Miracle-dz/UniFAR-FTUs huggingface dataset:
Conformal Spherical Parametrization for High Genus Surfaces

Surface parameterization establishes bijective maps from a surface onto a topologically equivalent standard domain. It is well known that the spherical parameterization is limited to genus-zero surfaces. In this work, we design a new parameter domain, two-layered sphere, and present a framework for mapping high genus surfaces onto sphere. This setup allows us to transfer the existing applications based on general spherical parameterization to the field of high genus surfaces, such as remeshing, consistent parameterization, shape analysis, and so on. Our method is based on Riemann surface theory. We construct meromorphic functions on surfaces: for genus one surfaces, we apply Weierstrass P-functions; for high genus surfaces, we compute the quotient between two holomorphic one-forms. Our method of spherical parameterization is theoretically sound and practically efficient. It makes the subsequent applications on high genus surfaces very promising.
A new method for multiple attribute group decision making based on interval-valued intuitionistic fuzzy aggregation operators and transformation techniques of interval-valued intuitionistic fuzzy values

This paper proposes a new multiple attribute group decision making (MAGDM) method based on the proposed interval-valued intuitionistic fuzzy averaging operators. The proposed multiple attribute group decision making method has the advantage that it can overcome the drawbacks of the existing methods for multiple attribute group decision making in interval-valued intuitionistic fuzzy environments.
Food and Nutrient Intake and Nutritional Status of Finnish Vegans and Non-Vegetarians

Background Vegetarian and vegan diets have become more popular among adolescents and young adults. However, few studies have investigated the nutritional status of vegans, who may be at risk of nutritional deficiencies. Objective To compare dietary intake and nutritional status of Finnish long-term vegans and non-vegetarians. Methods Dietary intake and supplement use were estimated using three-day dietary records. Nutritional status was assessed by measuring biomarkers in plasma, serum, and urine samples. Vegans’ (n = 22) data was compared with those of sex- and age-matched non-vegetarians (n = 19). Results All vegans adhered strictly to their diet; however, individual variability was marked in food consumption and supplementation habits. Dietary intakes of key nutrients, vitamins B12 and D, were lower (P < 0.001) in vegans than in non-vegetarians. Nutritional biomarker measurements showed lower concentrations of serum 25-hydroxyvitamin D3 (25(OH)D3), iodine and selenium (corrected for multiple comparisons, P < 0.001), Vegans showed more favorable fatty acid profiles (P < 0.001) as well as much higher concentrations of polyphenols such as genistein and daidzein (P < 0.001). Eicosapentaenoic acid proportions in vegans were higher than expected. The median concentration of iodine in urine was below the recommended levels in both groups. Conclusions Long-term consumption of a vegan diet was associated with some favorable laboratory measures but also with lowered concentrations of key nutrients compared to reference values. This study highlights the need for nutritional guidance to vegans.
Vitamin D Intake and Status in 6-Year-Old Icelandic Children Followed up from Infancy

High serum 25-hydroxyvitamin D (25(OH)D) levels have been observed in infants in Nordic countries, likely due to vitamin D supplement use. Internationally, little is known about tracking vitamin D status from infancy to childhood. Following up 1-year-old infants in our national longitudinal cohort, our aims were to study vitamin D intake and status in healthy 6-year-old Icelandic children (n = 139) and to track vitamin D status from one year of age. At six years, the mean 25(OH)D level was 56.5 nmol/L (SD 17.9) and 64% of children were vitamin D sufficient (25(OH)D ≥ 50 nmol/L). A logistic regression model adjusted for gender and breastfeeding showed that higher total vitamin D intake (Odds ratio (OR) = 1.27, 95% confidence interval (CI) = 1.08–1.49), blood samples collected in summer (OR = 8.88, 95% CI = 1.83–43.23) or autumn (OR = 5.64, 95% CI = 1.16–27.32) compared to winter/spring, and 25(OH)D at age one (OR = 1.02, 95% CI = 1.002–1.04) were independently associated with vitamin D sufficiency at age six. The correlation between 25(OH)D at age one and six was 0.34 (p = 0.003). Our findings suggest that vitamin D status in infancy, current vitamin D intake and season are predictors of vitamin D status in early school age children. Our finding of vitamin D status tracking from infancy to childhood provides motivation for further studies on tracking and its clinical significance.
Automatic generation of time efficient digital signal processing software

Optimal use of high-speed programmable digital signal processors generally demands familiarity with machine architectural features and hence, production of programs whose structure reflects and exploits those features. In contrast, it is apparent that little effort has been made to develop programming techniques which fully realize the signal processing computational capability of standard minicomputers. In this paper, it is shown that a functional high-level language signal processing program can easily be modified so as to produce a similar program which, when executed, automatically generates another program containing precomputed algorithm sequencing and data access information. The generated program will then utilize central processor arithmetic and logical capability only for data-dependent computation. In this way, instructions normally associated with computation for program sequencing/control or data access are eliminated, and all benefits of increased algorithm complexity for reduction of data-dependent arithmetic computation are in fact realized as decreased program execution time. Examples are given of Fortran programs which generate Fortran FFT subroutines and, for completeness, assembly language realizations of the Pfeifer/Blankinship autocorrelation algorithm. Results demonstrate that, using this technique, standard minicomputers may execute digital signal processing algorithms faster than peripheral processors which normally require standard minicomputers as host processors.
Health‐related quality of life among adolescents: a comparison between subjects at risk for psychosis and other help seekers

Schizophrenia is a severe illness associated with poor health‐related quality of life (HRQoL), and there is some evidence that a risk state for psychosis is associated with decreased HRQoL. The aim of the present study was to investigate group differences in HRQoL in help seekers at risk for psychosis and not at risk for psychosis.
Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets

MOTIVATION Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. RESULTS We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. AVAILABILITY Scripts written in Python and R are available at http://biosoft.kaist. ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
A Mining Algorithm For Email's Relationships Based on Neural Networks

The analysis of the vast storehouse of email content accumulated or produced by individual users has received relatively little attention other than for specific tasks such as relationship. Current email analysis in standard client applications consists of keyword based matching techniques for relationship of email files. We have implemented a tool, called the email mining set (EMS) for analyzing email archives which includes a graphical display to explore relationships between users and groups of email users. Our design goal is to embed the technology into standard email clients, such as foxmail and Outlook, revealing far more information about a userpsilas relationship is otherwise now possible.
Disamibiguating and Interpreting Verb Definitions

To achieve our goal of building a comprehensive lexical database out of various on-line resources, it is necessary to interpret and disambiguate the information found in these resources. In this paper we describe a Disambiguation Module which analyzes the content of dictionary definitions, in particular, definitions of the form "to VERB with NP". We discuss the semantic relations holding between the head and the prepositional phrase in such structures, as well as our heuristics for identifying these relations and for disambiguating the senses of the words involved. We present some results obtained by the Disambiguation Module and evaluate its rate of success as compared with results obtained from human judgments.
Impact of a Replacement Algorithm for Vitamin D Deficiency in Adult Hematopoietic Stem Cell Transplant Patients

Adults undergoing hematopoietic stem cell transplant (HSCT) are at risk for vitamin D deficiency. After HSCT, exposure to sunlight is restricted, and patients may experience poor nutrition and malabsorption from HSCT-related side effects. Vitamin D affects bone health and immunologic processes. The aim of this project is to establish a process for monitoring and treating vitamin D deficiency and to evaluate if therapeutic vitamin D levels are attainable posttransplant using an HSCT vitamin D replacement algorithm. A multidisciplinary group led by advanced practice providers established a workflow for monitoring and supplementing vitamin D and created an HSCT vitamin D replacement guideline. The medical records of 144 adult HSCT patients were reviewed, and the records of another 72 patients were reviewed a year later. Historical baseline data before the intervention found that 81% of patients were vitamin D deficient and 30% received supplementation. Postintervention and at 1-year follow-up, 76% and 65% of patients were vitamin D deficient before transplant and 97.1% and 100%, respectively, received supplementation for vitamin D deficiency. Post-HSCT compliance with monitoring demonstrated that approximately 91% of patients had a vitamin D level checked within 6 months of transplant. After implementation of the algorithm, there was a statistically significant difference (p < .001) between deficient vitamin D levels pretransplant (72.9%) and posttransplant (26.4%). Results demonstrate sustained compliance over a 2-year period with monitoring and supplementation of vitamin D pre- and peritransplant. Aggressive vitamin D repletion posttransplant decreased the incidence of vitamin D deficiency in HSCT patients. Further study is needed to investigate the long-term effects of vitamin D repletion on posttransplant complications.
Effects of Silver Nanoparticles on Multiple Drug-Resistant Strains of Staphylococcus aureus and Pseudomonas aeruginosa from Mastitis-Infected Goats: An Alternative Approach for Antimicrobial Therapy

Recently, silver nanoparticles (AgNPs) have been widely used in various applications as antimicrobial agents, anticancer, diagnostics, biomarkers, cell labels, and drug delivery systems for the treatment of various diseases. Microorganisms generally acquire resistance to antibiotics through the course of antibacterial therapy. Multi-drug resistance (MDR) has become a growing problem in the treatment of infectious diseases, and the widespread use of broad-spectrum antibiotics has resulted in the development of antibiotic resistance by numerous human and animal bacterial pathogens. As a result, an increasing number of microorganisms are resistant to multiple antibiotics causing continuing economic losses in dairy farming. Therefore, there is an urgent need for the development of alternative, cost-effective, and efficient antimicrobial agents that overcome antimicrobial resistance. Here, AgNPs synthesized using the bio-molecule quercetin were characterized using various analytical techniques. The synthesized AgNPs were highly spherical in shape and had an average size of 11 nm. We evaluated the efficacy of synthesized AgNPs against two MDR pathogenic bacteria, namely, Pseudomonas aeruginosa and Staphylococcus aureus, which were isolated from milk samples produced by mastitis-infected goats. The minimum inhibitory concentrations (MICs) of AgNPs against P. aeruginosa and S. aureus were found to be 1 and 2 μg/mL, respectively. Our findings suggest that AgNPs exert antibacterial effects in a dose- and time-dependent manner. Results from the present study demonstrate that the antibacterial activity of AgNPs is due to the generation of reactive oxygen species (ROS), malondialdehyde (MDA), and leakage of proteins and sugars in bacterial cells. Results of the present study showed that AgNP-treated bacteria had significantly lower lactate dehydrogenase activity (LDH) and lower adenosine triphosphate (ATP) levels compared to the control. Furthermore, AgNP-treated bacteria showed downregulated expression of glutathione (GSH), upregulation of glutathione S-transferase (GST), and downregulation of both superoxide dismutase (SOD) and catalase (CAT). These physiological and biochemical measurements were consistently observed in AgNP-treated bacteria, thereby suggesting that AgNPs can induce bacterial cell death. Thus, the above results represent conclusive findings on the mechanism of action of AgNPs against different types of bacteria. This study also demonstrates the promising use of nanoparticles as antibacterial agents for use in the biotechnology and biomedical industry. Furthermore, this study is the first to propose the mode of action of AgNPs against MDR pathogens isolated from goats infected with subclinical mastitis.
Natural Variation in Small Molecule–Induced TIR-NB-LRR Signaling Induces Root Growth Arrest via EDS1- and PAD4-Complexed R Protein VICTR in Arabidopsis[C][W]

This chemical genetics work reveals natural variation in a newly identified R protein homolog, named VICTR, that produces primary root growth arrest in response to the small molecule DFPM. DFPM perception and signal transduction require early components of the plant R gene resistance signaling network, and the R protein VICTR coresides in complexes not only with EDS1 but also PAD4. In a chemical genetics screen we identified the small-molecule [5-(3,4-dichlorophenyl)furan-2-yl]-piperidine-1-ylmethanethione (DFPM) that triggers rapid inhibition of early abscisic acid signal transduction via PHYTOALEXIN DEFICIENT4 (PAD4)- and ENHANCED DISEASE SUSCEPTIBILITY1 (EDS1)-dependent immune signaling mechanisms. However, mechanisms upstream of EDS1 and PAD4 in DFPM-mediated signaling remain unknown. Here, we report that DFPM generates an Arabidopsis thaliana accession-specific root growth arrest in Columbia-0 (Col-0) plants. The genetic locus responsible for this natural variant, VICTR (VARIATION IN COMPOUND TRIGGERED ROOT growth response), encodes a TIR-NB-LRR (for Toll-Interleukin1 Receptor–nucleotide binding–Leucine-rich repeat) protein. Analyses of T-DNA insertion victr alleles showed that VICTR is necessary for DFPM-induced root growth arrest and inhibition of abscisic acid–induced stomatal closing. Transgenic expression of the Col-0 VICTR allele in DFPM-insensitive Arabidopsis accessions recapitulated the DFPM-induced root growth arrest. EDS1 and PAD4, both central regulators of basal resistance and effector-triggered immunity, as well as HSP90 chaperones and their cochaperones RAR1 and SGT1B, are required for the DFPM-induced root growth arrest. Salicylic acid and jasmonic acid signaling pathway components are dispensable. We further demonstrate that VICTR associates with EDS1 and PAD4 in a nuclear protein complex. These findings show a previously unexplored association between a TIR-NB-LRR protein and PAD4 and identify functions of plant immune signaling components in the regulation of root meristematic zone-targeted growth arrest.
Efficient query processing using histograms in a columnar database

The invention relates to efficient query processing using histograms in a columnar database. A probabilistic data structure is generated for efficient query processing using a histogram for unsorted data in a column of a columnar database. A bucket range size is determined for multiples buckets of a histogram of a column in a columnar database table. In at least some embodiments, the histogram may be a height-balanced histogram. A probabilistic data structure is generated to indicate for which particular buckets in the histogram there is a data value stored in the data block. When an indication of a query directed to the column for select data is received, the probabilistic data structure for each of the data blocks storing data for the column may be examined to determine particular ones of the data blocks which do not need to be read in order to service the query for the select data.
High Phase Order Induction Motors - Part I. Description and Theoretical Considerations

The characteristics of induction motors having more than three phases are presented. The sequence sets of the symmetrical component method are used to determine the inductances with time harmonics in the source waveform such as for inverter sources. The effect of stator coil pitch on these inductances is explained. It is shown that some of these harmonics cannot induce rotor currents in motors having many phases, thereby reducing the torque pulsations and rotor I2R loss below the values for three-phase motors. Other advantages are lower current per phase and the ability of the motor to start and run with one phase open. Six and nine-phase motors are found to be especially attractive.
Determination of Cepheid parameters by light-curve template fitting

We describe techniques to characterize the light curves of regular variable stars by applying principal component analysis (PCA) to a training set of high-quality data, and to fit the resulting light-curve templates to sparse and noisy photometry to obtain parameters such as periods, mean magnitudes etc. The PCA approach allows us to efficiently represent the multiband light-curve shapes (LCSs) of each variable, and hence quantitatively describe the average behaviour of the sample as a smoothly varying function of period, and also the range of variation around this average. In this paper we focus particularly on the utility of such methods for analysing Hubble Space Telescope (HST) Cepheid photometry, and present simulations which illustrate the advantages of our PCA template-fitting approach. These are: accurate parameter determination, including LCS information; simultaneous fitting to multiple passbands; quantitative error analysis; objective rejection of variables with non-Cepheid-like light curves or those with potential period aliases. We also use PCA to confirm that Cepheid LCSs are systematically different (at the same period) between the Milky Way and the Large and Small Magellanic Clouds, and consider whether LCS might therefore be used to estimate the mean metallicities of Cepheid samples, thus allowing metallicity corrections to be applied to derived distance estimates.
Effect of exposure to p,p'-DDE on male hormone profile in Mexican flower growers

Objectives p,p'-Dichlorodiphenyldichloroethene (p,p'-DDE) acts as an androgen receptor antagonist, however data regarding its hormonal effects in men are limited. The objective of this study was to evaluate the association between serum levels of p,p'-DDE and reproductive hormone profile in Mexican male flower growers. Methods A longitudinal study was carried out in a population of men working in the production of flowers and ornamental plants in two Mexican states during July–October 2004 (rainy season) and December 2004–May 2005 (dry season). A questionnaire including information on socioeconomic characteristics, tobacco and alcohol use, presence of chronic and acute diseases, occupational history and anthropometry was used and blood and urine samples were obtained. Serum levels of p,p'-DDE were analysed by gas chromatography; FSH, LH, testosterone, oestradiol, inhibin B and prolactin levels were measured by enzymatic immunoassay. Urinary levels of dialkylphosphates (DAPs) were analysed by gas chromatography. Associations between serum levels of p,p'-DDE and male reproductive hormones (both transformed to their natural logarithm) were evaluated using multivariate generalised estimating equation (GEE) models. Results Median p,p'-DDE levels were 677.2 ng/g lipid (range 9.4–12 696.5) during the rainy season and 626.7 ng/g lipid (range 9.4–13 668.1) during the dry season. After adjusting for potential confounders (age, body mass index, state of residence and DAPs), p,p'-DDE levels were negatively associated with prolactin (β=−0.04; 95% CI −0.07 to −0.008) and testosterone (β=0.04; 95% CI −0.08 to 0.005) and positively with inhibin B (β=0.11; 95% CI 0.02 to 0.21). Conclusion These results indicate that p,p'-DDE can affect hypothalamic–pituitary–gonadal axis function in humans.
Loss of cholinergic and dopaminergic amacrine cells in streptozotocin-diabetic rat and Ins2Akita-diabetic mouse retinas.

PURPOSE To identify amacrine cells that are vulnerable to degeneration during the early stages of diabetes. METHODS Whole retinas from streptozotocin (STZ)-diabetic rats and Ins2(Akita) mice were fixed in paraformaldehyde. Apoptotic cells in the retina were quantified using terminal dUTP nick-end labeling (TUNEL) and active caspase-3 (CM-1) immunohistochemistry. Immunohistochemical markers for choline acetyltransferase (ChAT) and tyrosine hyroxylase (TH) were also used to quantify populations of amacrine cells in the Ins2Akita mouse retinas. RESULTS The number of TUNEL-positive nuclei increased from 29+/-4 in controls to 72+/-9 in the STZ-diabetic rat retinas after only 2 weeks of diabetes. In rats, CM-1-immunoreactive (IR) cells were found primarily in the inner nuclear and ganglion cell layers after 2, 8, and 16 weeks of diabetes. At each end point, the number of CM-1-IR cells in the retina was elevated by diabetes. Approximately 2% to 6% of the CM-1-IR cells in the inner nuclear layer (INL) were double-labeled for TH immunoreactivity. After 6 months of diabetes in the Ins2Akita mouse, the morphology of the labeled ChAT-IR and TH-IR amacrine cell somas and dendrites appeared normal. A quantitative analysis revealed a 20% decrease in the number of cholinergic and a 16% decrease in dopaminergic amacrine cells in the diabetic mouse retinas, compared with the nondiabetic control. CONCLUSIONS Dopaminergic and cholinergic amacrine cells are lost during the early stages of retinal neuropathy in diabetes. Loss of these neurons may play a critical role in the development of visual deficits in diabetes.