Miracle-dz/UniFAR-FTUs huggingface dataset:
Do You Really Like Her Post?: Network-Based Analysis for Understanding Like Activities in SNS

As social network services (SNS) are expanding from friend-based to interest-based, users form a new type of relationships, namely interest-based relationships, with friends and others through social activities (e.g., likes, comments). Although such relationships are highlighted in the common-identity theory and have important values in theoretical and practical aspects, little evidence exists in the literature pertaining to the explanation of social activities as a central component for social network analysis and an association with friendship. In this paper, we build like networks in Instagram and analyze them through the lens of two salient aspects - friendship and interest - that constitute social networks. Our study results (1) show ambiguous interpretations of the like activities between users who are friends, based on the comparative analysis between friend- and non-friend-based like networks, and (2) demonstrate strong signals of the hashtag characterizing the interest-based relationships in users and content. Our research substantiates and gives insights on the common-identity theory applied in online social networks through data-driven, empirical analysis.
Multi-Channel Sellers Traffic Allocation in Large-scale E-commerce Promotion

Large-scale online promotions, such as Double 11 and Black Friday, are of great value to e-commerce platforms nowadays. Traditional methods are not successful when we aim to maximize global Gross Merchandise Volume (GMV) in the promotion scenarios due to three limitations. The first is that the GMV of sellers varies significantly from daily scenarios to promotions. Second, these methods do not consider explosive demands in promotions, so that a consumer may fail to purchase some popular items due to sellers' limited capacities. Third, the traffic distribution over sellers presents divergence in different channels, thus rendering the performance of the traditional single-channel methods far from optimal in creating commercial values. To address these problems, we design a Multi-Channel Sellers Traffic Allocation (MCSTA) optimization model to obtain optimal page view (PV) distribution concerning global GMV. Then we propose a general constrained non-smooth convex optimization solution with a Multi-Objective Shortest Distance (MOSD) hyperparameter tuning method to solve MCSTA. This is the first work to systematically address this issue in the scenario of large-scale online promotions. The empirical results show that MCSTA achieves significant improvement of GMV by 1.1% based on A/B test during Alibaba's "Global Shopping Festival", one of the world's largest online sales events. Furthermore, we deploy MCSTA in other popular scenarios, including everyday promotion and video live stream service, to showcase that MCSTA can be widely applied in e-commerce and online entertainment services.
Deriving Geolocations in Wikipedia

We study the problem of deriving geolocations for Wikipedia pages. To this end, we introduce a general four-step process to location derivation, and consider different instantiations of this process, leveraging both textual and categorical data. Extensive experimentation shows that our methods provide good precision-recall trade-offs and improvements over text-only methods. Hence, our system can be used to augment the geographic information of Wikipedia, and to enable more effective geographic information retrieval.
CSSA'20: Workshop on Combining Symbolic and Sub-Symbolic Methods and their Applications

There has been a rapid growth in the use of symbolic representations along with their applications in many important tasks. Symbolic representations, in the form of Knowledge Graphs (KGs), constitute large networks of real-world entities and their relationships. On the other hand, sub-symbolic artificial intelligence has also become a mainstream area of research. This workshop brought together researchers to discuss and foster collaborations on the intersection of these two areas.
Distribution, Age Structure, and Growth of Bigheaded Carps in the Lower Tennessee and Cumberland Rivers

Abstract Invasive Asian carps Hypophthalmichthys nobilis (Bighead Carp) and H. molitrix (Silver Carp), collectively referred to as bigheaded carps, were introduced to the US in the 1970s to control noxious algae blooms in aquaculture ponds. Fish subsequently escaped, and by the 1980s bigheaded carps were widespread and established in the upper Mississippi River, lower Missouri River, and the Ohio River and some of its tributaries. We sampled bigheaded carps in the lowermost reservoirs on the Tennessee River (Kentucky Lake) and Cumberland River (Lake Barkley) in 2015 and 2016 using multiple gears, including gill nets, hoop nets, electrofishing, and cast nets, to describe their distribution and estimate several population attributes. Additional electrofishing samples on the Duck River, a system renowned for its diverse ichthyofauna and mussel communities, revealed that Silver Carp range extends 220 river kilometers (rkm) upstream below the Columbia Dam. We collected a total of 737 Silver Carp and 10 Bighead Carp through the course of this study. The maximum total lengths and ages were 1385 mm and 22 years for Bighead Carp and 1005 mm and 13 years for Silver Carp. The Silver Carp populations in both reservoirs had the same pattern of strong year classes (2010, 2011, 2012, and 2015) and similar growth rates, which were faster than what has been reported for other populations around the globe. Some young-of-year Silver Carp were collected 180 and 110 rkm upstream in Kentucky Lake and Lake Barkley, respectively, and they may represent the first evidence of natural reproduction in those reservoirs or their tributaries.
DTMBIO 2020: The Fourteenth International Workshop on Data and Text Mining in Biomedical Informatics

Over a decade, as a specialized workshop in the field of text mining applied to biomedical informatics, DTMBIO (ACM international workshop on Data and Text Mining in Biomedical Informatics) has been held annually in conjunction with one of the largest data management conferences, CIKM. The purpose of DTMBIO is to foster discussions regarding the state-of-the-art applications of data and text mining on biomedical research problems. To address our purpose, we bring together researchers working on computer science and bio/medical informatics area including text mining and high throughput genomic data analysis, such as the next generation Sequencing (NGS) data. DTMBIO 2020 will help scientists navigate emerging trends and opportunities in the evolving area of informatics related techniques and problems in the context of biomedical research.
Trends in mean growth and stability in temperate vertebrate populations

Considerable controversy exists over the nature of the “Biodiversity Crisis. ” While some studies suggest declining diversity, others suggest no loss on average. Population declines necessarily precede species loss and may therefore be a more sensitive metric. We examine trends in abundances to test the hypotheses: (1) losses are experienced disproportionately by some taxa, in particular amphibians; (2) positive trends in alien or unexploited species mask declines in native or exploited species, respectively; (3) populations are becoming more unstable, and variances of within‐population growth rates are increasing.
The Cost of Reproduction in Annual Meadow Grass

Studies of the evolution of life histories assume that there are costs to reproduction, although there is little experimental evidence for their existence. In this paper some populations of annual meadow grass (Poa annua L.) are analyzed, to test for the existence of these costs. The results show that there is a price to be paid for high rates of reproduction early in life, in lower rates and smaller plant size subsequently. There are also signs that high rates of reproduction very early in life increase subsequent risks of mortality. A possible form for the relationship is considered from a model of reproduction, growth, and survival. The implications of the observed and predicted costs to the evolution of life histories in annual meadow grass are discussed.
Social status and ejaculate composition in the house mouse

Sperm competition theory predicts that males should tailor ejaculates according to their social status. Here, we test this in a model vertebrate, the house mouse (Mus musculus domesticus), combining experimental data with a quantitative proteomics analysis of seminal fluid composition. Our analyses reveal that both sperm production and the composition of proteins found in seminal vesicle secretions differ according to social status. Dominant males invested more in ejaculate production overall. Their epididymides contained more sperm than those of subordinate or control males, despite similar testes size between the groups. Dominant males also had larger seminal vesicle glands than subordinate or control males, despite similar body size. However, the seminal vesicle secretions of subordinate males had a significantly higher protein concentration than those of dominant males. Moreover, detailed proteomic analysis revealed subtle but consistent differences in the composition of secreted seminal vesicle proteins according to social status, involving multiple proteins of potential functional significance in sperm competition. These findings have significant implications for understanding the dynamics and outcome of sperm competition, and highlight the importance of social status as a factor influencing both sperm and seminal fluid investment strategies. This article is part of the theme issue ‘Fifty years of sperm competition’.
Biofilm formation by Mycobacterium avium ssp. paratuberculosis in aqueous extract of schmutzdecke for clarifying untreated water in water treatment operations

AIMS To determine the effect of aqueous extract of schmutzdecke on adhesion and biofilm formation by three isolates of Mycobacterium avium ssp. paratuberculosis (Map) under laboratory conditions. METHODS AND RESULTS Strains of Mycobacterium avium ssp. paratuberculosis in aqueous extract of schmutzdecke were subjected to adhesion tests on two topologically different substrata i.e. aluminium and stainless steel coupons. Biofilm formation was then monitored in polyvinyl chloride (PVC) plates. All the three strains adhered onto both coupons, howbeit greatly on aluminium than stainless steel. In the PVC plates, however, all strains developed biofilms which were observed by spectrophotometric analysis. CONCLUSIONS The environmental isolates of Map attained higher cell proliferation in both filtered and unfiltered aqueous extracts of schmutzdecke (FAES and UAES respectively) compared with the human isolate. Furthermore, the results showed that irrespective of the media used, Map might have developed biofilm by its genetic competence to do so under favourable conditions that the immediate environment might have provided. Significance and impact of the study Composites of the schmutzdecke which is the dirty layer formed within 10 to 20 days of operation of a slow sand filter bed had a proliferative effect on Map. Therefore when entrapped, Map could form a biofilm and access human populations through potable water. Therefore, schmutzdecke should be monitored and scraped periodically to curtail its support for environmentally persistent pathogens that can pose health risks to humans. Highlights Schmutzdecke; a reservoir of nutrient composites atop slow sand filter bed Adhesion by Map on aluminium and stainless steel coupons was achieved Map strains from water sources developed biofilms better than the human strain In distilled water, biofilm formation by all strains was evident Protracted build-up of schmutzdecke may proliferate waterborne pathogens
A review of approaches to land use changes modeling

ABSTRACT Being a widespread phenomenon, land use changes are being increasingly evaluated by modeling methods, including statistical modeling. Land use changes models facilitate interpreting the causes and consequences of land use dynamics and support policy-makers in taking rational decisions. Literature offers numerous land use models developed by researchers from various fields. The goal of the article was to review the existing methods of land use change modeling, in particular, statistical models. It is, therefore, a synthesis of the knowledge found in previous studies in this domain. The discussion is based on four areas: (1) the role of modeling and models in land use changes studies, (2) major land use changes modeling methods, their advantages and limitations, (3) integrated approach to modeling, (4) and land use changes modeling in Poland. Results indicate that there are many land use changes modeling methods, each with its advantages and drawbacks. It is not an easy challenge to select the right one. Such factors as the goal of the model and research problem should be taken into consideration. The article is intended first of all for researchers and modelers in pursuit of new research methods or improving their models.
Consumption Trends During the COVID-19 Crisis: How Awe, Coping, and Social Norms Drive Utilitarian Purchases

As the coronavirus disease 2019 (COVID-19) crisis continues to worsen globally, there exists a widespread enthusiasm for buying utilitarian products in the retail market, irrespective of culture or nationality. However, the questions of whether and why being involved in a public health emergency like the COVID-19 crisis could modify consumer behaviors have been underexplored by previous literature. Drawing on the theory of awe that highlights the important role in influencing human behaviors when they are facing unexpected events that transcends the frame of existing references, the present research aims to clarify the relationship between COVID-19 involvement and consumer preference for utilitarian versus hedonic products. We collected data from 512 Chinese participants (319 women; average age 29.11 years; SD = 11.89) during the outbreak of COVID-19. The results of structural equation modeling showed that COVID-19 involvement was positively related to the preference for utilitarian products (vs. hedonic products). More importantly, this relationship could be explained via the mediated effects of awe, problem-focused coping, and social norm compliance. The present research emphasizes the non-negligible role of public health emergencies in modifying consumer behavior and the role of awe in explaining the psychological influence of public health emergencies.
The Longitudinal Association Between Cardiovascular Risk and Cognitive Function in Middle-Aged and Older Adults in China: A Nationally Representative Cohort Study

Objective: China has the largest population living with dementia, causing a tremendous burden on the aging society. Cardiovascular disease (CVD) may trigger a cascade of pathologies associated with cognitive aging. We aim to investigate the association between cardiovascular risk (CVR) factors and cognitive function in the nationally representative cohort in China. Methods: Participants were recruited from 150 counties in 28 provinces via a four-stage sampling method. The outcomes included several cognitive tasks. The independent variable was a composite score of cardiovascular risk calculated from sex-specific equations. We fitted the time-lagged regression to model the association between CVR and cognition. Besides, we performed cross-group analyses to test for model invariance across sex and age. We thus constrained path coefficients to be equal across each grouping variable (e.g., sex) and compared the fit of this constrained model with an unconstrained model in which the path coefficients were allowed to vary by group. Results: A total of 3,799 participants were included in the final analyses. We found that the CVR had a negative linear association with global cognition (β = −0.1, p < 0.01). Additionally, CVR had inverse linear associations with domain-specific measurements of memory and learning, calculation, orientation, and visual–spatial ability (all values of p < 0.01). Regarding sex and age moderation, males had a more pronounced association between higher CVR and worse general cognition, immediate recall, orientation, calculation, and visual–spatial ability (all values of p < 0.0001). In contrast, females exhibited a slightly larger negative association in delayed recall. Older participants (>65 years old) had a more pronounced association between higher CVR and worse calculation ability (p = 0.003). Conclusion: CVD are risk factors for lower global cognition and cognitive subdomains in middle-aged and older adults in China.
Eleven-Month-Olds Link Sound Properties With Animal Categories

We examined 11-month-olds’ tendency to generalize properties to category members, an ability that may contribute to the inductive reasoning abilities observed in later developmental periods. Across three experiments, we tested 11-month-olds’ (N = 113) generalization of properties within the cat and dog categories. In each experiment, infants were familiarized to animal–sound pairings (i.e., dog barking; cat meowing) and tested on this association and the generalization of the sound property to new members of the familiarized categories. After familiarization with a single exemplar, 11-month-olds generalized the sound to new category members that were both highly similar and less similar to the familiarized animal (Experiment 1). When familiarized with mismatched animal–sound pairings (Experiment 2; i.e., dog meowing; cat barking), 11-month-olds did not learn or generalize the sound properties, suggesting that infants have pre-existing expectations about the links between the characteristic sound properties and the animal categories. When familiarized with unfamiliar sound–animal pairings (Experiment 3; i.e., dog-unfamiliar sound), 11-month-olds linked the animals with the novel sounds but did not generalize to new category members. Taken together, these findings highlight the conditions under which young infants generalize properties from one exemplar to other category members.
Brain Age Prediction of Children Using Routine Brain MR Images via Deep Learning

Predicting brain age of children accurately and quantitatively can give help in brain development analysis and brain disease diagnosis. Traditional methods to estimate brain age based on 3D magnetic resonance (MR), T1 weighted imaging (T1WI), and diffusion tensor imaging (DTI) need complex preprocessing and extra scanning time, decreasing clinical practice, especially in children. This research aims at proposing an end-to-end AI system based on deep learning to predict the brain age based on routine brain MR imaging. We spent over 5 years enrolling 220 stacked 2D routine clinical brain MR T1-weighted images of healthy children aged 0 to 5 years old and randomly divided those images into training data including 176 subjects and test data including 44 subjects. Data augmentation technology, which includes scaling, image rotation, translation, and gamma correction, was employed to extend the training data. A 10-layer 3D convolutional neural network (CNN) was designed for predicting the brain age of children and it achieved reliable and accurate results on test data with a mean absolute deviation (MAE) of 67.6 days, a root mean squared error (RMSE) of 96.1 days, a mean relative error (MRE) of 8.2%, a correlation coefficient (R) of 0.985, and a coefficient of determination (R2) of 0.971. Specially, the performance on predicting the age of children under 2 years old with a MAE of 28.9 days, a RMSE of 37.0 days, a MRE of 7.8%, a R of 0.983, and a R2 of 0.967 is much better than that over 2 with a MAE of 110.0 days, a RMSE of 133.5 days, a MRE of 8.2%, a R of 0.883, and a R2 of 0.780.
Characterization of the N-terminal Region of the RNA-Binding Protein Smaug in Post-transcriptional Regulation During Drosophila Embryogenesis

The Drosophila sequence-specific RNA-binding protein Smaug (Smg) regulates the expression of mRNAs in the early fly embryo. It is the founding member of a conserved family of post-transcriptional regulators defined by an RNA-binding sterile alpha motif (SAM) domain. Smg regulates gene expression through its ability to repress the translation, and/or induce degradation of target mRNAs. Through a structure-function analysis using smg truncation mutants, I show that sequences Nand C-terminal to the Smg SAM domain are involved, and have partially redundant roles in mRNA decay. Moreover, another conserved region of Smg modulates the mRNA decay function of the N-terminal sequences in a transcript-specific manner. Finally, sequences within the Smg Nand C-terminal regions are also required for the degradation of Smg protein.
Geometric morphometrics and face shape characteristics associated with chronic disease in the elderly

The aging process is something that occurs naturally during the lifetime of the human being. It causes biological, psychological and social changes in the body. Anthropometry, which until the late nineteenth century was a common tool in clinical and taxonomic practices, has gained great importance as a public health measure. This methodology is also important in the evaluation of morbidities in individuals and their social practices. Thus, the objective of the present study was to evaluate facial shape characteristics in the elderly, associated with chronic diseases such as diabetes and hypertension, based on two-dimensional images of the lateral and frontal views of the face. Analysis of discriminant function and cross validation presented significant differences (p<0.01), for sexual dimorphism in both views and the presence and/or absence of diabetes and hypertension (p<0.01). For the male sex, the highest classifications were related to the complete lateral and frontal views, in 75.2% and 81.2% of cases, respectively. In terms of the female sex, they referred to the frontal view without the orolabial region or jaw (71.4%). There was variation in the facial bilateral symmetry in the elderly, with the presence of fluctuating and directional asymmetry (p<0.01). Despite morphological variations associated with aging, it is possible to use geometric morphometrics techniques to observe characteristics in facial shape related to the presence of diabetes, hypertension, and the presence or absence of both diseases.
Growth and physiological characterization of low nitrogen responses in Tibetan wild barley (Hordeum spontaneum) and cultivated barley (Hordeum vulgare)

ABSTRACT Development of crop cultivars with high yield under low nitrogen (N) supply is a basic approach for the enhancement of agricultural sustainability. The previous studies showed that Tibetan wild barley shows wider genetic diversity in abiotic stress and poor fertility tolerance. In this study, four barley genotypes (two Tibetan wild and two cultivated), differing in N use efficiency (NUE), were characterized for their growth and physiological responses to low N stress. The genotypes ZD9 (cultivated) and XZ149 (wild) with high NUE performed better in terms of shoot dry weight (DW) and photosynthetic parameters under both low and normal N levels and had higher antioxidative enzyme activities, N concentration, and accumulation in both shoots and roots under low N stress. The current results showed the substantial difference among barley genotypes in low N tolerance and verified the significance of Tibetan wild barley in the genetic improvement of cultivated barley in NUE.