Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Chest Pain and Risk of Cardiovascular Disease with Coronary Atherosclerosis in Patients with Inflammatory Joint Diseases

Objectives The relation between chest pain and coronary atherosclerosis (CA) in patients with inflammatory joint diseases (IJD) has not been explored previously. Our aim was to evaluate the associations of the presence of chest pain and the predicted 10-year risk of cardiovascular disease (CVD) by use of several CVD risk algorithms, with CA verified by multidetector computed tomography (MDCT) coronary angiography. Methods Detailed information concerning chest pain and CVD risk factors was obtained in 335 patients with rheumatoid arthritis and ankylosing spondylitis. In addition, 119 of these patients underwent MDCT coronary angiography. Results Thirty-one percent of the patients (104/335) reported chest pain. Only six patients (1.8%) had atypical angina pectoris (pricking pain at rest). In 69 patients without chest pain, two thirds had CA, while in those who reported chest pain (n = 50), CA was present in 48.0%. In a logistic regression analysis, chest pain was not associated with CA (dependent variable) (p = 0.43). About 30% (Nagelkerke R2) of CA was explained by any of the CVD risk calculators: Systematic Coronary Risk Evaluation, Framingham Risk Score, or Reynolds Risk Score. Conclusion The presence of chest pain was surprisingly infrequently reported in patients with IJD who were referred for a CVD risk evaluation. However, when present, chest pain was weakly associated with CA, in contrast to the predicted CVD risk by several risk calculators which was highly associated with the presence of CA. These findings suggest that clinicians treating patients with IJD should be alert of coronary atherosclerotic disease also in the absence of chest pain symptoms.
Aggregated-Proof Based Hierarchical Authentication Scheme for the Internet of Things

The Internet of Things (IoT) is becoming an attractive system paradigm to realize interconnections through the physical, cyber, and social spaces. During the interactions among the ubiquitous things, security issues become noteworthy, and it is significant to establish enhanced solutions for security protection. In this work, we focus on an existing U2IoT architecture (i.e., unit IoT and ubiquitous IoT), to design an aggregated-proof based hierarchical authentication scheme (APHA) for the layered networks. Concretely, 1) the aggregated-proofs are established for multiple targets to achieve backward and forward anonymous data transmission; 2) the directed path descriptors, homomorphism functions, and Chebyshev chaotic maps are jointly applied for mutual authentication; 3) different access authorities are assigned to achieve hierarchical access control. Meanwhile, the BAN logic formal analysis is performed to prove that the proposed APHA has no obvious security defects, and it is potentially available for the U2IoT architecture and other IoT applications.
Probabilistic Analysis of a Motif Discovery Algorithm for Multiple Sequences

We study a natural probabilistic model for motif discovery that has been used to experimentally test the quality of motif discovery programs. In this model, there are $k$ background sequences, and each character in a background sequence is a random character from an alphabet $\Sigma$. A motif $G=g_1g_2\cdots g_m$ is a string of $m$ characters. Each background sequence is implanted into a probabilistically generated approximate copy of $G$. For an approximate copy $b_1b_2\cdots b_m$ of $G$, every character $b_i$ is probabilistically generated such that the probability for $b_i\neq g_i$ is at most $\alpha$. In this paper, we give the first analytical proof that multiple background sequences do help with finding subtle and faint motifs. This work is a theoretical approach with a rigorous probabilistic analysis. We develop an algorithm that under the probabilistic model can find the implanted motif with high probability when the number of background sequences is reasonably large. Specifically, we prove that for $\alpha 0$ such that if the length of the motif is at least $\delta_0\log n$, the alphabet has at least $t_0$ characters, and there are at least $\delta_1\log n_0$ input sequences, then in $O(n^3)$ time our algorithm finds the motif with probability at least $1-\frac{1}{2^x}$, where $n$ is the longest length of any input sequence and $n_0\leq n$ is an upper bound for the length of the motif.
Young People, Ethics, and the New Digital Media: A Synthesis from the GoodPlay Project

Social networking, blogging, vlogging, gaming, instant messaging, downloading music and other content, uploading and sharing their own creative work: these activities made possible by the new digital media are rich with opportunities and risks for young people. This report, part of the GoodPlay Project, undertaken by researchers at Harvard Graduate School of Education's Project Zero, investigates the ethical fault lines of such digital pursuits. The authors argue that five key issues are at stake in the new media: identity, privacy, ownership and authorship, credibility, and participation. Drawing on evidence from informant interviews, emerging scholarship on new media, and theoretical insights from psychology, sociology, political science, and cultural studies, the report explores the ways in which youth may be redefining these concepts as they engage with new digital media. The authors propose a model of "good play" that involves the unique affordances of the new digital media; related technical and new media literacies; cognitive and moral development and values; online and offline peer culture; and ethical supports, including the absence or presence of adult mentors and relevant educational curricula. This proposed model for ethical play sets the stage for the next part of the GoodPlay project, an empirical study that will invite young people to share their stories of engagement with the new digital media.The John D. and Catherine T. MacArthur Foundation Reports on Digital Media and Learning
Resource Allocation for OFDM System Based on Evolutionary Algorithm

The conventional resource allocation method is so-called two-step method in OFDM system. The two-step method can reduce the computational complexity. However, it's solution accuracy is not very good. This paper proposes an improved two-step method. This method combines evolutionary algorithm with simulated annealing thought, and can take into account the sub-carrier distribution and power distribution at the same time. Meanwhile this paper improves the evaluation criteria for fairness, so that the algorithm can better balance between capacity and fairness. Numerical experiments show that the proposed algorithm is effective.
A Performance Prediction Method with an Equation-Based Behavioral Model for a Single-Bit Single-Loop Sigma-Delta Modulator

An equation-based behavioral model has been developed to predict the real performance of a single-loop single-bit Sigma Delta Modulator SDM. By using this prediction flow, not only can the circuit specifications be acquired, including the gain, bandwidth, slew rate of the OPAMPs, and the capacitor value in the switched-capacitor circuits, but the real performance of the SDM can also be predicted. The switched-capacitor circuits according to the required circuit specifications are employed to design a fourth-order feed-forward FF SDM with an over-sampling ratio OSR of 64 and a bandwidth of 10kHz using a TSMC 0. 35i¾µm CMOS process. The measurement results reveal that the SDM with an input frequency of 2.5kHz and a supply voltage of 3.3V can achieve a dynamic range of 90dB and a spurious-free dynamic range SFDR of 85dB under the signal bandwidth of 10kHz and a sampling frequency of 1.28MHz, respectively. The precision of the equation-based behavioral model has been validated by experimental measurements, and its inaccuracy is less than 4%.
Unique and Overlapping Expression Patterns among Members of Photosynthesis-Associated Nuclear Gene Families in Arabidopsis1[W][OA]

Light provides crucial positional information in plant development, and the morphogenetic processes that are orchestrated by light signals are triggered by changes of gene expression in response to variations in light parameters. Control of expression of members of the RbcS and Lhc families of photosynthesis-associated nuclear genes by light cues is a paradigm for light-regulated gene transcription, but high-resolution expression profiles for these gene families are lacking. In this study, we have investigated expression patterns of members of the RbcS and Lhc gene families in Arabidopsis (Arabidopsis thaliana) at the cellular level during undisturbed development and upon controlled interference of the light environment. Members of the RbcS and Lhc gene families are expressed in specialized territories, including root tip, leaf adaxial, abaxial, and epidermal domains, and with distinct chronologies, identifying successive stages of leaf mesophyll ontogeny. Defined spatial and temporal overlap of gene expression fields suggest that the light-harvesting and photosynthetic apparatus may have a different polypeptide composition in different cells and that such composition could change over time even within the same cell.
Determinants of initiation, implementation, and discontinuation of amoxicillin by adults with acute cough in primary care

Aim To investigate the determinants of adherence to amoxicillin in patients with acute lower respiratory tract infection. Materials and methods Three European data sets were used. Adherence data were collected using self-reported diaries. Candidate determinants included factors relating to patient, condition, therapy, health care system/provider, and the study in which the patient participated. Logistic and Cox regression models were used to investigate the determinants of initiation, implementation, and discontinuation of amoxicillin. Results Although initiation differed across samples, implementation and discontinuation were similar. Determinants of initiation were days waited before consulting, duration of prescription, and being in a country where a doctor-issued sick certificate is required for being off work for <7 days. Implementation was higher for older participants or those with abnormal auscultation. Implementation was lower for those prescribed longer courses of amoxicillin (≥8 days). Time from initiation to discontinuation was longer for longer prescriptions and shorter for those from countries where single-handed practices were widespread. Conclusion Nonadherence to amoxicillin was largely driven by noninitiation. Differing sets of determinants were found for initiation, implementation, and discontinuation. There is a need to further understand the reasons for these determinants, the impact of poor adherence to antibiotics on outcomes, and to develop interventions to improve antibiotic use when prescribed.
Discovering Relevant Services in Pervasive Environments Using Semantics and Context

Recent advances have enabled provision and consumption of mobile services by small handheld devices. These devices have limited capability in terms of processing ability, storage space, battery life, network connectivity and bandwidth, which presents new challenges for service discovery architectures. As a result, there is an increased imperative to provide service requesters with services which are the most relevant to their needs, to mitigate wastage of precious device capacity and bandwidth. Service semantics must be captured to match services with requests, on meaning not syntax. Furthermore, requester and service context must be utilized during the discovery process. Thus, there is a need for a service discovery model that brings together ‘semantics’ and ‘context’. We present a case for bringing together semantics and context for pervasive service discovery by illustrating improved levels of precision and recall, or in other words increased relevance. We also present our model for integrating semantics and context for pervasive service discovery.
Enhancing multihop routing protocols in wireless sensor networks using LEACH-1R

Energy consumption is one of the most important factors in wireless sensors networks (WSN). In fact, many protocols have been modified to enhance the lifetime of deployed sensors networks. In our work, we are investigating multihop clustering protocols such as MR-LEACH and MH-LEACH as well as their modified version that integrate the LEACH-1R protocol that which aids to stabilize the network at the phase of clustering. Experimental results shows a clear advantage when LEACH-1R was integrated in both MR-LEACH and MH-LEACH in term of energy consumption, life time, and stability of the network when compared to their original version.
Minimum Distortion Data Hiding for Compressed Images

ACKNOWLEDGEMENTS Many people have contributed to this work. It is impossible to name all of them. I am thankful to everyone who has been with me during this incredible journey. I would like to thank my advisor Nikil Jayant first. He has been a role model to all of us. He has always provided support whenever we need, and never stopped believing in what we can do. His brilliance, attention and positive attitude towards life is always to be remembered. While working with Dr. Jayant, I had the chance of observing not only how a brilliant person tackles research problems, but how a great director interacts with people from very difficult backgrounds and walks of life to develop something together. I would like to thank Dr. Mersereau and Dr. Hayes next. I would like to thank them for the courses they have prepared for us and for their great contributions to CSIP and GCATT and to the academic culture of the school. Nothing would be the same without them. I would also like to thank Dr. Mynatt and Dr. Barry for being in my thesis committee. Finally, I would like to thank my friends, my supporters during difficult times and sources of joy in good ones. I believe Georgia Tech is great because of its students; not the other way around. I will always remember the days I was surrounded with curious, smart people; discussing books, movies and life in general. For some reason I am thinking that our days were the best days of my life. I hope life after school would prove me wrong. Here is a list that I want to keep within this document: Brian,
Massive developments of microbial mats following phytoplankton blooms in a naturally eutrophic bay: Implications for nitrogen cycling

Benthic nitrogen processes have received substantial attention because the release of nutrients from sediments can contribute to the requirements of pelagic primary production; their study can also give an estimation of the importance of the sediment as a source or a sink of nutrients. Concepción Bay is located in central Chile and is the largest (167.4 km2) and most enclosed embayment on the Chilean coastline. The bay is characterized by a strong hydrographic variability produced by the spring/summer seasonal upwelling of Equatorial subsurface waters (ESSW), rich in nutrients (~25 µM NO3−) and poor in oxygen (≪44.6 µM). The area was studied in order to understand the consequences of phytodetrital deposition and oxygen deficiency on the environment and benthic communities. The study was carried out by sampling at a single station (28‐m depth) in the inner part of the bay during winter (June 1998) and spring/summertime (November 1998 and January and March 1999). It was focused on measurements of benthic nitrogen fluxes, sulfate reduction, and denitrification rates before and after a phytoplankton bloom. Additionally, samples from the flocculent layer and from a semipurified bacterial mat were incubated under controlled oxygen conditions to determine NH4+ production. NH4+ exchange showed a clear seasonal pattern, with influxes during the winter (27.6 ± 4.9 mmol m−2 d−1) and high effluxes during the summer (36.6 and 20.8 mmol m−2 d−1) when the accumulation of fresh organic matter (evidenced as chlorophyll a) produced a flocculent layer over the sediments. Besides natural hypoxia of the bottom water associated with ESSW, the large input of organic matter resulted in anoxia within the sediment, as a consequence of respiration processes, and an enhancement in sulfate reduction rates (up to 200 mmol m−2 d−1). The flocculent layer then provided a favorable environment for the extensive development of Beggiatoa spp. mats. Overall, during the sampling period, NO3− was consumed at an average rate of 1.33 mmol m−2 d−1. In the summer, denitrification appeared to be partially inhibited by the very negative redox conditions and could explain only 24% of the NO3− uptake by the sediment. The balance may be due to NO3− incorporation into Beggiatoa spp. Short incubations with these bacteria suggest that they are able to produce NH4+ by dissimilatory NO3− reduction, taking advantage of their ability to store NO3−, though its uptake was not observed in these experiments. The NH4+ flux obtained using Beggiatoa spp. mat cultures was 5 mmol m−2 d−1, which accounts for 17% of the total NH4+ efflux during the summer period (January and March). The ecological implications of a large input of organic matter, evidenced by the presence of a flocculent benthic layer and Beggiatoa spp. , are discussed in relation to their contribution, during the upwelling season, toward the long‐term eutrophication of Concepcion Bay.
ADHD classification by a texture analysis of anatomical brain MRI data

The ADHD-200 Global Competition provides an excellent opportunity for building diagnostic classifiers of Attention-Deficit/Hyperactivity Disorder (ADHD) based on resting-state functional MRI (rs-fMRI) and structural MRI data. Here, we introduce a simple method to classify ADHD based on morphological information without using functional data. Our test results show that the accuracy of this approach is competitive with methods based on rs-fMRI data. We used isotropic local binary patterns on three orthogonal planes (LBP-TOP) to extract features from MR brain images. Subsequently, support vector machines (SVM) were used to develop classification models based on the extracted features. In this study, a total of 436 male subjects (210 with ADHD and 226 controls) were analyzed to show the discriminative power of the method. To analyze the properties of this approach, we tested disparate LBP-TOP features from various parcellations and different image resolutions. Additionally, morphological information using a single brain tissue type (i.e., gray matter (GM), white matter (WM), and CSF) was tested. The highest accuracy we achieved was 0.6995. The LBP-TOP was found to provide better discriminative power using whole-brain data as the input. Datasets with higher resolution can train models with increased accuracy. The information from GM plays a more important role than that of other tissue types. These results and the properties of LBP-TOP suggest that most of the disparate feature distribution comes from different patterns of cortical folding. Using LBP-TOP, we provide an ADHD classification model based only on anatomical information, which is easier to obtain in the clinical environment and which is simpler to preprocess compared with rs-fMRI data.
Annotare—a tool for annotating high-throughput biomedical investigations and resulting data

Summary: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis. Availability and Implementation: Annotare is available from http://code.google. com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows. Contact: rshankar@stanford.edu
Complicated Information Processing

We find that the complexity of information processing can delay the updating of prices to incorporate new information, and thus result in return predictability in the cross section of assets. In particular, we exploit a novel setting in which the exact same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-process firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this complicated processing yields returns of 117 basis points per month. Consistent with processing complexity driving the return relation, we further document that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sellside analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-process firms predict the future forecast revisions of more complicated firms. JEL Classification: G10, G11, G14
Separating Dynamic Consumer, Competitor and Company Response to Marketing Actions: Exclusion Restrictions on Var-Based Impulse Response Functions

Long-term marketing effectiveness is a high priority research topic for managers (Marketing Science Institute 2002), and recent research applied flexible models of dynamic market interactions to measure the net long-term performance impact of marketing actions. Unfortunately, this net long-term impact is challenging to interpret, as it emerges from the complex interplay among dynamic reactions of several market players. This paper introduces and formally compares restricted policy simulations based on structural VAR-models in order to distinguish three dynamic forces: consumer response, competitor response and company response.
Images as Spatial Sound Maps

tools for spatial composition typically model just a small subset of the spatial audio cues known to researchers. As composers explore this medium it has become evident that the nature of spatial sound perception is complex. Yet interfaces for spatial composition are often simplistic and the end results can be disappointing. This paper presents an interface that is designed to liberate the composer from thinking of spatialised sound as points in space. Instead, visual images are used to define sound in terms of shape, size and location. Images can be sequenced into video, thereby creating rich and complex temporal soundscapes. The interface offers both the ability to craft soundscapes and also compose their evolution in time. Keywordsaudio, surround sound, ambisonics, granular synthesis, decorrelation, diffusion.
How Informative is a Term?: Dispersion as a measure of Term Specificity

Similarity functions assign scores to documents in response to queries. These functions require as input statistics about the terms in the queries and documents, where the intention is that the statistics are estimates of the relative informativeness of the terms. Common measures of informativeness use the number of documents containing each term (the document frequency) as a key measure. We argue in this paper that the distribution of within-document frequencies across a collection is also pertinent to informativeness, a measure that has not been considered in prior work: the most informative words tend to be those whose frequency of occurrence has high variance. We propose use of relative standard deviation (RSD) as a measure of variability incorporating within-document frequencies, and show that RSD compares favourably with inverse document frequency (IDF), in both in-principle analysis and in practice in retrieval, with small but consistent gains.