Miracle-dz/UniFAR-FTUs huggingface dataset:
Multicampaign Assignment Reflecting Group-based Response Suppression

Companies have made their best efforts to sustain ongoing relations with their customers and thus generate as much revenue and profits as possible through CRM (Customer Relationship Management). One of the key marketing tools of CRM is target marketing. Target marketing is a marketing strategy that analyzes certain goods and services preferred by existing customers, develops new goods and services that fit with the customers' preferences, and targets those goods and services. As many companies carry out personalized target marketing, most customers may encounter several similar marketing campaigns simultaneously, thereby making the campaigns less effective and efficient than specifically-personalized campaigns. Furthermore, when a customer is offered several marketing campaigns, his or her response is highly dependent on the total number of campaigns recommended to him or her. With this being said, this research shall suggest a strategy to deliver more effective and efficient multicampaigns and hence maximize customer satisfaction by applying different response suppression functions into various customer groups.
Tree and word embedding based sentence similarity for evaluation of good answers in intelligent tutoring system

This article presents an approach to examining the similarity of the sentences. In our approach, Euler algorithm was used to generate a series of words based on tree and S⊘rensen-Dice coefficient was applied to determine the similarity between compared trees. The emphasis is on defining the similarity between the correct and incorrect answers from the Yahoo Question and Answer of the Non-Factual Data Set. Proposed algorithm was used on two types of trees. First is the constituency tree generated by Stanford CoreNLP, and second is custom-made algorithm that produces second type of tree, called knowledge tree which is derived from parse tree. In our comparison, Zhuang-Sasha algorithm was also used. Second approach that was used for sentence comparison uses Word2Vec model for finding word embedding's and calculating sentence average vector, after that cosine distance was applied to determine similarity between two sentences. Results generated with this method were compared with our method in finding sentence similarity based on knowledge tree. Approach described in this paper can be used in evaluation of correct answers which will be used in our implementation of Intelligent Tutoring System.
Individual brief psychotherapy with sexually abused girls

SUMMARY This paper describes the clinical analysis of process notes from individual therapy sessions of twenty girls between 6 and 14 who had been sexually abused. Factors were identified from the material which could facilitate the future therapy for girls, particularly how their experience was that of losing a containing maternal object and then the subsequent trauma of sexual abuse.
Adherence to Mediterranean Diet Offers an Additive Protection Over the Use of Statin Therapy: Results from the ATTICA Study (2002-2012).

BACKGROUND AND AIMS The protective role of Mediterranean diet on cardiovascular disease (CVD) risk has been extensively discussed in the literature, but its incremental effect over the use of CVD risk reducing agents (such as hypolipidemic treatment) has rarely been evaluated. METHODS The ATTICA study was carried out in the Athens area during 2001-2002 and included 3042 participants free of CVD at baseline (49.8% men, aged 18-89 years). Adherence to Mediterranean diet was assessed using the MedDietScore (range 0-55) and statin use was recorded for all subjects. During 2011-2012, 2583 out of the 3042 baseline participants attended the 10-year follow-up of the ATTICA study (15% lost-to-follow-up) and CVD development was recorded. RESULTS Adherence to Mediterranean diet (highest tertile) decreased CVD risk by 29.3% (Hazard Ratio (HR): 0.707, 95% Confidence Intervals (CI): 0.537-0.831) as compared with the lowest tertile, independently of statin use. Patients with hyperlipidemia on a statin that adopted unhealthy dietary habits (lowest tertile) had 75% increased CVD risk than normolipidemic subjects with healthy dietary habits (HR=1.75, 95%CI: 1.33-2.29). The addition of Mediterranean diet tertiles in the multivariable model reclassified 46.7% of the participants to CVD risk categories. CONCLUSION Adherence to Mediterranean diet confers a considerable reduction in CVD risk, independently of gender, age, family history of CVD, diabetes mellitus, smoking status, hypertension and physical activity status. Therefore, CVD prevention strategies should involve the implementation of a Mediterranean diet in both the general population and patients on a statin.
Phosphorylation of CTP Synthetase on Ser36, Ser330, Ser354, and Ser454 Regulates the Levels of CTP and Phosphatidylcholine Synthesis in Saccharomyces cerevisiae*

The Saccharomyces cerevisiae URA7-encoded CTP synthetase is phosphorylated and stimulated by protein kinase C. We examined the hypothesis that Ser36, Ser330, Ser354, and Ser454, contained in a protein kinase C sequence motif in CTP synthetase, were target sites for the kinase. Synthetic peptides containing a phosphorylation motif at these serine residues served as substrates for protein kinase C in vitro. Ser → Ala (S36A, S330A, S354A, and S454A) mutations in CTP synthetase were constructed by site-directed mutagenesis and expressed normally in a ura7 ura8 double mutant that lacks CTP synthetase activity. The CTP synthetase activity in extracts from cells bearing the S36A, S354A, and S454A mutant enzymes was reduced when compared with cells bearing the wild type enzyme. Kinetic analysis of purified mutant enzymes showed that the S36A and S354A mutations caused a decrease in the Vmax of the reaction. This regulation could be attributed in part by the effects phosphorylation has on the nucleotide-dependent oligomerization of CTP synthetase. In contrast, CTP synthetase activity in cells bearing the S330A mutant enzyme was elevated, and kinetic analysis of purified enzyme showed that the S330A mutation caused an elevation in the Vmax of the reaction. In vitro data indicated that phosphorylation of CTP synthetase at Ser330 affected the phosphorylation of the enzyme at another site. The phosphorylation of CTP synthetase at Ser36, Ser330, Ser354, and Ser454 residues was physiologically relevant. Cells bearing the S36A, S354A, and S454A mutations had reduced CTP levels, whereas cells with the S330A mutation had elevated CTP levels. The alterations in CTP levels correlated with the regulatory effects CTP has on the pathways responsible for the synthesis of the membrane phospholipid phosphatidylcholine.
Modeling user emotion in interactive play environments: a fuzzy physiological approach

Researchers are integrating emerging technologies into interactive play environments, and established game markets continue to expand, yet evaluating play environments is challenging. While task performance metrics are commonly used to objectively and quantitatively analyse productivity systems; with play systems, the quality of the experience, not the performance of the participant is important. This research presents three experiments that examine users' physiological signals to continuously model user emotion during interaction with play technologies. Modeled emotions are powerful because they capture usability and playability, account for user emotion, are quantitative and objective, and can be represented continuously. In Experiment One we explored how physiological signals respond to interaction with play technologies. We collected a variety of physiological measures while observing participants playing a computer game in four difficulty conditions, providing a basis for experimental exploration of this domain. In Experiment Two we investigated how physiological signals differ between play conditions, and how physiological signals co-vary with subjective reports. A different physiological response was observed when playing a computer game against a co-located friend versus a computer. When normalized, the physiological results mirrored subjective reports. In Experiment Three we developed a method for modeling emotion using physiological data. A fuzzy logic model transformed four physiological signals into arousal and valence. A second fuzzy logic model transformed arousal and valence into five emotions: boredom, challenge, excitement, frustration, and fun. The modeled emotions' means were evaluated with test data, and exhibited the same trends as the reported emotions for fun, boredom, and excitement, but modeled emotions revealed differences between three play conditions, while differences between reported emotions were not significant. Mean emotion modeled from physiological data fills a knowledge gap for objective and quantitative evaluation of entertainment technologies. Using our technique, user emotion can be analyzed over an entire experience, revealing variance within and between conditions. This continuous representation has a high evaluative bandwidth, and is important because the process , not the outcome of playing determines success. The continuous representation of modeled emotion is a powerful evaluative tool, that when combined with other approaches, forms a robust method for evaluating user interaction with play technologies.
Query answering techniques on uncertain and probabilistic data: tutorial summary

Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and the rapidly increasing amount of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task and has attracted more and more interest from the database community. Recently, uncertain data management has become an emerging hot area in database research and development. In this tutorial, we systematically review some representative studies on answering various queries on uncertain and probabilistic data.
Exogenous Application of Growth Enhancers Mitigate Water Stress in Wheat by Antioxidant Elevation

The present study was conducted to investigate the response of two wheat cultivars (AARI-11 and Millat-11) to a foliar application of four growth enhancers which include: {H2O (water), MLE30 (moringa leaf extract), KCl (potassium chloride), and BAP (benzyl-amino purine)}, within the six irrigation water-regimes which are applied at the various critical growth stages such as crown root initiation (CRI), tillering (T), booting (B), and heading (H). Irrigation water-regimes include: CRI+T+B, CRI+T, CRI+B, T+B, T+H, and control (CRI+T+B+H). The growth enhancers i.e., H2O, MLE30 (1:30), KCl (2%), and BAP (50 mg L−1) were applied @ 500 L ha−1 at tillering and heading stages. The results demonstrated some increased quantities of both enzymatic (superoxide dismutase, peroxidase, catalase) and non-enzymatic (ascorbic acid, phenol) antioxidants in leaves of AARI-11 when MLE30 was applied under T+B and T+H irrigation water-regimes. Similar results were also observed in the case of leaf chlorophyll “a” and “b” and K+ contents in both cultivars under control, T+B and CRI+T+B irrigation water regimes. AARI-11 produced the highest biological and grain yield, due to the application of MLE30 and BAP under control, CRI+T+B, T+B, and T+H irrigation water-regimes. However, KCl lagged behind among the treatments set for both cultivars under all the irrigation water-regimes. Foliar spray of MLE30 remained prominent growth enhancer and stresses mitigating agent under water deficit conditions particularly under T+B and T+H irrigation water-regimes. Moreover, economic analysis indicated that the foliar application of MLE30 is a cost effective and environment friendly strategy for the maximum yield and income.
Advanced differentially non-coherent code acquisition in jamming and data modulation

We consider differentially non-coherent code tinting acquisition in direct-sequence code-division multiple access (DS-CDMA) communication system. An advanced method for differentially non-coherent acquisition, DC-MUSIC, was proposed and noticed to combine the benefits of both conventional differentially non-coherent matched filter and traditional MUSIC estimator in a meaningful way. We evaluate DC-MUSIC in the presence of tone jamming and data modulation. Especially, we study the effects of imperfect removal of data modulation. This is crucial for any differentially coherent/non-coherent acquisition schemes, since they exploit temporal correlation of signals. Simulation results are presented.
A Survey on MR Brain Image Segmentation Using SOM Based Strategies

Magnetic Resonance (MR) image segmentation has greater influence in image guided surgery, therapy evaluation and diagnosis fields. Several supervised and unsupervised segmentation techniques are available for image segmentation. Supervised segmentation has less demand in medical field because it needs a priori knowledge, assistance from external entity. Whereas unsupervised segmentation yield good results without any a priori knowledge. Self Organizing Map (SOM) is an unsupervised clustering technique. The SOM is an Artificial Neural Network (ANN) which has a feed-forward structure. The SOM features are very useful in data analysis and data visualization, which makes it as an important tool in brain MR image segmentation. SOM map quality depends upon the learning parameters, map topology and map size. A comprehensive survey on SOM based automatic MR image segmentation methods are presented below.
Prevalence of and risk factors for binge eating behaviour in 6930 adults starting a weight loss or maintenance programme

Abstract Objective Conflicting data are available on the prevalence of binge eating behaviour (BE) in individuals seeking to lose or maintain weight. The present study aimed to estimate the prevalence of and the risk factors for BE in a large sample of men and women starting a weight loss or maintenance programme. Design Cross-sectional study. BE was defined as a Binge Eating Scale (BES) score ≥18. The State-Trait Anxiety Inventory and the Italian Depression Questionnaire were used to assess anxiety and depression. Besides sex, age and BMI, marital status, educational level, smoking and physical activity were evaluated as potential risk factors for BE. Uni- and multivariable Poisson working regression models were used to estimate prevalence ratios (PR) and marginal probabilities. Setting Nutritional research centre. Subjects Adults (n 6930; 72 % women) with a median age of 46 years (range 18–81 years) were consecutively studied. Results BE prevalence in the pooled sample was 17 %. At multivariable analysis, being a woman (PR=2·70), smoking (PR=1·15) and increasing BMI (PR=1·05 for 1 kg/m2 increase) were risk factors for BE. On the contrary, being older (PR=0·99 for 1-year increase), performing physical activity (PR=0·89) and being married (PR=0·88) were protective factors for BE. Anxiety and depression were more common in subjects with BE. Conclusions BE is common in individuals seeking to lose or maintain weight. The prevalence of BE is higher in young obese women. However, BE is present also in men, elders and normal-weight subjects.
Homework Assignment Preference Scale for Science Courses: A Validity and Reliability Study

Homework assignments are have important role in learning process. In literature emphasizes that homework assignments do not attract students’ attention and that students do homework assignment just for the sake of formality. It is concretely argued that assigned homework assignment should take into consideration students’ preferences, interests, and needs. In this study, the “Homework Assignment Preference Scale” was developed to determine students’ homework assignment preferences within the scope of a science course. A pilot study was conducted with 155 middle school students, and the main study was conducted with 924 middle school students. Exploratory factor analysis and principal components analysis were conducted to ensure the construct validity of the scale. Hierarchical cluster analysis and confirmatory factor analysis were performed to confirm the emergent factor structures. Results showed that the scale was a valid and reliable tool.
Metabolism of Cryptic Peptides Derived from Neuropeptide FF Precursors: The Involvement of Insulin-Degrading Enzyme

The term “cryptome” refers to the subset of cryptic peptides with bioactivities that are often unpredictable and very different from the parent protein. These cryptic peptides are generated by proteolytic cleavage of proteases, whose identification in vivo can be very challenging. In this work, we show that insulin-degrading enzyme (IDE) is able to degrade specific amino acid sequences present in the neuropeptide pro-NPFFA (NPFF precursor), generating some cryptic peptides that are also observed after incubation with rat brain cortex homogenate. The reported experimental findings support the increasingly accredited hypothesis, according to which, due to its wide substrate selectivity, IDE is involved in a wide variety of physiopathological processes.
Bilateral recovering of sharp edges on feature-insensitive sampled meshes

A variety of computer graphics applications sample surfaces of 3D shapes in a regular grid without making the sampling rate adaptive to the surface curvature or sharp features. Triangular meshes that interpolate or approximate these samples usually exhibit relatively big error around the insensitive sampled sharp features. This paper presents a robust general approach conducting bilateral filters to recover sharp edges on such insensitive sampled triangular meshes. Motivated by the impressive results of bilateral filtering for mesh smoothing and denoising, we adopt it to govern the sharpening of triangular meshes. After recognizing the regions that embed sharp features, we recover the sharpness geometry through bilateral filtering, followed by iteratively modifying the given mesh's connectivity to form single-wide sharp edges that can be easily detected by their dihedral angles. We show that the proposed method can robustly reconstruct sharp edges on feature-insensitive sampled meshes.
Exploring the impact of sex and offence history on moral reasoning in adults with mild intellectual disabilities

Background: There is a small growing body of literature exploring moral reasoning in adult male offenders with mild intellectual disabilities (ID). These offenders have demonstrated more mature moral reasoning than their non-offending counterparts. No published studies have explored this in females with ID, despite the existence of sex differences in moral reasoning being widely debated. This study aims to address this gap in the literature. Methods: Using a cross-sectional 2 (Sex: Men vs Women) X 2 (Offence history: Offenders vs Non-Offenders) between-subjects design, 68 adults with mild ID from secure settings and community settings were recruited. In addition to an assessment of intellectual functioning, participants completed the Socio-Moral Reflection Measure- Short Form (SRM-SF; Gibbs, Basinger & Fuller, 1992) and the Emotional Problem Scale (EPS; Prout & Strohmer, 1991). An informant version of the EPS was also used. Results: Offenders with ID demonstrated stage 2(3) reasoning, significantly higher than the stage 2 reasoning demonstrated by non-offenders. Offenders’ moral reasoning was higher on six of the individual SRM-SF constructs, however differences disappeared on two constructs after controlling for Full Scale IQ. Non-offenders reasoned below stage 2 on the Law and Legal Justice constructs, where decision making driven by obeying authority and avoiding punishment was likely to have prevented them offending. No significant sex differences were found. Total SRM-SF scores were not significantly related to offence severity. A significant positive relationship was found between moral reasoning and emotional/behavioural problems, with the study partially supporting the prediction that offenders would have higher EPS scores. XV Conclusions: Offenders, irrespective of sex, engaged in more mature moral reasoning than non-offenders, supporting previous findings. This study attempted to address methodological limitations of previous studies, such as through using a measure standardised for ID. Further research would be valuable to help develop suitable and effective interventions for this client group.
Practical Resource Provisioning and Caching with Dynamic Resilience for Cloud-Based Content Distribution Networks

Content distribution networks (CDNs) built on clouds have recently started to emerge. Compared to conventional CDNs, cloud-based CDNs have the benefit of cost efficient hosting services without owning infrastructure. However, resource provisioning and replica placement in cloud CDNs involve a number of challenging issues, mainly due to the dynamic nature of demand patterns. To deal with this dynamic nature, this paper proposes a set of novel algorithms to solve the joint problem of resource provisioning and caching (i.e., replica placement) for cloud-based CDNs with an emphasis on handling the dynamic demand patterns. Firstly, we propose a provisioning and caching algorithm framework called Differential Provisioning and Caching (DPC) algorithm, which aims to rent cloud resources to build CDNs and whereby to cache contents so that the total rental cost can be minimized while all demands are served. DPC consists of 2 steps. Step 1 first maximizes total demands supported by unexpired resources. Then, step 2 minimizes the total rental cost for new resources to serve all remaining demands. For each step we design both greedy and iterative heuristics, each with different advantages over the existing approaches. Moreover, to dynamically adjusts the placement of contents and route maps, we further propose the Caching and Request Balancing (CRB) algorithm, which is light-weight and thus can be frequently executed as a companion of DPC to maximize the total demands. Performance evaluation results are presented to demonstrate the effectiveness and competitiveness of our approaches when compared to existing algorithms.
How well do children aged 5–7 years recall food eaten at school lunch?

Abstract Objective: This study aimed to determine the accuracy with which children aged 5 to 7 years were able to report the food eaten at a school lunch. Subjects/setting: Two hundred and three children (103 boys, 100 girls) aged 5–7 years were recruited from three primary schools in Oxford. Design: Trained investigators made observational records of the school dinner and packed lunch intakes of four or five children per session. Children were interviewed within two hours of finishing the lunchtime meal and asked to provide a free recall of their meal. When the child had completed the recall, non-directive prompts were used to assess if the child was able to remember anything else. Foods recalled were classified as matches (recalled food agreed with observation), omissions (failed to report a food observed) or phantoms (recalled food was not observed). Results: The percentage of accurate recall was significantly higher (P<0.01) in children eating packed lunch (mean 70±29%) than in children consuming school dinners (mean 58±27%). This difference may have been due to increased familiarity of foods in packed lunches. Leftovers were not readily reported in this age group. Prompts and cues enhanced recall by all children. Conclusions: This study indicated that there was a wide range in the ability of children aged 5–7 years to recall intake from a packed lunch and/or school dinner. This dietary assessment method is unlikely to be suitable at an individual level. Investigators using dietary recall to estimate food intake in children aged 5–7 years need to be aware of the limitations of this method.