTextures (NT) [13]. We train our model on one of them and test it on all four approaches. We refer to the experiment results in DCL [11]. From Table 1, our method consistently surpasses all competitors by a clear margin in most cases. Specifically, when training on DF and testing on F2F, FS and NT, our approach achieves 12.08%, 23.48% and 15.05% gain in terms of AUC respectively. These overwhelming results give explanations that our method sufficiently excavates adaptive frequency features and discover the relation of essential forged clues in spatial and frequency domain via dynamic graph learning, thus improving the cross-manipulation performance. Robustness Analysis on FF++/WildDeepfake Dataset. In view of the ubiquity of image processing on social media, we investigate the robustness of our proposed model by training on original WildDeepfake [18] dataset and testing on WildDeepfake samples that are subverted by common unseen perturbations suggested by [1,4–6]. As shown in Table 2, a serious of experiments are conducted to demonstrate the robustness of our proposed SFGD against noise and blur perturbations. In detail, we train our SFDG model on the clean data and then insert GaussianNoise, SaltPepperNoise, and GaussianBlur to the test samples. We evaluate the robustness of the forgery detection model utilizing the decay
Lines, Able to Differentiate In Transgenic Mice Carrying the Large T Gene: An Alternative Brain Cell Immortalization

Permanent untransformed cell lines have been established from the cerebral cortex of transgenic mice that carry the polyoma virus large T gene. The immortalized cells described here synthesize laminin and neural cell adhesion molecules and induce primary neurons to develop neuritic processes. As shown by immunofluorescence and immunoblotting assays, they begin to synthesize the glial fibrillary acidic protein (GFAP) after confluence. Double labelling experiments indicated that GFAP expression is reversibly correlated with the arrest of cell division. The present cells also display adrenergic, serotoninergic, and high levels of muscarinic receptors coupled to the phosphatidyl-inositol signalling pathway. Taken together, our data show that these cell lines constitute homogeneous cell material that has retained the main differentiative, functional, and growth properties of normal astrocytes. Therefore, such clonal untransformed cell lines should be useful for further molecular studies, addressing terminal differentiation of glial cells, glio-neuronal interactions, and astroglial expression of receptors for neurotransmitters. Furthermore, we suggest that this approach of cell immortalization by the use of transgenic mice carrying a non-trans-forming oncogene might be extended to a variety of cell types.
The continuous ad\`eles on $\overline{\mathbb Q}$

In 2009, Allcock and Vaaler defined a topology on the set $Y$ of places of $\overline{\mathbb Q}$. While they employed this topology to study the completion of the group $\overline{\mathbb Q}^\times/\overline{\mathbb Q}^\times_{\mathrm{tors}}$ with respect to the Weil height, we consider a different application. Specifically, we use properties of the topology on $Y$ to create an analog of the ad\`eles for $\overline{\mathbb Q}$ called the continuous ad\`eles. The finiteness condition, which is typically enforced in the definition of the ad\`eles of a global field, is replaced with a weaker compactness condition. When equipped with an appropriate topology, we prove that the continuous ad\`eles form a topological ring which contains the ad\`ele ring of every number field as a topological subring. Additionally, we show that the Weil height is well-defined on the continuous ad\`eles.
A SECOND-ORDER PARTITIONED METHOD FOR BIOCONVECTIVE FLOWS WITH CONCENTRATION DEPENDENT VISCOSITY

This work is focused on the mathematical and computational modeling of bioconvection, which describes the mixing of fluid and micro-organisms exhibiting negative geotaxis movement under the force of gravity. The collective population moves towards the surface of the fluid, generating a Rayleigh–Taylor instability, where initial fingers of organisms plummet to the bottom. The inherent drive to swim vertically generates large collective flow patterns that persist in time. We model the flow using the Navier-Stokes equations for an incompressible, viscous fluid, coupled with the transport equation describing the concentration of the micro-organisms. We use a nonlinear semigroup approach to prove the existence of solutions. We propose a partitioned, second-order, time adaptive numerical method based on the Cauchy’s one-legged ‘θ -like’ scheme. We prove that the method is energy-stable, and for small time steps, the iterative procedure in the partitioned algorithm is linearly convergent. The numerical results confirm the expected second-order of accuracy. We also present a computational study of a chaotic system describing bioconvection of motile flagellates.
The Role of Multiple Imputation in Noninferiority Trials for Binary Outcomes

ABSTRACT We consider the role of multiple imputation (MI) when analyzing noninferiority (NI) clinical trials with missing data. When the endpoint is measured longitudinally, direct-likelihood methods can be used. In this article, the focus is on the situation in which the endpoint is not measured longitudinally but other relevant data are measured at or after baseline prior to planned collection of the primary endpoint data. Simulation results are presented for various scenarios based on the missingness mechanism, the dropout rate, and the size of NI margin. When the endpoint is binary, the ratio of the amount of missing data to the noninferiority margin will affect the operating characteristics of any analysis strategy (whether imputation based or not), an issue that is unique to noninferiority trials. Biased estimates of treatment effect under missingness, not completely at random, may arise when using a misspecified imputation model lacking treatment effect, resulting in substantially inflated Type I error rates in noninferiority trials by making the two groups appear more similar, opposite the usual impact in superiority trials. As in superiority trials, MI will have most benefit when data are missing at random, and the important predictor variables are included in the imputation model.
The Impact of Proportional Transaction Costs on Systematically Generated Portfolios

The effect of proportional transaction costs on systematically generated portfolios is studied empirically. The performance of several portfolios (the index tracking portfolio, the equally-weighted portfolio, the entropy-weighted portfolio, and the diversity-weighted portfolio) in the presence of dividends and transaction costs is examined under different configurations involving the trading frequency, constituent list size, and renewing frequency. Moreover, a method to smooth transaction costs is proposed.