Miracle-dz/UniFAR-FTUs huggingface dataset:
A Continuous-Time Sigma-Delta Modulator with a Hybrid Loop Filter and Capacitive Feedforward

A continuous-time (CT) sig ma -delta (ΣΔ) modulator clocked at 128 MHz with a hybrid active-passive loop filter is presented for WCDMA applications. The proposed 5 th -order loop filter arch itecture mainly consists of two passive integrators and three active integrators. To erase the summation amp lifier used in the chain of integrators with weighted feedforward summat ion (CIFF ) topology, the capacitive feedforward structure is employed. In addition, local feedback resistors form the bridge-T network to reduce the chip area. The p rototype chip is fabricated with TSM C 0.18 μm CMOS technology. Under the supply voltage of 1.8 V, measured results have achieved the best FOM of 2.67 pJ/conv, a dynamic range of 62 d B, a SNDR of 60.26 d B, an ENOB of 9.72 bit, IM3 of -48 d B and a power consumption of 9 mW over a 2 M Hz signal bandwidth. Including pads, the chip area is 0.642 (1.07 x 0.6) mm 2 .
Short Text Classification Using kNN Based on Distance Function

- In the present day circumstances nowadays, the scope of short text such as Twitter messages, blogs, chat massages, book and movie summaries, forum, news feeds, and customer review is increasing very drastically. These applications pose a tremendous challenge to the text classifications due to sparseness of the relevant data & lack of similarity between the words. Short text classification is nothing but a process of assigning various input short texts to one or more target categories based on its contents. Here we compared various algorithms such as Support Vector Machine, Naive Bayes, K-Nearest Neighbor, etc. . Based on this comparison I have selected knn for this. This paper includes various methods to reduce processing time and give good accuracy for testing instances.
No reward could be similar to penalty: Evidence from feedback negativity and P300

Previous studies have shown that two components of event-related potentials, the feedback negativity (FN) and P300, respond to feedback information of reward and penalty. The present study investigated the response of FN and P300 to neutral (neither reward nor penalty) outcome in an EEG level control task. Reward, penalty and neutral feedbacks were presented to participants randomly. The results showed that FN and P300 responded to the outcome information in a similar way. Both of them differed between reward condition and non-reward condition (penalty as well as neutral). It was noteworthy that neutral feedback elicited similar FN and P300 as penalty in amplitude, latency and scalp topography. This result may support an emotional-motivational mechanism that underlies a rapid but coarse early evaluation of the outcome information.
Integrated Plan-based Control of Autonomous Service Robots in Human Environments

In this article we present an overview of recent extensions to the RHINO system, a system for controlling autonomous robots. We identify computational principles that enable RHINO to accomplish complex, diverse, and dynamically changing tasks in human working environments. These principles include plan-based high-level control, probab ilistic reasoning, plan transformation, and context and resour ceadaptive reasoning. We show how these principles are incorporated into RHINO’s software modules. Long-term experiments demonstrate the practicality of our approach.
Combining Optical Character Recognition ( OCR ) and Edge Detection Techniques to Filter Image-Based Spam

Early spam filtering systems were designed for text-based spam format. However, the emergence and prevalence of image-based spam mails has resulted into newer challenges that renders mechanisms for filtering text-based spam mails inefficient for image-based spam. This research work employed pattern recognition (Grey scaling, edge detection and binarization) in combination with Object Character Recognition (OCR) mechanisms to analyze and classify image-based spam e-mails. The resulting system is an enhancement of existing OCR systems that suffers from the problem of noise generated around spam messages embedded in images. Findings from research show that the hybridized system outperforms OCR-based systems in terms of classification and efficiency.
Protein fold Classification with Genetic Algorithms and Feature Selection

Protein fold classification is a key step to predicting protein tertiary structures. This paper proposes a novel approach based on genetic algorithms and feature selection to classifying protein folds. Our dataset is divided into a training dataset and a test dataset. Each individual for the genetic algorithms represents a selection function of the feature vectors of the training dataset. A support vector machine is applied to each individual to evaluate the fitness value (fold classification rate) of each individual. The aim of the genetic algorithms is to search for the best individual that produces the highest fold classification rate. The best individual is then applied to the feature vectors of the test dataset and a support vector machine is built to classify protein folds based on selected features. Our experimental results on Ding and Dubchak's benchmark dataset of 27-class folds show that our approach achieves an accuracy of 71.28%, which outperforms current state-of-the-art protein fold predictors.
The Role of Realism and Anthropomorphism in the Selection of Avatars

In a project designed to test how viewers evaluate and choose avatars to represent them online, viewers (N = 261) evaluated 92 potential avatars that varied along three dimensions – gender of the image, anthropomorphism (humanness), and realism (veridicality). Consistent with the predictions of information processing theory, results indicated that anthropomorphic qualities increased perceived realism and subsequent homophily judgments. As predicted by the uncanny valley hypothesis, viewers preferred avatars with levels of realism and anthropomorphism matched and were more critical of imperfections of avatars with higher levels of anthropomorphism. Image gender and anthropomorphism were found to produce a combination of positive and negative effects on competence ratings and selection of avatars. The theoretical and practical implications of these visible feature effects of avatars are discussed.
Gait in Children with Attention-Deficit Hyperactivity Disorder in a Dual-Task Paradigm

The aim was to examine gait in school-aged children with attention-deficit hyperactivity disorder (ADHD) and typically developing controls in a dual-task paradigm. Thirty children with ADHD (without or off medication) aged 7–13 years and 28 controls walked without an additional task (single-task walking) and while performing a concurrent cognitive or motor task (dual-task walking). Gait was assessed using GAITRite recordings of spatiotemporal and variability gait parameters. Compared to single-task walking, dual-tasking significantly altered walking performance of children with and without ADHD, whereby dual-task effects on gait were not different between the two groups. For both children with ADHD and controls the motor concurrent task had a stronger effect on gait than the cognitive concurrent task. Gait in children with and without ADHD is affected in a dual-task paradigm indicating that walking requires executive functions. Future investigations of children's dual-task walking should account for the type of concurrent tasks.
Direct computation of shape from shading

A direct method for the recovery of surface shape from image shading is presented. The method in its basic form is applicable to shading patterns obtained when a distant overhead point light-source illuminates a convex or concave Lambertian surface possessing a single extremal point at which surface height has either a local maximum or local minimum. A key quality of the method is its ability to operate without explicit prerequisite information concerning the shape of the sought-after surface. Consideration is also given to the manipulation of images of more complex surface shapes.
NICOTINE CONTROL OF DOPAMINE SIGNALING IN THE VENTRAL TEGMENTAL AREA

Midbrain dopaminergic (DA) neurons signal motivational properties of natural reinforces and addictive drugs. Nico tine, like other drugs of abuse, boosts DA output from the ventral tegmental area (VTA). This increase results from direct stimulation of nicotinic acetylcholine recept ors (nAChRs) expressed in the VTA. However, how the DA signal is constructed in the VTA and how nicotine changes this signal remains controversial. In particular, in vivo and in vitro experimental paradigms reach contradictory conclusions about the key target of nicotine action: direct DA cell stimulation or indirect effects mediated through the GABAergic inter-neurons. We address these issues by building and analysing a computational model of the VTA circuitry and nAChR function, based on known activation and desensitization properties of the nAChR subtypes. We show that the apparent data mismatch between in vitro and in vivo recordings can be reconciled by differences in the afferent input activity. We find that the GABA cells are principle in causing nicotine dependent DA signals. We pin-point the specific contributions of various nAChRs to the DA signal. Finally, we show that DA neuron response to afferent inputs is altered in the presence of nicotine so a s to favor phasic dopaminergic release. These results identify mechanisms by which the VTA mediates the rewarding properties of nicotine that lead to addictive behavior.
The second edition of the MISRA C guidelines

Nine years ago, I finally finished a book entitled “Safer C”, (Hatton 1995). The theme of this book was not to promote the use of C in highintegrity and safety critical systems, but simply to make the point that uninhibited coding in this language was entirely inappropriate for such systems. However, if measures were in place to prevent the reoccurrence of very well known fault modes in this language, all the evidence suggested that C was just as capable of producing high reliability systems as any of the other programming languages . I defended this viewpoint with measurements on a large number of released systems and of course, we should never forget that in spite of a software process which would be deemed chaotic (level 1) by the Capability Maturity Model, the open source community has voluntarily produced one of the most reliable complex applications in history in this language, the Linux kernel. For example, on my office systems, we have now reached 15 server years without any failures on three different kernel releases, a level my Windows systems cannot even approach. We must also of course not forget that at the other end of the scale, some truly lamentable systems have been produced in the same language.
Optimization strategies for a java virtual machine interpreter on the cell broadband engine

Virtual machines (VMs) such as the Java VM are a popular format for running architecture-neutral code in a managed runtime. Such VMs are typically implemented using a combination of interpretation and just-in-time compilation (JIT). A significant challenge for the portability of VM code is the growing popularity of multi-core architectures with specialized processing cores aimed at computation-intensive applications such as media processing. Such cores differ greatly in architectural design compared to traditional desktop processors. One such processing core is the Cell Broadband Engine's (Cell BE) Synergistic Processing Element (SPE). An SPE is a light weight VLIW processor core with a SIMD vector instruction set. In this paper we investigate some popular interpreter optimizations and introduce new optimizations exploiting the special hardware properties offered by the Cell BE's SPE
Self-Indexed Grammar-Based Compression

Self-indexes aim at representing text collections in a compressed format that allows extracting arbitrary portions and also offers indexed searching on the collection. Current self-indexes are unable of fully exploiting the redundancy of highly repetitive text collections that arise in several applications. Grammar-based compression is well suited to exploit such repetitiveness. We introduce the first grammar-based self-index. It builds on Straight-Line Programs (SLPs), a rather general kind of context-free grammars. If an SLP of n rules represents a text T[1, u], then an SLP-compressed representation of T requires 2n log 2 n bits. For that same SLP, our self-index takes O(n log n) + n log 2 u bits. It extracts any text substring of length m in time O((m + h) log n), and finds occ occurrences of a pattern string of length m in time O((m(m + h) + h occ) log n), where h is the height of the parse tree of the SLP. No previous grammar representation had achieved o(n) search time. As byproducts we introduce (i) a representation of SLPs that takes 2n log 2 n(1 + o(1)) bits and efficiently supports more operations than a plain array of rules; (ii) a representation for binary relations with labels supporting various extended queries; (iii) a generalization of our self-index to grammar compressors that reduce T to a sequence of terminals and nonterminals, such as Re-Pair and LZ78.
The use of multiple displacement amplification to amplify complex DNA libraries

Complex libraries for genomic DNA and cDNA sequencing analyses are typically amplified using bacterial propagation. To reduce biases, large numbers of colonies are plated and scraped from solid-surface agar. This process is time consuming, tedious and limits scaling up. At the same time, multiple displacement amplification (MDA) has been recently developed as a method for in vitro amplification of DNA. However, MDA has no selection function for the removal of ligation multimers. We developed a novel method of briefly introducing ligation reactions into bacteria to select single insert DNA clones followed by MDA to amplify. We applied these methods to a Gene Identification Signatures with Paired-End diTags (GIS-PET) library, which is a complex transcriptome library created by pairing short tags from the 5′ and 3′ ends of cDNA fragments together, and demonstrated that this selection and amplification strategy is unbiased and efficient.
Effect of Zoledronate on Oral Wound Healing in Rats

Purpose: Osteonecrosis of the jaw (ONJ) is a growing concern in patients who receive bisphosphonates that target osteoclasts. As osteoclasts play multifunctional roles in the bone marrow, their suppression likely affects bone homeostasis and alters wound healing of the jaw. The objective was to delineate the impact of osteoclast suppression in the bone marrow and wound healing of the jaw. Experimental Design: Zoledronate was administered to senile rats for 14 weeks. A portion of the gingiva was removed to denude the palatal bone. Gene expression in the bone marrow was assessed and histologic sections were analyzed to determine the wound healing status. Results: Angiogenesis-related genes, CD31 and VEGF-A, were not altered by zoledronate. VEGF-C, which plays a role in lymphangiogenesis, was suppressed. There was a decrease in gene expression of Tcirg1 and MMP-13. Bone denudation caused extensive osteocyte death indicative of bone necrosis. In zoledronate-treated rats, the necrotic bone was retained in the wound while, in controls, osteoclastic resorption of the necrotic bone was prominent. Even though large necrotic bone areas existed in zoledronate-treated rats, overlaying soft tissue healed clinically. Immunohistochemical staining showed rich vascularity in the overlaying soft tissue. Conclusions: Zoledronate therapy impacts bone marrow by suppressing genes associated with lymphangiogenesis and tissue remodeling, such as VEGF-C and MMP-13. Zoledronate was associated with impaired osseous wound healing but had no effect on angiogenic markers in the bone marrow or soft tissue wound healing. Zoledronate selectively blunts healing in bone but does not affect soft tissue healing in the oral cavity. Clin Cancer Res; 17(6); 1405–14. ©2010 AACR.
Risk factors of caregiver burden among patients with Alzheimer's disease or related disorders: a cross-sectional study.

BACKGROUND Caregivers play a major role in the care of patients with dementia and are themselves at higher risk of disease. OBJECTIVES We investigate which factors are associated with caregivers burden of outpatients visiting a memory clinic and how functional autonomy and behavioral and psychological symptoms can influence caregiver burden. METHODS The study population was chosen from outpatients with progressive cognitive complaint. The caregiver burden was measured with the short version of the Zarit Burden Interview (ZBI). The relationship was assessed between the ZBI and the patients characteristics, including Neuropsychiatric Inventory (NPI), Instrumental Activities of Daily Living scale (IADL), the Mini-Mental State Examination (MMSE), etiology, and stage of the cognitive impairment. RESULTS In a population of 548 patients, IADL, NPI, antidepressant drugs, and MMSE were found to be related to ZBI, while diagnosed etiology and disease stage were not significant: ZBI decreased by 0.34 point for every unit of IADL, and by 0.03 point for every unit of MMSE; ZBI increased by 0.03 point for every unit of NPI. From the IADL scale, the ability to handle finances, food preparation, responsibility to take medications, mode of transportation, and ability to use the telephone increased the ZBI. Five areas of the NPI increased the ZBI: apathy, agitation, aberrant motor behavior, appetite disorders (p < 0.001), and irritability (p = 0.03). CONCLUSION Caregivers experience a higher burden due to disease symptoms such as impairment of functional autonomy and behavioral and cognitive impairment, whatever the etiology of the cognitive decline.
Who is More Free? A Comparison of the Decision-Making of Private and Public School Principals

ABSTRACT While substantial school choice research focuses on student achievement outcomes, little has explored the mechanisms involved in producing such outcomes. We present a comparative analysis of private and public school principals using data from the School and Staffing Survey (SASS) 2011–2012. We add to the literature by examining the differences in private and public school principals’ abilities to influence important decisions at their schools from a nationally representative sample of 9,230 school principals. Results indicate that private school leadership exhibits more autonomy in influencing school level policies, perhaps explaining private school advantages.
The Gigue Is Up: High Culture Gets Game

This paper documents the design, development, and extensive play-testing of a Flash-based Baroque music game, “Tafelkids: The Quest for Arundo Donax”, focusing on the tension between constructing an online resource that an audience aged 8-14 would find fun and engaging, and the directive to include historical information and facts, as well as convey some of the sounds, musical structures and conventions of Baroque music, history and culture through play. We further document 3 large play testing sessions, in which we observed, in total, over 150 students aged 12-14 play the game. We conclude with a discussion of the particular challenges in designing a bridge from propositions to play, in effect digitally re-mediating, Baroque music education and thereby address the broader epistemological question of what and how we may best learn, and learn best, from games and play.
On the Effect of Fluctuating Recombination Rates on the Decorrelation of Gene Histories in the Human Genome

We show how to incorporate fluctuations of the recombination rate along the chromosome into standard gene-genealogical models for the decorrelation of gene histories. This enables us to determine how small-scale fluctuations (Poissonian hot-spot model) and large-scale variations (Kong et al. 2002) of the recombination rate influence this decorrelation. We find that the empirically determined large-scale variations of the recombination rate give rise to a significantly slower decay of correlations compared to the standard, unstructured gene-genealogical model assuming constant recombination rate. A model with long-range recombination-rate variations and with demographic structure (divergent population) is found to be consistent with the empirically observed slow decorrelation of gene histories. Conversely, we show that small-scale recombination-rate fluctuations do not alter the large-scale decorrelation of gene histories.
T HE RECOGNITION SYSTEM OF SENTENTIAL NOUNS PHRASE STRUCTURE USING CONDITIONAL R ANDOM F IELD MODEL

The important problem of word segmentation in Thai language is sentential noun phrase. The existing studies try to minimize the problem. But there is no research that solves this problem directly. This study investigates the approach to resolve this problem using conditional random fields which is a probabilistic model to segment and label sequence data. The results present that the corrected data of noun phrase was detected more than 78.61 % based on our technique.
Pull-Driven Scheduling for Pipe-Spool Installation: Simulation of Lean Construction Technique

Many construction processes include installation of unique materials in specific locations in the facility being built: materials and locations must match before installation can take place. Mismatches due to delay and uncertainty in supplying materials or completing prerequisite work at those locations hamper field productivity. This is illustrated here using a model of a materials-management process with a matching problem that typifies fast-track process-plant projects. The uniqueness of materials and locations combined with the unpredictability in duration and variation in execution quality of various steps in the supply chain allow for different ways to sequence material delivery and work area completion. Several alternatives are described. Their impact on process execution is illustrated by means of probabilistic process models. One model reflects total lack of coordination between delivery and work area completion prior to the start of construction; a second one describes perfect coordination. The corresponding materials staging buffers and construction progress are plotted based on output from discrete-event simulation models. A third probabilistic model then illustrates the use of the lean construction technique called pull-driven scheduling. Real-time feedback regarding the status of progress on site is provided to the fabricator off site so process steps can be re-sequenced opportunistically. This yields smaller buffers and earlier project completion and, when properly accounted for, increased productivity.
Backpropagation for Neural Dnf{ and Cnf{networks

The architecture of a neural network with its links and weights can be viewed as a knowledge representation. To overcome the black{box problem of not knowing what knowledge is hidden in a neural architecture, we present a strictly logically operating network. Each neuron represents either a disjunc-tion or conjunction of its inputs and the net thus performs the function of a logic formula. This formula can be extracted from the net after completed training. The well{known backpropagation algorithm is adapted to train such logical neural nets. An on{line pruning algorithm is also implemented to eliminate redundant weights.