Miracle-dz/UniFAR-FTUs huggingface dataset:
Floating-Point Arithmetic for Computational Geometry Problems with Uncertain Data

It has been suggested in the literature that ordinary finite-precision floating-point arithmetic is inadequate for geometric computation, and that researchers in numerical analysis may believe that the difficulties of error in geometric computation can be overcome by simple approaches. It is the purpose of this paper to show that these suggestions, based on an example showing failure of a certain algorithm for computing planar convex hulls, are misleading, and why this is so. It is first shown how the now-classical backward error analysis can be applied in the area of computational geometry. This analysis is relevant in the context of uncertain data, which may well be the practical context for computational-geometry algorithms such as, say, those for computing convex hulls. The exposition will illustrate the fact that the backward error analysis does not pretend to overcome the problem of finite precision: it merely provides a way to distinguish those algorithms that overcome the problem to whatever extent it is possible to do so. It is then shown that often the situation in computational geometry is exactly parallel to other areas, such as the numerical solution of linear equations, or the algebraic eigenvalue problem. Indeed, the example mentioned can be viewed simply as an example of the use of an unstable algorithm, for a problem for which computational geometry has already discovered provably stable algorithms. Finally, the paper discusses the implications of these analyses for applications in three-dimensional solid modeling. This is done by considering a problem defined in terms of a simple extension of the planar convex-hull algorithm, namely, the verification of the well-formedness of extruded objects. A brief discussion concerning more difficult problems in solid modeling is also included.
Combined mitochondrial and nuclear DNA sequences resolve the interrelations of the major Australasian marsupial radiations.

Australasian marsupials include three major radiations, the insectivorous/carnivorous Dasyuromorphia, the omnivorous bandicoots (Peramelemorphia), and the largely herbivorous diprotodontians. Morphologists have generally considered the bandicoots and diprotodontians to be closely related, most prominently because they are both syndactylous (with the 2nd and 3rd pedal digits being fused). Molecular studies have been unable to confirm or reject this Syndactyla hypothesis. Here we present new mitochondrial (mt) genomes from a spiny bandicoot (Echymipera rufescens) and two dasyurids, a fat-tailed dunnart (Sminthopsis crassicaudata) and a northern quoll (Dasyurus hallucatus). By comparing trees derived from pairwise base-frequency differences between taxa with standard (absolute, uncorrected) distance trees, we infer that composition bias among mt protein-coding and RNA sequences is sufficient to mislead tree reconstruction. This can explain incongruence between trees obtained from mt and nuclear data sets. However, after excluding major sources of compositional heterogeneity, both the "reduced-bias" mt and nuclear data sets clearly favor a bandicoot plus dasyuromorphian association, as well as a grouping of kangaroos and possums (Phalangeriformes) among diprotodontians. Notably, alternatives to these groupings could only be confidently rejected by combining the mt and nuclear data. Elsewhere on the tree, Dromiciops appears to be sister to the monophyletic Australasian marsupials, whereas the placement of the marsupial mole (Notoryctes) remains problematic. More generally, we contend that it is desirable to combine mt genome and nuclear sequences for inferring vertebrate phylogeny, but as separately modeled process partitions. This strategy depends on detecting and excluding (or accounting for) major sources of non-historical signal, such as from compositional non-stationarity. [Base composition; combined data; marsupial; mitochondrial genome; phylogeny. ].
Development of an ion microbeam system for irradiating single plant cell[s].

An ion microbeam system for irradiating single plant cells was developed to analyze exact biological effects of ion beams. Tobacco BY-2 protoplasts were used as a model of single plant cells. Protoplasts were cultured in thin agarose medium on a specially designed irradiation-vessel, which has a CR-39 nuclear track detector (a 100-micrometer thick sheet). The colony formation rate of unirradiated protoplasts was 22.7 +/- 6.7% (mean +/- SE of 3 different experiments) after a month of culture. Protoplasts were irradiated with programmed numbers of 18.3 MeV/u carbon ions that had been collimated by a 20-micrometer phi micro-aperture. After the irradiation, the positions within the protoplasts that were hit with ions were accurately determined by etching the CR-39 sheet in 13.4M KOH solution at 27 degrees centigrade for 9 h. The hit rate of the carbon ion microbeam, i.e., the percent of the ion particles that hit the protoplast that they were aimed at, was 56.9 +/- 2.4% (mean +/- SE of 7 different replications).
Using Wikipedia with associative networks for document classification

We demonstrate a new technique for building associative networks based on Wikipedia, comparing them to WordNet-based associative networks that we used previously, nding the Wikipedia-based networks to perform better at document classification. Additionally, we compare the performance of associative networks to various other text classification techniques using the Reuters-21578 dataset, establishing that associative networks can achieve comparable results.
Perceptibility of haptic digital watermarking of virtual textures

Digital watermarking refers to the process of embedding a digital code into an image, video, printed document or audio media. The code should not interfere with the normal use of the media but can be recovered later. With the growing interest in haptic interactions for training and museum displays, it is only a matter of time that haptic digital media become available on the Internet. For example, one will soon be able to feel the shape of Michaelangelo 's David or Japan's Big Buddha by downloading a file that can be "played" on a force-feedback device. The haptic file may contain surface texture data in addition to topography so that David feels like marble and Big Buddha wood. In the meanwhile, the need for haptic digital watermarking will arise for protecting haptic media contents. This paper introduces for the first time the idea of haptic watermarking and shows one way to embed a watermark into a host surface texture signal. We also demonstrate the imperceptibility of the texture watermark in a psychophysical experiment.
Behavior Analysis Based SMS Spammer Detection in Mobile Communication Networks

In a communication network, automatic short message service (SMS) spammer detection is a big challenge for a telecommunication operator nowadays, especially with the development of the rich communication services (RCS). Three main problems exist in the areas of research and real practice. They are (1) the whole-volume content based SMS spam detection techniques cannot be easily used on the side of network due to the issue of user privacy, (2) traditional ways to filter the spam according to the combination of key words and sending frequency can be easily bypassed by adding the interference words, (3) Most of them result in a great deal of manual review after the automatic filtering due to a low precision rate. To make up the aforementioned gaps, we study the user behavior characteristics. A two-dimensional visualized result indicates that any combination of two user behavior attributes cannot distinguish the abnormal users from the whole set by splitting the 2-dimensional space. Thus, the integration of multiple user behavior attributes is exploited to train the classifier in a labeled set by machine learning algorithms, respectively, including decision tree, random forest, supported vector machine (SVM), logistic regression, and self-organized feature mapping (SOM). The performance comparison indicates that random forest is a good choice to balance the tradeoff of the precision rate and the recall rate, and in an acceptable time. The experimental result shows the proposed method without the knowledge of SMS content has a significant improvement in terms of precision rate and recall rate compared with the traditional method using the combination of key words and sending frequency used in most of existing networks.
A red meat-derived glycan promotes inflammation and cancer progression

Significance We present an unusual mechanism for the well-known association between red meat consumption and carcinoma risk involving the nonhuman sialic acid N-glycolylneuraminic acid (Neu5Gc). We first evaluate the Neu5Gc content of various foods to show that red meats are particularly rich in orally bioavailable Neu5Gc and then investigate human-like Neu5Gc-deficient mice fed this form of Neu5Gc. When such mice were challenged with anti-Neu5Gc antibodies, they developed evidence of systemic inflammation. Long-term exposure to this combination resulted in a significantly higher incidence of carcinomas (five-fold increase) and an association with Neu5Gc accumulation in the tumors. Similar mechanisms may contribute to the association of red meat consumption with other diseases, such as atherosclerosis and type 2 diabetes, which are also exacerbated by inflammation. A well known, epidemiologically reproducible risk factor for human carcinomas is the long-term consumption of “red meat” of mammalian origin. Although multiple theories have attempted to explain this human-specific association, none have been conclusively proven. We used an improved method to survey common foods for free and glycosidically bound forms of the nonhuman sialic acid N-glycolylneuraminic acid (Neu5Gc), showing that it is highly and selectively enriched in red meat. The bound form of Neu5Gc is bioavailable, undergoing metabolic incorporation into human tissues, despite being a foreign antigen. Interactions of this antigen with circulating anti-Neu5Gc antibodies could potentially incite inflammation. Indeed, when human-like Neu5Gc-deficient mice were fed bioavailable Neu5Gc and challenged with anti-Neu5Gc antibodies, they developed evidence of systemic inflammation. Such mice are already prone to develop occasional tumors of the liver, an organ that can incorporate dietary Neu5Gc. Neu5Gc-deficient mice immunized against Neu5Gc and fed bioavailable Neu5Gc developed a much higher incidence of hepatocellular carcinomas, with evidence of Neu5Gc accumulation. Taken together, our data provide an unusual mechanistic explanation for the epidemiological association between red meat consumption and carcinoma risk. This mechanism might also contribute to other chronic inflammatory processes epidemiologically associated with red meat consumption.
Modeling eating pathology: The role of gender, sociocultural, and individual factors

Eating pathology is an increasing problem in the United States and other Western countries. This study examined gender differences and specific known psychological correlates of eating pathology. Sociocultural variables, such as thin-ideal internalization, and individual factors, such as perfectionism and experiential avoidance, were also evaluated. A sample of 257 female and 165 male undergraduates (n = 423) completed a battery of surveys online. Structural equation modeling (SEM) was used to model the relationships among the variables. The results show that the best fitting model included perfectionism rather than thin-ideal internalization leading to body dissatisfaction. There is support for experiential avoidance as a mediating variable between body dissatisfaction, dieting, and thin-idealization and binge eating. Results also show that men engaged in more binge eating and exercise than women and less vomiting and laxative use than women. These findings suggest that individual factors, specifically perfectionism and experiential avoidance, are strongly related to eating pathology, particularly binge eating.
Pain relief and safety after major surgery A prospective study of epidural and intravenous analgesia in 2696 patients

Background: Adverse effects may still limit the use of continuous epidural and intravenous analgesia in surgical wards. This study postulated that postoperative epidural analgesia was more efficient, and had fewer side‐effects than intravenous morphine. The aim was to investigate efficacy, adverse effects and safety of the treatments in a large patient population.
Sleep-disordered breathing and myocardial ischemia in patients with coronary artery disease.

STUDY OBJECTIVES To examine the occurrence of nocturnal myocardial ischemia and its relationship to sleep-disordered breathing (apneas and oxygen desaturations) in randomly selected men and women undergoing coronary angiography because of angina pectoris. DESIGN An observational study using an overnight sleep study and Holter recording to examine disordered breathing (oxyhemoglobin desaturations > or = 4% and apnea-hypopneas), heart rates, and ST-segment depressions (> or = 1 mm, > or = 1 min). SETTING University Hospital, Umeå, a teaching hospital in northern Sweden. PATIENTS One hundred thirty-two men and 94 women referred for consideration of coronary intervention were randomly included, by lot. RESULTS ST-segment depressions occurred in 59% (134 of 226) of the patients, and nocturnal ST-segment depressions occurred in 31% (69 of 226). A ST-segment depression occurred within 2 min after an apnea-hypopnea or desaturation in 12% (27 of 226) of patients. This temporal association was seen in 19% of nocturnal ST-segment depressions (71 of 366), more frequently in men (p < 0.01) and in more severely disordered breathing (p < 0.001). Most of these ST-segment depressions were preceded by a series of breathing events: three or more apnea-hypopneas or desaturations or both in 70% (50 of 71). CONCLUSION Episodes of nocturnal myocardial ischemia are common in patients with angina pectoris. However, a temporal relationship between sleep-disordered breathing and myocardial ischemia is present only in a minority of the patients, but occurs more frequently in men and in more severely disordered breathing.
Face Recognition Based on the Probability Support Vector Machines

Face recognition is very important in intelligent meeting scenario. An approach to face recognition based on the probability support vector machines is proposed in this paper. In this approach, an approach of the posterior probability output of multi-class SVM is modeled. One-against-one multi-class SVMs with probability output are chosen as the classifiers for face recognition. Considering the real need of face recognition in intelligent meeting scene, the frontal faces are detected and extracted based on the ratio between the face area and head area. The input of the SVM classifier is the raw image of the frontal face area, and the output is the probability of the tested face in each class, and the recognized face denotes the class with the highest probability. Experimental results have showed that this approach makes better application in real meeting scenario.
Substratum-growth factor collaborations are required for the mitogenic activities of activin and FGF on embryonal carcinoma cells

When P19 mouse embryonal carcinoma cells are grown in a serum-free N2 medium on surfaces of tissue culture plastic, they die within two days. The death of these P19 cells is prevented by activin A and basic FGF (bFGF). The cells do not divide under these conditions. However, when P19 cells are cultured on substrata of extracellular matrix proteins such as laminin and fibronectin, activin A and bFGF are potent mitogens. These data show that the substratum to which cells are exposed can regulate their mitogenic response to growth factors.
Contrast-enhanced MR imaging of hepatic lesions treated with percutaneous ethanol ablation therapy.

PURPOSE Magnetic resonance (MR) images were correlated with results of fine-needle aspiration (FNA) to determine the role of MR imaging in evaluating hepatic neoplasms treated with percutaneous ethanol ablation therapy (PEAT). MATERIALS AND METHODS Contrast material-enhanced and unenhanced MR images were obtained in 11 patients with hepatic neoplasms before PEAT (13 studies) and at intervals after PEAT (25 studies). FNA was performed at each follow-up visit. RESULTS After PEAT, the MR appearance of the lesions was extremely variable. Also, the signal characteristics of most lesions did not change significantly with any sequence over time. Of eight lesions that demonstrated contrast enhancement before therapy, four demonstrated persistent enhancement and four showed loss of enhancement. Six of these lesions had no viable tumor at FNA. T2-weighted sequences most often showed mixed signal intensity regardless of T2-weighted imaging appearance before therapy. CONCLUSION The MR appearance of PEAT-treated hepatic lesions is not a reliable indicator of residual or recurrent tumor.
This Article Has Been Accepted for Publication in a Future Issue of Ieee Transactions on Mobile Computing. 1 Performance Analysis of Csma/ca Based Medium Access in Full Duplex Wireless Communications

—Full duplex communication promises a paradigm shift in wireless networks by allowing simultaneous packet transmission and reception within the same channel. While recent prototypes indicate the feasibility of this concept, there is a lack of rigorous theoretical development on how full duplex impacts medium access control (MAC) protocols in practical wireless networks. In this paper, we formulate the first analytical model of a CSMA/CA based full duplex MAC protocol for a wireless LAN network composed of an access point serving mobile clients. There are two major contributions of our work: First, our Markov chain-based approach results in closed form expressions of throughput for both the access point and the clients for this new class of networks. Second, our study provides quantitative insights on how much of the classical hidden terminal problem can be mitigated through full duplex. We specifically demonstrate that the improvement in the network throughput is up to 35-40% over the half duplex case. Our analytical models are verified through packet level simulations in ns-2. Our results also reveal the benefit of full duplex under varying network configuration parameters, such as number of hidden terminals, client density, and contention window size.
Antihelmintic treatment alters the parasite community in a wild mouse host

Individuals are often co-infected with several parasite species, yet the consequences of drug treatment on the dynamics of parasite communities in wild populationshaverarelybeenmeasured.Here,weexperimentallyreducednema- todeinfectioninawildmousepopulationandmeasuredtheeffectsonothernon-target parasites. A single oral dose of the anthelmintic, ivermectin, significantly reduced nematode infection, but resulted in a reciprocal increase in other gastro-intestinal parasites, specifically coccidial protozoans and cestodes. These results highlight the possibility that drug therapy may have unintended consequences for non-target parasites and that host–parasite dynamics cannot always be fully understood in the framework of single host–parasite interactions
Hirschsprung disease, associated syndromes and genetics: a review

Hirschsprung disease (HSCR, aganglionic megacolon) represents the main genetic cause of functional intestinal obstruction with an incidence of 1/5000 live births. This developmental disorder is a neurocristopathy and is characterised by the absence of the enteric ganglia along a variable length of the intestine. In the last decades, the development of surgical approaches has importantly decreased mortality and morbidity which allowed the emergence of familial cases. Isolated HSCR appears to be a non-Mendelian malformation with low, sex-dependent penetrance, and variable expression according to the length of the aganglionic segment. While all Mendelian modes of inheritance have been described in syndromic HSCR, isolated HSCR stands as a model for genetic disorders with complex patterns of inheritance. The tyrosine kinase receptor RET is the major gene with both rare coding sequence mutations and/or a frequent variant located in an enhancer element predisposing to the disease. Hitherto, 10 genes and five loci have been found to be involved in HSCR development.
Evaluation of network robustness for given defense resource allocation strategies

Since the 9/11 terrorist attacks, the effective and efficient protection of critical information infrastructures has become an even more important issue. To enhance network survivability, a network operator needs to invest a fixed amount of budget and distribute it properly. However, a potential attacker always adjust his attack strategies to compromise a network at minimal cost, if he knows the resource allocation strategy of the network operator. In this paper, we first evaluate the survivability of a given network under two different metrics; that is, we assess the minimal attack cost incurred by an attacker. The two survivability metrics are assumed to be the connectivity of at least one given critical origin-destination pair (OD pair) and that of all given critical OD pairs. We then analyze the problem with two optimization-based models, in which the problem structure is, by nature, a mixed integer programming problem.
A weighted similarity measure approach to predict intensive care unit transfers

Classification models have proven useful for predicting clinical interventions and patient outcomes. One of the key issues that affect the predictive ability of supervised learning frameworks in the healthcare scenario is imbalance in data sets. In addition, non-uniform data collection processes in clinical scenarios lead to poor quality data sets. We designed a novel approach to predict Intensive Care Unit (ICU) transfers based on a weighted-similarity measure for patients outside of ICUs. The approach uses similarity between patient vital signs as input features for training the model. To address the data quality issues, we demonstrate the use of various up-sampling and down-sampling techniques to handle imbalanced data sets and train a classifier on a re-sampled data set. The data set used for testing the approach is derived from the MIMIC III database. We compare our results with the clinically accepted methodology to capture patient's health state, assisting in clinical decision making. Our model outperforms the standard methodology used in clinical decision making in standard scoring metrics such as F1-score, False Positive Rate and Mathew's Correlation Coefficient [MCC].
Semantic maps for IoT network reorganization in face of sensor malfunctioning

As technology evolves, the Internet of Things (IoT) is gaining more importance for constituting a foundation to reach better connectivity between people and things. For this to happen, certain strategies and processes are considered to enhance and grant optimal interoperability between the heterogenous devices of a typical IoT network. Two major key aspects of these networks are autonomous error recovery and network reorganization, which are usually based on physical redundancy and aim to return the network to a similar working state, as it was before the error. This process is of great importance when regarding the amount of data and devices that the ever-growing IoT networks have to manage and the number of situations that are associated with this aspect. This work proposes a solution to integrate the previously mentioned processes in IoT networks with the support of semantic maps as a mean to accomplish redundancy. It uses network metadata and a function-oriented recovery methodology to provide the network the tools to be more autonomous and reliable, without compromising performance.