Miracle-dz/UniFAR-FTUs huggingface dataset:
The ectomycorrhizal fungal communities react differently to climatic, edaphic and spatial variables depending on their host species

Ectomycorrhizal (ECM) fungal community structures can vary across sites at a regional scale (>1,000 km), affected by abiotic and biotic environments, dispersal abilities of the fungi, or ecological drift, even among forests of the same host tree species. The spatial patterns of such variation may differ among associated host species and their growth environments, but our knowledge about this remains limited. In the present study, we aimed to investigate whether the ECM fungal community structures (i.e. species richness and species composition) at the regional scale and their driving factors vary across hosts.
Does Talking at the End of Life Matter?: Exploring the Associations between Final Conversations (Fcs) and Coping Strategies

ABSTRACT The purpose of this investigation was to quantitatively examine associations between retrospectively recalled final conversations (FCs) with the outcome of coping strategies. Two-hundred thirty-six individuals participated in an online survey. Correlations revealed significant, positive associations between the FCs factors with coping strategies. Moreover, multiple regressions revealed the following: messages of identity significantly predicted positive reappraisal and cognitive monitoring; difficult relationship talk significantly predicted self and other distancing; and, messages of spirituality significantly predicted the use of faith as a coping tool. Overall, results suggest that retrospectively recalled engagement in FCs are associated with coping strategies after the death of a relational partner. Theoretical and practical implications, limitations, and future directions are discussed.
Determination of the interaction between the receptor binding domain of 2019-nCoV spike protein, TMPRSS2, cathepsin B and cathepsin L, and glycosidic and aglycon forms of some flavonols

The novel coronavirus (COVID-19, SARS-CoV-2) is a rapidly spreading disease with a high mortality. In this research, the interactions between specific flavonols and the 2019-nCoV receptor binding domain (RBD), transmembrane protease, serine 2 (TMPRSS2), and cathepsins (CatB and CatL) were analyzed. According to the relative binding capacity index (RBCI) calculated based on the free energy of binding and calculated inhibition constants, it was determined that robinin (ROB) and gossypetin (GOS) were the most effective flavonols on all targets. While the binding free energy of ROB with the spike glycoprotein RBD, TMPRSS2, CatB, and CatL were –5.02, –7.57, –10.10, and –6.11 kcal/mol, the values for GOS were –4.67, –5.24, –8.31, and –6.76, respectively. Furthermore, both compounds maintained their stability for at least 170 ns on respective targets in molecular dynamics simulations. The molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations also corroborated these data. Considering Lipinski’s rule of five, ROB and GOS exhibited 3 (MW>500, N or O>10, NH or OH>5), and 1 (NH or OH>5) violations, respectively. Neither ROB nor GOS showed AMES toxicity or hepatotoxicity. The LD50 of these compounds in rats were 2.482 and 2.527 mol/kg, respectively. Therefore, we conclude that these compounds could be considered as alternative therapeutic agents in the treatment of COVID-19. However, the possible inhibitory effects of these compounds on cytochromes (CYPs) should be verified by in vitro or in vivo tests and their adverse effects on cellular energy metabolism should be minimized by performing molecular modifications if necessary.
TDCA-Net: Time-Domain Channel Attention Network for Depression Detection

Depression is a psychiatric disorder and has many adverse effects on our society. Some studies have shown that speech signals are closely related to emotion and stress, and many speech-based automatic depression detection methods have been proposed. However, previous work is based on spectrogram or hand-crafted features, which may lose some useful information related to depression patterns. And there is no evidence that the ﬁlter bank designed from perceptual evidence is optimal for depression detection. In order to learn the more discriminative feature representation related to depression, we propose an end-to-end time-domain channel attention network (TDCA-Net) for depression detection. The TDCA-Net directly models time-domain speech signals based on dilated convolution block, which can increase the receptive ﬁeld exponentially and aggregate multiscale contextual information associated with depression. Besides, we employ the efﬁcient channel attention (ECA) module to model dependencies of channels and improve the sensitivity of the model to information related to depression. Experimental results on the AVEC2013 and the AVEC2014 datasets illustrate the effectiveness of our method.
Age Estimation with Speech-Age Model for Heterogeneous Speech Datasets

This paper describes an age estimation method from speech signals for heterogeneous datasets. Although previous studies in the speech ﬁeld evaluate age prediction models with held-out testing data within the same dataset recorded in a consistent setting, such evaluation does not measure real performance. The difﬁculty of heterogeneous datasets is overﬁtting caused by the corpus-speciﬁc properties: transfer function of the recording environment and distributions of age and speaker. We propose a speech-age model and its integration with sequence neural networks (NNs). The speech-age model represents the ambiguity of age as a probability distribution, which also virtually extends the limited range of age distribution of each corpus. A Bayesian generative model successfully integrates the speech-age model and the NNs. We also applied mean normalization technique to cope with the transfer function problem. Experiments showed that our proposed method outperformed the base-line neural classiﬁer for completely open test sets in the age distribution and recording setting.
Icon Generation Based on Generative Adversarial Networks

Icon design is an important part of UI design, and a design task that designers often encounter. During the design process, it is important to highlight the function of icons themselves and avoid excessive similarity with similar icons, i.e., to have a certain degree of innovation and uniqueness. With the rapid development of deep learning technology, generative adversarial networks (GANs) can be used to assist designers in designing and updating icons. In this paper, we construct an icon dataset consisting of 8 icon categories, and introduce state-of-the-art research and training techniques including attention mechanism and spectral normalization based on the original StyleGAN. The results show that our model can effectively generate high-quality icons. In addition, based on the user study, we demonstrate that our generated icons can be useful to designers as design aids. Finally, we discuss the potential impacts and consider the prospects for future related research.
The STING antagonist H‐151 ameliorates psoriasis via suppression of STING/NF‐κB‐mediated inflammation

Psoriasis is a chronic inflammatory skin disease associated with both innate and adaptive immune responses. The stimulator of interferon genes (STING) protein engages in sensing of cytosolic DNA to initiate dsDNA‐driven immune responses. In vitro and in vivo anti‐psoriasis effects of STING antagonist H‐151 were explored.
Enhancing Arsenic Solidification/Stabilisation Efficiency of Metallurgical Slag-Based Green Mining Fill and Its Structure Analysis

To dispose of arsenic-containing tailings with low carbon and high efficiency, sodium sulphate (Na2SO4), sodium hydroxide (NaOH), calcium nitrate Ca(NO3)2 and calcium hydroxide Ca(OH)2 were independently added to metallurgical slag-based binder (MSB) solidification/stabilisation (S/S)-treated tailings (MSTs) to enhance the MST arsenic S/S performance. Results showed that only Ca(OH)2 could increase the unconfined compressive strength of MST from 16.3 to 20.49 MPa and decrease the leachate As concentration from 31 μg/L to below 10 μg/L. Na3AsO4·12H2O and NaAsO2 were used to prepare pure MSB paste for mechanism analysis. The results of microstructure analyses showed the high specific surface area and amorphous properties of calcium–sodium aluminosilicate hydrate facilitated the adsorption or solid-solution formation of As(V) and As(III). As(V) formed an inner-sphere complex in ettringite, whereas As(III) formed an outer-sphere complex, and the relatively larger size and charge of As(V) compared with SO42− restrict substitution inside channels without affecting the ettringite structure under high loading of As(V). The added Ca(OH)2 promoted the hydration reaction of MSBs and facilitated the formation of a Ca–As(V) precipitate with low solubility, from Ca4(OH)2(AsO4)2·4H2O (Ksp = 10−27.49) to Ca5(AsO4)3(OH) (Ksp = 10−40.12). This work is beneficial for the application of cement-free MSB in the S/S process.
Predicting neuropsychiatric symptoms of Parkinson’s disease with measures of striatal dopaminergic deficiency

The role of nigrostriatal dopaminergic neurons degeneration is well established in the pathophysiology of Parkinson’s disease. However, it is unclear if and how the degeneration of the dopamine pathways affects the manifestation of the neuropsychiatric symptoms (NPS) of Parkinson’s disease (PD). Dopamine transporter (DAT) imaging, a technique to measure the reduction in the dopamine transporters is increasingly used as a tool in the diagnosis of PD. In this study, we examine if the baseline dopamine transporter density in the striatum measured by striatal binding ratio (SBR) is associated with the longitudinal onset and/or progression of NPS in PD as measured by the part 1 of Movement Disorder Society - Unified Parkinson’s Disease Rating Scale, over four years. Data of patients with PD and an abnormal screening present on 123I-ioflupane single-proton emission computed tomography were obtained from Parkinson’s Progression Markers Initiative (PPMI) database. Latent Growth Modeling (LGM), a statistical technique that can model the change over time while considering the variability in rate of change at the individual level was used to examine the progression of NPS over time. The results indicate the SBR did not correlate with the baseline NPS but did correlate with the rate of change of NPS (p<0.001) over the next four years, even after eliminating age related variance which can be a significant confounding factor. In conclusion, this study showed gradual worsening in NPS in patients with Parkinson’s disease which inversely correlates with the density of the dopamine transporters as measured by SBR at baseline.
Challenge and hope for parents who have cancer

https://doi.org/10.30574/ijsra.2021. 3.1. 0125 Abstract Parents who have cancer face particular problems in their relationships with children. This study aims to clarify 1) the current status of challenge/hope in parental cancer, 2) the factors related to challenge/hope, and 3) the relationship between challenge/hope and QOL/stress-coping ability. Cross-sectional national survey was conducted at designated cancer hospitals in Japan. Participants were undergoing cancer treatment and have children under 18 years old. The questionnaire included demographic data, QOL, ability to cope with stress, and challenge/hope. From 11 hospitals, 54 patients (response rate: 79.4%) participated. Majority of participants were female (72.2%) with the mean age of 39.3 ± 5.3 (SD). The total score was QOL (FACT-G: 50.4 ± 16.2), stress-coping ability (SOC: 46.7 ± 10.4). The main challenges were an inability to fulfill the parental role and children’s mental suffering due to loneliness. The main aspects of hope were the value of the children’s present self, being a parent, and strengthening family bonds. Gender and disease duration were significantly related with challenge/hope. Challenge was significantly related with QOL/stress-coping ability. Parents who have cancer derive hope from their relationship with their children, although they feel a gap between their ideal role/value as a parent and their current score of challenge/hope with the total score of QOL/stress-coping. The answering style was “Strongly agree,” “Agree,” “Neither,” “Disagree,” and “Strongly disagree. ” Each item was rated from 1 to 5 points on a 5-point Likert-type scale, with the total for challenge scored between 13 to 65 points, and for hope between 12 to 60 points. The higher the score indicates higher the challenge/hope.
Clinic, community, and in-between: the influence of space on real-time translation of medical expertise by frontline healthcare professionals in marginal tribal communities

In this article, we explore real-time translation work undertaken by frontline healthcare professionals as they interact with marginal tribal communities in Western India. Our 1-year ethnographic study of a healthcare organization delivering obstetric and gynaecological care to tribal communities helps us understand how obstetric counsellors translate allopathic medical expertise across epistemological boundaries to the tribal community they serve, in localized comprehensible forms. We identify four distinct mechanisms of translation work—Interpreting, Annotating, Norming, and Justifying—which differentially deploy and integrate elements of tribal vocabulary, symbols, knowledge, and imaginations of health and body with specific aspects of clinical diagnosis and prescription, making the latter meaningful and actionable in the process. Furthermore, we use configurational approach—Qualitative Comparative Analysis—to investigate how the type of space where the interaction between the counsellors and tribal women patients happens influences the translation work undertaken. We find that counsellors engage in spatially differentiated translation work. They predominantly use justifying and norming in clinical space (hospital); interpreting and annotating in community space (village or school); and interpreting and norming in the overlapping in-between space (outdoor patient department). Our study contributes to translation literature by showing how real-time translation is undertaken in practice, especially in a setting representing high-stakes institutional translation, and how translation work is influenced by the type of space in which interactions happen.
Acute Brain Activation Patterns of High- Versus Low-Frequency Stimulation of the Anterior Nucleus of the Thalamus During Deep Brain Stimulation for Epilepsy.

BACKGROUND Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is an increasingly utilized treatment of drug-resistant epilepsy. To date, the effect of high-frequency stimulation (HFS) vs low-frequency stimulation (LFS) in ANT DBS is poorly understood. OBJECTIVE To assess differences in the acute effect of LFS vs HFS in ANT DBS utilizing blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). METHODS In this prospective study of 5 patients with ANT DBS for epilepsy, BOLD activation and deactivation were modeled for 145-Hz and 30-Hz ANT stimulation using an fMRI block design. Data were analyzed with a general linear model and combined via 2-stage mixed-effects analysis. Z-score difference maps were nonparametrically thresholded using cluster threshold of z > 3.1 and a (corrected) cluster significance threshold of P = . 05. RESULTS HFS produced significantly greater activation within multiple regions, in particular the limbic and default mode network (DMN). LFS produced minimal activation and failed to produce significant activation within these same networks. HFS produced widespread cortical and subcortical deactivation sparing most of the limbic and DMN regions. Meanwhile, LFS produced deactivation in most DMN and limbic structures. CONCLUSION Our results show that HFS and LFS produce substantial variability in both local and downstream network effects. In particular, largely opposing effects were identified within the limbic network and DMN. These findings may serve as a mechanistic basis for understanding the potential of HFS vs LFS in various epilepsy syndromes.
Lie Point Symmetries, Traveling Wave Solutions and Conservation Laws of a Non-linear Viscoelastic Wave Equation

This paper studies a non-linear viscoelastic wave equation, with non-linear damping and source terms, from the point of view of the Lie groups theory. Firstly, we apply Lie’s symmetries method to the partial differential equation to classify the Lie point symmetries. Afterwards, we reduce the partial differential equation to some ordinary differential equations, by using the symmetries. Therefore, new analytical solutions are found from the ordinary differential equations. Finally, we derive low-order conservation laws, depending on the form of the damping and source terms, and discuss their physical meaning.
Dynamical power flow and trapping-force properties of two-dimensional Airy-beam superpositions

Abruptly autofocusing beams have attracted more and more attention because of their potential applications in optical manipulation. Here, we not only experimentally and theoretically investigate dynamical propagation properties of two-dimensional (2D) Airy--beam superpositions in free space and disordered media, but also study their stability, dynamical power flow, and trapping force properties from a different point. 2D Airy-beam superpositions have superior stability and can easily control their autofocusing propagations and trapping forces through a changing number of superimposing beams, truncated factor, scale factor, initial position, and the angle between two wings of 2D Airy beams. Based on the analysis of the evolution of power flow and trapping force, it is demonstrated that 2D Airy-beam superpositions repeat many autofocusing propagations, leading to a series of focuses and stable trapping positions to appear in propagation. Compared to traditional autofocusing beams, i.e., circular Airy beams and one-dimensional Airy-beam superpositions, 2D Airy-beam superpositions can show a better optical trapping performance in theory. Moreover, we used 2D Airy-beam superpositions as an optical tweezer to trap particles in the experiment and quantitatively analyzed trapping force properties such as trap stiffness via the power spectra method. The experimental results further demonstrate that 2D Airy-beam superposition can show better optical trapping ability than the circular Airy beam. Our work provides a systematic understanding of the propagation and trapping properties of 2D Airy-beam superpositions in theory and experiment. It is helpful for the further applications of autofocusing beams on the optical tweezer, especially in biomedical research.
Class-Based Neural Network Language Model for Second-Pass Rescoring in ASR

Language model rescoring, especially neural network language model (NNLM) rescoring, is widely used to achieve improved performance in a second-pass automatic speech recognition (ASR) system. The rescoring NNLM is usually trained separately from the ASR system. Typically, the two’s training corpora are different, leading to the vocabulary mismatch problem, consequently degrading ASR performance. Previous research focuses more on the language domain mismatch problem, while the vocabulary mismatch problem, which may also cause signiﬁcant performance degradation, has not been well studied. This paper proposes a novel class-based NNLM framework to address the vocabulary mismatch problem for language model rescoring. Here, OOV words (unknown words to the rescoring NNLM are called OOV words for short) are assigned to well-trained classes of NNLM and inherit the class probability. Experiments show that class-based NNLM rescoring can signiﬁcantly reduce performance degradation due to vocabulary mismatch.
Brand Positioning Fuel Stations on High-Tier Fuel Category

Companies need to build and maintain a competitive advantage. In the retail industry, the competition landscape will change when global brands enter the market, i.e. gas stations in Indonesia. Hence, it is essential to identify brand positioning in consumers' minds compared to competitor brands. This study examines the positioning of significant gas stations based on some attributes that refer to previous studies and in-depth interviews. The objects are high-tier fuel managed by three major brands, namely Pertamina, Shell, and British Petroleum (BP). Using purposive sampling and online surveys, data were collected from 256 respondents of Pertamina, Shell, and BP, further analyzed by MultiDimensional Scaling in developing a perceptual map. The findings indicate that Pertamina is perceived as more related to the station's tangible aspects, while Shell and BP were perceived as related to brand image and services. Even though the products are similar, this study clarifies differences in how consumers perceived these brands.
Pollination Biology of an Endemic Hawaiian Tree, Erythrina sandwicensis (Fabaceae: Papilionoideae), in a Novel Ecosystem1

Abstract: Tropical dry forest ecosystems are among the most endangered ecosystems globally. In Hawai‘i, dry forest species are under threat due to habitat destruction, invasive species, and a loss of mutualisms including pollinators. Understanding the pollination biology of species at risk can inform conservation strategies. This study aimed to identify the breeding system and types of floral visitors to Erythrina sandwicensis (Fabaceae) or wiliwili, an iconic Hawaiian tree in decline and with little regeneration. We conducted hand-pollination trials and observed visitors in two sites: a botanical garden and a forest site. We compared fruit set, seed set, seed germination, seedling growth rate, and seedling size across four pollination treatments: open control, autogamy, geitonogamy, and xenogamy. We found that wiliwili is visited by a novel suite of non-native visitors. All treatments produced seeds, but the xenogamous (cross) treatment produced significantly more fruit and seeds than the control or other treatments. Seedlings produced from cross-pollinated treatments were also taller and had wider basal diameters after twenty-eight days of growth. These results indicate that wiliwili employs a mixed-mating system, and that trees are pollen limited. Enhancing current populations of wiliwili to promote cross-pollination could help increase population regeneration.
Media-centric and Politics-centric Views of Media and Democracy: A Longitudinal Analysis of Political Communication and the International Journal of Press/Politics

ABSTRACT Political communication is a dynamic, interdisciplinary field that has grown in stature and reach in recent decades, becoming more international in scope and orientation while gaining respect in political science as a legitimate area of inquiry. In the evolving and participatory media-politics landscape, it becomes important to ask how the cross-disciplinary project of political communication research is keeping pace with changing conditions that provide a greater structural role for the press in politics and new technology in the enactment of citizenship. To track these trends in research, this paper reports the results of a longitudinal content analysis of research articles published in the journals Political Communication and the International Journal of Press/Politics for the period 1996-2016. For each year, we selected one issue at random and examined all research articles in that issue, excluding reviews, invited theme essays, and commentaries. Altogether, 229 articles were included in the analysis. Results indicate a noticeable increase in the internationalization of political communication research over the 20-year analysis period, a slight decrease in research expressing a negative evaluative tone toward the media over time, and consistent growth in the percentage of articles with a media-centric focus, defined as positioning the press as a central consideration in the study and regarding news media as central to democratic life. In light of these findings, the unique interpretive lenses that researchers adopt depending on discipline are explored in relation to ongoing developments in political communication research.