Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Radiomics Features for Automated Detection of Cardiac Abnormality in Patients with Pacemaker

Cardiac pacemakers are used in the treatment of patients with symptomatic bradycardia. The pacemaker paces the heart at the predetermined rate to maintain uninterrupted cardiac activity. Usually, pacemaker lead will be connected to the right atrium (RA) and right ventricle (RV) in dual-chamber pacemaker implantation and RV alone in single-chamber pacemaker implantation. This alters the route of proper conduction across the myocardial cells. The cell-to-cell conduction transmission in pacing delays the activation of selected intraventricular myocardial activation. Pacing-induced cardiomyopathy (PICM) is most commonly defined as a drop in left ventricle ejection fraction (LVEF) in the setting of chronic, high-burden right ventricle (RV) pacing. Currently, very few effective treatments are standard for PICM which rely on the detection of the RV pacing. Such treatments have primarily focused on upgrading to cardiac resynchronization therapy (CRT) when LVEF has dropped. However, the early and accurate detection of these stress factors is challenging. Cardiac desynchrony and interventricular desynchrony can be determined by various echocardiographic techniques, including M-mode, Doppler method, tissue Doppler method, and speckle tracking echocardiography which is subjective measures and shows a significant difference between RV and LV preejection period where the activation of LV is delayed considerably. Computer-aided diagnosis (CAD) is a noninvasive technique that can classify the ultrasound images of the heart in pacemaker-implanted patients and healthy patients with normal left ventricular systolic function and further detect the variations in pacemaker functions in its early stage using heart ultrasound images. Developing such a system requires a vast and diverse database to reach optimum performance. This paper proposes a novel CAD tool for the accurate detection of pacemaker variations using machine learning models of decision tree, SVM, random forest, and AdaBoost. The models have been used to extract radiomics features in terms of textures and then screened by their Relief-F scores for selection and ranking to be classified into nine groups consisting of up to 250 radiomics features. Ten best features were fed to the machine learning models. The R-wave dataset achieved a maximum test performance accuracy of 97.73% with four features in the random forest model. The T-wave dataset achieved a maximum test performance accuracy of 96.59% with three features in the SVM model. Our experimental results demonstrate the system's robustness, which can be developed as an early and accurate detection system for pacing-induced cardiomyopathy.
Cytokinins induce prehaustoria coordinately with quinone and phenolic signals in the parasitic plant Striga hermonthica

Orobanchaceae parasitic plants are major threats to global food security, causing severe agricultural damage worldwide. Parasitic plants derive water and nutrients from their host plants through multicellular organs called haustoria. The formation of a prehaustorium, a primitive haustorial structure, is provoked by host-derived haustorium-inducing factors (HIFs). Quinones, including 2,6-dimethoxy-p-benzoquinone (DMBQ), and phenolics, including syringic acid, are of most potent HIFs for various species in Orobanchaceae, but except non-photosynthetic holoparasites, Phelipanche and Orobanche spp. On the other hand, cytokinin phytohormones was reported to induce prehaustoria in Phelipanche ramosa. However, little is known about whether cytokinins act as HIFs in the other parasitic species. Moreover, the signaling pathways for quinones, phenolics and cytokinins in prehaustorium induction are not well understood. This study showed that cytokinins act as HIFs in Striga hermonthica but not in Phtheirospermum japonicum. Using chemical inhibitors for each type of HIF, we demonstrated that cytokinins activate prehaustorium formation through a signaling pathway that overlaps with the quinone and phenolic HIF pathways in S. hermonthica. Host root exudates activated S. hermonthica cytokinin biosynthesis and signaling genes, and inhibitors blocking any of three types of HIFs perturbed the prehaustorium-inducing activity of exudates, indicating that host root exudates include a mixture of HIFs. Our study reveals the importance of cytokinins for prehaustorium formation in obligate parasitic plants.
Dark Energy Survey Year 1 Results: Cross-correlation between Dark Energy Survey Y1 galaxy weak lensing and South Pole weak lensing

We cross-correlate galaxy weak lensing measurements from the Dark Energy Survey (DES) year-one data with a cosmic microwave background (CMB) weak lensing map derived from South Pole Telescope (SPT) and Planck data, with an effective overlapping area of 1289 deg 2 . With the combined measurements from four source galaxy redshift bins, we obtain a detection significance of 5 . 8 σ . We fit the amplitude of the correlation functions while fixing the cosmological parameters to a fiducial Λ CDM model, finding A ¼ 0 . 99 (cid:2) 0 . 17 . We additionally use the correlation function measurements to constrain shear calibration bias, obtaining constraints that are consistent with previous DES analyses. Finally, when performing a cosmological analysis under the Λ CDM model, we obtain the marginalized constraints of Ω m ¼ 0 . 261 þ 0 . 070 − 0 . 051 and S 8 ≡ σ 8 ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ Ω m = 0 . 3 p ¼ 0 . 660 þ 0 . 085 − 0 . 100 . These measurements are used in a companion work that presents cosmological constraints from the joint analysis of two-point functions among galaxies, galaxy shears, and CMB lensing using DES, SPT, and Planck data.
Is it Time to Reassess the Focal Role of Core PCE Inflation in Assessing the Trend in PCE Inflation?

“Core” PCE inflation—that is, inflation in PCE-ex-food-and-energy—is widely used as an estimate of trend inflation. But it is long overdue for replacement. The original rationale of core inflation was to remove volatile items with transitory shocks. But aside from gasoline, the list of excluded items is far from optimal. Core inflation also su˙ers from other severe deficiencies, common to all exclusion indexes. Excluded items often have persistent trends; thus excluding them imparts a significant time-varying bias. Items that are not excluded can experience high volatility, and will cause exclusion indexes to depart notably from trend inflation—as core PCE has done at crucial moments. Two other prominent trend inflation measures, trimmed mean PCE inflation and median PCE inflation, gracefully address these issues (though neither is perfect). A wide variety of evidence comparing these three trend measures is provided. The findings indicate that, for a variety of considerations that are relevant for both trend inflation estimation and for monetary policy deliberations and communication, either trimmed mean PCE inflation or median PCE inflation are superior measures.
BAYESIAN ADAPTIVE ESTIMATION OF HIGH DIMENSIONAL VECTORS

The normal mean estimation problem has a central role in statistical estimation. The maximum likelihood estimator (MLE) is a traditional estimator for this problem. Under the squared error loss, the MLE is unbiased, minimax, best invariant, and admissible when the parameter’s dimension is one or two. However, when the parameter’s dimension is three or higher, it is inadmissible and can be uniformly dominated by other estimators. In the past half century, a great amount of research has been devoted to developing optimal estimators in high dimensional settings. The Bayesian approaches are highly appealing for this problem. However, selecting a prior becomes challenging when the parameter’s dimension is high. Subjective elicitation of prior knowledge is almost infeasible. Therefore, we have to turn to some formal methods. In this dissertation, we develop a class of new prior distributions, namely, the adaptive inverted-Beta (AIB) priors, that lead to Bayesian estimators that often outperform many common estimators in the literature when the parameter is high dimensional. In the first part, Chapter 2, we focus on the situations where the observations are independent from a high dimensional normal distribution. We incorporate both global and local parameters in our AIB priors, so that different dimensions of the parameter can be shrunk by different factors. Most existing priors in the literature assume that data have a certain sparsity level. Instead, we utilize a hierarchical
Strong ground motion simulation in the urban area of Catania on the basis of a detailed geological survey

Catania is one of the cities with major seismic hazard in Italy. In history the city was repeatedly hit by destructive earthquakes, e.g., the events of 1 169, 1542 and 1693, all with estimated magnitudes around or above 7. The purpose of our research is the study of site effects and response of soil in the Catania urban area based on synthetic simulations. We have considered three scenarios with earthquakes whose magnitudes range from 5.5 to 7.0 and whose epicentral distances are supposed to be in the range 12-35 km. The subsurface geology of the urban area of Catania is characterized by a marlyclay substratum overlain by lavas, sands and conglomerates. The lava thickness range from a few to over 60 meters, while the thickness of sand terraces ranges from a few to 30 meters. Our study is based on ca. 100 boreholes from which geotechnical and geophysical data were available. We calculated synthetic accelerograms and response spectra at all borehole sites. The results highlight the importance of the subsurface geological conditions, in particular the presence of low velocity layers which enhance seismic loading. On the other hand thick lava layers act as "protecting shields" against earthquake shaking. Transactions on the Built Environment vol 38 © 1999 WIT Press, www.witpress. com, ISSN 1743-3509
Deep resilience: An evolutionary perspective on calcification in an age of ocean acidification

The success of today’s calcifying organisms in tomorrow’s oceans depends, in part, on the resilience of their skeletons to ocean acidification. To the extent this statement is true there is reason to have hope. Many marine calcifiers demonstrate resilience when exposed to environments that mimic near-term ocean acidification. The fossil record similarly suggests that resilience in skeletons has increased dramatically over geologic time. This “deep resilience” is seen in the long-term stability of skeletal chemistry, as well as a decreasing correlation between skeletal mineralogy and extinction risk over time. Such resilience over geologic timescales is often attributed to genetic canalization—the hardening of genetic pathways due to the evolution of increasingly complex regulatory systems. But paradoxically, our current knowledge on biomineralization genetics suggests an opposing trend, where genes are co-opted and shuffled at an evolutionarily rapid pace. In this paper we consider two possible mechanisms driving deep resilience in skeletons that fall outside of genetic canalization: microbial co-regulation and macroevolutionary trends in skeleton structure. The mechanisms driving deep resilience should be considered when creating risk assessments for marine organisms facing ocean acidification and provide a wealth of research avenues to explore.
Preliminary analysis of noisy image lossy compression by discrete atomic transform-based coder

Remote sensing provides data (images) important for many modern applications. Image number and average size tend to increase. This makes their transfer via communication lines, storage, and dissemination problematic. Thus, compression should be applied where lossy compression is mostly used. Most methods of lossy compression assume that images do not contain noise. Meanwhile, images are often noisy, and this should be considered in the design and performance analysis of image compression techniques. Lossy compression has already been studied by several coders. However, it has not been investigated for the recently proposed atomic transform-based techniques that possess several advantages, in particular, the ability to provide privacy of compressed data. The main subject of this paper is the peculiarities of noisy image lossy compression by an atomic transform-based coder. Our goal is to analyze whether the considered compression method provides the noise filtering effect and the so-called optimal operation point. The task is to obtain rated distortion curves for the atomic transform-based coder applied to noisy images and to analyze their behavior for several performance characteristics such as quality metrics and compression ratio. In the first order, the monotonicity of the main dependence is of interest. The main results are as follows. First, it is shown that the dependencies have non-monotonic behavior and the appearance of analogs of optimal operation point is possible, at least, for such metric as maximal absolute error. Second, there is a specific dependence of compression ratio on a parameter called UBMAD that controls compression. Experiments have been performed on several noisy test images having different complexity and contaminated by noise of different intensities. In conclusion, it is demonstrated that one more coder might have optimal operation points for images having a rather simple structure. However, at the moment, it is difficult to predict its existence and the corresponding coder parameters.
PhishAri : Automatic Realtime Phishing Detection on Twitter Anupama Aggarwal

With the advent of online social media, phishers have started using social networks like Twitter, Facebook, and Foursquare to spread phishing scams. Twitter is an immensely popular microblogging network where people post short messages of 140 characters called tweets. It has over 100 million active users who post about 200 million tweets everyday. Phishers have started using Twitter as a medium to spread phishing because of this vast information dissemination. Due to constraints of limited text space in social systems like Twitter, phishers have begun to use URL shortener services. In this study, we first provide an overview of phishing attacks for this new scenario. One of our main conclusions was that phishers use URL shorteners not only for reducing space but also to hide their identity. We also observed that social media websites like Facebook, Habbo, Orkut are competing with e-commerce services like PayPal, eBay in terms of traffic and focus of phishers. 1 Further, it is difficult to detect phishing on Twitter unlike emails because of the quick spread of phishing links in the network, short size of the content, and use of URL obfuscation to shorten the URL. We developed a technique, PhishAri, 2 which detects phishing on Twitter in realtime. We use Twitter specific features along with URL features to detect whether a tweet posted with a URL is phishing or not. Some of the Twitter specific features we used are tweet content and its characteristics like length, hashtags, and mentions. Other Twitter features used are the characteristics of the Twitter user posting the tweet such as age of the account, number of tweets, and the follower-followee ratio. These TTwitterwitter specific features coupled with URL based features proved to be a strong mechanism to detect phishing tweets. We used machine learning classification techniques and detected phishing tweets with an accuracy of 92.52%. We deployed our system for end-users by providing an easy to use Chrome browser extension. The extension works in realtime and classifies a tweet as phishing or safe. In this research, we showed that we were able to detect phishing tweets at zero hour with high accuracy which is much faster than public blacklists and as well as Twitter’s own defense mechanism to detect malicious content. We also performed a quick user evaluation of PhishAri in a laboratory study to evaluate the usability and effectiveness of PhishAri and showed that users like and find it convenient to use PhishAri in real-world. Currently, there are 74 active users of PhishAri chrome extension. To the best of our knowledge, this is the first realtime, comprehensive and usable system to detect phishing on Twitter. Phi.sh/$oCiaL: the phishing landscape through short URLs, Best Paper Award at CEAS 2011 PhishAri: Automatic Realtime Phishing Detection on Twitter, Best Paper Award at APWG, eCRS 2012
Fluorescence Polarization Assays for Organic Compounds in Food Safety.

Elevated concentrations of toxic organic compounds observed in food products pose serious dangers to human health. Both natural and artificial pollutants can cause food contamination. The stages of food production, packaging, transportation, and storage can also largely cause the appearance of undesirable substances in food products. The health consequences of ingesting food containing toxic contaminants range from mild gastroenteritis to deaths resulting from dysfunctional internal organs and neurological syndromes. The World Health Organization (WHO) sets recommendations for the content of such chemicals in food, including a minimum allowable concentration considered safe for human consumption. However, the control of food products from chemical pollutants is necessary. Moreover, fast, sensitive, and inexpensive methods are needed to detect them at the point of need. Currently, immune analysis methods are most widely used to determine pollutants in food. The development of fluorescence polarization immunoassay (FPIA) methods in a competitive format is a powerful and modern tool for detecting organic molecules in various matrices, thereby making FPIA methods useful for food safety applications. Due to the availability of portable devices for measuring the fluorescence polarization signal, FPIA methods can be used at the point of need. The variety of fluorescent labels and recognizing elements (receptors, monoclonal and polyclonal antibodies, and nanobodies) permits fluorescence polarization (FP) assays to detect significantly lower limits of organic substances. The FP assay is a homogeneous, fast, and quantitative method. The development of various formats of FP assays makes them promising in determining food pollutants. This review summarizes publications on FP analyses for detecting organic contaminants (pesticides, hormones, toxins, antibiotics, and other pharmaceuticals) in food products during 2018-2023. Further, it demonstrates the prospects for using this method to determine pollutants at the point of need and for detecting high molecular weight substances, fungi, and bacterial infections during food safety inspections.
On randomized representations of graphs using short labels

Informative labeling schemes consist in labeling the nodes of graphs so that queries regarding any two nodes (e.g., are the two nodes adjacent? ) can be answered by inspecting merely the labels of the corresponding nodes. Typically, the main goal of such schemes is to minimize the label size, that is, the maximum number of bits stored in a label. This concept was introduced by Kannan et al. [STOC'88] and was illustrated by giving very simple and elegant labeling schemes, for supporting adjacency and ancestry queries in n-node trees; both these schemes have label size 2log n. Motivated by relations between such schemes and other important notions such as universal graphs, extensive research has been made by the community to further reduce the label sizes of such schemes as much as possible. The current state of the art adjacency labeling scheme for trees has label size log n+O(log*n) by Alstrup and Rauhe [FOCS'02], and the best known ancestry scheme for (rooted) trees has label size log n+O(√log n) by Abiteboul et al., [SICOMP 2006]. This paper aims at investigating the above notions from a probabilistic point of view. Informally, the goal is to investigate whether the label sizes can be improved if one allows for some probability of mistake when answering a query, and, if so, by how much. For that, we first present a model for probabilistic labeling schemes, and then construct various probabilistic one-sided error schemes for the adjacency and ancestry problems on trees. Some of our schemes significantly improve the bound on the label size of the corresponding deterministic schemes, while the others are matched with appropriate lower bounds showing that, for the resulting guarantees of success, one cannot expect to do much better in term of label size.
CHLOROPLAST DNA PHYLOGEOGRAPHY OF THE COMMON BEECH (FAGUS SYLVATICA L.) IN EUROPE

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Instruction Sets and Beyond: Computers, Complexity, and Controversy

You can set out a simple set of axioms and deduction rules but the thing is that All they do is to reduce the complexity of some tasks so that they can be carried out Roger Penrose suggested that we need new physics to go beyond the Turing limit. So a self modifying instruction following program doesn't help at all. Instruction Sets and Beyond: Computers, Complexity, and Controversy. more. less. Colwell, R.P., Hitchcock, C.Y. , III, Jensen, E.D. , Brinkley Sprunt, H.M. , Kollar. In all research that utilizes a computer, instructions for the research are stored in software and The complexity of the data generation mechanism and the computational Here is the link to his talk: Everything Is Dangerous: A Controversy. “one of the most amazing set of presentations I have attended in recent memory.
Cloning of the Vibrio cholerae recA gene and construction of a Vibrio cholerae recA mutant

A recombinant plasmid carrying the recA gene of Vibrio cholerae was isolated from a V. cholerae genomic library, using complementation in Escherichia coli. The plasmid complements a recA mutation in E. coli for both resistance to the DNA-damaging agent methyl methanesulfonate and recombinational activity in bacteriophage P1 transductions. After determining the approximate location of the recA gene on the cloned DNA fragment, we constructed a defined recA mutation by filling in an XbaI site located within the gene. The 4-base pair insertion resulted in a truncated RecA protein as determined by minicell analysis. The mutation was spontaneously recombined onto the chromosome of a derivative of V. cholerae strain P27459 by screening for methyl methanesulfonate-sensitive variants. Southern blot analysis confirmed the presence of the inactivated XbaI site in the chromosome of DNA isolated from one of these methyl methanesulfonate-sensitive colonies. The recA V. cholerae strain was considerably more sensitive to UV light than its parent, was impaired in homologous recombination, and was deficient in induction of a temperate vibriophage upon exposure to UV light. We conclude that the V. cholerae RecA protein has activities which are analogous to those described for the RecA protein of E. coli.