Miracle-dz/UniFAR-FTUs huggingface dataset:
Birds of a feather flock together: The Nigerian cyber fraudsters (yahoo boys) and hip hop artists.

This study sets out to examine the ways Nigerian cyber-fraudsters (Yahoo-Boys) are represented in hip-hop music. The empirical basis of this article is lyrics from 18 hip-hop artists, which were subjected to a directed approach to qualitative content analysis and coded based on the moral disengagement mechanisms proposed by Bandura (1999). While results revealed that the ethics of Yahoo-Boys, as expressed by musicians, embody a range of moral disengagement mechanisms, they also shed light on the motives for the Nigerian cybercriminals' actions. Further analysis revealed additional findings: “glamorization/de-glamorization of cyber-fraud” and “sex-roles-and-cultures”. Having operated within the constraint of what is currently available (a small sample size), this article has drawn attention to the notion that Yahoo-Boys and some musicians may be “birds of a feather. ” Secondly, it has exposed a “hunter-and-antelope-relationship” between Yahoo-Boys and their victims. Thirdly, it has also highlighted that some ethos of law-abiding citizens is central to Yahoo-Boys’ moral enterprise. Yahoo-Boys, therefore, represent reflections of society. Arguably, given that Yahoo-Boys and singers are connected, and the oratory messages of singers may attract more followers than questioners, this study illuminates the cultural dimensions of cyber-fraud that emanate from Nigeria. In particular, insights from this study suggest that cyber-fraud researchers might look beyond traditional data sources (e.g., cyber-fraud statistics) for the empirical traces of “culture in action” that render fraudulently practices acceptable career paths for some Nigerian youths.
A Critical Analysis of Atoh7 (Math5) mRNA Splicing in the Developing Mouse Retina

The Math5 (Atoh7) gene is transiently expressed during retinogenesis by progenitors exiting mitosis, and is essential for ganglion cell (RGC) development. Math5 contains a single exon, and its 1.7 kb mRNA encodes a 149-aa polypeptide. Mouse Math5 mutants have essentially no RGCs or optic nerves. Given the importance of this gene in retinal development, we thoroughly investigated the possibility of Math5 mRNA splicing by Northern blot, 3′RACE, RNase protection assays, and RT-PCR, using RNAs extracted from embryonic eyes and adult cerebellum, or transcribed in vitro from cDNA clones. Because Math5 mRNA contains an elevated G+C content, we used graded concentrations of betaine, an isostabilizing agent that disrupts secondary structure. Although ∼10% of cerebellar Math5 RNAs are spliced, truncating the polypeptide, our results show few, if any, spliced Math5 transcripts exist in the developing retina (<1%). Rare deleted cDNAs do arise via RT-mediated RNA template switching in vitro, and are selectively amplified during PCR. These data differ starkly from a recent study (Kanadia and Cepko 2010), which concluded that the vast majority of Math5 and other bHLH transcripts are spliced to generate noncoding RNAs. Our findings clarify the architecture of the Math5 gene and its mechanism of action. These results have implications for all members of the bHLH gene family, for any gene that is alternatively spliced, and for the interpretation of all RT-PCR experiments.
The influence of gliotransmission on higher cognitive functions

In recent years, the understanding of synaptic modulation by neuron-astrocyte interactions has evolved considerably, contributing to build up the concept of the “tripartite synapse”. This concept is based on the dynamic dialogue between astrocytes and neurons that complements and modulates the communication between preand post-synaptic structures. However, it remains elusive how this interaction between neurons and astrocytes translates into network computation of behavior. Astrocytes were described to release gliotransmitters (such as glutamate, GABA, ATP or D-Serine) by means of several mechanisms, being exocytosis the more extensively studied. This process is mediated by the vesicular machinery and SNARE complex formation between vesicles and the target membrane, ultimately resulting in the release of the vesicular content. Transmitter release is essential for astrocyte signaling and a disruption of this phenomenon is expected to impact on the function of neuronal networks, with consequences for the computation of higher brain functions. In this thesis, our main goal was to evaluate the influence of transmitter release by astrocytes on brain circuits responsible for cognitive functions, such as learning and memory. Throughout this work, we studied the transgenic dnSNARE mouse model that displays a conditional blockade of transmitter release by exocytosis, selectively in astrocytes. This was achieved by allowing the conditional expression of the dominant negative domain of vesicular SNARE protein synaptobrevin II (dnSNARE), which interferes with the SNARE complex formation, impairing vesicular release. Four weeks after the induction of transgene transcription, the levels of transgenic protein reached its maximum. The dnSNARE transgenes are expressed exclusively by astrocytes and display inter-subject variability. The quantification of dnSNARE transgene expression levels allowed to discriminate high “expressor” subjects to be analyzed throughout. Mice were first evaluated by performing in vivo electrophysiological recordings of local field potentials from neuronal populations of cognitive related brain regions: dorsal hippocampus and prefrontal cortex. This functional network evaluation was followed by a thorough assessment of cognitive ability of these mice, by performing a battery of behavioral tests. These tests addressed different cognitive tasks mainly dependent from the performance of the hippocampus-prefrontal network. This functional assessment was complemented by a morphological characterization of neurons and astrocytes to address structural correlates of network function.
Investor Reaction to Higher Earnings Management Incentives of Overoptimistic CEOs

We examine whether investors recognize and rationally impound into the share price the possible earnings management of overoptimistic CEOs at the time the management forecast is issued, rather than the perceived (actual) earnings management at the announcement of realized earnings. We first confirm that investors underreact to management earnings forecasts issued by overoptimistic managers. Next we find that the market reacts more positively to the earnings announcements of overoptimistic CEOs when realized earnings are slightly above or below forecasted earnings compared to those of non-optimistic managers. This confirms our expectations that investors react negatively to the higher earnings management incentives of overoptimistic managers when the forecast is issued and not to actual signs of earnings management when earnings are announced.
Counterfeit alcohol distribution: A criminological script network analysis

This paper analyses a series of subsequent and connected investigations by a domestic European regulator on the network of distribution of counterfeit alcohol across two jurisdictions. The analysis mixes script analysis, a narrative framework for enhancing the understanding of how crimes unfold and are organized, with multi-node multi-link social network analysis, to observe the social structure in which crime scripts take place. We focus our attention on the key players that occupy strategic positions within the network of the crime commission process, from where they overview and control the various phases (scenes) and perform brokerage activities across the scenes, and on strategies of concealment of illicit products beyond the facade of legitimate business. Our findings indicate that actors in charge of managing the proceeds of the criminal activity are also the ones better positioned to monitor the entire process. The overall structure of the criminal network shows a good level of resilience and efficiency, although actors do not adopt common traits of a criminal lifestyle that facilitate secrecy and covertness. We believe that, by shifting the analysis from the nature of the group organization to the network of links between all the aspects of a crime commission process, the organizational structure and its weakest links become more detectable, easier to compare across proto- and meta-scripts, and ultimately more prone to situational preventive measures.
Relationship Of Setting And Gender With Teachers’ Self Efficacy In Pakistan

The most common disparities registered by a large majority of education researchers in Pakistan are related to students’ outcomes by location and gender. However, these differences do not highlight the ‘invisible’ disparities between the self-efficacy of ‘teachers by location and gender. The objective of our research was to assess the direction and strength of the relationship between gender, rural/urban setting and the self and collective efficacies of Pakistani teachers. The research question for the study was; do self and collective efficacies of teachers differ by location and gender? Data for the study were collected over a period of eighteen months in 2015-16 through two instruments; a self-efficacy questionnaire with 24 items and a Collective self-efficacy questionnaire with 21 items. The sample was selected with a combination of different sampling techniques including snowballing and convenience sampling. Data were analyzed with the help of statistical measures of association. Our findings reveal that female teachers from rural areas have the lowest self-efficacy scores but their male counterparts have the highest followed by the urban male teachers. These results partially re-confirm the findings of similar studies as far as females are concerned but rural males being more efficacious than their urban counterparts is a different find; it suggests that the sources of efficacy may be different for males and females in rural setting. Our findings also reinforce the need for enhancing teachers’ motivation and confidence through teacher preparation and training programs. The study makes a significant contribution to the field of teacher education. © 2019 Published by Future Academy www.FutureAcademy. org.UK
ParseIT: A Question-Answer based Tool to Learn Parsing Techniques

Parsing (also called syntax analysis) techniques cover a substantial portion of any undergraduate Compiler Design course. We present ParseIT, a tool to help students understand the parsing techniques through question-answering. ParseIT automates the generation of tutorial questions based on the Context Free Grammar provided by the student and generates feedback for the student solutions. The tool generates multiple-choice questions (MCQs) and fill in the blank type questions, and evaluates students' attempts. It provides hints for incorrect attempts, again in terms of MCQs. The hints questions are generated for any correct choice that is missed or any incorrect choice that is selected. Another interesting form of hint generated is an input string that helps the students identify incorrectly filled cells of a parsing table.
A Color-based Technique for Measuring Visible Loss for Use in Image Data Communication 1

The concept of the global information infrastructure and speciically that of the World Wide Web (WWW) has led to users accessing data of diierent media including images and video data over a wide area network. These data objects have sizes the order of megabytes and communication time is very large. The data size can be reduced without losing information by applying loss-inducing techniques and this will lead to reduction in communication time. Several loss-inducing techniques have been developed and each image is treated diierently by each technique. In some cases an acceptable quality of the image is obtained and in some cases it is not. In this paper we develop a color-based technique to quantify the data loss when a loss-inducing technique is applied to an image. This will result in estimating whether the resulting image is indistinguishable from the original with respect to the human eye. We illustrate its use to classify images according to the loss they can tolerate. This avoids redundant communication of a high quality image when a lower quality image can satisfy the application resulting in the conservation and better usage of network resources. We present the technique, the communication time saved, and an experimental evaluation to prove the validity of the technique.
Prior affinity measures on matches for ICP-like nonlinear registration of free-form surfaces

In this paper, we show that several well-known nonlinear surface registration algorithms can be put in an ICP-like framework, and thus boil down to the successive estimation of point-to-point correspondences and of a transformation between the two surfaces. We propose to enrich the ICP-like criterion with additional constraints and show that it is possible to minimise it in the same way as the original formulation, with only minor modifications in the update formulas and the same convergence properties. These constraints help the algorithm to converge to a more realistic solution and can be encoded in an affinity term between the points of the surfaces to register. This term is able to encode both a priori knowledge and higher order geometrical information in a unified manner. We illustrate the high added value of this new term on synthetic and real data.
A continuous-time low-pass sigma-delta ADC chip design for LTE communication application and bio-signal acquisitions

This paper presents a continuous time lowpass sigma-delta ADC for LTE communication with a chain of integrators and with capacitive feedforward summation (CICFF) plus circuit - which is an ideal function for implementation in low power applications. The summation of feedforward signals is achieved by capacitors plus, without the essential thing of any extra active components which can be used for electroencephalogram (EEG) or electrocardiogram (ECG) signal acquisition systems. The quantizer uses a 1-bit comparator which can achieve high linearity easily. The chip was implemented in 1.8 V supply voltage which works as a part of the biological signal acquisition system. Tested results have achieved a dynamic range of 52 dB over a 5 MHz signal bandwidth, a peak SNDR of 55.33 dB and power dissipation of 24.5 mW.
A study on the use of OpenGL in window systems

OpenGL is getting used more in window system as a way of improving performance and enabling new functionality. Examples of two systems using different approaches of how OpenGL is being used are Quartz Extreme and Fresco. Quartz Extreme uses window composition which assures fast redisplay and Fresco on the other hand uses a structured graphics approach which utilises OpenGL on a much lower level compared to Quartz Extreme which operates at a window level. Fresco’s way brings great flexibility and an ability to mix 2D and 3D-objects on the desktop. But each of the approaches has its problems; Quartz extreme requires a large amount of memory for buffering of the window contents and Fresco has performance problems when redisplaying complex structures.
Constructing a Theory- and Evidence-Based Treatment Rationale for Complex eHealth Interventions: Development of an Online Alcohol Intervention Using an Intervention Mapping Approach

Background Due to limited reporting of intervention rationale, little is known about what distinguishes a good intervention from a poor one. To support improved design, there is a need for comprehensive reports on novel and complex theory-based interventions. Specifically, the emerging trend of just-in-time tailoring of content in response to change in target behavior or emotional state is promising. Objective The objective of this study was to give a systematic and comprehensive description of the treatment rationale of an online alcohol intervention called Balance. Methods We used the intervention mapping protocol to describe the treatment rationale of Balance. The intervention targets at-risk drinking, and it is delivered by email, mobile phone text messaging, and tailored interactive webpages combining text, pictures, and prerecorded audio. Results The rationale of the current treatment was derived from a self-regulation perspective, and the overarching idea was to support continued self-regulation throughout the behavior change process. Maintaining the change efforts over time and coping adaptively during critical moments (eg, immediately before and after a lapse) are key factors to successful behavior change. Important elements of the treatment rationale to achieving these elements were: (1) emotion regulation as an inoculation strategy against self-regulation failure, (2) avoiding lapses by adaptive coping, and (3) avoiding relapse by resuming the change efforts after a lapse. Two distinct and complementary delivery strategies were used, including a day-to-day tunnel approach in combination with just-in-time therapy. The tunnel strategy was in accordance with the need for continuous self-regulation and it functions as a platform from which just-in-time therapy was launched. Just-in-time therapy was used to support coping during critical moments, and started when the client reports either low self-efficacy or that they were drinking above target levels. Conclusions The descriptions of the treatment rationale for Balance, the alcohol intervention reported herein, provides an intervention blueprint that will aid in interpreting the results from future program evaluations. It will ease comparisons of program rationales across interventions, and may assist intervention development. By putting just-in-time therapy within a complete theoretical and practical context, including the tunnel delivery strategy and the self-regulation perspective, we have contributed to an understanding of how multiple delivery strategies in eHealth interventions can be combined. Additionally, this is a call for action to improve the reporting practices within eHealth research. Possible ways to achieve such improvement include using a systematic and structured approach, and for intervention reports to be published after peer-review and separately from evaluation reports.
The Regulation of Muscle Structure and Metabolism by Mio/dChREBP in Drosophila

All cells require energy to perform their specialized functions. Muscle is particularly sensitive to the availability of nutrients due to the high-energy requirement for muscle contraction. Therefore the ability of muscle cells to obtain, store and utilize energy is essential for the function of these cells. Mio, the Drosophila homolog of carbohydrate response element binding protein (ChREBP), has recently been identified as a nutrient responsive transcription factor important for triglyceride storage in the fly fat body. However, the function of Mio in muscle is unknown. In this study, we characterized the role of Mio in controlling muscle function and metabolism. Decreasing Mio levels using RNAi specifically in muscle results in increased thorax glycogen storage. Adult Mio-RNAi flies also have a flight defect due to altered myofibril shape and size in the indirect flight muscles as shown by electron microscopy. Myofibril size is also decreased in flies just before emerging from their pupal cases, suggesting a role for Mio in myofibril development. Together, these data indicate a novel role for Mio in controlling muscle structure and metabolism and may provide a molecular link between nutrient availability and muscle function.
Framing inclusion: intellectual disability, interactive kinds and imaginary companions

ABSTRACT A central aspect of inclusion is to grant all children opportunities to participate and gain from a fellowship in school. However, some categorised groups of children are more prone to segregation and exclusion than others. Drawing on philosopher Ian Hacking’s theories of the interactive relationship between how categories influence the categorised, the structures children are subjected to in schools affect how a child constructs her or his identity. The empirical data of this article are based upon a child (Will) labelled as intellectually disabled who spends most of his time in school segregated from his peers. In this segregated context, he has constructed a universe of imaginary companions and pretended identities (roles) that he frequently interacts with and enters. In relation to the attitudes, approaches and organisational practices that educational institutions subject groups of children to, the discussion questions whether the ascribed roles and function of Will’s imaginary universe is a result of and/or a response to the institutional structures in which he finds himself. If this is the case, the educational system, from policy to practice, has to ask itself what kinds of people do they wish to construct.
Optimizing Community and Hospital Services Using the Cancer Support Source Program

Background: The Cancer Support Community developed the Cancer Support Source (CSS) to assess the needs of cancer patients with distress. Each item on this self-administered questionnaire represents an area of concern which the patient rates and indicates their need for action with a “staff person,” but no details about the category of staff is given. Objective: To examine the factor structure of the CSS and to increase its utility to triage patients for referral to services based on a needs assessment. Methods: Data from 690 patients who completed the CSS over a 1-year period were analyzed. In study 1, an exploratory principal component analysis was conducted. In study 2, the fit of this proposed model was evaluated with confirmatory factor analysis (CFA). Results: Three factors were retained in the final CFA: emotional distress, physical health concerns, and resource needs. This model demonstrated adequate fit, Root Mean Square Error of Approximation (RMSEA)= 0.056, Comparitive Fit Index (CFI) = . 907, Standardized Root Mean Square Residual (SRMR) = 0.050. Conclusions: Three factors are proposed as CSS subscales to guide referral and coordinate services: Emotional Distress/Patient and Family Counselor, Physical Health Concerns/Medical Care Provider, and Resource Needs/Case Management-Clinical Social Worker. The clinical utility of these referral subscales should be established with additional research.
Computer Vision and Pattern Recognition 2005 Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior

We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We report results on a series of experiments comparing recognition engines, including Ad-aBoost, support vector machines, linear discriminant analysis. We also explored feature selection techniques, including the use of AdaBoost for feature selection prior to classification by SVM or LDA. Best results were obtained by selecting a subset of Gabor filters using AdaBoost followed by classification with Support Vector Machines. The system operates in real-time, and obtained 93% correct generalization to novel subjects for a 7-way forced choice on the Cohn-Kanade expression dataset. The outputs of the clas-sifiers change smoothly as a function of time and thus can be used to measure facial expression dynamics. We applied the system to to fully automated recognition of facial actions (FACS). The present system classifies 17 action units, whether they occur singly or in combination with other actions , with a mean accuracy of 94.8%. We present preliminary results for applying this system to spontaneous facial expressions.