Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-Translational Regulation of Oct4 Transcriptional Activity

Oct4 is a key component of the molecular circuitry which regulates embryonic stem cell proliferation and differentiation. It is essential for maintenance of undifferentiated, pluripotent cell populations, and accomplishes these tasks by binding DNA in multiple heterodimer and homodimer configurations. Very little is known about how formation of these complexes is regulated, or the mechanisms through which Oct4 proteins respond to complex extracellular stimuli which regulate pluripotency. Here, we provide evidence for a phosphorylation-based mechanism which regulates specific Oct4 homodimer conformations. Point mutations of a putative phosphorylation site can specifically abrogate transcriptional activity of a specific homodimer assembly, with little effect on other configurations. Moreover, we performed bioinformatic predictions to identify a subset of Oct4 target genes which may be regulated by this specific assembly, and show that altering Oct4 protein levels affects transcription of Oct4 target genes which are regulated by this assembly but not others. Finally, we identified several signaling pathways which may mediate this phosphorylation and act in combination to regulate Oct4 transcriptional activity and protein stability. These results provide a mechanism for rapid and reversible alteration of Oct4 transactivation potential in response to extracellular signals.
Low cost MAV platform AR-drone in experimental verifications of methods for vision based autonomous navigation

Several navigation tasks utilizing a low-cost Micro Aerial Vehicle (MAV) platform AR-drone are presented in this paper to show how it can be used in an experimental verification of scientific theories and developed methodologies. An important part of this paper is an attached video showing a set of such experiments. The presented methods rely on visual navigation and localization using on-board cameras of the AR-drone employed in the control feedback. The aim of this paper is to demonstrate flight performance of this platform in real world scenarios of mobile robotics.
Stories of transformation: using personal narrative to explore transformative experience among undergraduate peer mentors

Abstract While past researchers suggest undergraduate peer mentors (PMs) benefit from mentoring their peers, this experience is rarely associated with transformative learning. Using narrative analysis of authentic mentoring stories, we explored how particular types of mentoring experiences contribute to transformative learning for PMs of first-year university students. In this study, transformation was more likely when PMs engaged in meaningful routines and everyday practices; exercised purposeful “pretending” in unfamiliar aspects of their role; embraced challenge and surprise; regularly reflected on experiences; and were mentored by supportive faculty and staff. Findings have implications for PM selection and training, as well as program design.
Actively mode-locked 1.5-μm 10-GHz picosecond fiber laser using a monolithic semiconductor optical amplifier/electroabsorption modulator

In this letter, we demonstrate a novel 10-GHz actively modelocked polarization-maintaining fiber ring laser that utilizes a single device for gain, loss modulation, optical isolation, and repetition rate adjustment. This monolithic device incorporates a semiconductor optical amplifier with an electroabsorption modulator and provides net gain of 2.1 dB. The repetition rate of the 1.5-/spl mu/m picosecond pulsetrains can be tuned by 2 ppm through perturbation of the electroabsorption modulator reverse bias.
Collaborative Filtering Recommendation Algorithm Based on Cloud Model Clustering of Multi-indicators Item Evaluation

Collaborative filtering recommendation algorithm is a personalized recommendation algorithm that is used widely in e-commerce recommendation system. In this paper, a collaborative filtering recomendation algorithm based on cloud model clustering of multi-indicators item evaluation is proposed. In the algorithm, the item evaluation is the object, time weighted function is introduced to item evaluation, soft culsters item based on cloud model and gets the recommended items. The algorithm solves problems of data updating and history validity of evaluation in the collaborative filtering algorithm. Soft cluster item based on cloud model is achieved to avoid the defects bringed by hard division.
Bulk Biased RF Energy Harvesting Dedicated to 900MHz/2.4GHz ISM Bands

The Radiofrequency (RF) energy harvesting is a widespread technique to extend the lifetime of devices in low power applications such as Wireless Sensor Networks (WSNs). Among the key building blocks featuring the RF harvester, the rectifier converts the incident AC signal into a DC output voltage. This paper presents the comparison between a multi-stage traditional CMOS voltage multiplier and a multi-stage voltage multiplier using bulk biasing to overcome the threshold voltage drop. The two rectifiers operate at 900MHz and 2.4GHz ISM bands and are prototyped using a standard CMOS 130nm process. The bulk-biased rectifier achieves a significant increase in power efficiency and low voltage-drop. Considering a case of study for supplying a load of 3.6 µW, the overall power efficiency reaches 48%, which is an improvement of 17% compared with the traditional circuit.
Energy efficient distributed connected dominating sets construction in wireless sensor networks

One important characteristic of wireless sensor networks is energy stringency. Constructing a connected dominating set (CDS) has been widely used as a topology control strategy to reduce the network communication overhead. In the paper, a novel energy efficient distributed connected dominating set algorithm based on coordinated reconstruction mechanism is presented to further prolong the network lifetime and balance energy consumption. The algorithm is with O(n) time complexity and O(n) message complexity. The simulation results show that our algorithm outperforms several existing algorithms in terms of network lifetime and CDS performance.
geomorph: an r package for the collection and analysis of geometric morphometric shape data

Many ecological and evolutionary studies seek to explain patterns of shape variation and its covariation with other variables. Geometric morphometrics is often used for this purpose, where a set of shape variables are obtained from landmark coordinates following a Procrustes superimposition. We introduce geomorph: a software package for performing geometric morphometric shape analysis in the r statistical computing environment. Geomorph provides routines for all stages of landmark‐based geometric morphometric analyses in two and three‐dimensions. It is an open source package to read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform statistical analyses of shape variation and covariation, and to provide graphical depictions of shapes and patterns of shape variation. An important contribution of geomorph is the ability to perform Procrustes superimposition on landmark points, as well as semilandmarks from curves and surfaces. A wide range of statistical methods germane to testing ecological and evolutionary hypotheses of shape variation are provided. These include standard multivariate methods such as principal components analysis, and approaches for multivariate regression and group comparison. Methods for more specialized analyses, such as for assessing shape allometry, comparing shape trajectories, examining morphological integration, and for assessing phylogenetic signal, are also included. Several functions are provided to graphically visualize results, including routines for examining variation in shape space, visualizing allometric trajectories, comparing specific shapes to one another and for plotting phylogenetic changes in morphospace. Finally, geomorph participates to make available advanced geometric morphometric analyses through the r statistical computing platform.
Reduction of Campylobacter jejuni in Broiler Chicken by Successive Application of Group II and Group III Phages

Background Bacteriophage treatment is a promising tool to reduce Campylobacter in chickens. Several studies have been published where group II or group III phages were successfully applied. However, these two groups of phages are different regarding their host ranges and host cell receptors. Therefore, a concerted activity of group II and group III phages might enhance the efficacy of a treatment and decrease the number of resistant bacteria. Results In this study we have compared the lytic properties of some group II and group III phages and analysed the suitability of various phages for a reduction of C. jejuni in broiler chickens. We show that group II and group III phages exhibit different kinetics of infection. Two group III and one group II phage were selected for animal experiments and administered in different combinations to three groups of chickens, each containing ten birds. While group III phage CP14 alone reduced Campylobacter counts by more than 1 log10 unit, the concomitant administration of a second group III phage (CP81) did not yield any reduction, probably due to the development of resistance induced by this phage. One group of chickens received phage CP14 and, 24 hours later, group II phage CP68. In this group of animals, Campylobacter counts were reduced by more than 3 log10 units. Conclusion The experiments illustrated that Campylobacter phage cocktails have to be carefully composed to achieve the best results.
Breast Ultrasound Images Enhancement Using Fuzzy Logic

This paper presents an enhancement algorithm of the breast ultrasound image based on fuzzy logic. In order to fulfill the task of enhancement, we normalize the images and fuzzify the normalized images. Then we extract the edge and textural information in fuzzy domain and increase the contrast ratio measuring the degree of enhancement on the exchange of those ratios of the entire and partial information of image, and finally transform the enhanced ultrasound images back to the gray-scale domain using the defuzzification operation. Tested on a variety of ultrasound images, it is confirmed by the experimental results that the algorithm has better performance in enhancing images of the breast diseased parts.
The Catlin Multitype and Biholomorphic Equivalence of Models

The paper introduces an alternative approach to a fundamental C-R invariant-the Catlin multitype. It is applied to a general smooth hypersurface in C^n+1, not necessarily pseudoconvex. Using this approach, we prove biholomorphic equivalence of models and give an explicit description of biholomorphisms between different models. A constructive finite algorithm for computing the multitype is described. The results can be viewed as providing a necessary step in understanding local biholomorphic equivalence of Levi degenerate hypersurfaces in C^n+1.
Complementary Versus Competitive Framing Effects in the Context of Pro-Environmental Attitudes and Behaviors

This study examined the effects of complementary and competitive framing environments on people’s support for and attitudes toward pro-environmental behaviors (PEBs) and green energy technologies (GETs). Results suggest that frames have different effects on attitudes and policy support. Relative to the control group, complementary anti-climate action frames lowered attitudes toward PEBs and GETs. Competitive frames led to attitudes toward GETs that were significantly different from the complementary pro- and anti-frame conditions. For policy support, significant differences were found between the complementary pro- and anti-frames, and between the competitive and complementary pro-climate action frames for PEBs.
Database Cross Matching: A Novel Source of Fictitious Forensic Cases

Due to privacy concern and data protection laws, it is very difficult to obtain real forensic data for forensic face recognition research. In this paper, we introduce the concept of Database Cross Matching (DCM) as a novel source of fictitious but challenging forensic cases. DCM refers to the task of finding the subjects that are common in two different data sets. For most pairs of independent data sets, there will be no common subjects. However, for some data sets captured at the same institution, but independently and at different times, there is a high probability of finding some common subjects. We demonstrate the feasibility of DCM using the PIE and MultiPIE data set that were captured at the same institution in 2000 and 2004 respectively. We denote the task of finding the subjects that are common in PIE and MultiPIE data as PIE $\cap$ MultiPIE problem. Evaluation of the five face recognition systems applied to the PIE $\cap$ MultiPIE problem show that DCM can indeed create very challenging forensic problems.
Features for Killer Apps from a Semantic Web Perspective

There are certain features that that distinguish killer apps from other ordinary applications. This chapter examines those features in the context of the semantic web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing semantic web applications. Killer apps are highly tranformative technologies that create new e-commerce venues and widespread patterns of behaviour. Information technology, generally, and the Web, in particular, have benefited from killer apps to create new networks of users and increase its value. The semantic web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. The authors hope that this chapter will help to highlight some of the common ingredients of killer apps in e-commerce, and discuss how such applications might emerge in the semantic web.
Experiences of 5th Grade Students Participating in Active Gaming-Assisted Physical Education Lessons

The aim of present study is to explore the experiences of 5 th grade students, who participated in physical education courses structured based on the active gaming program. The qualitative case study model was employed in this study. Twelve 5 th grade students attending the physical education lessons were involved in present study. The physical education lessons were taught by using “SMART Trainer” system having 3 wall units for 12 weeks. The data were collected using semi-structured focus group discussions, observation notes, rubric, and video records. The content analysis method was used in analyzing the data. The findings were gathered under two categories, two main themes, and four sub-themes. In first category, the previous experiences of students regarding the physical education lessons are to play same games, to watch movies or to take other lessons when they were in the classroom, and to play traditional games or to be left free when they were outside. The fun, the skill-difficulty level, the decrease in awareness of time, the visual-auditory stimulants and the teacher support, which are reflected to the physical education lessons under the motivation theme, are among the important experiences playing role in motivation of students. In physical competence and confidence dimension, the fundamental movement skills assessments made by practitioners as their main function indicate that the majority of students are at adequate levels, whereas it was determined that the self-confidence from the physical aspect developed in parallel with the development of fundamental movement abilities that teachers perceive from their students.
Mutational analysis of a Dcp2-binding element reveals general enhancement of decapping by 5′-end stem-loop structures

mRNA decapping is a critical step in the control of mRNA stability and gene expression and is carried out by the Dcp2 protein. Dcp2 is an RNA-binding protein that must bind the RNA in order to recognize the cap for hydrolysis. We previously demonstrated that a 60 nucleotide (nt) element at the 5′ end of the mRNA encoding Rrp41 is preferentially bound and decapped by Dcp2. Here, we demonstrate that enhanced decapping of this element is dependent on the structural integrity of its first 33 nt and not its primary sequence. The structure consists of a stem-loop positioned <10 nt from the 5′ end of the mRNA. The generality of a stem-loop structure in enhanced Dcp2-mediated decapping was underscored by the identification of additional potential Dcp2 substrate mRNAs by a global analysis of human mRNAs containing a similar predicted stem-loop structure at their respective 5′ end. These studies suggest a general role for 5′ stem-loops in enhancing decapping activity and the utilization of this structure as a predictive tool for Dcp2 target substrates. These studies also demonstrate that Dcp2 alone in the absence of additional proteins can preferentially associate with and modulate mRNA decapping.
Upper bounds on the average probability of undetected error for the ensembles of both product and concatenated codes

By utilizing the method to get the upper bound on the average probability of undetected error for all binary linear systematic block codes, we newly get each upper bound on the average probability of undetected error for the ensembles of all binary product codes and all binary expansions of concatenated codes which include the constructive algebraic codes satisfying Shannon's channel coding theorem or being the asymptotically good. By comparing those upper bounds, we can clearly show that the average capability of concatenation structure is stronger than that of product codes, although the bound for concatenated codes is below that for the ensemble of all binary linear systematic block codes.
An Integrated Learning Approach to Teaching an Undergraduate Information Systems Course

This paper describes the redesign and implementation of an introductory Information Systems class. The redesign was guided by principles drawn from the experiential and active learning literature. Central to the redesign are two simulated companies: petGRO, a fictional ERP-enabled pet food and accessories e-tailer, and beans4all, a technology consulting company of which all registered students are employees. Students work in solution crews throughout the semester to solve a set of technology-related challenges that their client, petGRO, is facing. Initial student response to the redesign has been mixed. Survey responses indicate that students have an increased interest in IS after taking the course. There was a significant increase in students’ perception of the usefulness of the knowledge gained from the course in subsequent courses. However, this result is countered by a decrease in students’ perception of whether the course led to an improvement in their academic skills. Open-ended comments reveal the polarizing nature of the redesign but with more positive than negative comments.
The International Congress for global Science and Technology Table of Contents Forward and Inverse Fuzzy Magnetorheological Damper Models for Control Purposes

The magnetorheological (MR) damper behavior is described by a set of nonlinear differential equations, which are unsuitable in control applications. This paper illustrates the effectiveness of adaptive neuro-fuzzy inference system (ANFIS) in building both forward and inverse MR damper models. The forward model is obtained by training noisy data generated from simulation of the nonlinear differential equations with low pass filter. Input selection method is applied to find the most appropriate inputs to train the inverse model. Finally, the numerical simulation proves that the two models established based on ANFIS can track the MR damper force for different amplitude and frequency. In addition, we can predict the voltage required to be applied to produce a known force determined from control law with high performance.
Edge-preserving photometric stereo via depth fusion

We present a sensor fusion scheme that combines active stereo with photometric stereo. Aiming at capturing full-frame depth for dynamic scenes at a minimum of three lighting conditions, we formulate an iterative optimization scheme that (1) adaptively adjusts the contribution from photometric stereo so that discontinuity can be preserved; (2) detects shadow areas by checking the visibility of the estimated point with respect to the light source, instead of using image-based heuristics; and (3) behaves well for ill-conditioned pixels that are under shadow, which are inevitable in almost any scene. Furthermore, we decompose our non-linear cost function into subproblems that can be optimized efficiently using linear techniques. Experiments show significantly improved results over the previous state-of-the-art in sensor fusion.
Being online: a critical view of identity and subjectivity in new virtual learning spaces

Being a learner, becoming a learner and belonging to learning communities are important themes for both educators and educational researchers. This special issue explores these issues, theorising and exploring how identities are developed online, and asks what the educational impact is. Here, we set the scene for this work, locating it in terms of wider educational concerns of identity, inclusivity and change.
Activity B κ PC-3 Cells Is Associated with Increased Nuclear Factor-Differentiation of Androgen-Independent Prostate Cancer

Recently, we have reported that inosine 5V-monophosphate dehydrogenase inhibitors, such as mycophenolic acid (MPA), induce the differentiation of PC-3 cells, which are derived from a human androgen-independent prostate cancer, into cells with a phenotype resembling maturing prostate secretory cells. Here, we describe such differentiation induced by the histone deacetylase inhibitor tributyrin. The maturation was defined by cytoplasmic vacuole production and induction of CD10, CD46, CD55, GRP78, keratin 17, and zinc-A-2-glycoprotein. To identify additional genes associated with tributyrininduced PC-3 cell differentiation and to gain some insight into the mechanism that underlies this differentiation, we have, by means of microarray analyses, compared tributyrininduced gene expression patterns with those of MPA, which initiates PC-3 cell differentiation by a dissimilar mode of action. We suggested that genes induced by both tributyrin and MPA would be most likely associated with differentiation rather than with the unique action of each particular inducer. Our results indicated that tributyrin or MPA induced the expression of a large number of common genes, including genes known or assumed to be NF-KB dependent. The NF-KB dependency of a group of these genes, which included the PC-3 cell differentiation marker keratin 17, was confirmed by using two common NF-KB activation inhibitors, Bay11-082 and TMB-8, and p65 subunit of NF-KB complex specific small interfering RNA. Taken together, our results implicate both NF-KB–dependent and NF-KB–independent genes in the processes leading to PC-3 cell differentiation induced by tributyrin and MPA. (Cancer Res 2005; 65(24): 11588-96)
Throughput and fairness of multiple TCP connections in wireless networks

TCP suffers from poor throughput performance in wireless networks. Furthermore, when multiple TCP connections compete at the base station, link errors and congestion lead to serious unfairness among the connections. Although the issue of TCP performance in wireless networks has attracted significant attention, most reports focus only on TCP throughput and assume that there is only a single connection in a congestion-free network. This paper studies the throughput and fairness of popular improvement mechanisms (the Snoop [8] and ELN [5]) and TCP variants with multiple TCP connections. Simulation results show that the improvement mechanisms under investigation are effective to improve TCP throughput in a wireless network. However, they cannot provide fairness among multiple TCP connections. From the studies presented, it is concluded that mechanisms to enhance TCP fairness are needed in wireless networks