Miracle-dz/UniFAR-FTUs huggingface dataset:
Social-spam profile detection based on content classification and user behavior

Web-based social system enables new community-based opportunities for participants to engage, share and interact. The rapid growth of Facebook has triggered a dramatic increase in spam volume and sophistication. Spammers post their status or comment in Page to send spam content to their friends or other users in the network. In this paper, we consider the problem of detecting spam accounts on Facebook based on comment content and user social behavior. We will propose a hybrid approach using Maximum Entropy (Maxent) model for classifying user comments as either spam or non-spam. We carefully conducted an empirical evaluation for our model on a large collection of comments in Vietnamese Facebook Pages and achieved promising results with an average accuracy of more than 90%.
A cautionary tale: how to delete mouse haemopoietic stem cells with busulphan

In this study treating mice with the ‘correct’ dose of busulphan did not necessarily destroy all haematopoietic stem cells. In certain circumstances host stem cells survived undetected and subsequently resumed haemopoiesis. This may apply to the use of busulphan clinically. We found that the following conditions determined the deletion of mouse stem cells using busulphan: (1) graft size – grafting more than 106 marrow cells (∼0·3% of the animal's stem cells) concealed the survival of stem cells; (2) dose of busulphan – insufficient busulphan did not kill all host stem cells; (3) old or improperly stored busulphan failed to delete all host stem cells; furthermore (4) the survival of host stem cells should be assessed by typing many kinds of circulating cells; and (5) tests should be carried out to determine if busulphan has killed all host stem cells by typing circulating blood cells at appropriate intervals.
Measuring attitudes towards Christianity among 12‐ to 18‐year‐old pupils in Catholic schools

Summary The Francis scale of attitude towards Christianity Form ASC4B, developed originally for use among eight to 16‐year‐olds in non‐denominational schools was completed by 3114 pupils between the ages of 12 and 18 in Roman Catholic state maintained secondary schools. The results support the reliability and unidimensionality of the scale among this different population and extended age range. Norms are presented for pupils attending state maintained Catholic secondary schools, for boys and girls from each year group separately.
The Effect of Peer Victimization on Learning

ABSTRACT The present study looks at how family processes and the classroom norms influence students' employment of learning strategy in junior secondary schools in Hong Kong. It employed an ecological perspective to look at how family factors and classroom factors uniquely and combined to influence students. Nineteen secondary schools with 948 Secondary 2 students and their family members participated in the cross-sectional survey for the research. Findings of the study suggest that peer victimization norm in the classroom plays a moderating role in the association between socioeconomic background and students' use of achievement strategy in learning Chinese. The result of the research is suggested to have important implications for home-school relations in Hong Kong, as well as the restructuring of the school process to create a more supportive and nurturing environment for learning and teaching.
Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.
Population-Based Studies of Bullying in Young Children

markdownabstract__Abstract__ School bullying is defined as repeated and intentional aggression toward the peers who have difficulty to stop or counteract such harassment.1,2 Bullying and victimization have serious negative effects on health and functioning of children.3-5 Detecting and preventing bullying problems early in the schooling process is an opportunity to protect children from long-lasting adverse health consequences.6,7 A comprehensive understanding of school bullying, its prevalence and the associated with it risk factors form the basis of evidence-based prevention programs. Whereas the importance of early preventive efforts has been widely recognized8,9, studies of bullying among young elementary school children remain scarce, as most of research is usually carried out among adolescents. With the help of large, prospective, population- based studies of children from preschool age onwards, we can gain a better understanding of the risk factors associated with bullying. This thesis describes several population-based studies that address bullying involvement in early elementary school, with a specific focus on its assessment, prevalence and early-age predictors.
Costimulation and Autoimmune Diabetes in BB Rats

Costimulatory signals regulate T‐cell activation. To investigate the role of costimulation in autoimmunity and transplantation, we studied the BB rat model of type 1 diabetes. Diabetes‐prone BB (BBDP) rats spontaneously develop disease when 55–120 days of age. We observed that two anti‐CD28 monoclonal antibodies (mAb) with different functional activities completely prevented diabetes in BBDP rats. Anti‐CD154 mAb delayed diabetes, whereas treatment with CTLA4‐Ig or anti‐CD80 mAb accelerated disease. Anti‐CD86 or anti‐CD134L mAbs had no effect. Diabetes resistant BB (BBDR) rats are disease‐free, but >95% of them develop diabetes after treatment with polyinosinic‐polycytidylic acid and an mAb that depletes Treg cells. In the induced BBDR model, anti‐CD154 mAb delayed onset of diabetes, whereas CTLA4‐Ig, anti‐CD134L or either of the anti‐CD28 mAbs had little or no effect. In contrast, blockade of the CD134‐CD134L pathway was highly effective for preventing autoimmune recurrence against syngeneic islet grafts in diabetic BBDR hosts. Blockade of the CD40‐CD154 pathway was also effective, but less so. These data suggest that the effectiveness of costimulation blockade in the treatment of type 1 diabetes is dependent on both the costimulatory pathway targeted and the mechanism of induction, stage, intensity and duration of the pathogenic process.
Carbon Emission Control Policies within China’s Power Generation Sector

The paper examines the potential for emissions control policy using the example of the power generation sector in China. The analytical model is developed using a joint production function, where carbon emissions and electricity are jointly produced using capital and fossil fuel inputs. Abatement of emissions can be achieved by investment in two types of capital – production capital that improves the production efficiency, or abatement capital that removes the emissions. The analytical model shows that economic growth can be achieved while still keeping the emission stock at a stable level. The results are estimated using data from China's electricity generation sector. The results show that the level of the tax required to stabilize emissions depends greatly on the efficiency of abatement activities. As an illustration of this result, one finding shows that the required emission tax would be reduced greatly from 16 to 5 yuan per ton of emission when the abatement technology is improved from removing 10% to 30% of emissions flow.
Beyond Simple Classifications: Contemporary Information Systems Development Projects as Complex Adaptive Systems

Contemporary Information Systems Development (ISD) takes place in a dynamic environment and is generally acknowledged as a complex activity. We investigate whether complex adaptive systems (CAS) theory is relevant as a theoretical foundation for understanding ISD, and if so, what kind of conception can be achieved by utilizing the theory? We introduce key CAS concepts and describe an emergent method framework for understanding ISD. Extending existing research, our main contribution is twofold: We first show how CAS and CAS principles are advantageous for comprehending and organizing ISD in general, beyond any particular development approach chosen for the execution of a project such as agile development. Thereby, we contribute to a complexity theory of ISD. Second, we back up our argument with a coherent empirical account of contemporary ISD, and thus contribute with practical advice for ISD derived from this perspective to successfully cope with complexity in ISD in an adaptive manner.
What Is Diversity?

The term diversity seems to carry a wide array of definitions. These definitions can affect the ways teachers understand and employ the term as well as the ways in which they approach sociocultural differences in their classrooms. The current study included a survey of preservice teachers’ beliefs about various identities associated with terms such as diversity and multicultural in order to better understand what is meant by these terms. Each identity was explored within the context of the classroom, including efficacy for multicultural instruction, sense of responsibility for teaching about diverse people, and sense of advocacy for oppressed groups. The findings suggest preservice teachers hold a limited view of what constitutes diversity, which affects their senses of efficacy, responsibility, and advocacy as individuals and as teachers.
Optimized Motor Imagery Paradigm Based on Imagining Chinese Characters Writing Movement

Background: motor imagery (MI) is a mental representation of motor behavior. The MI-based brain computer interfaces (BCIs) can provide communication for the physically impaired. The performance of MI-based BCI mainly depends on the subject’s ability to self-modulate electroencephalogram signals. Proper training can help naive subjects learn to modulate brain activity proficiently. However, training subjects typically involve abstract motor tasks and are time-consuming. Methods: to improve the performance of naive subjects during motor imagery, a novel paradigm was presented that would guide naive subjects to modulate brain activity effectively. In this new paradigm, pictures of the left or right hand were used as cues for subjects to finish the motor imagery task. Fourteen healthy subjects (11 male, aged 22–25 years, and mean 23.6±1.16) participated in this study. The task was to imagine writing a Chinese character. Specifically, subjects could imagine hand movements corresponding to the sequence of writing strokes in the Chinese character. This paradigm was meant to find an effective and familiar action for most Chinese people, to provide them with a specific, extensively practiced task and help them modulate brain activity. Results: results showed that the writing task paradigm yielded significantly better performance than the traditional arrow paradigm (p < 0.001). Questionnaire replies indicated that most subjects thought that the new paradigm was easier. Conclusion: the proposed new motor imagery paradigm could guide subjects to help them modulate brain activity effectively. Results showed that there were significant improvements using new paradigm, both in classification accuracy and usability.
Investigating Rocks and Sand Addressing Multiple Learning Styles through an Inquiry-Based Approach

2, 3, 4 ® In early September, kindergarten teachers and parents noticed that children were very curious about rocks. Pockets and cubbies swelled with personal collections from the playground, the park, and other nearby outdoor places. Rocks and pebbles were exchanged like gifts, and crystals and fossils soon became classroom currency. As they played, the children began to invent and develop a descriptive rock vocabulary to more clearly differentiate and communicate obvious and subtle differences. There were the sparkly ones, the marking ones, the volcanic ones, the ones that look like metal, the fossils, and the crystals. Then there were the kind that came from the fairies and even the ones from the moon. Children asked each other questions based on their observations: How did you get that to be so sparkly? How do you think this rock was made? Where did you find that one? Thinking together in these ways helps children build deeper understandings and allows them to develop a scaffold on which to build more meaningful connections. By listening carefully to children as they ask questions and talk together, teachers can incorporate children’s questions and interests into an inquiry-based curriculum that supports various types of learners.
A BAX/BAK and Cyclophilin D-Independent Intrinsic Apoptosis Pathway

Most intrinsic death signals converge into the activation of pro-apoptotic BCL-2 family members BAX and BAK at the mitochondria, resulting in the release of cytochrome c and apoptosome activation. Chronic endoplasmic reticulum (ER) stress leads to apoptosis through the upregulation of a subset of pro-apoptotic BH3-only proteins, activating BAX and BAK at the mitochondria. Here we provide evidence indicating that the full resistance of BAX and BAK double deficient (DKO) cells to ER stress is reverted by stimulation in combination with mild serum withdrawal. Cell death under these conditions was characterized by the appearance of classical apoptosis markers, caspase-9 activation, release of cytochrome c, and was inhibited by knocking down caspase-9, but insensitive to BCL-XL overexpression. Similarly, the resistance of BIM and PUMA double deficient cells to ER stress was reverted by mild serum withdrawal. Surprisingly, BAX/BAK-independent cell death did not require Cyclophilin D (CypD) expression, an important regulator of the mitochondrial permeability transition pore. Our results suggest the existence of an alternative intrinsic apoptosis pathway emerging from a cross talk between the ER and the mitochondria.
Brief Communication: Discordant ability of the triglyceride to apolipoprotein B ratio to predict triglyceride-rich lipoprotein particle size in normal-weight and obese men

The atherogenicity of triglyceride-rich lipoproteins (TRLs) is dependent of their particle size as it determines their metabolic fate. Since TRL possess a single apolipoprotein B (Apo B) molecule per particle, the triglyceride (TG)/Apo B ratio has been used as a convenient method to estimate TRL size. The aim of this study was to validate this approach by correlating the serum TG/Apo B ratio, and the TRL particle size measured by dynamic light scattering (DLS). Twenty-four male volunteers (12 normal-weight and 12 obese individuals) received a high-fat meal. Preprandial (0 h) and postprandial (2 and 4 h) serum samples were collected after meal ingestion, and TRLs were isolated. Serum TG and Apo B levels were quantified, and the TG/Apo B ratio was plotted against TRL particle size measured by DLS for correlation. A strong association between TRL particle size and serum TG/Apo B ratio for normal-weight subjects (P ≤ 0.001) was observed but not for obese subjects (P = 0.6116). TG/Apo B ratio correlates with particle size in healthy normal-weight males but not in obese individuals. Whether this ratio is useful to estimate TRL size in females and in other dyslipidemic patients should be subject of future investigations.
PipeProbe: a mobile sensor droplet for mapping hidden pipeline

This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm.
Healing trabecular microfractures in the bodies of lumbar vertebrae.

Thepresence ofnodular aggregates ofwovenbone situated onporotic trabeculae hasbeendescribed in thepatella inchondromalacia patellae (Darracott andVernon-Roberts, 1971) andinthefemoral headin osteoarthrosis andrheumatoid arthritis (Todd, Freeman,andPirie, 1972). Thedistribution andmicrostructure ofthenodular aggregates indicate that they mayrepresent someformofnewboneformation or buttressing effect atsites oftrabecular stress (Darracott andVernon-Roberts, 1971)orcallus formation surrounding thesites oftrabecular fractures (Toddandothers, 1972). Thepresence offractures through trabeculae withsurrounding callus formed ofwovenbonehasalsobeendescribed in idiopathic aseptic necrosis ofthefemoral head(Lagier, 1971). Themicrostructure anddistribution ofthese trabecular lesions inthepatella andfemoral headhas stimulated ustosearch forsimilar lesions inthebodies oflumbar vertebrae, since diffuse orfocal osteoporosis isacommonfinding inthis region after the fifth decade, andsince itisalso clear that this region oftheskeleton isconstantly subjected tosevere mechanical stresses throughout life. Thepossibility thatsuchlesions could beconcerned inthegenesis ofbackpainwasalsoconsidered whenwestarted this study.
On Priming Security and Insecurity

It is exciting to see the remarkable advances made in our understanding of relationship cognition as the field matures. Mikulincer and Shaver (2007) offer an artic ulate and persuasive overview of their recent work on security-enhancing interventions, clearly documenting many positive effects of "security priming. " I find lit tle to argue with in this well-crafted piece, so I will focus my attention instead on some of the remaining questions the authors identify for future research. In particular, Mikulincer and Shaver point out that much research remains to be done to identify the precise mechanisms whereby security primes have their ef fects, and to work toward interventions that might be long lasting. I agree that these are critical questions. I believe that some answers to these questions, or at least some helpful clues, might actually be found by re visiting some of the earlier literature regarding the acti vation of security (and insecurity). I will examine some of these studies, shaping my comments around sev eral questions: What are some core elements of secu rity primes? Are the cognitive mechanisms of security largely rooted in associations? Can security-providing activation patterns be modified? When do security providing interventions work best and last longest?
Combinatorial Benders' Cuts for the Strip Packing Problem

We study the strip packing problem, in which a set of two-dimensional rectangular items has to be packed in a rectangular strip of fixed width and infinite height, with the aim of minimizing the height used. The problem is important because it models a large number of real-world applications, including cutting operations where stocks of materials such as paper or wood come in large rolls and have to be cut with minimum waste, scheduling problems in which tasks require a contiguous subset of identical resources, and container loading problems arising in the transportation of items that cannot be stacked one over the other.The strip packing problem has been attacked in the literature with several heuristic and exact algorithms, nevertheless, benchmark instances of small size remain unsolved to proven optimality. In this paper we propose a new exact method that solves a large number of the open benchmark instances within a limited computational effort. Our method is based on a Benders' decomposition, in which in the master we cut items into unit-width slices and pack them contiguously in the strip, and in the slave we attempt to reconstruct the rectangular items by fixing the vertical positions of their unit-width slices. If the slave proves that the reconstruction of the items is not possible, then a cut is added to the master, and the algorithm is reiterated.We show that both the master and the slave are strongly (N-script)(P-script)-hard problems and solve them with tailored preprocessing, lower and upper bounding techniques, and exact algorithms. We also propose several new techniques to improve the standard Benders' cuts, using the so-called combinatorial Benders' cuts, and an additional lifting procedure. Extensive computational tests show that the proposed algorithm provides a substantial breakthrough with respect to previously published algorithms.
Semi-supervised learning using label mean

Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances in the efficient training of the (supervised) SVM. In this paper, we show that S3VMs, with knowledge of the means of the class labels of the unlabeled data, is closely related to the supervised SVM with known labels on all the unlabeled data. This motivates us to first estimate the label means of the unlabeled data. Two versions of the meanS3VM, which work by maximizing the margin between the label means, are proposed. The first one is based on multiple kernel learning, while the second one is based on alternating optimization. Experiments show that both of the proposed algorithms achieve highly competitive and sometimes even the best performance as compared to the state-of-the-art semi-supervised learners. Moreover, they are more efficient than existing S3VMs.
A discriminative language model with pseudo-negative samples

In this paper, we propose a novel discriminative language model, which can be applied quite generally. Compared to the well known N-gram language models, discriminative language models can achieve more accurate discrimination because they can employ overlapping features and nonlocal information. However, discriminative language models have been used only for re-ranking in specific applications because negative examples are not available. We propose sampling pseudo-negative examples taken from probabilistic language models. However, this approach requires prohibitive computational cost if we are dealing with quite a few features and training samples. We tackle the problem by estimating the latent information in sentences using a semiMarkov class model, and then extracting features from them. We also use an online margin-based algorithm with efficient kernel computation. Experimental results show that pseudo-negative examples can be treated as real negative examples and our model can classify these sentences correctly.