Miracle-dz/UniFAR-FTUs huggingface dataset:
Bone Marrow Mesenchymal Stem Cells Attenuate Mitochondria Damage Induced by Hypoxia in Mouse Trophoblasts

Objective We aimed to observe the change of mitochondrial function and structure as well as the cell function induced by hypoxia in mouse trophoblasts, and moreover, to validate the restoration of these changes after co-culture with bone marrow mesenchymal stem cells (hereinafter referred to as “MSCs”). Further, we explored the mechanism of MSCs attenuating the functional damage of trophoblasts caused by hypoxia. Methods Cells were divided into two groups, trophoblasts and MSCs+trophoblasts respectively, and the two groups of cells were incubated with normoxia or hypoxia. Chemiluminescence was used to assay the β-HCG and progesterone in cell culture supernatants quantitatively. Western blotting and PCR were applied to detect the expression of Mfn2, MMP-2, MMP-9 and integrin β1 in the two groups. The mitochondrial membrane potential of each group of cells was detected with JC-1 dye and the ATP content was measured by the phosphomolybdic acid colorimetric method. We utilized transmission electron microscopy for observing the ultrastructure of mitochondria in trophoblasts. Finally, we assessed the cell apoptosis with flow cytometry (FCM) and analyzed the expression of the apoptosis related genes—Bcl-2, Bax, Caspase3 and Caspase9 by western blotting. Results The results showed that the Mfn2 expression was reduced after 4 h in hypoxia compared with that in normoxia, but increased in the co-culture group when compared with that in the separated-culture group (p<0.05). In addition, compared with the separated-culture group, theβ-HCG and progesterone levels in the co-culture group were significantly enhanced (p<0.05), and so were the expressions of MMP-2, MMP-9 and integrin β1 (p<0.05). Moreover, it exhibited significantly higher in ATP levels and intensified about the mitochondrial membrane potential in the co-culture group. TEM revealed disorders of the mitochondrial cristae and presented short rod-like structure and spheroids in hypoxia, however, in the co-culture group, the mitochondrial cristae had a relatively regular arrangement and the mitochondrial ultrastructure showed hyperfusion. The expression of Bax, Caspase3 and Caspase9 was decreased in the co-culture group when compared with that in trophoblast cells cultured alone (p<0.05), while the Bcl-2 levels and the Apoptosis Index (AI) were markedly increased in the co-culture group (p<0.05). Conclusion Bone marrow mesenchymal stem cells can attenuate mitochondria damage and cell apoptosis induced by hypoxia; the mechanism could be upregulating the expression of Mfn2 in mouse trophoblasts and changing mitochondrial structure.
Exploring Relationships Between Physical Activity, Leisure Involvement, Self-Efficacy, and Motivation via Participant Segmentation

Research objectives were both applied and conceptual. Actionable segments of physical activity participants were developed using leisure involvement profiles. Also explored were links between leisure involvement, a construct primarily developed and applied in leisure literature, and psychological variables found to influence participation in physical activity literature. A community-based sample of 384 adults completed measures of five involvement facets and psychological, demographic, and behavioral variables. Cluster analysis revealed four groups: Extremely Involved, Quite Involved, Moderately Involved, and Marginally Involved. Scores for physical activity behavior, self-efficacy, motivations, and body mass index were most positive for the Extremely Involved, with a linear decline across the three remaining segments (p < .05). Few demographic between-group differences were found. The data suggest that leisure involvement provides an effective means of segmenting physically active leisure participants for purposes of research and health promotion, and that self-efficacy and motivation for physical activity were predictably linked to involvement.
Planning, Maps, and Children's Lives: A Cautionary Tale

Planners are increasingly seeing children's maps as an appropriate consultation and participation method for enabling children's knowledge, views and experiences to be included in planning. A study was undertaken with 163 children aged nine to eleven in Dunedin, New Zealand, to understand children's relationships to their neighbourhood and the wider city. Children in the interview evidenced rich connections with their home environment and local community, but often did not produce “good” maps. Maps are useful as a tool for talking with children about their lives but, on their own, can give planners only limited insights into children's “real world” environmental cognition and community connection.
Extending the Combined Model for Congestion Control to Heterogeneous Networks

TCP and UDP are the dominant transport protocols on the Internet. The first one is used for reliable transport, while the second one for multimedia applications. Their behavior is quite different, which makes coexistence a challenge. Namely, TCP is responsive to potential network problems, such as congestion, while UDP completely ignores it. The need to come up with a protocol that somehow extracts the "good" attributes of both TCP and UDP, and leaves out the less favorable to the Internet, has proved to be a challenging research venue. Rather then going for an "entirely" new protocol, our objectives have been to keep TCP as is, while using the mobile agent paradigm for UDP control. The proposed solution termed as Combined Model for Congestion Control (CM4CC) has been limited to wired networks. Today, the Internet is an aggregation of both wired and wireless infrastructures; the article focuses on the CM4CC extension in heterogeneous networks.
Lepton flavor violation in tau decays

We study lepton flavor violation (LFV) in tau decays induced by heavy Majorana neutrinos within two models: (I) the Standard Model with additional right–handed heavy Majorana neutrinos, i.e., a typical seesaw–type model; (II) the Standard Model with left–handed and right–handed neutral singlets, which are inspired by certain scenarios of SO(10) models and heterotic superstring models with E6 symmetry. We calculate various LFV branching ratios and a T–odd asymmetry. The seesaw Model I predicts very small branching ratios for LFV processes in most of the parameter space, although in a very restricted parameter region it can reach maximal branching ratios Br(τ → �γ )∼10 −9 and Br(τ → 3� )∼10 −10 . In contrast, Model II may show branching ratios Br(τ → eγ)∼10 −8 and Br(τ → 3e) < ∼ 10 −9 , over a sizable region of the parameter space, large enough to be tested by experiments in the near future.
Rough Information Set and Its Applications in Decision Making

The decision making in the real world is inevitably characterized with vagueness, and imprecision due to incomplete knowledge. To this end, we combine the information set with the rough set theory to represent both the vagueness and imprecision at the same time. We term the proposed structure as rough information set that has information sets based on fuzzy equivalence relations as its building blocks. The usefulness of the proposed structure is demonstrated through a case study in credit scoring analysis, and a biometrics application on knuckle-based recognition.
EVOLUTION AND SUCCESS OF ONLINE NEWSPAPERS An empirical investigation of goals, business models and success

: In the evolving IS literature on business models for digital products, there seems to be a common belief that the positive feedback effect will lead to price competition and biased concentration of the market. However, there are not many serious empirical analyses studying this assumption carefully. In this paper we propose an examination of the goals and success of online newspapers in a homogenous and well-developed market. We evaluate the generic goals and their attainment, growth and concentration patterns, and the business models applied in order to test our hypotheses on the effects of revenue logic and the concentration of business capabilities among the online newspapers. Our empirical tests with data from 42 online versions showed that online versions had different evolution trends in national versus regional markets. Contrary to our hypothesis, the business model had only a marginal effect on the success scores compared with experience and orientation. Our analyses indicated that there was non-linear growth in both revenue and key capability factors, but that companies were still able to increase their revenue by devoting resources to manpower and marketing. Therefore we rejected our hypothesis on a dominating positive feedback effect.
Flexible Abstraction Layers for VR Application Development

The development of domain-specific virtual reality applications is often a slow and laborious process. The integration of the domain-specific functionality in an interactive Virtual Environment requires close collaboration between domain expert and VR developer, as well as the integration of domain-specific data and software in a VR application. The software environment needs to support the entire development process and software life cycle, from the early stages of iterative, rapid prototyping to a final end-user application. In this paper, we propose the use of flexible abstraction layers in the form of a dynamic scripting language, which act as the glue between VR system components and external software libraries and applications. First, we discuss the motivation and potential of our approach, after which we overview related approaches. Then, we describe the integration of a Python interpreter in our VR toolkit. The potential of our integration approach is demonstrated by rapid prototyping features, the flexible extension of core functionality and the integration of an external toolkit. We conclude with an overview of implications our approach has for the future development of new framework features and application integration
Integrated processing in multimodal argumentation

The question addressed in this paper is simple. If the argumentative function of a multimodal narrative text requires the integration of the information from different modes, among which verbal ones, what model for the order of processing and the integration of information do we need to adopt? Using discourse analysis as a method, we will argue that such a model needs to meet a number of requirements. We will argue that at least partially we are still in the realm of linguistic connectionism. By that we mean that the processing of the verbal modes is cognitively connected with and is influenced by the processing of other modes, perhaps similar to what has been argued that is the case in the multimodal processing of speech and gesture. The integration of for example a verbal speech voice-over mode with a pictorial mode is not a post-perception, late, dominantly conscious inference process that operates on more or less finalized mental representations of the separate modes. It depends on perceptual paring, on stipulated cross-modal congruence, and on cross-modal interactions between initial perceptions and knowledge based inferences. We will show how a unitary source assumption leads to cross-modal temporal paring as well as to the projection of the structure of one mode on the other mode. A model needs to allow such cross-modal connections to account for the fact that for example simultaneously appearing forms in two modes are interpreted as a crossmodal metaphor in which the structure receiving mode is taken to be the source domain.
Generalization of learned predator recognition: an experimental test and framework for future studies

While some prey species possess an innate recognition of their predators, others require learning to recognize their predators. The specific characteristics of the predators that prey learn and whether prey can generalize this learning to similar predatory threats have been virtually ignored. Here, we investigated whether fathead minnows that learned to chemically recognize a specific predator species as a threat has the ability to generalize their recognition to closely related predators. We found that minnows trained to recognize the odour of a lake trout as a threat (the reference predator) generalized their responses to brook trout (same genus as lake trout) and rainbow trout (same family), but did not generalize to a distantly related predatory pike or non-predatory suckers. We also found that the intensity of antipredator responses to the other species was correlated with the phylogenetic distance to the reference predator; minnows responded with a higher intensity response to brook trout than rainbow trout. This is the first study showing that prey have the ability to exhibit generalization of predator odour recognition. We discuss these results and provide a theoretical framework for future studies of generalization of predator recognition.
Issues of Social Data Analytics with a New Method for Sentiment Analysis of Social Media Data

Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There is a need to plug this research gap by developing effective analytic methods and approaches for sentiment analysis of data in non-English languages. These analyses of non-English language data should be integrated with the analysis of data in English language to better understand sentiments and address people-centric issues, particularly in multilingual societies. In addition, developing a high accuracy method, in which the customization of training datasets is not required, is also a challenge in current sentiment analysis. To address these various limitations and issues in current research, we propose a method that employs a new sentiment analysis scheme. The new scheme enables us to derive dominant valence as well as prominent positive and negative emotions by using an adaptive fuzzy inference method (FIM) with linguistics processors to minimize semantic ambiguity as well as multi-source lexicon integration and development. Our proposed method overcomes the limitations of the existing methods by not only improving the accuracy of the algorithm but also having the capability to perform analysis on non-English languages. Several case studies are included in this paper to illustrate the application and utility of our proposed method.
Simultaneous Control for Position and Vibration of Space Robotic Manipulator with Lightweight Flexible Arm

This study presents a synthesis scheme on a target history for the simultaneous control of position and vibration of a space robotic manipulator with a flexible arm. As an essential problem in the manipulator with a flexible arm, its vibration is easily induced by self-motion and external disturbance. Therefore, in this study, the authors develop the long, lightweight and forceful manipulator for a planetary lander and propose the control scheme not to require additional sensors and actuators for suppression of the vibration based on a feedforward control. The induced vibration of the manipulator is confirmed through the brief experiment and the command shaping method in the proposed control scheme is described in this paper. Finally, the numerical calculation with the control for the sample object is performed.
MAUVE Runtime: A Component-Based Middleware to Reconfigure Software Architectures in Real-Time

Developing robotic applications requires to design and implement complex software architectures. These architectures must embed advanced algorithms that include capacities to adapt to unforeseen events like external disturbances, sensor or actuator failures. To improve the system robustness, its behavior should be adapted at runtime by a reconfiguration of its software architecture. Such reconfiguration must be done safely and efficiently, while ensuring functional constraints and a minimal quality of service of the system. Among these constraints, preserving real-time properties of the reconfiguration process is a key feature. In this paper, we present the preliminary design of a new component-based middleware that allows to perform software architecture reconfigurations with a focus on real-time constraints.
Neighbors Matter: Causal Community Effects and Stock Market Participation

This paper establishes a causal relation between an individual's decision of whether to own stocks and average stock market participation decision of the individual's community. We instrument for the average ownership of an individual's community with lagged average ownership of the states in which one's non-native neighbors were born. Combining this instrumental variables approach with controls for individual and community fixed effects, a broad set of time-varying individual and community controls, and state-by-year effects, rules out alternative explanations. To further establish that word-of-mouth communication drives this causal effect, we show that the results are stronger in more sociable communities.
Characterization of the tet(M) determinant of Tn916: evidence for regulation by transcription attenuation

The nucleotide sequence of the tetracycline resistance determinant tet(M), located on conjugative transposon Tn916 of Enterococcus faecalis, was determined and found to encode a 72,486-dalton protein exhibiting a high degree of homology with other tet(M) determinants. A short open reading frame corresponding to a 28-amino-acid peptide and containing a number of inverted repeat sequences was noted immediately upstream of tet(M), suggesting that regulation might occur by a mechanism involving transcriptional attenuation. Transcription analyses found this to indeed be the case, showing that the expression of tet(M) resulted from an extension of a small transcript representing the upstream leader region into the resistance determinant. Exposure of cells to tetracycline resulted in a significant increase in the amount of tet(M) transcription; this increase could be explained on the basis of increased transcriptional read-through from the upstream transcript. A model suggesting how transcriptional attenuation might operate in this system is presented.
Identification of human neutralizing antibodies against MERS-CoV and their role in virus adaptive evolution

Significance The recently emerged Middle East Respiratory Syndrome coronavirus (MERS-CoV) causes severe respiratory disease with ∼43% mortality. There is no licensed vaccine or antiviral for MERS. Here we identified seven human neutralizing Abs (nAbs) against MERS-CoV. These nAbs bind to three epitope groups in the viral Spike protein–receptor interface, blocking virus attachment. Five residues in the viral receptor-binding domain critical for neutralization escape were identified. Further study indicated that four of five mutations not only confer neutralization resistance but also impair receptor binding and viral fitness. This panel of nAbs offers the possibility of developing human mAb-based immunotherapy. The newly emerging Middle East Respiratory Syndrome coronavirus (MERS-CoV) causes a Severe Acute Respiratory Syndrome-like disease with ∼43% mortality. Given the recent detection of virus in dromedary camels, zoonotic transfer of MERS-CoV to humans is suspected. In addition, little is known about the role of human neutralizing Ab (nAb) pressure as a driving force in MERS-CoV adaptive evolution. Here, we used a well-characterized nonimmune human Ab-phage library and a panning strategy with proteoliposomes and cells to identify seven human nAbs against the receptor-binding domain (RBD) of the MERS-CoV Spike protein. These nAbs bind to three different epitopes in the RBD and human dipeptidyl peptidase 4 (hDPP4) interface with subnanomolar/nanomolar binding affinities and block the binding of MERS-CoV Spike protein with its hDPP4 receptor. Escape mutant assays identified five amino acid residues that are critical for neutralization escape. Despite the close proximity of the three epitopes on the RBD interface, escape from one epitope did not have a major impact on neutralization with Abs directed to a different epitope. Importantly, the majority of escape mutations had negative impacts on hDPP4 receptor binding and viral fitness. To our knowledge, these results provide the first report on human nAbs against MERS-CoV that may contribute to MERS-CoV clearance and evolution. Moreover, in the absence of a licensed vaccine or antiviral for MERS, this panel of nAbs offers the possibility of developing human mAb-based immunotherapy, especially for health-care workers.
Elaborative-interrogation and prior-knowledge effects on learning of facts

Canadian and West German adults were presented facts about Canadian provinces and West German states (at the time of the study, West Germany was a separate nation of what is now the Federal Republic of Germany). Participants in the elaborative-interrogation condition rationalized why each fact was sensible. Reading-to-understand participants read the facts with the goal of comprehending each one. After presentation of all facts, subjects were asked to match provinces and states to facts associated with them. These performances were compared with matching in a no-exposure-control condition. Prior knowledge had a striking effect on learning in both the elaborative-interrogationand reading-to-understand conditions
Detecting seeded motifs in DNA sequences

The problem of detecting DNA motifs with functional relevance in real biological sequences is difficult due to a number of biological, statistical and computational issues and also because of the lack of knowledge about the structure of searched patterns. Many algorithms are implemented in fully automated processes, which are often based upon a guess of input parameters from the user at the very first step. In this paper, we present a novel method for the detection of seeded DNA motifs, composed by regions with a different extent of variability. The method is based on a multi-step approach, which was implemented in a motif searching web tool (MOST). Overrepresented exact patterns are extracted from input sequences and clustered to produce motifs core regions, which are then extended and scored to generate seeded motifs. The combination of automated pattern discovery algorithms and different display tools for the evaluation and selection of results at several analysis steps can potentially lead to much more meaningful results than complete automation can produce. Experimental results on different yeast and human real datasets proved the methodology to be a promising solution for finding seeded motifs. MOST web tool is freely available at .