Miracle-dz/UniFAR-FTUs huggingface dataset:
Involvement of a Non-Human Sialic Acid in Human Cancer

Sialic acids are common monosaccharides that are widely expressed as outer terminal units on all vertebrate cell surfaces, and play fundamental roles in cell–cell and cell–microenvironment interactions. The predominant sialic acids on most mammalian cells are N-glycolylneuraminic acid (Neu5Gc) and N-acetylneuraminic acid (Neu5Ac). Neu5Gc is notable for its deficiency in humans due to a species-specific and species-universal inactivating deletion in the CMAH gene encoding the hydroxylase that converts CMP-Neu5Ac to CMP-Neu5Gc. However, Neu5Gc is metabolically incorporated into human tissues from dietary sources (particularly red meat), and detected at even higher levels in some human cancers. Early life exposure to Neu5Gc-containing foods in the presence of certain commensal bacteria that incorporate dietary Neu5Gc into lipooligosaccharides can lead to generation of antibodies that are also cross-reactive against Neu5Gc-containing glycans in human tissues (“xeno-autoantigens”). Such anti-Neu5Gc “xeno-autoantibodies” are found in all humans, although ranging widely in levels among individuals, and displaying diverse and variable specificities for the underlying glycan. Experimental evidence in a human-like Neu5Gc-deficient Cmah−/−mouse model shows that inflammation due to “xenosialitis” caused by this antigen–antibody interaction can promote tumor progression, suggesting a likely mechanism for the well-known epidemiological link between red meat consumption and carcinoma risk. In this review, we discuss the history of this field, mechanisms of Neu5Gc incorporation into tissues, the origin and specificities of human anti-Neu5Gc antibodies, their use as possible cancer biomarkers, implications of xenosialitis in cancer initiation and progression, and current and future approaches toward immunotherapy that could take advantage of this unusual human-specific phenomenon.
Radiographic Pneumonia in Young, Highly Febrile Children With Leukocytosis Before and After Universal Conjugate Pneumococcal Vaccination

Objectives: Studies before the introduction of conjugate pneumococcal vaccine demonstrated a high rate of radiographic pneumonia among highly febrile young children with leukocytosis and no other identified source of infection. We sought to evaluate the impact of universal vaccination with Prevnar (pneumococcal conjugate vaccine [PCV]) on the incidence and characteristics of occult and nonoccult radiographic pneumonia among these children. Methods: Retrospective cohort study of children younger than 5 years seen in an urban pediatric emergency department with temperature 39°C or higher, white blood cell count 20,000/&mgr;L or higher, and chest radiograph performed. Pneumonia was defined as focal infiltrate or consolidation on chest radiograph as read by an attending radiologist. Occult pneumonia was defined as radiographic pneumonia in the absence of lower respiratory tract signs or cough. Results: Before universal pneumococcal vaccination, radiographic pneumonia was found in 190 (21%) of 889 (95% confidence interval [CI], 19-24) eligible children compared with 61 (18%) of 335 (95% CI: 14, 23) eligible children after universal vaccination (P = 0.27). Occult pneumonia was identified in 61 (15%) of 404 (95% CI, 12-19) pre-PCV compared with 13 (9%) of 147 (95% CI, 5-15) post-PCV (P = 0.07). In children younger than 2 years, radiographic pneumonia was identified in 121 (17%) of 709 (95% CI, 14-20) pre-PCV and 26 (10%) of 254 (95% CI, 7-15) post-PCV (P = 0.01). Conclusions: Clinicians should continue to consider chest radiography in young highly febrile children with leukocytosis and no other identified source of infection.
Methods for Efficient Network Coding

I. INTRODUCTION Random linear network coding is a multicast communication scheme in which all participating nodes send out coded packets formed from random linear combinations of packets received so far. This scheme is capacity-achieving for single sessions over lossy wireline or wireless packet networks [1], [2], [3], [4]. Thus, from the point of view of efficiently utilizing transmissions, random linear network coding is an attractive strategy. However, it is not presently attractive from the point of view of efficiently utilizing computational resources. To decode a k-packet-long message, a decoder needs to invert a k×k dense matrix, which, using Gaussian elimination, requires O(k 3) operations (or O(k 2) operations per input symbol). Once the matrix inverse is computed, applying the inverse to the received coded packets to recover the message requires O(k 2) operations (or O(k) operations per input symbol). Although the former computation is more costly than the latter as a function of k, it is usually the latter cost that dominates, since the latter computation depends on the length of the packets (which is usually on the order of kilobytes), while the former does not. This dominant cost can make the computational resources required for random linear network coding prohibitive [5]. But a random linear code is a somewhat na¨ıve code. By picking the code randomly, we ensure that the code is efficient at communicating information but, at the same time, by employing little design in the code, we obtain a code that is computationally inefficient. Thus, a natural code design question arises: can we design a network code that preserves the communication efficiency of a random linear code and achieves better computational efficiency? In this paper, we give an affirmative answer to this question. The code that we present as our answer achieves significantly better computational efficiency and is based primarily on techniques that are now quite standard in the literature on erasure codes. That said, our application of these techniques to network coding requires some novel ideas. First, we partition
Online Error Detection for High Data Rate Distributed Applications

Laguna Peralta, Ignacio. M.S.E.C. E. , Purdue University, Ago 2008. Online Error Detection for High Data Rate Distributed Applications. Major Professor: Saurabh Bagchi. Distributed systems comprising interacting services need runtime error detection to catch errors arising from software bugs, hardware errors, or unexpected operating conditions. A significant class of detection systems performs detection at the application level, based on the state of the application. For example, rule-based systems match rules against the application’s state deduced by the detection system at runtime. Many largescale distributed applications generate a high rate of messages which can overwhelm the capacity of the detection system. An approach to handle this is sampling, that is, processing only a fraction of the messages. However, this approach leads to nondeterminism with respect to the detection system’s view of what state the application is in. This in turn leads to inaccuracies in matching state-based rules causing degradation in the quality of detection. In this work, we present an approach to select the messages to sample and process such that the non-determinism is minimized. Next, we present a Hidden Markov Model-based technique to probabilistically identify which application states are most likely so that the detection system can perform rule-based detection for only those states. We demonstrate the techniques in a detection system called Monitor applied to a Java-based three-tier online banking system. The techniques do not need application modifications or a priori application model, but do require knowledge of expected application behavior to come up with the rules. We empirically evaluate accuracy and precision of detection under different load conditions and compare our solution with two other state-of-the-art systems: Pinpoint and Convolution algorithm.
Electrocardiography for the diagnosis of left ventricular hypertrophy: revisiting an old friend in times of austerity.

H ypertension (HTN) is the most important risk factor for the development of left ventricular hypertrophy (LVH). In hypertensive patients, LVH occurs as a compensatory adaptation to pressure overload. It is difficult to determine the exact prevalence of LVH in hypertensive populations. Apart from drawbacks related to different diagnostic modalities and the criteria used, there are additional multiple inherent difficulties in hypertensives: uncertainty about the severity and duration of hypertension, the intensity of treatment, the patients’ compliance, the duration and type of treatment. The latter have significant effects on left ventricular mass of a given hypertensive population [1]. Of particular value may be studies in untreated HTN populations, indicating prevalence of LVH up to 50%. Overall, it seems that the incidence of echocardiographically diagnosed LVH is about 20–30% in patients with mild–moderate HTN and 50–60% in those with severe HTN [2]. The diagnosis of LVH can be made by several ways but most commonly it is identified by the ECG; however, the most sensitive method is the echocardiogram (Echo). Regardless of the diagnostic modality, LVH is an independent risk factor as strong as age for predicting future cardiovascular events, including myocardial infarction, stroke, sudden cardiac death and heart failure [3]. ECG data from the Framingham study showed that new development of LVH carried relative risk for coronary heart disease (CHD) of approximately two-to-five fold in men and 1.5 fold in women [2]. The presence also of depolarization abnormalities identifies individuals with LVH who are at increased risk for CHD. In studies with Echo – validated LVH, adjusted relative risk of cardiovascular disease is 50% higher for each 50 g/m increase in left ventricular mass index (LVMI) in both men and women. Concentric hypertrophy
Adaptively Weighted Association Statistics Methods Motivation for Efficiency of Subgroup Weighting

We investigate methods for testing gene-disease outcome associations in situations where the genetic relationship potentially varies among subjects with differing environmental or clinical attributes. We propose a strategy which modestly increases multiple testing by evaluating weighted test statistics which focus (or enrich) association tests within subgroups and use a Monte-Carlo method, based on simulating from the approximate large sample distribution of the statistics, to control type 1 error. We also introduce a stage-wise calculated test statistic which allows more complex weighting on multiple environmental variables. Results from simulation studies confirm improved power of the proposed approaches compared to marginal testing in many situations. INTRODUCTION Assessing the association of genomic attributes with disease outcomes is an important and ongoing area of applied research. Commonly, many univariate marginal tests are calculated for a large number of genomic features. For instance, in human genetic association studies with single nucleotide polymorphisms (SNPs) thousands of SNPs are tested for association with disease outcomes. However, given the typical focus on univariate or marginal testing, there are concerns that more complex relationships , such as multiple genes acting in concert or gene-environment (or gene-treatment) interactions, could attenuate the marginal effect size and reduce the power to detect true associations. For instance, the association of the gene with survival may be present only in smokers or prior smokers, or in patients taking a specific treatment. One strategy is to exhaustively test gene-environment interactions in addition to testing marginal gene associations with outcome. However, interaction testing with many genes is often more difficult due to limited power and can lead to conducting a very large number of tests. Alternatively, if there is reason to suspect that the genetic association is stronger within a subgroup of subjects with specific treatment or set of clinical/environmental attributes , other more powerful test statistics can be constructed. We propose computationally simple test statistics that can exploit such subgroup associations if they exist. The goal is to modestly increase the search by weighting the association tests within subgroups of subjects. We note that constructing tests based on ordered overlapping subgroups of subjects has been previously investigated for linkage analysis [Hauser et al., 2004]. In that case, partial sums of lod scores were calculated for families ranked on a covariate interest. We also introduce a natural extension of the subgroup statistics motivated by statistical ''boosting'' to define weights. A subgroup weighted test can be more …
Cataract blindness: challenges for the 21st century

Cataract prevalence increases with age. As the world's population ages, cataract-induced visual dysfunction and blindness is on the increase. This is a significant global problem. The challenges are to prevent or delay cataract formation, and treat that which does occur. Genetic and environmental factors contribute to cataract formation. However, reducing ocular exposure to UV-B radiation and stopping smoking are the only interventions that can reduce factors that affect the risk of cataract. The cure for cataract is surgery, but this is not equally available to all, and the surgery which is available does not produce equal outcomes. Readily available surgical services capable of delivering good vision rehabilitation must be acceptable and accessible to all in need, no matter what their circumstances. To establish and sustain these services requires comprehensive strategies that go beyond a narrow focus on surgical technique. There must be changes in government priorities, population education, and an integrated approach to surgical and management training. This approach must include supply of start-up capital equipment, establishment of surgical audit, resupply of consumables, and cost-recovery mechanisms. Considerable innovation is required. Nowhere is this more evident than in the pursuit of secure funding for ongoing services.
Resource Allocation with Budgets : Optimal Stable Allocations and Optimal Lotteries ∗

We introduce the resource allocation problem where a planner needs to purchase different resources from providers of different qualities and costs, and the planner allocates the resources/providers to consumers with different preferences. The planner has a budget that limits how much he can spend on the resources. He wants to maximize the social welfare generated from the consumers, while keeping his total expenditure for purchasing the resources within his budget. Previous studies have either focused on the resource acquisition part, with one buyer and many strategic sellers, or the resource allocation part, with one seller and many strategic buyers. This is for the first time both providers and consumers are included in the picture. The consumers do not pay for the resources and will act to maximize their individual utilities. Thus the planner must use proper rationing tools to make sure that they will stick to the providers allocated to them. Two widely existing rationing tools are studied in this paper: waiting times and lotteries (and the combination of them). We characterize (sometimes partially) the structures of optimal allocation schemes when different rationing tools are used, and we identify conditions under which lotteries can do better and under which waiting times can do better. We also settle the computation complexity for computing/approximating them. For resource allocation with waiting times, we show that the optimal solution is NP-hard to find, and we construct an FPTAS for it. For resource allocation with lotteries, we show that for a large class of the problem the optimal solution has a surprisingly simple structure, and can be solved by a linear program. Following our results, neither waiting time nor lottery is absolutely better than the other in terms of generating social welfare. A planner should choose an appropriate tool based on the conditions that we identify. Our results then let the planner computes/approximates the corresponding optimal allocations efficiently. Indeed, our results are the first systematic study of both rationing tools when resource acquisition and resource allocation occur together (which is often the case in real life), and we provide useful approaches for future study on this more general and realistic model.
Personalized location aware recommendation system

A Personalized location aware recommendation system has been designed and evaluated in this paper. The idea is to infer user's preferences and thus to recommend nearby locations such as hospitals, food courts, shopping and so on. User's current search contexts are rarely considered by the well known location recommendation system named FOURSQUARE (https://foursquare.com/). Thus, the paper enhances the system by incorporating personalization features to provide personalized location suggestions based on users' preferences. Typical recommender systems make use of community opinions/reviews to help users identify useful items from a large search space e.g., Search for nearby health care centre or hospital specialized for heart problems, restaurant specialized for vegetarian, etc. The technique used by current systems is collaborative filtering algorithm which analyzes reviews from group of people to find correlations of similar users and to suggest top items to a querying user. The limitation with considering group opinions is that individual user preferences are not leveraged. Thus the proposed system analyzes location aware reviews in order to understand the community user experiences and further it is matched with a specific user search preference to suggest preferable locations for meeting their goal especially when they are in a new place.
The Neural Basis of Imitation is Body Part Specific

Imitation is an important constituent of the behavioral repertoire of human beings. We use imitation for learning motor skills, for facilitating comprehension of other persons’ actions and mental states, and as a communicative reference to actions or people. Although some non-human species display imitative behaviors, none of them equals the versatility and perfection of human imitation. The versatility and apparent ease of human imitation is, however, not at all self-evident when one considers the neural and cognitive transformations that must be accomplished for successful imitation. Imitation of meaningless gestures poses a particular challenge for our brain, because similarity between the body of the model and one’s own body must bridge fundamental differences between the perspective and modalities of perceiving and controlling one’s own and other bodies. We analyzed the locations of left-hemisphere lesions disturbing imitation of meaningless gestures and found a clear-cut body part specificity. Disturbed imitation of finger postures was associated with anterior lesions including the opercular portion of the inferior frontal gyrus, whereas disturbed imitation of hand postures was associated with posterior lesions affecting the inferior parietal lobule and temporo-parieto-occipital junction. These locations do not correspond with known somatotopic maps of motor representations. Rather, they argue for an intermediate step of processing interpolated between perception and execution of gestures as has been suggested by the mirror neuron and the body part coding hypotheses.
Cooperation via Social Networks

Abstract Sufficiently frequent interaction between partners has been identified by, a.o. , Axelrod as a more-or-less sufficient condition for stable cooperation. The underlying argument is that rational cooperation is ensured if short-term benefits from opportunistic behavior are offset by the long-term costs of sanctions imposed on the culprit. In this paper, we develop a model for ‘embedded trust’ in which a trustee interacts with a number of trustors who may communicate via a social network with each other about the behavior of the trustor. The analysis reconfirms the standard predictions about how the level of trust depends on the payoffs and shadow of the future. We provide new predictions both on between-network effects (“which network is more favorable for cooperation? ”) and on within-network effects (“in what network position can you trust more? ”).
Four Critical Years: A Methodological Review

Astin's Four Critical Years, despite its large amount of data presenta­ tion and empirical emphasis, is not a research report and apparently was never intended to be. Rather is it a summary of findings and conclusions drawn from a massive and complex research effort, with major emphasis on the author's interpretations and suggestions for policy, and only a modicum of attention to methodological detail. Researchers will, as a consequence, pro­ bably find the book itself incomplete and insufficient to let them understand exactly how the study was carried out and how some of the conclusions and policy implications were derived. Less technically-oriented professionals, such as policymakers and decision-makers in higher education will, however, ask such broader questions of the study's methodology, as:
Margin Trading from A to Z: A Complete Guide to Borrowing, Investing and Regulation

Preface. About the Author. Chapter 1. Cash Accounts. Sale of Securities. Paying for Securities by the Sale of Other Securities. Delivery against Payment. Employee Stock Options. Chapter One Questions. Chapter 2. Initial Federal Margin Requirements. Purchases. Sales. Meeting a Margin Call. Chapter Two Questions. Chapter 3. Initial and Minimum Maintenance Requirements. Initial Requirements. House Requirements. NYSE Minimum Maintenance Requirements. Chapter Three Questions. Chapter 4. The Special Memorandum Accounts. Customer's Account. Chapter Four Questions. Chapter 5. Short Sales. Covering Short Sales. NYSE Minimum Maintenance Requirements. Sample Transactions. Short Sale versus the Box or Short against the Box. Prime Broker. Chapter Five Questions. Chapter 6. Bonds. U.S. Government Securities. Zero-coupon Government Obligations. Municipals. Nonconvertible Corporate Bonds. Chapter Six Questions. Chapter 7. Miscellaneous Categories. When-Issued and When-Distributed Transactions. Segregation of Customer's Securities. Review of Customers' Accounts. Interest charges. Margin of New Issues. Day trades. Chapter Seven Questions. Chapter 8. Options. Definition. Additional Definitions Related to the Type of Options. Examples. Requirements for the Purchase and/or Sale of Options. Long-Term Equity Anticipation Securities. Other Types of Options. Additional Details Concerning Options. Chapter Eight Questions. Chapter 9. Portfolio Margining. Margin Deficiencies. Chapter 9 Questions. Appendix A. The Federal Reserve. Appendix B. Customer Margin Account and SMA Sheets. Appendix C. Answers to Chapter Questions. Appendix D. Final Examination Questions. Appendix E. Final Examination Answers. Glossary of Terms. Index.