Miracle-dz/UniFAR-FTUs huggingface dataset:
S-allele Diversity Suggests No Mate Limitation in Small Populations of a Self-incompatible Plant

Abstract Small populations of self-incompatible plants are assumed to be threatened by a limitation of compatible mating partners due to low genetic diversity at the self-incompatibility (S) locus. In contrast, we show by using a PCR-RFLP approach for S-genotype identification that 15 small populations (N= 8–88) of the rare wild pear (Pyrus pyraster) displayed no mate limitation. S-allele diversity within populations was high (N= 9–21) as was mate availability (92.9–100%). Although population size and S-allele diversity were strongly related, no relationship was found between population size and mate availability, gene diversity (He), or fixation index (FIS), based on five neutral microsatellite loci. As we determined the principal mate availability within populations based on the S-genotypes observed, the realized mate availability under natural conditions may differ from our estimates, for example, due to spatially limited pollen dispersal. We therefore urge studies on self-incompatible plants to proceed from the simple assessment of principal mate availability to the determination of realized mate availability in natural populations.
Hourglass Arrays and Other Novel 2-D Sparse Arrays With Reduced Mutual Coupling

Linear [one-dimensional (1-D)] sparse arrays such as nested arrays and minimum redundancy arrays have hole-free difference coarrays with <inline-formula><tex-math notation="LaTeX">$O(N^2)$</tex-math></inline-formula> virtual sensor elements, where <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> is the number of physical sensors. The hole-free property makes it easier to perform beamforming and DOA estimation in the coarray domain which behaves like an uniform linear array. The <inline-formula><tex-math notation="LaTeX">$O(N^2)$</tex-math> </inline-formula> property implies that <inline-formula><tex-math notation="LaTeX">$O(N^2)$</tex-math></inline-formula> uncorrelated sources can be identified. For the 2-D case, planar sparse arrays with hole-free coarrays having <inline-formula><tex-math notation="LaTeX">$O(N^2)$</tex-math></inline-formula> elements have also been known for a long time. These include billboard arrays, open box arrays (OBA), and 2-D nested arrays. Their merits are similar to those of the 1-D sparse arrays mentioned above, although identifiability claims regarding <inline-formula> <tex-math notation="LaTeX">$O(N^2)$</tex-math></inline-formula> sources have to be handled with more care in 2-D. This paper introduces new planar sparse arrays with hole-free coarrays having <inline-formula><tex-math notation="LaTeX"> $O(N^2)$</tex-math></inline-formula> elements just like the OBA, with the additional property that the number of sensor pairs with small spacings such as <inline-formula><tex-math notation="LaTeX">$\lambda /2$</tex-math></inline-formula> decreases, reducing the effect of mutual coupling. The new arrays include half-open box arrays, half-open box arrays with two layers, and hourglass arrays. Among these, simulations show that hourglass arrays have the best estimation performance in presence of mutual coupling.
SecSpace: prototyping usable privacy and security for mixed reality collaborative environments

Privacy mechanisms are important in mixed-presence (collocated and remote) collaborative systems. These systems try to achieve a sense of co-presence in order to promote fluid collaboration, yet it can be unclear how actions made in one location are manifested in the other. This ambiguity makes it difficult to share sensitive information with confidence, impacting the fluidity of the shared experience. In this paper, we focus on mixed reality approaches (blending physical and virtual spaces) for mixed presence collaboration. We present SecSpace, our software toolkit for usable privacy and security research in mixed reality collaborative environments. SecSpace permits privacy-related actions in either physical or virtual space to generate effects simultaneously in both spaces. These effects will be the same in terms of their impact on privacy but they may be functionally tailored to suit the requirements of each space. We detail the architecture of SecSpace and present three prototypes that illustrate the flexibility and capabilities of our approach.
Browser-Side Countermeasures for Deceptive Phishing Attack

Phishing is a form of online identity theft. Phishers use social engineering to steal victims' personal identity data and financial account credentials. Social engineering schemes use spoofed e-mails to lure unsuspecting victims into counterfeit websites designed to trick recipients into divulging financial data such as credit card numbers, account usernames, passwords and social security numbers. This is called a deceptive phishing attack. In this paper, a thorough overview of a deceptive phishing attack and its countermeasure techniques, which is called anti-phishing, is presented. Firstly, technologies used by phishers and the definition, classification and future works of deceptive phishing attacks are discussed. Following with the existing browser-side anti-phishing techniques in literatures and research-stage technologies are shown, and a thorough analysis which includes the advantages and shortcomings of countermeasures is given.
Characterization of a Real Internet Radio Service

The increase in the number of Web-pages where links to Internet-radios are offered has made these services one of the most popular in nowadays Internet. This popularity has motivated the interest of the scientific community and a lot of research has been carried out in order to improve and study these services. This paper presents the analysis of the Internet-radio hosted by the www.asturies. com digital newspaper. The study has been performed thanks to a log database stored over a period of almost two years. The traffic between every service device has been studied and different elements about users' behaviour have been analyzed. The conclusions are essential to improve the configuration of one of these services. Service models for Internet-radio services can be developed and help managers to test different configurations or predict future situations, avoiding problems in advance
ROC curves and confidence intervals: getting them right

Editor,—It is encouraging to see an increasing recognition of the desirability of quoting confidence intervals (CI) in association with indices of the performance of diagnostic tests. It is unfortunate, therefore, when errors are made in the calculation and interpretation of these, as happened in two recent papers in Heart . A few errors spoil Collinson's1 otherwise useful introduction to ROC curves. First he has defined the prevalence of disease wrongly. Using the notation in his table 1, the prevalence is not (TP+FN)/(TN+FP) but (TP+FN)/(TP+FN+TN+FP), where the denominator is in fact just the total study size. Brackets are essential here to clarify numerator and denominator—these are omitted from several expressions in Collinson's paper. His expression for the likelihood ratio is also incorrect: it should be [TP/(TP+FN)]/[1−TN/(TN+FN)]. Second, Collinson1 notes that variation in the prevalence of disease “will greatly affect the test performance”. While the sensitivity and specificity may vary according to setting (and hence disease prevalence)2 more often the opposite is true. Indeed it is often noted as a characteristic of these measures that they are not affected by disease prevalence.3 For example, the sensitivity of a test is unaffected by how many disease negative patients are included in the study. Third, he makes a common error in relation to CIs. He suggests that one should compare two sensitivities by seeing whether their CIs overlap. In fact the difference between two sensitivities may be statistically significant even when the CI overlap. The correct procedure when …
Incorporating Language Syntax in Visual Text Recognition with a Statistical Model

The use of a statistical language model to improve the performance of an algorithm for recognizing digital images of handwritten or machine-printed text is discussed. A word recognition algorithm first determines a set of words (called a neighborhood) from a lexicon that are visually similar to each input word image. Syntactic classifications for the words and the transition probabilities between those classifications are input to the Viterbi algorithm. The Viterbi algorithm determines the sequence of syntactic classes (the states of an underlying Markov process) for each sentence that have the maximum a posteriori probability, given the observed neighborhoods. The performance of the word recognition algorithm is improved by removing words from neighborhoods with classes that are not included on the estimated state sequence. An experimental application is demonstrated with a neighborhood generation algorithm that produces a number of guesses about the identity of each word in a running text. The use of zero, first and second order transition probabilities and different levels of noise in estimating the neighborhood are explored.
Work Productivity in Rheumatoid Arthritis: Relationship with Clinical and Radiological Features

Objective. To assess the relationship between work productivity with disease activity, functional capacity, life quality and radiological damage in patients with rheumatoid arthritis (RA). Methods. The study included consecutive employed patients with RA (ACR'87), aged over 18. Demographic, disease-related, and work-related variables were determined. The reduction of work productivity was assessed by WPAI-RA. Results. 90 patients were evaluated, 71% women. Age average is 50 years old, DAS28 4, and RAQoL 12. Median SENS is 18 and HAQ-A 0.87. Mean absenteeism was of 14%, presenting an average of 6.30 work hours wasted weekly. The reduction in performance at work or assistance was of 38.4% and the waste of productivity was of 45%. Assistance correlated with DAS28 (r = 0.446; P < 0.001), HAQ-A (r = 0.545; P < 0.001) and RAQoL (r = 0.475; P < 0.001). Lower total productivity was noticed in higher levels of activity and functional disability. Patients with SENS > 18 showed lower work productivity than those with SENS < 18 (50 versus 34; P = 0.04). In multiple regression analysis, variables associated with reduction of total work productivity were HAQ-A and RAQoL. Conclusion. RA patients with higher disease severity showed higher work productivity compromise.
The Use of Artificial Neural Networks in Prediction of Congenital CMV Outcome from Sequence Data

A large number of CMV strains has been reported to circulate in the human population, and the biological significance of these strains is currently an active area of research. The analysis of complex genetic information may be limited using conventional phylogenetic techniques. We constructed artificial neural networks to determine their feasibility in predicting the outcome of congenital CMV disease (defined as presence of CMV symptoms at birth) based on two data sets: 54 sequences of CMV gene UL144 obtained from 54 amniotic fluids of women who contracted acute CMV infection during their pregnancy, and 80 sequences of 4 genes (US28, UL144, UL146 and UL147) obtained from urine, saliva or blood of 20 congenitally infected infants that displayed different outcomes at birth. When data from all four genes was used in the 20-infants’ set, the artificial neural network model accurately identified outcome in 90% of cases. While US28 and UL147 had low yield in predicting outcome, UL144 and UL146 predicted outcome in 80% and 85% respectively when used separately. The model identified specific nucleotide positions that were highly relevant to prediction of outcome. The artificial neural network classified genotypes in agreement with classic phylogenetic analysis. We suggest that artificial neural networks can accurately and efficiently analyze sequences obtained from larger cohorts to determine specific outcomes. The ANN training and analysis code is commercially available from Optimal Neural Informatics (Pikesville, MD).
Self-identity or self-esteem? Vivid and nonvivid imagers' responses to threat to self-differentiation

Chez des sujets differentiellement capables de former des images visuelles nettes, on a etudie les effets de la manipulation du degre de leur similitude a un echantillon de 10000 autres personnes, sur l'etat de leur humeur general et leur acceptation de soi. On a trouve que les sujets les moins capables d'imagerie reagissent a l'information d'une forte similitude par une baisse de la positivite de leur humeur, et une diminution de leur acceptation de soi. En revanche, chez les sujets capables d'imagerie, la baisse de la positivite de l'humeur n'est pas liee aux changements (positifs) de l'acceptation de soi
Biological and Non-biological Synthesis of Metallic Nanoparticles: Scope for Current Pharmaceutical Research

Nanotechnology in pharmacy and medicine is going to have a major impact on the survival of the human race. The unique optical, catalytic, electronic and physical properties (melting point) of metallic nanoparticles have made them potential candidates in the field of nanotechnology. The synthesis of metallic nanoparticles is being carried out by various methods. Method of synthesis is one of the important factors, which largely influences their biological effectiveness. Moreover, conventional physical and chemical processes involve the use of expensive chemicals and these methods are non-ecofriendly. The present review outlined different non-biological and biological methods of synthesizing metallic nanoparticles for therapeutic applications including a good emphasis on green expertise in this field. Updated tools of characterization and potential applications of metallic nanoparticles in the field of pharmacy are also reviewed.
What is the role of endoscopic sinus surgery in adult patients with cystic fibrosis?

BACKGROUND Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population, with an estimated incidence of 1:2500 to 1:3000 among newborns. In patients with CF, there is a defect in chloride ion transport resulting in a reduction in the water content of secretions. The more viscous mucus impairs normal mucociliary patterns and causes mechanical obstruction of the paranasal sinuses. The prevalence of sinus disease in patients with CF is estimated to be between 90% and 100%, with nasal polyposis occurring in up to two-thirds of CF patients. Given that sinonasal disease affects nearly all CF patients, appropriate treatment is a critical concern. This review describes the evidence regarding endoscopic sinus surgery (ESS) in patients with CF.
Coalescent processes in subdivided populations subject to recurrent mass extinctions

We investigate the infinitely many demes limit of the genealogy of a sample of individuals from a subdivided population that experiences sporadic mass extinction events. By exploiting a separation of time scales that occurs within a class of structured population models generalizing Wright's island model, we show that as the number of demes tends to infinity, the limiting form of the genealogy can be described in terms of the alternation of instantaneous scattering phases that depend mainly on local demographic processes, and extended collecting phases that are dominated by global processes. When extinction and recolonization events are local, the genealogy is described by Kingman's coalescent, and the scattering phase influences only the overall rate of the process. In contrast, if the demes left vacant by a mass extinction event are recolonized by individuals emerging from a small number of demes, then the limiting genealogy is a coalescent process with simultaneous multiple mergers (a $\Xi$-coalescent). In this case, the details of the within-deme population dynamics influence not only the overall rate of the coalescent process, but also the statistics of the complex mergers that can occur within sample genealogies. These results suggest that the combined effects of geography and disturbance could play an important role in producing the unusual patterns of genetic variation documented in some marine organisms with high fecundity.
Behavioural and physiological responses to increased foraging effort in male mice

SUMMARY Free-living animals must forage for food and hence may face energetic constraints imposed by their natural environmental conditions (e.g. ambient temperature, food availability). Simulating the variation in such constraints, we have experimentally manipulated the rate of work (wheel running) mice must do to obtain their food, and studied the ensuing behavioural and physiological responses. This was done with a line of mice selectively bred for high spontaneous wheel running and a randomly bred control line that vary in the amount of baseline wheel-running activity. We first determined the maximum workload for each individual. The maximum workload animals could engage in was around 23 km d–1 in both control and activity-selected mice, and was not associated with baseline wheel-running activity. We then kept mice at 90% of their individual maximum and measured several physiological and behavioural traits. At this high workload, mice increased wheel-running activity from an average of 10 to 20 km d–1, and decreased food intake and body mass by approximately 20%. Mass-specific resting metabolic rate strongly decreased from 1.43 to 0.98 kJ g–1 d–1, whereas daily energy expenditure slightly increased from 2.09 to 2.25 kJ g–1 d–1. Costs of running decreased from 2.3 to 1.6 kJ km–1 between baseline and workload conditions. At high workloads, animals were in a negative energy balance, resulting in a sharp reduction in fat mass as well as a slight decrease in dry lean mass. In addition, corticosterone levels increased, and body temperature was extremely low in some animals at high workloads. When challenged to work for food, mice thus show significant physiological and behavioural adjustments.
Analysis of thermal therapy using infrared diode lasers operated in continuous wave and pulsed mode

The design (software control) guidelines are presented for medical laser systems based on the analysis of the tissue temperature response to various lasers at both cw and pulsed modes. By solving the laser volume-heating diffusion equation, we analyze the roles of various laser and tissue (or water) parameters on the laser-heated solution temperature profiles, including laser intensity, pulse-width, on-off ratio, absorption and thermal constants of the solution or tissues. Two experimental setups are designed to measure the real-time temperature profiles change under laser interactions with results compared to the computer simulations. One experiment uses nano-gold solution which is heated by a diode laser at 808 nm and temperature increases on the surface and inside the solution are monitored for feedback controlled laser on-off time. The other experiment uses water as the solution and heated by a diode laser at 1450 nm. Our new finding includes the optimal control of the laser on-off time and the adjustment of absorption coefficient by off-resonance excitation. The finding and novel features are analyzed theoretically. Correspondence to: Jui-Teng Lin, New Vision Inc., 5F, No. 27, Lane 10, Jiuquan St. Da-tung Dist. Taipei, Taiwan, Tel: 886-961-306-877; E-mail: jtlin55@gmail.com
Mutation in an Essential Housekeeping Gene Lymphocytes on a Melanoma Result from a Single Point Two Antigens Recognized by Autologous Cytolytic T Updated

We have pursued our analysis of antigens recognized by autologous cytolytic T lymphocytes (CTLs) on the melanoma cells of patient LB33. This patient enjoys an unusually favorable evolution, which is associated with a strong and sustained antitumor CTL response. We reported previously the analysis of two melanoma cell lines, MEL.A and MEL.B, which were derived from metastases removed from the patient at 5 years’ distance. Autologous CTL clones derived from blood lymphocytes recognized several antigens presented by different HLA class I molecules on MEL.A. The MEL.B cells resisted lysis by these CTLs because they have lost expression of most HLA molecules, suggesting that they were selected in vivo by the anti-MEL.A CTL response. One of the MEL.A antigens was shown to result from a point mutation in the tumor. Here we report the cloning of a gene that encodes two other MEL.A antigens. This new gene, MUM-2, is expressed ubiquitously. In the melanoma cells of patient LB33, it contains a point mutation that changes one amino acid in the translated protein. Two different antigenic peptides, one presented to CTL by HLAB44 molecules and another by HLA-C6 molecules, overlap and contain the mutated residue. GeneMUM-2 is homologous to an essential yeast gene, bet5, that was recently shown to be implicated in the vesicular transport of proteins from the endoplasmic reticulum to the Golgi. In a mutant yeast with a disrupted bet5gene, both the wild-type and the mutatedMUM-2 genes could complement forbet5function. These results indicate that the antigenic mutation does not destroy the function of the protein, a function that is conserved in eukaryotic cells. The identification of these antigens suggests that point mutations could be the major cause of the strong immunogenicity of MEL.A cells.
Tensor-Based Dictionary Learning for Spectral CT Reconstruction

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods.