Miracle-dz/UniFAR-FTUs huggingface dataset:
Children's high-level writing skills: development of planning and revising and their contribution to writing quality.

BACKGROUND It is well established that the activity of producing a text is a complex one involving three main cognitive processes: Planning, translating, and revising. Although these processes are crucial in skilled writing, beginning and developing writers seem to struggle with them, mainly with planning and revising. AIMS To trace the development of the high-level writing processes of planning and revising, from Grades 4 to 9, and to examine whether these skills predict writing quality in younger and older students (Grades 4-6 vs. 7-9), after controlling for gender, school achievement, age, handwriting fluency, spelling, and text structure. SAMPLE Participants were 381 students from Grades 4 to 9 (age 9-15). METHOD Students were asked to plan and write a story and to revise another story by detecting and correcting mechanical and substantive errors. RESULTS From Grades 4 to 9, we found a growing trend in students' ability to plan and revise despite the observed decreases and stationary periods from Grades 4 to 5 and 6 to 7. Moreover, whereas younger students' planning and revising skills made no contribution to the quality of their writing, in older students, these high-level skills contributed to writing quality above and beyond control predictors. CONCLUSION The findings of this study seem to indicate that besides the increase in planning and revising, these skills are not fully operational in school-age children. Indeed, given the contribution of these high-level skills to older students' writing, supplementary instruction and practice should be provided from early on.
Application of Reinforcement Learning in Development of a New Adaptive Intelligent Traffic Shaper

In this paper, we have taken advantage of reinforcement learning to develop a new traffic shaper in order to obtain a reasonable utilization of bandwidth while preventing traffic overload in other part of the network and as a result, reducing total number of packet dropping in the whole network. We used a modified version of Q-learning in which a combination of neural networks keeps the data of Q-table in order to make the operation faster while keeping the required storage as small as possible. This method shows satisfactory results in simulations from the aspects of keeping dropping probability low while injecting as many packets as possible into the network in order to utilize the free bandwidth as much as possible. On the other hand the results show that the system can perform in situations that are not originally designed to act in
Mid-price prediction based on machine learning methods with technical and quantitative indicators

Stock price prediction is a challenging task, in which machine learning methods have recently been successfully used. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical indicators and quantitative analysis and test their validity on short-term mid-price movement prediction for Nordic TotalView-ITCH stocks. The suggested feature list represents one of the most extensive studies in the field of financial feature engineering. We focus on a wrapper feature selection method using entropy, least-mean squares, and linear discriminant analysis. We also introduce a novel quantitative feature based on adaptive logistic regression for online learning. The proposed feature is consistently selected as the first feature among a large number of indicators used in this study. We further examine the best combinations of features using a high-frequency limit order book Nordic database. Our results suggest that sorting methods and classifiers can be used in such a way that one can reach the best classification performance with a combination of only a few advanced hand-crafted features.
Forensic content detection through power consumption

Digital forensic investigators are facing challenging problems of finding clues and solving crimes involving digital data. Advanced metering devices (smart meters) are being installed throughout electric networks in Europe and in the United States. The high-resolution energy consumption data which are transmitted by some smart meters to the utility company allow identification and monitoring of equipment within consumers' homes. Our research shows that the analysis of the household's electricity usage profile at a 0.5s-1 sample rate permits identification of audiovisual content. By collecting a single household smart meter data over a period of one month, our forensic results also show that audiovisual content identification is not heavily obstructed by typical electric appliance activities in a household.
Compact mmWave FMCW radar: Implementation and performance analysis

Due to an increasing demand in channel capacity and bandwidth, there has been a growing interest in the millimeter wave (mmWave) spectrum [1]-[3]. Many researchers overcame the challenges of implementing extremely high frequency systems and secured large bandwidths comparable to that of fiber optics [4]. The mmWave spectrum offers numerous advantages not only in the wireless communication field but also in the field of sensors and radar technology [5]. Indeed, transmitting shorter wavelengths helps radars achieve higher range accuracy with smaller antenna footprints.
Family medicine education in India: A panoramic view

Introduction: In the recent years, there has been renewed interest in strengthening primary care for improved health services delivery. Family medicine with its holistic principles is an effective approach for building primary care workforce in resource constraint settings. Even though this discipline is well established and mainstreamed in Western countries, the same is yet to occur in low- and middle-income nations. India with its paradigm shift for universal health coverage is strategically poised to embrace family medicine as a core component of its health system. However, till date, a clear picture of family medicine teaching across the country is yet to be available. Methods: This paper makes an attempt to assess the landscape of family medicine teaching in India with an aim to contribute to a framework for bolstering its teaching and practice in coming years. The objective was to obtain relevant information through a detailed scan of the health professional curricula as well as mapping independent academic programs. Specific areas of interest included course content, structure, eligibility criteria, and accreditation. Results: Our findings indicate that teaching of family medicine is still in infancy in India and yet to be mainstreamed in health professional education. There are variations in family medicine teaching across academic programs. Conclusion: It is suggested that both medical and nursing colleges should develop dedicated Departments of Family Medicine for both undergraduate and postgraduate teaching. Further, more number of standalone diploma courses adopting blended learning methods should be made available for in-service practitioners.
The Hox proteins Ubx and AbdA collaborate with the transcription pausing factor M1BP to regulate gene transcription

In metazoans, the pausing of RNA polymerase II at the promoter (paused Pol II) has emerged as a widespread and conserved mechanism in the regulation of gene transcription. While critical in recruiting Pol II to the promoter, the role transcription factors play in transitioning paused Pol II into productive Pol II is, however, little known. By studying how Drosophila Hox transcription factors control transcription, we uncovered a molecular mechanism that increases productive transcription. We found that the Hox proteins AbdA and Ubx target gene promoters previously bound by the transcription pausing factor M1BP, containing paused Pol II and enriched with promoter‐proximal Polycomb Group (PcG) proteins, yet lacking the classical H3K27me3 PcG signature. We found that AbdA binding to M1BP‐regulated genes results in reduction in PcG binding, the release of paused Pol II, increases in promoter H3K4me3 histone marks and increased gene transcription. Linking transcription factors, PcG proteins and paused Pol II states, these data identify a two‐step mechanism of Hox‐driven transcription, with M1BP binding leading to Pol II recruitment followed by AbdA targeting, which results in a change in the chromatin landscape and enhanced transcription.
Nutritional Modulation of the Inflammatory Bowel Response

Crohn’s disease and ulcerative colitis represent distinct phenotypic forms of inflammatory bowel disease and continue to be a common cause of morbidity. The corticosteroids and the immunomodulatory drugs, which are the basis of treatment for the inflammatory bowel diseases, do not assure always satisfactory outcomes. Nutrition has been used in order to modify the inflammatory response of various chronic inflammatory diseases, including Crohn’s disease and ulcerative colitis. In the pathogenesis of inflammatory bowel diseases, the intestinal microflora and the intestinal mucosal disorders play a crucial role. Also, the release of reactive oxygen species is a significant factor of initiation and preservation of the inflammatory reaction in these diseases. The advantages of the nutritional treatment derive from the sequestration of intraluminal agents which may promote the inflammatory bowel response or, alternatively, nutrition is able to modify the immune response, reducing the uncontrolled inflammatory reaction. Furthermore, nutrition can enhance the mucosal barrier function and consists a significant source of antioxidants. This review focuses on certain nutritional components that modulate the inflammatory response of the bowel and aims to present a rational thesis regarding the use of nutritional agents in the management of inflammatory bowel diseases.
Effect of neovestitol–vestitol containing Brazilian red propolis on accumulation of biofilm in vitro and development of dental caries in vivo

The present study examined the influences of the neovestitol–vestitol (NV) containing fraction isolated from Brazilian red propolis on the development of biofilm and expression of virulence factors by Streptococcus mutans using saliva-coated surfaces of hydroxyapatite. In addition, NV was tested in a rodent model of dental caries to assess its potential effectiveness in vivo. Topical applications of NV (800 μg ml−1) significantly impaired the accumulation of biofilms of S. mutans by largely disrupting the synthesis of glucosyltransferase-derived exopolysaccharides and the expression of genes associated with the adaptive stress response, such as copYAZ and sloA. Of even greater impact, NV was as effective as fluoride (positive control) in reducing the development of carious lesions in vivo. NV is a promising natural anti-biofilm agent that targets essential virulence traits in S. mutans, which are associated with the formation of cariogenic biofilm and the subsequent onset of dental caries disease.
Tracking Epithelial Cell Junctions in C. elegans Embryogenesis With Active Contours Guided by SIFT Flow

Quantitative analysis of cell shape in live samples is an important goal in developmental biology. Automated or semi-automated segmentation and tracking of cell nuclei has been successfully implemented in several biological systems. Segmentation and tracking of cell surfaces has been more challenging. Here, we present a new approach to tracking cell junctions in the developing epidermis of C. elegans embryos. Epithelial junctions as visualized with DLG-1::GFP form lines at the subapical circumference of differentiated epidermal cells and delineate changes in epidermal cell shape and position. We develop and compare two approaches for junction segmentation. For the first method (projection approach), 3-D cell boundaries are projected into 2D for segmentation using active contours with a nonintersecting force, and subsequently tracked using scale-invariant feature transform (SIFT) flow. The resulting 2-D tracked boundaries are then back-projected into 3-D space. The second method (volumetric approach) uses a 3-D extended version of active contours guided by SIFT flow in 3-D space. In both methods, cell junctions are manually located at the first time point and tracked in a fully automated way for the remainder of the video. Using these methods, we have generated the first quantitative description of ventral epidermal cell movements and shape changes during epidermal enclosure.
Opening the "Black Box" of Network Externalities in Network Adoption

Recent theoretical work suggests that network externalities are a determinant of network adoption. However, few empirical studies have reported the impact of network externalities on the adoption of networks. As a result, little is known about the extent to which network externalities may influence network adoption and diffusion. Using electronic banking as a context and an econometric technique calledhazard modeling, this research examines empirically the impact of network externalities and other influences that combine to determine network membership. The results support thenetwork externalities hypothesis. We find that banks in markets that can generate a larger effective network size and a higher level of externalities tend to adopt early, while the size of a bank's own branch network (a proxy for the opportunity cost of adoption)decreases the probability of early adoption.
Intraperitoneal treatment with antimicrobial peptide rescues mice from a pulmonary Francisella infection

Our long-term goal is to identify new antimicrobial peptides that might be effective against pneumonic Francisella infection in mice. Previously, our group searched the peptidome of the American alligator for novel cationic antimicrobial peptides and identified a naturally-occurring C-terminal fragment of apolipoprotein C-1, which we called Apo6. This peptide was found to have antibacterial activity against the ESKAPE pathogens, including those exhibiting multi-drug resistance. In this work, we tested Apo6 and synthetic derivatives for antibacterial activity against Francisella tularensis including the virulent strain F. tularensis SchuS4. Francisella is inherently highly resistant to the cyclic peptide polymyxin antibiotics and beta-lactam antibiotics. We found that our synthetic peptide derivatives (called GATR peptides), designed with increased hydrophobicity and charge, had generally stronger in vitro antimicrobial activity against Francisella than the parent peptide Apo6. The GATR peptides had a greater effect on the bacterial membrane than the Apo6 peptide and were able to bind Francisella LPS, suggesting their mechanism of action against Francisella. Cytotoxicity experiments showed low cytotoxicity for most of the GATR peptides, and whole organism toxicity studies in the waxworm allowed us to down-select to two our lead peptides, GATR-3 and GATR-6. These peptides were tested in a murine pulmonary tularemia model. We found that the GATR-3 peptide rescued 50-60% of mice from lethal tularemia infection when administered systemically through the intraperitoneal route. This peptide is a candidate for further pre-clinical studies for a potential peptide-based approach to tularemia.
Security Analyses of Click-based Graphical Passwords via Image Point Memorability

We propose a novel concept and a model of image point memorability (IPM) for analyzing click-based graphical passwords that have been studied extensively in both the security and HCI communities. In our model, each point in an image is associated with a numeric index that indicates the point's memorability level. This index can be approximated either by automatic computer vision algorithms or via human assistance. Using our model, we can rank-order image points by their relative memorability with a decent accuracy. We show that the IPM model has both defensive and offensive applications. On the one hand, we apply the model to generate high-quality graphical honeywords. This is the first work on honeywords for graphical passwords, whereas all previous methods are only for generating text honeywords and thus inapplicable. On the other hand, we use the IPM model to develop the first successful dictionary attacks on Persuasive Cued Click Points (PCCP), which is the state-of-the-art click-based graphical password scheme and robust to all prior dictionary attacks. We show that the probability distribution of PCCP passwords is seriously biased when it is examined with the lens of the IPM model. Although PCCP was designed to generate random passwords, its effective password space as we measured can be as small as 30.58 bits, which is substantially weaker than its theoretical and commonly believed strength (43 bits). The IPM model is applicable to all click-based graphical password schemes, and our analyses can be extended to other graphical passwords as well.
Complexity effective memory access scheduling for many-core accelerator architectures

Modern DRAM systems rely on memory controllers that employ out-of-order scheduling to maximize row access locality and bank-level parallelism, which in turn maximizes DRAM bandwidth. This is especially important in graphics processing unit (GPU) architectures, where the large quantity of parallelism places a heavy demand on the memory system. The logic needed for out-of-order scheduling can be expensive in terms of area, especially when compared to an in-order scheduling approach. In this paper, we propose a complexity-effective solution to DRAM request scheduling which recovers most of the performance loss incurred by a naive in-order first-in first-out (FIFO) DRAM scheduler compared to an aggressive out-of-order DRAM scheduler. We observe that the memory request stream from individual GPU ? shader cores? tends to have sufficient row access locality to maximize DRAM efficiency in most applications without significant reordering. However, the interconnection network across which memory requests are sent from the shader cores to the DRAM controller tends to finely interleave the numerous memory request streams in a way that destroys the row access locality of the resultant stream seen at the DRAM controller. To address this, we employ an interconnection network arbitration scheme that preserves the row access locality of individual memory request streams and, in doing so, achieves DRAM efficiency and system performance close to that achievable by using out-of-order memory request scheduling while doing so with a simpler design. We evaluate our interconnection network arbitration scheme using crossbar, mesh, and ring networks for a baseline architecture of 8 memory channels, each controlled by its own DRAM controller and 28 shader cores (224 ALUs), supporting up to 1,792 in-flight memory requests. Our results show that our interconnect arbitration scheme coupled with a banked FIFO in-order scheduler obtains up to 91% of the performance obtainable with an out-of-order memory scheduler for a crossbar network with eight-entry DRAM controller queues.
Wireless Network Pricing

Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing mechanisms influence the fast growing modern wireless industry. This book first covers the basics of wireless communication technologies and microeconomics, before going in-depth about several pricing models and their wireless applications. The pricing models include social optimal pricing, monopoly pricing, price differentiation, oligopoly pricing, and network externalities, supported by introductory discussions of convex optimization and game theory. The wireless applications include wireless video streaming, service provider competitions, cellular usage-based pricing, network partial price differentiation, wireless spectrum leasing, distributed power control, and cellular technology upgrade. More information related to the book (including references, slides, and videos) can be found at ncel.ie. cuhk.edu. hk/content/wireless-network-pricing. Table of Contents: Introduction / Wireless Communications Basics / Economics Basics / Social Optimal Pricing / Monopoly and Price Discriminations / Oligopoly Pricing / Network Externalities / Outlook
Image descriptors based on fractal transform analysis

The Fractal Transform (FT) was originally introduced as a methodology for compressing digital images and representing them at different scales. The process of calculating an FT, generates a great deal of information about the affine similarities and dissimilarities of an image, most of which is discarded in compression applications. In this paper, we introduce the concept of Fractal Transform Analysis, and use it to derive new image descriptors. We present results of experiments in which description schemes comprised of some of these FT-based descriptors are applied to the problems of finding objects in an image, similar to a given object, of indexing images, and of querying an image database consisting of about 17,000 images. Complexity and timing data are also presented.
Fast Discovery of Relevant Subgroups using a Reduced Search Space

We consider a modified version of the local pattern discovery task of subgroup discovery, where subgroups dominated by other subgroups are discarded. The advantage of this modified task, known as relevant subgroup discovery, is that it avoids redundancy in the outcome. Although it was considered in many applications, so far no efficient and exact algorithm for this task has been proposed. One particular problem is that the correctness is not guaranteed if the standard pruning approach is applied. In this paper, we devise a new algorithm based on two ideas: For one, we use the theory of closed sets for labeled data to reduce the candidate space; for another we introduce a special search space traversal which allows the use of optimistic estimate pruning while guaranteeing the correctness of the solution. We show that although our algorithm solves a more valuable task than other (classical) approaches, it outperforms all existing subgroup discovery algorithms.
Draft Genome Sequence of Haloalkaliphilic Exiguobacterium sp. AB2 from Manleluag Ophiolitic Spring, Philippines

ABSTRACT Exiguobacterium sp. AB2 is a haloalkaliphilic bacterium isolated from a hyperalkaline spring in Manleluag, Pangasinan, Philippines. Sequencing of bacterial DNA assembled a 2.85 MB draft genome. Analysis suggests the presence of genes for tolerance to stresses such as elevated pH and salt concentrations and toxic metals.