Miracle-dz/UniFAR-FTUs huggingface dataset:
A Toolbox of Level Set Methods version 1.0

This document describes a toolbox of level set methods for solving time-dependent Hamilton-Jacobi partial differential equations (PDEs) in the Matlab programming environment. Level set methods are often used for simulation of dynamic implicit surfaces in graphics, fluid and combustion simulation, image processing, and computer vision. Hamilton-Jacobi and related PDEs arise in fields such as control, robotics, differential games, dynamic programming, mesh generation, stochastic differential equations, financial mathematics, and verification. The algorithms in the toolbox can be used in any number of dimensions, although computational cost and visualization difficulty make dimensions four and higher a challenge. All source code for the toolbox is provided as plain text in the Matlab m-file programming language. The toolbox is designed to allow quick and easy experimentation with level set methods, although it is not by itself a level set tutorial and so should be used in combination with the existing literature.
Socioeconomic Factors Affect Outcomes in Well-Differentiated Thyroid Cancer

Objectives The effects of socioeconomic status (SES) on the incidence of well-differentiated thyroid cancer (WDTC) are well researched. However, the association between SES and outcomes is not delineated. Our objective was to determine if SES affected outcomes of WDTC. Study Designs Retrospective database review. Setting Tertiary care medical center. Subjects and Methods The Henry Ford Virtual Data Warehouse Tumor Registry was used to identify cases of WDTC. Socioeconomic data were obtained through the 2010 US Census: median household income, percentage below poverty line, median household size, percentage rent versus own property, and general demographics. Survival was the primary outcome. Disease-specific survival was also calculated. Cox proportional hazards were calculated and a multivariate analysis performed. Results There were 1317 patients with WDTC. In multivariable analysis, median household income (hazard ratio [HR]: 0.85, 95% confidence interval [95% CI]: 0.79-0.91), household size (HR: 1.49, 95% CI: 1.09-2.14), younger age (HR: 1.97, 95% CI: 1.74-2.23), and female sex (HR: 0.50, 95% CI: 0.37-0.69) were significantly associated with survival. Controlling for stage revealed percentage below poverty line (stage I, HR: 0.51, 95% CI: 1.34-1.78; stage IV, HR: 1.28, 95% CI: 1.04-1.57) and median household income (HR: 0.84, 95% CI: 0.71-0.99) to be significant factors in survival. Median household income was a statistically significant variable for disease-related death (HR: 0.82, 95% CI: 0.69-0.96) Conclusions Along with effects on incidence, lower SES correlates with worse survival in WDTC. This suggests that a patient’s economic background, with younger age and female sex, influences one’s outcomes with regard to both overall and disease-specific death.
Identification of Equivalent Faults in Logic Networks

The properties of combinational logic functions and networks that influence equivalence among stuck-type faults are investigated. It is shown that the equivalence of certain types of faults depends only on the function being realized. For instance, the fault classes among primary input/output faults are of this type. It is shown that every irredundant realization of the two-variable EXCLUSIVE-OR function has a unique set of ten fault classes. A fault class F in a module M contained in a network N is called intrinsic, if F can be determined from M alone, i. e. , F is independent of N. Using the concepts of intrinsic equivalence and inversion parity, conditions for the equivalence and nonequivalence of two fault classes are obtained. These results are applied to the problem of equivalence identification in two-level logic networks where they provide a substantial reduction in the amount of computation required.
A Perceptron Reveals the Face of Sex

Recognizing the sex of conspecifics is important. Humans rely primarily on visual pattern recognition for this task. A wide variety of linear and nonlinear models have been developed to understand this task of sex recognition from human faces. ' These models have used both pixelbased and feature-based representations of the face for input. Fleming and Cottrell (1990) and Golomb et a! (1991) utilized first an autoencoder compression network on a pixel-based representation, and then a classification network. Brunelli and Poggio (1993) used a type of radial basis function network with geometrical face measurements as input. O'Toole and colleagues (1991, 1993) represented faces as principal components. When the hidden units of an autoencoder have a linear output function, then the N hidden units in the network span the first N principal components of the input (Baldi and Hornik 1989). Bruce et al. (1993) constructed a discriminant function for sex with 2-D and 3-D facial measures. In this note we compare the performance of a simple perceptron and a standard multilayer perceptron (MLP) on the sex classification task. We used a range of spatial resolutions of the face to determine how the reliability of sex discrimination is related to resolution. A normalized pixel-based representation was used for the faces because it explicitly retained texture and shape information while also maintaining geometric relationships. We found that the linear perceptron model can classify sex from facial images with 81% accuracy, compared to 92% accuracy with compression coding on the same data set (Golomb et al. 1991). The advantage of using a simple linear perceptron with normalized pixelbased inputs is that it allows us to see explicitly those regions of the face
The B95-8 isolate of Epstein-Barr virus arose from an isolate with a standard genome

Blot hybridization studies revealed that the deletion which characterizes the DNA from the B95-8 strain of Epstein-Barr virus was not present in the virus from which the B95-8 strain was derived (883L). The deletion event must have occurred during establishment of the B95-8 cell line or very soon afterward, since the deletion was present in Epstein-Barr virus DNA from a cell line established with B95-8 virus soon after it became available. The presence of the deletion correlates with decreased expression of the gp220 viral envelope glycoprotein.
Homozygous Familial Hypercholesterolemia in Spain: Prevalence and Phenotype-Genotype Relationship.

BACKGROUND Homozygous familial hypercholesterolemia (HoFH) is a rare disease characterized by elevated plasma levels of low-density lipoprotein cholesterol (LDL-C) and extremely high risk of premature atherosclerotic cardiovascular disease. HoFH is caused by mutations in several genes, including LDL receptor (LDLR), apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDL protein receptor adaptor 1 (LDLRAP1). No epidemiological studies have assessed HoFH prevalence or the clinical and molecular characteristics of this condition. Here, we aimed to characterize HoFH in Spain. METHODS AND RESULTS Data were collected from the Spanish Dyslipidemia Registry of the Spanish Atherosclerosis Society and from all molecular diagnoses performed for familial hypercholesterolemia in Spain between 1996 and 2015 (n=16 751). Clinical data included baseline lipid levels and atherosclerotic cardiovascular disease events. A total of 97 subjects were identified as having HoFH-of whom, 47 were true homozygous (1 for APOB, 5 for LDLRAP1, and 41 for LDLR), 45 compound heterozygous for LDLR, 3 double heterozygous for LDLR and PSCK9, and 2 double heterozygous for LDLR and APOB. No PSCK9 homozygous cases were identified. Two variants in LDLR were identified in 4.8% of the molecular studies. Over 50% of patients did not meet the classical HoFH diagnosis criteria. The estimated HoFH prevalence was 1:450 000. Compared with compound heterozygous cases, true homozygous cases showed more aggressive phenotypes with higher LDL-C and more atherosclerotic cardiovascular disease events. CONCLUSIONS HoFH frequency in Spain was higher than expected. Clinical criteria would underestimate the actual prevalence of individuals with genetic HoFH, highlighting the importance of genetic analysis to improve familial hypercholesterolemia diagnosis accuracy.
CT-Angiography–Based Evaluation of the Aortic Annulus for Prosthesis Sizing in Transcatheter Aortic Valve Implantation (TAVI)–Predictive Value and Optimal Thresholds for Major Anatomic Parameters

Background/Objectives To evaluate the predictive value of CT-derived measurements of the aortic annulus for prosthesis sizing in transcatheter aortic valve implantation (TAVI) and to calculate optimal cutoff values for the selection of various prosthesis sizes. Methods The local IRB waived approval for this single-center retrospective analysis. Of 441 consecutive TAVI-patients, 90 were excluded (death within 30 days: 13; more than mild aortic regurgitation: 10; other reasons: 67). In the remaining 351 patients, the CoreValve (Medtronic) and the Edwards Sapien XT valve (Edwards Lifesciences) were implanted in 235 and 116 patients. Optimal prosthesis size was determined during TAVI by inflation of a balloon catheter at the aortic annulus. All patients had undergone CT-angiography of the heart or body trunk prior to TAVI. Using these datasets, the diameter of the long and short axis as well as the circumference and the area of the aortic annulus were measured. Multi-Class Receiver-Operator-Curve analyses were used to determine the predictive value of all variables and to define optimal cutoff-values. Results Differences between patients who underwent implantation of the small, medium or large prosthesis were significant for all except the large vs. medium CoreValve (all p’s<0.05). Furthermore, mean diameter, annulus area and circumference had equally high predictive value for prosthesis size for both manufacturers (multi-class AUC’s: 0.80, 0.88, 0.91, 0.88, 0.88, 0.89). Using the calculated optimal cutoff-values, prosthesis size is predicted correctly in 85% of cases. Conclusion CT-based aortic root measurements permit excellent prediction of the prosthesis size considered optimal during TAVI.
A Rule-Based Temporal Analysis Method for Online Health Analytics and Its Application for Real-Time Detection of Neonatal Spells

Neonatal spells are cardiorespiratory events that occur in newborn infants with variable combinations of cessation of breathing, decrease in blood oxygen saturation and decrease in heart rate. A system using real-time temporal analysis of physiological data streams to accurately detect pauses in breathing and changes in heart rate and oxygen saturation for classifying neonatal spells is described. The system uses a multidimensional online health analytics environment that supports the acquisition, transmission and real-time processing of high volume, high rate data. A family of algorithms has been developed using IBM InfoSphere Streams, a scalable middleware component for analysing multiple streams of data in real-time. Respiratory pauses are identified by accurately detecting breaths and calculating time intervals between breaths. Changes in heart rate and blood oxygen saturation are identified by both threshold breaches and the detection of relative change by assessing a sliding baseline and generating alerts when values fall out of range. Events detected in individual signals are synced together based on timestamps and assessed using a classifier based on clinical rules to determine a classification of neonatal spells. The output of these algorithms has been shown, in a single use case study with 24 hours of patient data, to detect clinically significant events in heart rate, blood oxygen saturation and pauses in breathing. The accuracy for detecting these is 97.8%, 98.3% and 98.9% respectively. The accuracy for determining spells classifications is 98.9%. Future research will focus on the clinical validation of these algorithms.
Random walks and an O*(n5) volume algorithm for convex bodies

Abstract Given a high dimensional convex body K ⊆ IR by a separation oracle, we can approximate its volume with relative error ε, using O∗(n5) oracle calls. Our algorithm also brings the body into isotropic position. As all previous randomized volume algorithms, we use “rounding” followed by a multiphase Monte-Carlo (product estimator) technique. Both parts rely on sampling (generating random points in K), which is done by random walk. Our algorithm introduces three new ideas: • the use of the isotropic position (or at least an approximation of it) for rounding, • the separation of global obstructions (diameter) and local obstructions (boundary problems) for fast mixing, and • a stepwise interlacing of rounding and sampling.
Evidence-based common sense: the role of clinical history for the diagnosis of vasovagal syncope.

This editorial refers to ‘Diagnostic criteria for vasovagal syncope based on a quantitative history’† by R. Sheldon et al . , on page 344 In the present article a form of fainting is described for which the term ‘vasovagal syncope’ will be found most appropriate Sir Thomas Lewis, 1932 Syncope is a frequent clinical manifestation and represents ∼1–2% of emergency room visits and frequently leads to hospital admission and expensive and frequently unnecessary diagnostic tests.1,2 The cause of syncope is frequently reflex mediated, and particularly vasovagal responses closely followed by orthostatic hypotension and drug-induced syncope are the main causes.3 By and large, the prognosis of patients with vasovagal syncope is benign; however, quality of life may be severely affected in a significant proportion of patients. The most challenging problem surrounding the appropriate diagnosis of syncope is that at the time of medical assessment most patients are completely free of symptoms or worrisome clinical findings. The proper diagnosis lies then in a thorough recording of the events preceding and surrounding the syncopal episode, what most of us were taught in medical school as taking the clinical history. It is unclear when the first description of vasovagal syncope was reported in … *Corresponding author. Tel: +1 905 577 8004; fax: +1 905 521 8820. E-mail address : morillo{at}hhsc.ca or morillc{at}mcmaster.ca
The Association of the Immune Response Genes to Human Papillomavirus-Related Cervical Disease in a Brazilian Population

The genetic variability of the host contributes to the risk of human papillomavirus (HPV)-related cervical disease. Immune response genes to HPV must be investigated to define patients with the highest risk of developing malignant disease. The aim of this study was to investigate the association of polymorphic immune response genes, namely KIR, HLA class I and II, and single-nucleotide polymorphisms (SNPs) of cytokines with HPV-related cervical disease. We selected 79 non-related, admixed Brazilian women from the state of Paraná, southern region of Brazil, who were infected with high carcinogenic risk HPV and present cervical intraepithelial neoplasia grade 3 (CIN3), and 150 HPV-negative women from the same region matched for ethnicity. KIR genes were genotyped using an in-house PCR-SSP. HLA alleles were typed using a reverse sequence-specific oligonucleotide technique. SNPs of TNF −308G>A, IL6 −174G>C, IFNG +874T>A, TGFB1 +869T>C +915G>C, and IL10 −592C>A −819C>T −1082G>A were evaluated using PCR-SSP. The KIR genes were not associated with HPV, although some pairs of i(inhibitory)KIR-ligands occurred more frequently in patients, supporting a role for NK in detrimental chronic inflammatory and carcinogenesis. Some HLA haplotypes were associated with HPV. The associations of INFG and IL10 SNPs potentially reflect impaired or invalid responses in advanced lesions.
CDC/AHA Workshop on Markers of Inflammation and Cardiovascular Disease: Application to Clinical and Public Health Practice: report from the clinical practice discussion group.

The Centers for Disease Control and Prevention (CDC) in collaboration with the American Heart Association (AHA) convened a workshop in Atlanta, Ga, on March 14 and 15, 2002, titled, “CDC/AHA Workshop on Inflammatory Markers and Cardiovascular Disease: Applications to Clinical and Public Health Practice,” which was intended to address issues about the appropriate selection and use of inflammatory markers to predict cardiovascular disease (CVD) risk.1 Three concurrent discussion groups on issues related to laboratory, clinical, and population science were held. This report details the discussions and findings of the laboratory science group. 1. Of the inflammatory markers identified, C-reactive protein (CRP) has the analyte and assay characteristics that are the most conducive for use in practice. 2. To obtain a CRP concentration in metabolically stable patients, 2 measurements, fasting or nonfasting, should be made (optimally 2 weeks apart) and the results averaged. If the CRP level is >10 mg/L, then the test should be repeated and the patient examined for sources of infection or inflammation. 3. CRP results should be expressed only as milligrams per liter and expressed to 1 decimal point. 4. Risk assessment should be modeled after the lipids approach via 3 risk categories: low risk, average risk, and high risk. On the basis of the CRP population distributions, the following tertiles are recommended for categorizing patients: low risk, 3.0 mg/L. It should be recognized that other acute inflammatory conditions may result in mildly to moderately increased CRP levels, such as inflammatory bowel disease,2 rheumatoid arthritis,3 and long-term alcoholism.4 5. Performance goals for CRP measurement, similar to those developed for total cholesterol, HDL and LDL cholesterol, and triglycerides, need to be developed with a view toward better characterization of the total allowable error required to measure CRP reliably. …
Ethnic Differences in the Systemic Pharmacology for Ophthalmologists

Ophthalmology utilizes many topical and systemic medications in its practice. Although the ethnic differences among ophthalmic medications are not extensive, there are reported differences among the various medications. Mydriatic agents, immunosuppressive agents, and glaucoma medications are all utilized in the practice of ophthalmology and have shown documented ethnic differences. Although these differences are unlikely to alter the utilization of these medications, it is helpful to remember the differences in efficacy or side effects based on ethnicity.
Priming for self-esteem influences the monitoring of one’s own performance

Social cues have subtle effects on a person, often without them being aware. One explanation for this influence involves implicit priming of trait associations. To study this effect, we activated implicit associations in participants of ‘being Clever’ or ‘being Stupid’ that were task relevant, and studied its behavioural impact on an independent cognitive task (the n-back task). Activating a representation of ‘Clever’ caused participants to slow their reaction times after errors on the working memory task, while the reverse pattern was seen for associations to ‘Stupid’. Critically, these behavioural effects were absent in control conditions. Using functional magnetic resonance imaging, we show that the neural basis of this effect involves the anterior paracingulate cortex (area 32) where activity tracked the observed behavioural pattern, increasing its activity during error monitoring in the ‘Clever’ condition and decreasing in the ‘Stupid’ condition. The data provide a quantitative demonstration of how implicit cues, which specifically target a person’s self-concept, influences the way we react to our own behaviour and point to the anterior paracingulate cortex as a critical cortical locus for mediating these self-concept related behavioural regulations.
A Minimum Distortion Noise Reduction Algorithm With Multiple Microphones

The problem of noise reduction using multiple microphones has long been an active area of research. Over the past few decades, most efforts have been devoted to beamforming techniques, which aim at recovering the desired source signal from the outputs of an array of microphones. In order to work reasonably well in reverberant environments, this approach often requires such knowledge as the direction of arrival (DOA) or even the room impulse responses, which are difficult to acquire reliably in practice. In addition, beamforming has to compromise its noise reduction performance in order to achieve speech dereverberation at the same time. This paper presents a new multichannel algorithm for noise reduction, which formulates the problem as one of estimating the speech component observed at one microphone using the observations from all the available microphones. This new approach explicitly uses the idea of spatial-temporal prediction and achieves noise reduction in two steps. The first step is to determine a set of inter-sensor optimal spatial-temporal prediction transformations. These transformations are then exploited in the second step to form an optimal noise-reduction filter. In comparison with traditional beamforming techniques, this new method has many appealing properties: it does not require DOA information or any knowledge of either the reverberation condition or the channel impulse responses; the multiple microphones do not have to be arranged into a specific array geometry; it works the same for both the far-field and near-field cases; and, most importantly, it can produce very good and robust noise reduction with minimum speech distortion in practical environments. Furthermore, with this new approach, it is possible to apply postprocessing filtering for additional noise reduction when a specified level of speech distortion is allowed.
The Depth and Breadth of Google Scholar: An Empirical Study

The introduction of Google Scholar in November 2004 was accompanied by fanfare, skepticism, and numerous questions about the scope and coverage of this database. Nearly one year after its inception, many of these questions remain unanswered. This study compares the contents of 47 different databases with that of Google Scholar. Included in this investigation are tests for Google Scholar publication date and publication language bias, as well as a study of upload frequency. Tests show Google Scholar’s current strengths to be coverage of science and medical databases, open access databases, and single publisher databases. Current weaknesses include lack of coverage of social science and humanities databases and an English language bias.
MENTAL HEALTH IN THE CLIMACTERIC

Abstract. A representative sample of 899 middle‐aged urban Swedish women underwent a psychiatric interview on two occasions with 6 years between studies (waves). The point prevalence of all mental disorders was 39.9% at the first wave and 39.0% at the second. The corresponding one‐year onset rates of all mental disorders were 18.0% and 14.2%. No significant differences were found between ages or between waves. Major depressive episodes accounted for about half of the psychiatric morbidity. Those women whose menopause started early were more often mentally impaired than others and they also tended to have been more often impaired even before the climacteric (ages 30‐39).