Miracle-dz/UniFAR-FTUs huggingface dataset:
Food Web Topology in High Mountain Lakes

Although diversity and limnology of alpine lake systems are well studied, their food web structure and properties have rarely been addressed. Here, the topological food webs of three high mountain lakes in Central Spain were examined. We first addressed the pelagic networks of the lakes, and then we explored how food web topology changed when benthic biota was included to establish complete trophic networks. We conducted a literature search to compare our alpine lacustrine food webs and their structural metrics with those of 18 published lentic webs using a meta-analytic approach. The comparison revealed that the food webs in alpine lakes are relatively simple, in terms of structural network properties (linkage density and connectance), in comparison with lowland lakes, but no great differences were found among pelagic networks. The studied high mountain food webs were dominated by a high proportion of omnivores and species at intermediate trophic levels. Omnivores can exploit resources at multiple trophic levels, and this characteristic might reduce competition among interacting species. Accordingly, the trophic overlap, measured as trophic similarity, was very low in all three systems. Thus, these alpine networks are characterized by many omnivorous consumers with numerous prey species and few consumers with a single or few prey and with low competitive interactions among species. The present study emphasizes the ecological significance of omnivores in high mountain lakes as promoters of network stability and as central players in energy flow pathways via food partitioning and enabling energy mobility among trophic levels.
Swat: A system for detecting salient Wikipedia entities in texts

We study the problem of entity salience by proposing the design and implementation of Swat, a system that identifies the salient Wikipedia entities occurring in an input document. Swat consists of several modules that are able to detect and classify on‐the‐fly Wikipedia entities as salient or not, based on a large number of syntactic, semantic, and latent features properly extracted via a supervised process, which has been trained over millions of examples drawn from the New York Times corpus. The validation process is performed through a large experimental assessment, eventually showing that Swat improves known solutions over all publicly available datasets. We release Swat via an API that we describe and comment in the paper to ease its use in other software.
Betulinic acid-induced expression of nicotinamide adenine dinucleotide phosphate-diaphorase in the immune organs of mice: A possible role of nitric oxide in immunomodulation

The aim of the present study was to investigate the effects of betulinic acid (BetA) on the expression and distribution pattern of nicotinamide adenine dinucleotide phosphate diaphorase (NADPH-d), an indirect indicator of nitric oxide (NO) synthase in the thymus and spleen of mice. Mice were randomly assigned to four main groups (n=48 per group): Experimental group (BetA), positive control group (goniothalamin), vehicle control group (dimethyl sulfoxide) and control group (without vehicle). Each group was further divided into three equal subgroups according to the treatment length (4, 8 and 12 days). BetA treatment induced the expression of NADPH-d activity in the thymus and spleen without any significant changes in the morphology of the organs. Furthermore, the expression pattern of NADPH-d in BetA-treated animals was significantly increased compared with that in the control animals. NADPH-d expression in the thymus and spleen suggests that NO signaling may be a potential mechanism underlying the BetA-induced immunomodulation in these organs. These findings are of direct clinical relevance and may contribute to the further development of BetA as a therapeutic drug.
Vector Meson Photoproduction with a Linearly Polarized Beam

We propose a model based on Reggae theory to describe photoproduction of light vector mesons. We fit the SLAC data and make predictions for the energy and momentum-transfer dependence of the spin-density matrix elements in photoproduction of omega, rho degrees and phi mesons at E-gamma similar to 8.5 GeV, which are soon to be measured at Jefferson Lab.
Design Optimization of MBR System for Oily Wastewater Treatment in Port

The optimal design of MBR system for oil film wastewater was introduced. The influence of aeration rate, aeration structure and reactor structure on the average cross flow velocity was studied. The average cross flow velocity between films was 1.25~1.28 M/s is a reasonable parameter to effectively slow down membrane fouling. The actual operation of the 12-month project shows that the negative pressure of the membrane module is stable below 0.02MPa. G and does not exceed the critical operating pressure control standard 0.05Mpa at the time of far chemical cleaning. The MBR system is applied to the oil-pollution of the technical problems for the promotion of MBR system provides a reasonable reference data.
TMEM59 potentiates Wnt signaling by promoting signalosome formation

Significance Wnt/β-catenin signaling is crucial for adult homeostasis and stem cell maintenance, and its dysregulation is strongly associated to cancer. Upon Wnt binding, Wnt receptors assemble into large complexes called signalosomes that provide a platform for interactions with downstream effector proteins. The assembly and regulation of these signalosomes remains largely elusive. Here, we use internally tagged Wnt ligands as a tool to isolate and analyze the composition and regulation of endogenous Wnt receptor complexes. We identify a positive regulator of Wnt signaling that facilitates signalosome formation by promoting intramembrane receptor interactions. Our results reveal that the assembly of multiprotein Wnt signalosomes proceeds along well-ordered steps and involves regulated intramembrane interactions. Wnt/β-catenin signaling controls development and adult tissue homeostasis by regulating cell proliferation and cell fate decisions. Wnt binding to its receptors Frizzled (FZD) and low-density lipoprotein-related 6 (LRP6) at the cell surface initiates a signaling cascade that leads to the transcription of Wnt target genes. Upon Wnt binding, the receptors assemble into large complexes called signalosomes that provide a platform for interactions with downstream effector proteins. The molecular basis of signalosome formation and regulation remains elusive, largely due to the lack of tools to analyze its endogenous components. Here, we use internally tagged Wnt3a proteins to isolate and characterize activated, endogenous Wnt receptor complexes by mass spectrometry-based proteomics. We identify the single-span membrane protein TMEM59 as an interactor of FZD and LRP6 and a positive regulator of Wnt signaling. Mechanistically, TMEM59 promotes the formation of multimeric Wnt–FZD assemblies via intramembrane interactions. Subsequently, these Wnt–FZD–TMEM59 clusters merge with LRP6 to form mature Wnt signalosomes. We conclude that the assembly of multiprotein Wnt signalosomes proceeds along well-ordered steps that involve regulated intramembrane interactions.
Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer’s disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients.
Human-Guided Data Exploration

The outcome of the explorative data analysis (EDA) phase is vital for successful data analysis. EDA is more effective when the user interacts with the system used to carry out the exploration. In the recently proposed paradigm of iterative data mining the user controls the exploration by inputting knowledge in the form of patterns observed during the process. The system then shows the user views of the data that are maximally informative given the user's current knowledge. Although this scheme is good at showing surprising views of the data to the user, there is a clear shortcoming: the user cannot steer the process. In many real cases we want to focus on investigating specific questions concerning the data. This paper presents the Human Guided Data Exploration framework, generalising previous research. This framework allows the user to incorporate existing knowledge into the exploration process, focus on exploring a subset of the data, and compare different complex hypotheses concerning relations in the data. The framework utilises a computationally efficient constrained randomisation scheme. To showcase the framework, we developed a free open-source tool, using which the empirical evaluation on real-world datasets was carried out. Our evaluation shows that the ability to focus on particular subsets and being able to compare hypotheses are important additions to the interactive iterative data mining process.
Calcium signals act through histone deacetylase to mediate pronephric kidney morphogenesis

Background: Autosomal dominant polycystic kidney disease is the most common monogenetic kidney disorder and is linked to mutations in PKD1 and PKD2. PKD2, a Ca2+‐conducting TRP channel enriched in ciliated cells and gated by extracellular signals, is necessary to activate the multifunctional Ca2+/calmodulin–dependent protein kinase type 2 (CaMK‐II), enabling kidney morphogenesis and cilia stability. Results: In this study, antisense morpholino oligonucleotides and pharmacological compounds were employed to investigate the roles of class II HDAC family members (HDAC 4, 5, and 6) in Zebrafish kidney development. While all three class II HDAC genes were expressed throughout the embryo during early development, HDAC5‐morphant embryos exhibited anterior cysts and destabilized cloacal cilia, similar to PKD2 and CaMK‐II morphants. In contrast, HDAC4‐morphant embryos exhibited elongated cloacal cilia and lacked anterior kidney defects. Suppression of HDAC4 partially reversed the cilia shortening and anterior convolution defects caused by CaMK‐II deficiency, whereas HDAC5 loss exacerbated these defects. EGFP‐HDAC4, but not EGFP‐HDAC5, translocated into the nucleus upon CaMK‐II suppression in pronephric kidney cells. Conclusions: These results support a model by which activated CaMK‐II sequesters HDAC4 in the cytosol to enable primary cilia formation and kidney morphogenesis. Developmental Dynamics 247:807–817, 2018. © 2018 Wiley Periodicals, Inc.
Automatic Detection of Online Jihadist Hate Speech

We have developed a system that automatically detects online jihadist hate speech with over 80% accuracy, by using techniques from Natural Language Processing and Machine Learning. The system is trained on a corpus of 45,000 subversive Twitter messages collected from October 2014 to December 2016. We present a qualitative and quantitative analysis of the jihadist rhetoric in the corpus, examine the network of Twitter users, outline the technical procedure used to train the system, and discuss examples of use.
Near and Dear? Evaluating the Impact of Neighbor Diversity on Inter-Religious Attitudes

This paper provides experimental evidence on whether having religiously different neighbors affects attitudes about other religious groups and/or preferences for interreligious living. I exploit a natural experiment in a large Indian city in which Hindus and Muslims were randomly assigned units in a public housing complex with physically distinct "clusters" of four units. The lottery generates exogenous variation in the degree of religious diversity across clusters within the complex. I conduct an original survey of 1363 household that focuses on explicit and implicit attitudes about members of the other religion and willingness to live together. My estimates demonstrate that location influences interactions, in that individuals spend significant time with others in their cluster. Increased proximity and interaction, in turn, affect attitudes. Greater exposure to Muslims (the minority group) improves Hindus' explicit attitudes about Muslims by 0.25 to 0.40 standard deviations, depending on the measure, and increases their willingness to live with Muslims. Paralleling this, I observe significant reductions in implicit bias against Muslims (0.20 to 0.57 standard deviations) among Hindu children. While I observe no significant effects for Muslims, the overall effect is a convergence of attitudes across religious groups. As India expands public housing for the poor to accommodate rapid urbanization, deliberate mixing of religious groups can be a way of improving attitudes toward the religious minority.
Perceived Benefits and Challenges of a Risk-Based Approach to Multidisciplinary Chronic Kidney Disease Care: A Qualitative Descriptive Study

Background: The kidney failure risk equation (KFRE) provides an estimate of risk of progression to kidney failure, and may guide clinical care. Objective: We aimed to describe patient, family, and health care provider’s perspectives of the perceived benefits and challenges of using a risk-based approach to guide care delivery for patients with advanced chronic kidney disease (CKD), and refine implementation based on their input. Methods: We used qualitative methodology to explore perceived benefits and challenges of implementing a risk-based approach (using the KFRE) to determine eligibility for multidisciplinary CKD care in Southern Alberta. We obtained perspectives from patients and families through focus groups, as well as input from health care providers through interviews and open-ended responses from an online survey. Twelve patients/family members participated in 2 focus groups, 16 health care providers participated in an interview, and 40 health care providers responded to the survey. Results: Overall, participants felt that a KFRE-based approach had the potential to improve efficiency of the clinics by targeting care to patients at highest risk of kidney failure; however, they also expressed concerns about the impact of loss of services for lower risk individuals. Participants also articulated concerns about a perceived lack of capacity for adequate CKD patient care in the community. Our implementation strategy was modified as a result of participants’ feedback. Conclusions: We identified benefits and challenges to implementation of a risk-based approach to guide care of patients with advanced CKD. Based on these results, our implementation strategy has been modified by removing the category of referral back to primary care alone, and instead having that decision made jointly by nephrologists and patients among low-risk patients.
The Index of Emancipative Values: Measurement Model Misspecifications

This article reports evidence of misspecification of the measurement model for the index of emancipative values, a value construct used as a key explanatory variable in many important contributions to political science. It shows that the scale on which the index is measured is noninvariant across cultural zones and countries in the World Values Survey. In addition, it demonstrates that the current index composition mixes different value dimensions and their actual associations with various political outcomes, in particular the index of effective democracy. However, an analysis using a novel approximate Bayesian approach shows that at least one specific subdimension of emancipative values, known as pro-choice values, truly exists and may be validly measured and compared cross-nationally. The article also contributes to the recent discussion on whether emancipative values are a reflective or a formative construct by providing thought experiments and empirical evidence supporting the former interpretation.
Using a Learner-Topic Model for Mining Learner Interests in Open Learning Environments

The present study uses a text data mining approach to automatically discover learner interests in open learning environments. We propose a method to construct learner interests automatically from the combination of learner generated content and their dynamic interactions with other learning resources. We develop a learner-topic model to discover not only the learner’s knowledge interests (interest in generating content), but also the learner’s collection interests (interest in collecting content generated by others). Then we combine the extracted knowledge interests and collection interests to yield a set of interest words for each learner. Experiments using a dataset from the Learning Cell Knowledge Community demonstrate that this method is able to discover learners’ interests effectively. In addition, we find that knowledge interests and collection interests are related and consistent in their subject matter. We further show that learner interest words discovered by the learner-topic model method include learner self-defined interest tags, but reflect a broader range of interests.
Table Union Search on Open Data

We define the table union search problem and present a probabilistic solution for finding tables that are unionable with a query table within massive repositories. Two tables are unionable if they share attributes from the same domain. Our solution formalizes three statistical models that describe how unionable attributes are generated from set domains, semantic domains with values from an ontology, and natural language domains. We propose a data-driven approach that automatically determines the best model to use for each pair of attributes. Through a distribution-aware algorithm, we are able to find the optimal number of attributes in two tables that can be unioned. To evaluate accuracy, we created and open-sourced a benchmark of Open Data tables. We show that our table union search outperforms in speed and accuracy existing algorithms for finding related tables and scales to provide efficient search over Open Data repositories containing more than one million attributes.
PERUN : Virtual Payment Hubs over Cryptographic Currencies

Payment channels emerged recently as an efficient method for performing cheap micropayment transactions in cryptographic currencies. In contrast to the traditional on-chain transactions, payment channels have the advantage that they allow nearly unlimited number of transactions between parties without involving the blockchain. In this work, we introduce Perun, an off-chain channel system that offers a novel method for connecting channels that is more efficient than the existing technique of “routing transactions” over multiple channels. That is, in contrast to prominent existing solutions such as the Lightning Network, Perun does not require, for each individual payment, involvement of the intermediary over which the payment is routed. This is achieved by introducing a new technique called “virtual payment channels”. In this paper we formally model and prove security of this technique for routing payments over one intermediary, who can be viewed as a “payment hub” that has direct channels with several parties. Our scheme works over any cryptocurrency that provides Turing-complete smart contracts. As a proof of concept, we implemented Perun’s smart contracts in Ethereum.
Therapeutic Effect of Cucumis melo L. Extract on Insulin Resistance and the Gut Microbiome in Lepob/Lepob Mice

Obesity results in the progression of metabolic disorders, especially type 2 diabetes (T2DM). Obesity-induced insulin resistance (IR) is a causative factor of T2DM morbidity in obese people. It is generally held by clinicians that IR is caused by adiposity-related inflammation that is mediated by changes in composite ions in the gut microbiome. This experimental study was designed to investigate the effects of Cucumis melo L. (Cucumis) on obesity-induced IR in genetically leptin-deficient Lepob/Lepob mice. Specifically, we examined the anti-inflammatory effects of Cucumis and the effects of Cucumis on the gut microbiota. We evaluated glucose control by measuring FBS, performing the OGTT, quantifying serum IR, calculating the HOMA-IR, and determining the lipid profiles. To see whether inflammation was reduced, we analyzed adipose tissue macrophages as well as monocytes in the blood. We also profiled the gut microbiota to determine whether the ratios of microbial phyla changed. We found that Cucumis improved IR in obese mice and relieved inflammation in adipose tissue and blood. Simultaneously, the microbiota composition ratios changed. In conclusion, administration of Cucumis improved IR by reducing inflammation, thereby changing the gut microbiota composition. Cucumis is thus a promising treatment for obesity-induced insulin resistance and the inflammatory state.
The importance of imaging strategies for pre-clinical and clinical in vivo distribution of oncolytic viruses

Oncolytic viruses (OVs) are an emergent and unique therapy for cancer patients. Similar to chemo- and radiation therapy, OV can lyse (kill) cancer cell directly. In general, the advantages of OVs over other treatments are primarily: a higher safety profile (as shown by less adverse effects), ability to replicate, transgene(s) delivery, and stimulation of a host’s immune system against cancer. The latter has prompted successful use of OVs with other immunotherapeutic strategies in a synergistic manner. In spite of extended testing in pre-clinical and clinical setting, using biologically derived therapeutics like virus always raises potential concerns about safety (replication at non-intended locations) and bio-availability of the product. Recent advent in in vivo imaging techniques dramatically improves the convenience of use, quality of pictures, and amount of information acquired. Easy assessing of safety/localization of the biotherapeutics like OVs became a new potential weapon in the physician’s arsenal to improve treatment outcome. Given that OVs are typically replicating, in vivo imaging can also track virus replication and persistence as well as precisely mapping tumor tissues presence. This review discusses the importance of imaging in vivo in evaluating OV efficacy, as well as currently available tools and techniques.