Miracle-dz/UniFAR-FTUs huggingface dataset:
Correction: Bicoid gradient formation and function in the Drosophila pre-syncytial blastoderm

Bicoid (Bcd) protein distributes in a concentration gradient that organizes the anterior/ posterior axis of the Drosophila embryo. It has been understood that bcd RNA is sequestered at the anterior pole during oogenesis, is not translated until fertilization, and produces a protein gradient that functions in the syncytial blastoderm after 9–10 nuclear divisions. However, technical issues limited the sensitivity of analysis of pre-syncytial blastoderm embryos and precluded studies of oocytes after stage 13. We developed methods to analyze stage 14 oocytes and pre-syncytial blastoderm embryos, and found that stage 14 oocytes make Bcd protein, that bcd RNA and Bcd protein distribute in matching concentration gradients in the interior of nuclear cycle 2–6 embryos, and that Bcd regulation of target gene expression is apparent at nuclear cycle 7, two cycles prior to syncytial blastoderm. We discuss the implications for the generation and function of the Bcd gradient. DOI: 10.7554/eLife.13222. 001
Multilevel Depth and Image Fusion for Human Activity Detection

Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.
Expulsion of micronuclei containing amplified genes contributes to a decrease in double minute chromosomes from malignant tumor cells

Double minute chromosomes (DMs) are a hallmark of gene amplification. The relationship between the formation of DMs and the amplification of DM‐carried genes remains to be clarified. The human colorectal cancer cell line NCI‐H716 and human malignant primitive neuroectodermal tumor cell line SK‐PN‐DW are known to contain many DMs. To examine the amplification of DM‐carried genes in tumor cells, we performed Affymetrix SNP Array 6.0 analyses and verified the regions of amplification in NCI‐H716 and SK‐PN‐DW tumor cells. We identified the amplification regions and the DM‐carried genes that were amplified and overexpressed in tumor cells. Using RNA interference, we downregulated seven DM‐carried genes, (NDUFB9, MTSS1, NSMCE2, TRIB1, FAM84B, MYC and FGFR2) individually and then investigated the formation of DMs, the amplification of the DM‐carried genes, DNA damage and the physiological function of these genes. We found that suppressing the expression of DM‐carried genes led to a decrease in the number of DMs and reduced the amplification of the DM‐carried genes through the micronuclei expulsion of DMs from the tumor cells. We further detected an increase in the number of γH2AX foci in the knockdown cells, which provides a strong link between DNA damage and the loss of DMs. In addition, the loss of DMs and the reduced amplification and expression of the DM‐carried genes resulted in a decrease in cell proliferation and invasion ability.
Developing Social Capital in Networked Governance Initiatives: A lock-step approach

The International Institute for Sustainable Development (IISD) contributes to sustainable development by advancing policy recommendations on international trade and investment, economic policy, climate change and energy, and management of natural and social capital, as well as the enabling role of communication technologies in these areas. We report on international negotiations and disseminate knowledge gained through collaborative projects, resulting in more rigorous research, capacity building in developing countries, better networks spanning the North and the South, and better global connections among researchers, practitioners, citizens and policy-makers. IISD's vision is better living for all—sustainably; its mission is to champion innovation, enabling societies to live sustainably. IISD is registered as a charitable organization in Canada and has 501(c)(3) status in the United States. IISD receives core operating support from the Government of Canada, provided through the Canadian International Development Agency (CIDA), the International Development Research Centre (IDRC), and from the Province of Manitoba. The Institute receives project funding from numerous governments inside and outside Canada, United Nations agencies, foundations and the private sector. Acknowledgements: IISD's interest in networks goes back to the early 1990s. Two early milestones are worth specific mention. First is the report, Connecting with the World: Priorities for Canadian Internationalism in the 21st Century, delivered by a task force chaired by Maurice Strong (1996). This report focused on the need to accelerate the creation of substantive knowledge, and the need for knowledge-based networks to multiply, disseminate and expand knowledge. The other milestone is a study by Howard Clark (1998) who analyzed Canadian experiences with formal knowledge networks. It is entitled Formal Knowledge Networks: A Study of Canadian Experience.
Experiential approach to creation and use of assets in designing the family of software intensive systems

The paper presents an experiential approach to modeling of assets in designing the family of Software Intensive Systems (SIS). The reuse of any asset is being implemented as a typical work of a designer in accordance with the definite technique that is previously programmed. The offered approach is coordinated with simplifying the complexity on the base of interactions of designers with the accessible experience the kernel of which consists of models of assets included into Experience Base. The simplifying is being achieved by the use of the specialized pseudo-code language in programming of assets for their reuse.
Correlates of Brain Injuries in Women Subjected to Intimate Partner Violence: Identifying the Dangers and Raising Awareness

ABSTRACT Awareness of the highly detrimental and long-term sequelae of brain injuries, and in particular repetitive mild traumatic brain injuries (mTBIs/concussions), has been rapidly growing. Specifically, there has been significant focus on repetitive mTBIs in male athletes and military personnel. Unfortunately, what is likely the largest group of repetitive mTBI sufferers, namely women who experience intimate partner violence (IPV), has received scant attention. Women experiencing IPV sustain both repetitive mTBIs at a high rate and also strangulation-related anoxic/hypoxic brain injuries. Due to biological, psychosocial and trauma-related differences between these women and the (mostly) men who have been studied to date, we cannot generalize what is learned from these studies to women suffering from IPV-related TBIs. Here we summarize some research aimed at understanding the occurrence and sequelae of IPV-related TBIs among various samples (i.e., women in shelters or primary care, from the community, veterans). These data show that IPV-related TBIs are highly prevalent, and associated with a range of negative cognitive and psychological outcomes as well as structural and functional brain connectivity. These associations could not be accounted for by potential confounds (e.g., abuse severity, psychiatric symptoms), making it clear that these negative health outcomes were not merely artifacts of being in an abusive relationship. We highlight gaps in research and provide recommendations for clinical practice. We present ideas for future research to elucidate the mechanisms underlying the associations noted above, in hopes of providing new insights into the links between TBIs and health risks in women who have experienced IPV.
Association between Sarcopenic Obesity and Metabolic Syndrome in Postmenopausal Women: A Cross-sectional Study Based on the Korean National Health and Nutritional Examination Surveys from 2008 to 2011

Background Menopause contributes to an increase in visceral fat mass and a decrease in muscle protein synthesis. Therefore, we performed this study to examine their relationship how effect the changes of body composition as obesity and sarcopenia on metabolic syndrome (MS) as a predictor of cardiovascular disease in postmenopausal women. Methods Using data from the Korean National Health and Nutrition Examination Survey (KNHANES) from 2008 to 2011, we estimated that 4,183 postmenopausal women underwent dual energy X-ray absorptiometry scans. Sarcopenia was defined as an appendicular skeletal muscle mass divided by body weight that was less than 1 standard deviation below the sex specific mean for the young reference group. After classification into four groups, the results were adjusted with menopausal age and hormonal treatment. The relationship between sarcopenic obesity (SO) and MS in postmenopausal women was analyzed by logistic regression analysis in a complex sampling. Results In an unadjusted model, the odds ratio (OR) of MS for sarcopenia was 1.94 (95% confidence interval [CI], 1.52-2.49); the obesity group had an OR of 4.55 (95% CI, 3.63-5.71); and distinctly, the SO group had an OR of 6.26 (95% CI, 5.10-7.70). Even though there was controlling for variable adjustment, no definite difference was seen in the results. Conclusions Sarcopenia and obesity were associated with MS independent of other metabolic impairment risk factors in both early menopausal and postmenopausal women. The results showed that, in particular, the prevalence of MS has increased more in postmenopausal women compared with previous research.
Super-resolution for remote sensing images using content adaptive detail enhanced self examples

This paper proposes a single image super-resolution (SR) technique for remote sensing images using content adaptive detail enhanced self examples. This method exploits large number of similar patches exists in the remote sensing images by using self examples. A high frequency layer is extracted from the input low resolution image and details of the high frequency layer are enhanced using content adaptive method to form the self examples. The root mean square difference of feature vectors extracted from self examples is given to a Gaussian function to find the weight. Weighted average of pixel computed using weights predicts the pixels of the high resolution high frequency layer. The reconstructed high resolution high frequency layer is combined with the linearly interpolated high resolution image to form the final high resolution image. Qualitative and Quantitative experimental analysis show that the proposed method gives better results than other existing methods. The results have better visual quality since image details are well preserved.
The Moderating Role of Innovativeness on the Relationship between Entrepreneurship Educations And Student Entrepreneurial Intention

This study examined the moderating role of innovativeness on the relationship between entrepreneurship education and students' entrepreneurial intention among FUD final year students as at 2017/2018 academic session. The study used a cross-sectional research design with a quantitative questionnaire approach to collect the data. To validate the model, data from 282 final year students were analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM). Overall, the survey discovered that both entrepreneurship education and innovativeness are significantly and positively connected to entrepreneurial intention. This report also discovered that innovativeness play a part in moderating the entrepreneurship education and entrepreneurial intention relationship. The study used Human Capital Theory HCT as a theoretical basis of the subject. This survey served as one of the pioneering study with regard to HCT in a testing relationship of this nature. This study recommended that other researchers should employ this hypothesis with other antecedent of entrepreneurial intention for further proof. As a repercussion to policy, the government ought to guarantee not only inspiring students with entrepreneurship education, but also the robust spirit of innovativeness among students as it delivers a direct effect as well as strong interaction with entrepreneurship education in influencing students' entrepreneurial intention.
A Procedure for Failure Prognostic in Dynamic Systems

Abstract In maintenance field, many developments exist to support the prognostic activity. However, the implementation of an adequate and efficient prognostic tool can be a non trivial task as it is difficult to provide effective models of dynamic systems including the inherent uncertainty of prognostic. In this context, the purpose of the paper is to propose a procedure to generate a prognostic model. The work is based on the integration of bond graph tool and Dynamic Bayesian Networks. The first one provides a dynamic model of the system, and the second ones, thanks to their inference capability, enable to take into account uncertainty and are well suitable to perform diagnosis and prognostic. The proposed procedure is illustrated on an hydromechanical system.
Evolution of the Correlation between Expression Divergence and Protein Divergence in Mammals

Divergence of protein sequences and gene expression patterns are two fundamental mechanisms that generate organismal diversity. Here, we have used genome and transcriptome data from eight mammals and one bird to study the positive correlation of these two processes throughout mammalian evolution. We demonstrate that the correlation is stable over time and most pronounced in neural tissues, which indicates that it is the result of strong negative selection. The correlation is not driven by genes with specific functions and may instead best be viewed as an evolutionary default state, which can nevertheless be evaded by certain gene types. In particular, genes with developmental and neural functions are skewed toward changes in gene expression, consistent with selection against pleiotropic effects associated with changes in protein sequences. Surprisingly, we find that the correlation between expression divergence and protein divergence is not explained by between-gene variation in expression level, tissue specificity, protein connectivity, or other investigated gene characteristics, suggesting that it arises independently of these gene traits. The selective constraints on protein sequences and gene expression patterns also fluctuate in a coordinate manner across phylogenetic branches: We find that gene-specific changes in the rate of protein evolution in a specific mammalian lineage tend to be accompanied by similar changes in the rate of expression evolution. Taken together, our findings highlight many new aspects of the correlation between protein divergence and expression divergence, and attest to its role as a fundamental property of mammalian genome evolution.
Development of a tele-guidance system with fuzzy-based secondary controller

Dealing with the uncertainties of Internet characteristics is an important issue that needs being taken into account in developing Internet-based real-time systems. In this paper, we present our approach in applying fuzzy logic to develop back-up mechanisms for an Internet-based mobile robot to deal with unwanted network problems such as long delays or network interruptions. A tele-guidance application involving the remote control of a mobile robot via the Internet is set up as the context to verify the effectiveness and applicability of the proposed approach.
Development of an Indoor Location Based Service Test Bed and Geographic Information System with a Wireless Sensor Network

In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.
Sociodemographic Factors and Prejudice toward HIV and Hepatitis B/C Status in a Working-Age Population: Results from a National, Cross-Sectional Study in Japan

Background In many countries, HIV, hepatitis B virus (HBV), and hepatitis C virus (HCV) infected individuals may face discrimination and mistreatment from coworkers. Effective interventions to reduce workplace discrimination are therefore needed to protect these vulnerable populations. The current study investigated potential associations between sociodemographic factors and prejudice toward HIV and HBV/HCV infected colleagues within a Japanese working population. Methods An online anonymous, nationwide internet survey was administered to a cross-section of approximately 3,000 individuals in Japan. The survey comprised 14 questions focusing on demographics (five items), basic HIV or HBV/HCV knowledge (eight items), and potential prejudice toward HIV or HBV/HCV infected colleagues (one item). The sociodemographic characteristics evaluated were sex, age, educational level, employment status, and individual income; with multiple logistic regression used for the analysis. Results In total, 3,055 individuals were recruited for the HIV related survey and 3,129 for the HBV/HCV related survey. Older age was significantly and positively associated with prejudice toward HIV infected colleagues (p<0.01) and negatively associated with prejudice toward HBV/HCV infected colleagues (p<0.01). Statistically significant associations were not observed between other sociodemographic characteristics and potential prejudice toward HIV and HBV/HCV infected coworkers. Conclusion Overall, this study suggests that age may be associated with prejudice toward HIV and HBV/HCV infected colleagues among the working age population of Japan. As such, policy makers should consider the age of participants when formulating efforts to reduce prejudice toward HIV and HBV/HCV infected workers.
Analyzing the Distribution of a Large-Scale Character Pattern Set Using Relative Neighborhood Graph

The goal of this research is to understand the true distribution of character patterns. Advances in computer technology for mass storage and digital processing have paved way to process a massive dataset for various pattern recognition problems. If we can represent and analyze the distribution of a large-scale character pattern set directly and understand its relationships deeply, it should be helpful for improving character recognizer. For this purpose, we propose a network analysis method to represent the distribution of patterns using a relative neighborhood graph and its clustered version. In this paper, the properties and validity of the proposed method are confirmed on 410,564 machine-printed digit patterns and 622,660 handwritten digit patterns which were manually ground-truthed and resized to 16 times 16 pixels. Our network analysis method represents the distribution of the patterns without any assumption, approximation or loss.
Aligning coordinate frames in multi-robot systems with relative sensing information

In this paper, we present both centralized and distributed algorithms for aligning coordinate frames in multi-robot systems based on inter-robot relative position measurements. Robot orientations are not measured, but are computed by our algorithms. Our algorithms are robust to measurement error and are useful in applications where a group of robots need to establish a common coordinate frame based on relative sensing information. The problem of establishing a common coordinate frame is formulated in a least squares error framework minimizing the total inconsistency of the measurements. We assume that robots that can sense each other can also communicate with each other. In this paper, our key contribution is a novel asynchronous distributed algorithm for multi-robot coordinate frame alignment that does not make any assumptions about the sensor noise model. After minimizing the least squares error (LSE) objective for coordinate frame alignment of two robots, we develop a novel algorithm that out-performs state-of-the-art centralized optimization algorithms for minimizing the LSE objective. Furthermore, we prove that for multi-robot systems (a) with redundant noiseless relative sensing information, we will achieve the globally optimal solution (this is non-trivial because the LSE objective is non-convex for our problem), (b) with noisy information but no redundant sensing (e.g. sensing graph has a tree topology), our algorithm will optimally minimize the LSE objective. We also present preliminary results of the real-world performance of our algorithm on TurtleBots equipped with Kinect sensors.