Miracle-dz/UniFAR-FTUs huggingface dataset:
The Seven Scam Types: Mapping the Terrain of Cybercrime

Threat of cyber crime is a growing danger to the economy. Industries and businesses are targeted by cyber-criminals along with members of the general public. Since cyber crime is often a symptom of more complex criminological regimes such as laundering, trafficking and terrorism, the true damage caused to society is unknown. Dissimilarities in reporting procedures and non-uniform cyber crime classifications lead international reporting bodies to produce incompatible results which cause difficulties in making valid comparisons. A cyber crime classification framework has been identified as necessary for the development of an inter-jurisdictional, transnational, and global approach to identify, intercept, and prosecute cyber-criminals. Outlined in this paper is a cyber crime classification framework which has been applied to the incidence of scams. Content analysis was performed on over 250 scam descriptions stemming from in excess of 35 scamming categories and over 80 static features derived. Using hierarchical cluster and discriminant function analysis, the sample was reduced from over 35 ambiguous categories into 7 scam types and the top four scamming functions - identified as scamming business processes, revealed. The results of this research bear significant ramifications to the current state of scam and cyber crime classification, research and analysis, as well as offer significant insight into the business processes and applications adopted by scammers and cyber-criminals.
ARE RANGE‐SIZE DISTRIBUTIONS CONSISTENT WITH SPECIES‐LEVEL HERITABILITY?

The concept of species‐level heritability is widely contested. Because it is most likely to apply to emergent, species‐level traits, one of the central discussions has focused on the potential heritability of geographic range size. However, a central argument against range‐size heritability has been that it is not compatible with the observed shape of present‐day species range‐size distributions (SRDs), a claim that has never been tested. To assess this claim, we used forward simulation of range‐size evolution in clades with varying degrees of range‐size heritability, and compared the output of three different models to the range‐size distribution of the South American avifauna. Although there were differences among the models, a moderate‐to‐high degree of range‐size heritability consistently leads to SRDs that were similar to empirical data. These results suggest that range‐size heritability can generate realistic SRDs, and may play an important role in shaping observed patterns of range sizes.
A qualitative exploration of memory cuing by personal items in the home

We are surrounded by personal items that can trigger memories, such as photos, souvenirs and heirlooms. Also during holidays, we collect items to remind us of the events, but not all bring back memories to the same extent. Therefore, we explored peoples’ responses to personal items related to a holiday, using the home tour interviewing method. In total, 63 accounts of cuing responses from nine home tours were analysed using thematic analysis. This resulted in four types of cuing responses: (a) ‘no-memory’ responses, (b) ‘know’ responses, (c) ‘memory evoked think or feel’ responses and (d) ‘remember’ responses. For each of these cuing response categories, we looked into the types of items and their characteristics. Furthermore, we found that some items can evoke multiple memories. The majority of the memories’ content refers to events close to the moment of acquiring the item.
Data repositories in the Humanities and the Semantic Web: modelling, linking, visualising

The paper discusses the inherent potential of the Semantic Web and its related technologies for humanities research. The focal point lies on the extraction of semantic relations from heterogeneous XML based scholarly corpora using a webservice based infrastructure (XTriples). Especially the creation of methodologically distinct semantic corpora stemming from data sets originating in the humanities will be discussed. During this discussion, questions of modelling, linking, and visualising data from the humanities will be tackled as well. Finally, opportunities for further analysis and visualisation of semantically modelled data in the humanities are exemplarily presented and discussed.
White Syndrome in Acropora muricata: Nonspecific bacterial infection and ciliate histophagy

Selective antibiotic treatment of white syndrome (WS)‐affected corals (Acropora muricata) from Fiji was used to identify 3 potential bacterial pathogens of the disease. Interestingly, the suite of bacterial associates of the disease was different to that recently identified using identical primer sets for WS on the GBR and in the Solomon Islands. In addition to the three bacterial pathogenic candidates and as previously shown for WS and more recently for white band disease (WBD) in the Caribbean, all samples of the disease were specifically associated with the histophagous ciliate Philaster lucinda. From the pattern of disease progression and histopathology in relation to the selective elimination of microbial groups, we conclude that these ‘white’ diseases are a result of a nonspecific bacterial infection and a ‘secondary’ infection by the P. lucinda ciliate. Although we have not observed the initiation of infection, a nonspecific, multispecies bacterial infection appears to be a corequirement for WS lesion progression and we hypothesize that the bacterial infection occurs initially, weakening the defences of the host to predation by the ciliates. Such ciliate histophagy gives rise to the characteristic white band of denuded coral skeleton that gives these diseases their names. The characteristics of the microbial communities of WBD and WS appear identical, and since the bacterial associates of WS vary geographically (and/or temporally), there appears to be no logical distinction between WS in the Indo‐Pacific and WBD in the Caribbean.
Message Clustering based Matrix Factorization Model for Retweeting Behavior Prediction

Retweeting is an important mechanism for information diffusion in social networks. Through retweeting, message is reshared from one user to another user, forming large cascades of message forwarding. Most existing researches of predicting retweeting utilize user social relationships for modeling which leads to vast calculating amount. In this paper, we propose two message clustering based matrix factorization models for retweeting prediction. Unlike previous approaches, our models exploit the clustering relationships of messages instead of social relationships. Our models are quite general because we do not need any auxiliary information except for message content. Several experiments on real datasets show that our models are effective and outperform the state-of-the-art methods.
Comparing Tablets and PCs in teaching Mathematics: An attempt to improve Mathematics Competence in Early Childhood Education

The present study investigates and compares the influence of using computers and tablets, in the development of mathematical competence in early childhood education. For the implementation of the survey, we conducted a 14 weeks intervention, which included one experimental and one control group. Children in both groups were taught Mathematics according to Greek curriculum for early childhood education in conjunction with the use either of the same educational software, which depending on the group, were running on computers or on tablets. In order to evaluate the mathematical performance of children we used the Test of Early Mathematics Ability (TEMA-3). The sample consisted of 256 children in Greece. The results showed that, teaching with tablets comparatively to teaching with computers has contributed significantly to the development of children’s mathematical ability to a greater extent. Moreover, factors such as gender and age did not seem to differentiate the development of mathematical competence of children.
Predicting Cuisine from Ingredients

Over the years, people have tried to explore new ingredients and incorporate them into recipes or produce new recipes all together. One of the obvious relations that we would like to explore is the relation between ingredients and cuisines. We use the yummly data-set to study the problem of predicting cuisine of a recipe based on it’s ingredients. On testing several classiﬁers we observed that SVM works best for this prediction task.
Robust Lead Compensator Design for an Electromechanical Actuator Based on H∞ Theory

In this paper, we design a robust lead compensator for a real Electromechanical Actuator (EMA) harmonic drive by introducing an approach based on H∞ control theory. Here, we address three main topics; experimental identification, uncertainty modelling, and robust control design for a real EMA harmonic drive system. This method verifies good tradeoff between the powerful H∞ controller and the unique features of compensators, such as: simplicity, low cost and easy implementation. The H∞ controller and the extracted compensator are almost identical within the EMA bandwidth range. Simulation and test results prove the effectiveness of the proposed approach and the superiority of the performance of the designed robust EMA with lead compensator based on H∞ controller over the original EMA; this preference is pertaining to its robustness to parametric uncertainties and high performance.
PREVENT : An Algorithm for Mining Inter-transactional Patterns for the Prediction of Rare Events

In this paper we propose a data mining technique for the efficient prediction of rare events, such as heat waves, network intrusions and engine failures, using inter transactional patterns. Data mining is a research area that attempts to assist the decision makers with a set of tools to treat a wide range of real world problems that the traditional statistical and mathematical approaches are not enough in terms of efficiency and computational performance. Transaction databases, such as the ones in this paper that contain sets of events, require special approaches in order to extract valuable temporal knowledge. We utilize the framework of inter-transaction association rules, which associate events across a window of transactions. We propose an approach that extends sequential analysis to predict rare events in transaction databases. We formulate the problem of rare events prediction and we propose PREVENT, an algorithm that produces inter-transactional patterns for the fast and accurate prediction of a user-specified rare event. Finally, we provide experimental results and suggest some ideas for future research.
Statistical Analysis of Facial Expressions

Over the last decade, the statistical analysis of facial expressions has become an active research topic that finds potential applications in many areas. Some examples of interest are human-computer interfaces, image retrieval and human emotion analysis. Facial expressions reflect not only emotions but also other mental activities, social interaction and physiological signals. Humans detect and interpret faces and facial expressions in a scene with little effort; however, the development of an automated system that accomplishes this task is rather difficult. There are, in fact, several related problems. This paper, provides an overview of the different stages which can be distinguished in the organization of an automatic facial expression analysis system.
Centrally-mediated changes in urodynamic parameters during slow wave sleep

Hypothesis / aims of study Micturition does not normally occur during sleep. This is due in part to absence of fluid intake, the diurnal increase in antidiuretic hormone and circadian change in intrinsic bladder compliance. In addition, it is possible that there are central effects on bladder function due to dynamic changes in brain state. The general anaesthetic urethane promotes a condition of behavioural unconsciousness that closely mimics the full spectrum of natural sleep. The electroencephalogram (EEG) shows spontaneous and rhythmic changes in brain state that resemble slow wave, and rapid eye movement sleep (REM)-like brain sleep states with a period of around 11min (1). We used the urethane-anaesthetised rat preparation as a model system to facilitate mechanistic studies into changes in urodynamic parameters during continuous cystometry in sleep-like brain states.
A multi-label interactive image segmentation method based on region merging

Interactive image segmentation is becoming more and more popular. In this paper we describe a multi-label interactive image segmentation method which incorporates both seeded-region extension and region merging. First, Mean shift method is provided for the initial segmented regions, and then the users draw lines to mark the position and region of the foreground and background, following that, foreground regions expand based on the similarity with non-marker regions and foreground regions according to the ordered cluster, finally, based on maximal-similarity region merging strategy, we merge the initial regions to get the final segmentation result. The results of experiments show that with this method users could get a good segmentation result for most multi-cell images, also can revise the results and re-segment to get an ideal result.
The Metric FF Planning System Translating Ignoring Delete Lists to Numeric State Variables

Planning with numeric state variables has been a challenge for many years and was a part of the rd International Planning Competition IPC Currently one of the most popular and successful algorithmic techniques in STRIPS planning is to guide search by a heuristic function where the heuristic is based on relaxing the planning task by ignoring the delete lists of the available actions We present a natural extension of ignoring delete lists to numeric state variables preserving the relevant theoretical properties of the STRIPS relaxation under the condition that the numeric task at hand is monotonic We then identify a subset of the numeric IPC competition language linear tasks where monotonicity can be achieved by pre processing Based on that we extend the algorithms used in the heuristic planning system FF to linear tasks The resulting system Metric FF is according to the IPC results which we discuss one of the two currently most e cient numeric planners
Pediatric glioma stem cells: biologic strategies for oncolytic HSV virotherapy

While glioblastoma multiforme (GBM) is the most common adult malignant brain tumor, GBMs in childhood represent less than 10% of pediatric malignant brain tumors and are phenotypically and molecularly distinct from adult GBMs. Similar to adult patients, outcomes for children with high-grade gliomas (HGGs) remain poor. Furthermore, the significant morbidity and mortality yielded by pediatric GBM is compounded by neurotoxicity for the developing brain caused by current therapies. Poor outcomes have been attributed to a subpopulation of chemotherapy and radiotherapy resistant cells, termed “glioma stem cells” (GSCs), “glioma progenitor cells,” or “glioma-initiating cells,” which have the ability to initiate and maintain the tumor and to repopulate the recurring tumor after conventional therapy. Future innovative therapies for pediatric HGG must be able to eradicate these therapy-resistant GSCs. Oncolytic herpes simplex viruses (oHSV), genetically engineered to be safe for normal cells and to express diverse foreign anti-tumor therapeutic genes, have been demonstrated in preclinical studies to infect and kill GSCs and tumor cells equally while sparing normal brain cells. In this review, we discuss the unique aspects of pediatric GSCs, including markers to identify them, the microenvironment they reside in, signaling pathways that regulate them, mechanisms of cellular resistance, and approaches to target GSCs, with a focus on the promising therapeutic, genetically engineered oHSV.
Correcting perceived perspective distortions using object specific planar transformations

Distortions due to perspective projection is often described under the umbrella term of foreshortening in computer graphics and are treated the same way. However, a large body of literature from artists, perceptual psychologists and perception scientists have shown that the perception of these distortions is different in different situations. While the distortions themselves depend on both the depth and the orientation of the object with respect to the camera image plane, the perception of these distortions depends on other depth cues present in the image. In the absence of any depth cue or prior knowledge about the objects in the scene, the visual system finds it hard to correct the foreshortening automatically and such images need user input and external algorithmic distortion correction.In this paper, we claim that the shape distortion is more perceptible than area distortion, and quantify such perceived foreshortening as the non-uniformity across the image, of the ratio e of the differential areas of an object in the scene and its projection. We also categorize foreshortening into uniform and non-uniform foreshortening. Uniform foreshortening is perceived by our visual system as a distortion, even if e is uniform across the image, only when comparative objects of known sizes are present in the image. Non-uniform foreshortening is perceived when there is no other depth cue in the scene that can help the brain to correct for the distortion. We present a unified solution to correct these distortions in one or more non-occluded foreground objects by applying object-specific segmentation and affine transformation of the segmented camera image plane. Our method also ensures that the background undergoes minimal distortion and preserves background features during this process. This is achieved efficiently by solving Laplace's equations with Dirichlet boundary conditions, assisted by a simple and intuitive user interface.
Testicular Feminization or Androgen Insensitivity Syndrome (AIS) in Iran: a Retrospective Analysis of 30-Year Data

Background: Androgen insensitivity syndrome (AIS) or testicular feminization is a partial or complete inability of cell response to androgen. The cause is enzymatic defect in synthesis of testosterone, resulting sexually immature phenotypically female, with primary amenorrhea. There are three categories of AIS, complete, partial and mild, depending on the degree of external genital masculinization. The aim of this study was to find out chromosomal abnormalities, and correlation between AIS and maternal/paternal age, parents’ consanguineous marriage, family history and clinical observation, in Iranian AIS patients. Method: This study includes a retrospective data analysis of 72,000 families’ medical records in the Genetic Clinic in Tehran, during a 30-yr period (1984–2014). The essential basis for the patients’ referral to the clinic by gynecologists was primary amenorrhea. Cytogenetic abnormalities has been confirmed by chromosome G-banding and conventional staining methods. Results: Seventy AIS female patients with 46XY pattern were cytogenetically diagnosed and the frequency of AIS syndrome was estimated about 0.05% (∼70/140000). The results showed no association between AIS and maternal or paternal age nor were the marital pattern of the parents. The clinical findings illustrated that primary amenorrhea had the highest indication for referral of AIS patients for genetic counseling and cytogenetic study. Conclusion: No correlation was observed between AIS and maternal or paternal age or consanguineous marriages. Amenorrhea is the most clinically observed sign of AIS patients.
Low level laser irradiation stimulates mitochondrial membrane potential and disperses subnuclear promyelocytic leukemia protein

Low level laser irradiation (LLLI) is used to promote wound healing. Molecularly it is known to stimulate mitochondrial membrane potential (MMP), cytokine secretion, and cell proliferation. This study was designed to determine the influence of LLLI on the kinetics of MMP stimulation and decay, specific cytokine gene expression, and subcellular localization of promyelocytic leukemia (PML) protein on HaCaT human keratinocytes.
Targeting the Monocyte–Macrophage Lineage in Solid Organ Transplantation

There is an unmet clinical need for immunotherapeutic strategies that specifically target the active immune cells participating in the process of rejection after solid organ transplantation. The monocyte–macrophage cell lineage is increasingly recognized as a major player in acute and chronic allograft immunopathology. The dominant presence of cells of this lineage in rejecting allograft tissue is associated with worse graft function and survival. Monocytes and macrophages contribute to alloimmunity via diverse pathways: antigen processing and presentation, costimulation, pro-inflammatory cytokine production, and tissue repair. Cross talk with other recipient immune competent cells and donor endothelial cells leads to amplification of inflammation and a cytolytic response in the graft. Surprisingly, little is known about therapeutic manipulation of the function of cells of the monocyte–macrophage lineage in transplantation by immunosuppressive agents. Although not primarily designed to target monocyte–macrophage lineage cells, multiple categories of currently prescribed immunosuppressive drugs, such as mycophenolate mofetil, mammalian target of rapamycin inhibitors, and calcineurin inhibitors, do have limited inhibitory effects. These effects include diminishing the degree of cytokine production, thereby blocking costimulation and inhibiting the migration of monocytes to the site of rejection. Outside the field of transplantation, some clinical studies have shown that the monoclonal antibodies canakinumab, tocilizumab, and infliximab are effective in inhibiting monocyte functions. Indirect effects have also been shown for simvastatin, a lipid lowering drug, and bromodomain and extra-terminal motif inhibitors that reduce the cytokine production by monocytes–macrophages in patients with diabetes mellitus and rheumatoid arthritis. To date, detailed knowledge concerning the origin, the developmental requirements, and functions of diverse specialized monocyte–macrophage subsets justifies research for therapeutic manipulation. Here, we will discuss the effects of currently prescribed immunosuppressive drugs on monocyte/macrophage features and the future challenges.
An Analysis of the International Development of the Equity Method

The equity method was used as an early form of consolidation for all subsidiaries in the U.K. and for certain subsidiaries in the U.S. Another use of the method in some countries, even in the era of full consolidation, has been in the financial statements of investor legal entities. This seems to result from using the equity method as a technique for valuation or as an aid in the preparation of consolidated statements rather than as a form of consolidation. The method has also been used as a substitute for consolidation for excluded subsidiaries or for controlled companies not included in the definition of subsidiaries. Later, the equity method was introduced for joint ventures and then for other forms of ‘strategic alliance’, but the latter bring definitional problems, which have led to a consensus around an arbitrary threshold of 20 per cent of voting rights. This article traces these developments across time and space, and criticizes several of the past and present applications of the equity method. There is also an examination of the development of the terms ‘equity method’ and ‘associated company’.