Miracle-dz/UniFAR-FTUs huggingface dataset:
Viral diversity and zoonotic risk in endangered species

A growing body of evidence links zoonotic disease risk, including pandemic threats, to biodiversity loss and other upstream anthropogenic impacts on ecosystem health. However, there is little current research assessing viral diversity in endangered species. Here, combining IUCN Red List data on 5,876 mammal species with data on host-virus associations for a subset of 1,273 extant species, we examine the relationship between endangered species status and viral diversity, including the subset of viruses that can infect humans (zoonotic viruses). We show that fewer total viruses and fewer zoonotic viruses are known to infect more threatened species. After correcting for sampling effort, zoonotic virus diversity is mostly independent of threat status, but endangered species—despite a higher apparent research effort—have a significantly lower diversity of viruses, a property that is not explained by collinearity with host phylogeography or life history variation. Although this pattern could be generated by real biological processes, we suspect instead that endangered species may be subject to additional sampling biases not captured by the total volume of scientific literature (e.g., lower rates of invasive sampling may decrease viral discovery). Overall, our findings suggest that endangered species are no more or less likely to host viruses that pose a threat to humans, but future zoonotic threats might remain undiscovered in these species. This may be concerning, given that drivers of endangered species’ vulnerability such as habitat disturbance, wildlife trade, or climate vulnerability may increase virus prevalence in reservoirs and risk of spillover into humans.
On the similarities of representations in artificial and brain neural networks for speech recognition

How the human brain supports speech comprehension is an important question in neuroscience. Studying the neurocomputational mechanisms underlying human language is not only critical to understand and develop treatments for many human conditions that impair language and communication but also to inform artificial systems that aim to automatically process and identify natural speech. In recent years, intelligent machines powered by deep learning have achieved near human level of performance in speech recognition. The fields of artificial intelligence and cognitive neuroscience have finally reached a similar phenotypical level despite of their huge differences in implementation, and so deep learning models can—in principle—serve as candidates for mechanistic models of the human auditory system. Utilizing high-performance automatic speech recognition systems, and advanced noninvasive human neuroimaging technology such as magnetoencephalography and multivariate pattern-information analysis, the current study aimed to relate machine-learned representations of speech to recorded human brain representations of the same speech. In one direction, we found a quasi-hierarchical functional organisation in human auditory cortex qualitatively matched with the hidden layers of deep neural networks trained in an automatic speech recognizer. In the reverse direction, we modified the hidden layer organization of the artificial neural network based on neural activation patterns in human brains. The result was a substantial improvement in word recognition accuracy and learned speech representations. We have demonstrated that artificial and brain neural networks can be mutually informative in the domain of speech recognition. Author summary The human capacity to recognize individual words from the sound of speech is a cornerstone of our ability to communicate with one another, yet the processes and representations underlying it remain largely unknown. Software systems for automatic speech-to-text provide a plausible model for how speech recognition can be performed. In this study, we used an automatic speech recogniser model to probe recordings from the brains of participants who listened to speech. We found that the parts of the dynamic, evolving representations inside the machine system were a good fit for representations found in the brain recordings, both showing similar hierarchical organisations. Then, we observed where the machine’s representations diverged from the brain’s, and made experimental adjustments to the automatic recognizer’s design so that its representations might better fit the brain’s. In so doing, we substantially improved the recognizer’s ability to accurately identify words.
LANDSLIDES IN THE STATE OF PERNAMBUCO

Even though the occurrences of social and economic losses and fatal victims caused by landslides in Pernambuco are recurrent, one must consider that there is a gap in the systematization of information pertaining to such processes in a georeferenced spatial database at a state level, especially with regard to the location and types of triggering conditioning factors. This work is intended to evaluate the occurrence of landslides in the state of Pernambuco, the conditioning factors thereof, and the most affected areas. For such, a Geographic Database (Banco de Dados Geográfico - BDG) and an inventory map were created, based on the capture of landslides in the state between 1988 and 2019, both through secondary and primary sources. Lastly, all of the occurrences were catalogued in information plans, vectorized in a GIS (Geographic Information System) environment and correlated with thematic variables of the main conditioning factors. 3,138 landslides in Pernambuco were inventoried, which enabled the verification of behavior patterns regarding the occurrence of said processes in the state. The formation of this georeferenced spatial database may contribute to better understand the incidence of these processes, and thus subsidize the establishment of investigative methodologies and strategies related to the subject. Keywords: Inventory; Database; Mass Movements; Northeastern Brazil.
TRACE ELEMENTS IN FEATHERS AND EGGSHELLS OF TWO TROPICAL SEABIRDS FROM MALAYSIA

A. , A.S. , SURATMAN, S. , BIDAI, J.A. & 2021. Trace elements in feathers and eggshells of two tropical seabirds from Malaysia. Marine Ornithology 49: 335–341. Seabird feathers and eggshells are used as bio-monitors for trace metal contamination. Eleven trace element concentrations in wing primaries ( n = 21) and eggshells ( n = 8) are reported herein for two resident seabirds, Bridled Tern Onychoprion anaethetus and Black-naped Tern Sterna sumatrana , at Pulau Ling and Pulau Tokung Burung, Malaysia. Metal concentration followed the pattern Zn > Cr > Mn > Sr > Cu > Se > Ba > Pb > Cd > Ga > Li. Significant positive correlations existed among all trace metals, except for Cr in Black-naped Tern and Li and Cd in Bridled Tern feathers. We also analyzed metal concentrations in eggshells, and for Bridled Tern the concentration pattern was Zn > Mn > Se > Sr > Ba > Pb > Co > Cu > Cd, whereas for Black-naped Tern it was Cr > Zn > Mn > Ba > Sr > Se > Cu> Co > Pb. A pairwise positive correlation was significant among most trace metals in feather samples, indicating synergistic effects of two or more elements. More studies are needed to build a baseline database of trace metal concentrations in seabirds of Southeast Asia, as little research on this subject has been conducted in this region.
Perceptions of the COVID-19 Pandemic and Psychological Distress amongst Russian Citizens during Spring 2020

BACKGROUND: The COVID-19 pandemic has a ﬀ ected the emotional state of a wide range of people around the world. Studying the social and psychological factors of psychological distress is required in the context of the pandemic in di ﬀ erent countries. This study aims to explore the relationship between the emotional state of Russian citizens during the COVID-19 pandemic and their perceptions of it, and its dependence on various socio-demographic characteristics. METHODS: A socio-demographic questionnaire, the Russian version of the Perceived Stress Scale, the State Scale from Spilberger State-Trait Anxiety Inventory, and the modi ﬁ ed version of the Brief Illness Perception Questionnaire were used for the purposes of this study. The data was analyzed via descriptive statistics, ANOVA, Exploratory Factor Analysis, Correlation Analysis, Scale Consistency Analysis, and Structural Equation Modeling (Path Analysis Method). RESULTS: The study sample consisted of 1192 Russian-speaking respondents. The ﬁ ndings suggest that psychological distress a ﬀ ects all components of the ideas about the pandemic. The "Psychological distress" variable positively in ﬂ uences the "Threat to life" and "Fear of an unknown disease" components of the ideas about the pandemic, whereas the "Control" component (ideas about the ability to control events) is ambivalent. On the one hand, the severity of psychological distress reduces the idea of being able to control events; on the other, the psychological distress experienced increases the feeling of threat and uncertainty, and stimulates the control of these feelings to be realized. In addition, signi ﬁ cant di ﬀ erences were revealed in the nature of perceptions of the pandemic and psychological distress, as dependent on gender, age, type of employment, daily routine during self-isolation, income, as well as a fear of possible stigmatization with regard to COVID-19. It has been shown that underestimating the disease leads to improvement of psychological well-being. However, respondents who underestimated the danger of coronavirus paid less attention to the measures taken against the virus. If the respondent had relatives infected with COVID-19, they were found to perceive the COVID-19 pandemic as more threatening and less understandable. CONCLUSIONS: Through assessing a level of threat and fear of an unknown disease, we de ﬁ ned that psychological distress has a direct and mediated in ﬂ uence on the feeling of control over the pandemic. However, the results on the role of psychological distress and perceptions of the COVID-19 pandemic, taken together, appear rather contradictory. Further research exploring additional predictors of psychological well-being and distress during the COVID-19 pandemic is required to provide solid conclusions.
Can Evidence-Based Information Shift Preferences

We investigate the role of evidence-based information in shaping individuals’ preferences for trade policies through a series of survey experiments that contain randomized information treatments. Each information treatment provides a concise statement of economics research findings on how openness to trade has affected labor market outcomes and goods prices. Across annual surveys from 2018-2021, each administered on a representative sample of the US general population, we find that information highlighting the link between trade and manufacturing job losses significantly raises respondents’ propensity to select limits on imports as a preferred policy; this tendency is only partially offset if respondents receive additional information describing the accompanying expansion in non-manufacturing jobs. Strikingly (and rather paradoxically), information on the benefits of trade for goods prices also induces protectionist policy choices. Our exploration of underlying mechanisms shows that the treatment effects are not driven by the economic self-interest of respondents or a lack of persuasiveness. Instead, the information appears to reinforce respondents’ priors stemming from their political identity and concerns regarding China, while also eliciting loss-averse behavior. The findings point to the challenges in using short evidence-based messages to communicate the benefits of trade to the general public. JEL Codes: F1, F6, D8
On Specific Heat

INTRODUCTION: Heat capacity of a body is the quantity of heat required to raise the temperature of the body by 1C. The specific heat of a substance is the heat capacity per unit mass. Thus, heat capacity = mass x specific heat. The specific heat is essentially a measure of how thermally insensitive a substance is to the addition of energy. The water equivalent of a body is the mass of water, which would require the same amount of heat as the body in order to raise the temperature through one degree Celsius.
SELF-EFFICACY AND SELF-REGULATION WITH ACADEMIC PROCRASTINATION IN MUSLIM ADOLESCENTS DURING THE ONLINE LEARNING PERIOD Muslim Adolescents, Online Learning

This study aims to determine the relationship between self-efficacy and self-regulation with academic procrastination in Muslim adolescents during online learning. The research method used in this research is correlational quantitative. The subjects of this study were Muslim adolescents in one of the public high schools in Palembang. The sample of this study was 298 people taken by quota sampling technique. The instruments used are the self-efficacy, self-regulation, and academic procrastination scale. The results of data analysis with multiple regression analysis (assisted by SPSS version 26) showed that there was a significant relationship between self-efficacy and self-regulation with academic procrastination in online learning (Y = 237.034 + - 0.427X1 + - 0.241X2); (p<0.05) so that the research hypothesis is accepted with the effective contribution of X1 and X2 simultaneously on academic procrastination by 27%, while other variables outside this study influence the remaining 73%. Self-efficacy and self-regulation were negatively and significantly associated with academic procrastination in online learning (rx1 = -0.420; rx2= -0.400; p<0.05). It means that when the level of self-efficacy and self-regulation is high, the level of academic procrastination tends to be below. Conversely, when the level of self-efficacy and self-regulation is low, the level of academic procrastination tends to be high.
Analysis of biochars produced from the gasification of Pinus patula pellets and chips as soil amendments

In this work, biochar (BC), a co-product of the fixed bed gasification process of Pinus patula wood pellets (PL) and chips (CH), was characterized as soil amendment. The physicochemical properties and the mineral content of the pellet’s biochar (PL-BC) and the chips biochar (CH-BC) were analyzed following the NTC5167 Colombian technical standard. The BET surface area values of the BCs were 367,33 m 2 /g and 233,56 m 2 /g for the PL-BC and the CH-BC, respectively, and the pore volume was 0,20 cm 3 /g for the PL-BC and 0,13 cm 3 /g for the CH-BC. These characteristics favor the increase of the BCs water-holding capacity (WHC). Properties such as the pH (8,8-9,0), the WHC (219 %-186,4 %), the total organic carbon (33,8 %-23,9 %), the metalloid presence (Ca, Mg, K, Mn, Al, Si, and Fe), and the ash (1,92wt % - 2,74 wt %) and moisture contents (11,13wt %-11,63 wt %) for both BCs were found to be within the limits set by the standard. Furthermore, the presence of micro and macronutrients, such as Fe and phosphorus (P), and the alkaline pH, make possible the use of these BCs as amendments for acid soils.
Robustness Checks in Structural Analysis

Robustness checks, such as adding controls or sample splits, are a standard feature of reduced-form empirical research. Because of computational costs of reestimating alternative models, they are much less common in structural research using simulation-based methods. We propose a simple methodology to bypass this computational cost. Our approach relies on an approximation of the relationship between moments and parameters. It provides a computationally cheap way to run the potentially large number of structural estimations required for such robustness checks. We demonstrate the validity and usefulness of this methodology in the context of two standard applications in economics and ﬁnance: (1) dynamic corporate ﬁnance (2) life-cycle savings/consumption. This ﬁgure shows how estimated parameters vary as a function of m 16 , the standard deviation of 1-year log-growth rate of sales. In the data, m 16 = . 227 , which corresponds to the solid black vertical line. We consider alternative values for m 16 ranging from 5% to 35%. For each alternative value, we re-estimate the model using the benchmark approximation, and assuming all other moments remain at their empirical value. The ﬁgure plots the resulting estimated parameters.
Incidence and Risk Factors of Respiratory Distress Syndrome in Special Neonatal Care Unit

: The main objective of the study is to determine the incidence rate and common risk factors that cause RDS . by this we can advise mothers on early precaution and safety measures which helps to reduce the mortality rate. Our study involves 414 neonate subjects out of which 202 are under inclusion criteria and 212 are under exclusion criteria. Among which neonates are assessed using hospital criteria of RDS along with risk factors considerations, in which chest indrawing, grunting are common physical signs and c-section, prematurity, GD are more prone risk factors to neonates. All neonates’ mothers are examined by considering baby demographic details, antenatal details, details of labor, perinatal history, clinical examinations and risk factors was ascertained. Finally, we conclude that the incidence rate of RDS is 48.9% and prematurity, c-section and gestational diabetes are more prone risk factors for RDS.
Domain Reconstruction for UWB Car Key Localization Using Generative Adversarial Networks

We consider the car key localization task using ultra-wideband (UWB) signal measurements. Given labeled data for a certain car, we train a deep classifier to make the prediction about the new points. However, due to the differences in car models and possible environmental effects that might alter the signal propagation, data collection requires considerable effort for each car. In particular, we consider a situation where the data for the new car is collected only in one environment, so we have to utilize the measurements in other environments from a different car. We propose a framework based on generative adversarial networks (GANs) to generate missing parts of the data and train the classifier on it, mitigating the necessity to collect the real data. We show that the model trained on the synthetic data performs better than the baseline trained on the collected measurements only. Furthermore, our model closes the gap to the level of performance achieved when we would have the information about the new car in multiple environments by 35%.
Determining the Risk Level of Heavy Rain Damage by Region in South Korea

: For risk assessment, two methods, quantitative risk assessment and qualitative risk assessment, are used. In this study, we identiﬁed the regional risk level for a disaster-prevention plan for an overall area at the national level using qualitative risk assessment. To overcome the limitations of previous studies, a heavy rain damage risk index (HDRI) was proposed by clarifying the framework and using the indicator selection principle. Using historical damage data, we also carried out hierarchical cluster analysis to identify the major damage types that were not considered in previous risk-assessment studies. The result of the risk-level analysis revealed that risk levels are relatively high in some cities in South Korea where heavy rain damage occurs frequently or is severe. Five causes of damage were derived from this study—A: landslides, B: river inundation, C: poor drainage in arable areas, D: rapid water velocity, and E: inundation in urban lowlands. Finally, a prevention project was proposed considering regional risk level and damage type in this study. Our results can be used when macroscopically planning mid- to long-term disaster prevention projects.
Means of Musical Dialogues and Reciprocity

This study investigates improvisational music therapy (IMT) and its influence on the social interaction (SI) of a preschool child with autism spectrum disorder (ASD) in the Czech Republic. This case study tests the use of music therapy as an augmentative intervention for children with ASD. Using a qualitative design and incorporating microanalysis, the aim was to apply methodological protocols of direct and indirect observation on individual IMT sessions. Three SI domains were assessed using microanalysis in this single case study research: a) nonverbal communication, b) sharing, and c) solace. Varied musical features elicited certain intentional behaviors, allowing the interpretation of their meanings. The nonverbal communication studied shows intention to relate, self-awareness, awareness of others, and sharing. The IMT context provides a unique space for dialogues and reciprocity in a protected and settled environment. Children’s improved SI can provide insight into their ability to interact with others. IMT presents promising care for children with ASD, extending comprehensive care by including dimensions of individualization and an intrinsic, non-directive approach, allowing the child to acquire and further develop their own ways of expression for the regulation of SI. Ideas around the quality of SI within IMT need to be further investigated.
Tensin2 Is a Novel Diagnostic Marker in GIST, Associated with Gastric Location and Non-Metastatic Tumors

Simple Summary Most of the immunohistochemical markers for gastrointestinal stromal tumor (GIST) are also expressed in other sarcomas relevant for the differential diagnosis of GIST, and thus, new immunohistochemical markers can be of help in GIST diagnostics. Tensin2 (TNS2) was found to be downregulated in most human cancers but overexpressed in GIST; we therefore investigated the role of TNS2 as a diagnostic biomarker for GIST. The results provide conclusive evidence for the value of TNS2 as a sensitive and specific diagnostic biomarker for GIST, with stronger associations for gastric and non-metastatic tumors. These findings can be of use in the differential diagnosis of GIST, especially while trying to differentiate other tumors of the stomach, such as lipo- and leiomyosarcomas, from GISTs. Abstract GIST is a rare soft tissue sarcoma, for which KIT and DOG1 are used as highly sensitive diagnostic markers. Other diagnostic markers include CD34, protein kinase C θ, deficiency of succinate dehydrogenase complex subunit B, carbonic anhydrase II, and type I insulin-like growth factor receptor. We investigated the role of TNS2 as a diagnostic biomarker by using immunohistochemistry in 176 GISTs and 521 other sarcomas. All GISTs expressed TNS2, with intermediate or high expression in 71.4% of samples. The majority (89.8%) of other sarcomas were negative for TNS2, and intermediate to strong staining was only seen in 2.9% of samples. Strong TNS2 staining was associated with gastric location (gastric 52.8% vs. non-gastric 7.2%; p < 0.001), absence of metastases (non-metastatic tumors 44.3% vs. metastatic tumors 5.9%; p = 0.004), female sex (female 45.9% vs. male 33.8%; p = 0.029), and tumors of lower risk categories (very low or low 46.9% vs. intermediate 51.7% vs. high 29.0%; p = 0.020). TNS2 expression did not correlate with overall survival or metastasis-free survival. No associations between TNS2 expression and KIT/PDGFRA mutation status, tumor size, mitotic count, or age of the patient were detected. The results provide conclusive evidence for the value of TNS2 as a sensitive and specific diagnostic biomarker for GIST.