Miracle-dz/UniFAR-FTUs huggingface dataset:
Survival Analysis of Patients with High-Grade Gliomas Based on Data Mining of Imaging Variables

The authors compared survival prediction using machine-learning data-mining techniques versus traditional histopathologic analysis in a group of 74 tumors. They looked at 55 imaging variables, extracting the most important ones and comparing these with standard histology. The most important variables were: extent of resection, mass effects, volume of enhancing tumor, maximum T2 intensity, and mean trace intensity in non-enhancing or edematous surrounding areas. The accuracy of the data-mining method was 85% and based on Kaplan-Meier curves this predicted survival better than histology. BACKGROUND AND PURPOSE: The prediction of prognosis in HGGs is poor in the majority of patients. Our aim was to test whether multivariate prediction models constructed by machine-learning methods provide a more accurate predictor of prognosis in HGGs than histopathologic classification. The prediction of survival was based on DTI and rCBV measurements as an adjunct to conventional imaging. MATERIALS AND METHODS: The relationship of survival to 55 variables, including clinical parameters (age, sex), categoric or continuous tumor descriptors (eg, tumor location, extent of resection, multifocality, edema), and imaging characteristics in ROIs, was analyzed in a multivariate fashion by using data-mining techniques. A variable selection method was applied to identify the overall most important variables. The analysis was performed on 74 HGGs (18 anaplastic gliomas WHO grades III/IV and 56 GBMs or gliosarcomas WHO grades IV/IV). RESULTS: Five variables were identified as the most significant, including the extent of resection, mass effect, volume of enhancing tumor, maximum B0 intensity, and mean trace intensity in the nonenhancing/edematous region. These variables were used to construct a prediction model based on a J48 classification tree. The average classification accuracy, assessed by cross-validation, was 85.1%. Kaplan-Meier survival curves showed that the constructed prediction model classified malignant gliomas in a manner that better correlates with clinical outcome than standard histopathology. CONCLUSIONS: Prediction models based on data-mining algorithms can provide a more accurate predictor of prognosis in malignant gliomas than histopathologic classification alone.
The micro-macroscale correlation of NiTi mechanical behavior: a finite element analysis

One material that has found particular favor for use in biomedical endovascular stents is the near equi-atomic NiTi alloy, Nitinol. One remarkable trait exhibited by this superelastic material is the improvement of its fatigue performance with increasing mean strain [1, 2]. Clarification into this phenomenon still remains incomplete in literature. This study proposes a microstructural explanation for this unique macroscopic behavior; it is hypothesized stress-induced martensite (SIM) will stabilize with increasing strain which, in turn, leads to the observed increase in fatigue life. Finite Element Analysis (FEA) is employed to investigate the behavior of a ‘v-strut’ stent subcomponent under various strain levels. The volume fraction of SIM is analyzed to identify its potential influence on macroscopic response and, ultimately, fatigue behavior. In addition, a computational investigation is performed on the effect of crystallographic texture on macroscopic response. Granular transformational behavior is analyzed using FEA models with realistic and idealized grain structures, specifically evaluating the effect of individual grain orientations on the stress-induced martensite transformation (SIMT).
Amino Acid Sequence Requirement for Efficient Incorporation of Glycosylphosphatidylinositol-associated Proteins into the Cell Wall of Saccharomyces cerevisiae *

During cell wall biogenesis inSaccharomyces cerevisiae, some glycosylphosphatidylinositol (GPI)-attached proteins are detached from GPI moieties and bound to β-1,6-glucan of the cell wall. The amino acid sequence requirement for the incorporation of GPI-attached proteins into the cell wall was studied by using reporter fusion proteins. Only the short ω-minus region composed of five amino acids, which is located upstream of the ω site for GPI attachment, determined the cellular localization of the GPI-associated proteins. Within the ω-minus region, amino acid residues at the ω-4 or -5 and ω-2 sites were important for the cell wall incorporation. Yap3p, a well characterized GPI-anchored plasma membrane aspartic protease, was localized in the cell wall when the ω-minus region was mutated to sequences containing Val or Ile at the ω-4 or -5 site and Val or Tyr at the ω-2 site.
Motor cortex stimulation for pain control induces changes in the endogenous opioid system

Background: Motor cortex stimulation (MCS) for neuropathic pain control induces focal cerebral blood flow changes involving regions with high density of opioid receptors. We studied the possible contribution of the endogenous opioid system to MCS-related pain relief. Methods: Changes in opioid receptor availability induced by MCS were studied with PET scan and [11C]diprenorphine in eight patients with refractory neuropathic pain. Each patient underwent two preoperative (test–retest) PET scans and one postoperative PET scan acquired after 7 months of chronic MCS. Results: The two preoperative scans, performed at 2 weeks interval, did not show significant differences. Conversely, postoperative compared with preoperative PET scans revealed significant decreases of [11C]diprenorphine binding in the anterior middle cingulate cortex (aMCC), periaqueductal gray (PAG), prefrontal cortex, and cerebellum. Binding changes in aMCC and PAG were significantly correlated with pain relief. Conclusion: The decrease in binding of the exogenous ligand was most likely explained by receptor occupancy due to enhanced secretion of endogenous opioids. Motor cortex stimulation (MCS) may thus induce release of endogenous opioids in brain structures involved in the processing of acute and chronic pain. Correlation of this effect with pain relief in at least two of these structures supports the role of the endogenous opioid system in pain control induced by MCS.
Epitaxially Defined FinFET: Variability Resistant and High-Performance Technology

FinFET technology is prone to suffer from line edge roughness (LER)-based VT variation with scaling. It also lacks a simple implementation of multiple VT technology needed for power management. To address these challenges, in this paper we present an epitaxially defined FinFET (EDFinFET) as an alternate to FinFET architecture for nodes 15 nm and beyond. We show by statistical simulations that EDFinFET reduces overall VT variability with an 80% reduction in LER-based variability in comparison with FinFETs. We present dynamic threshold MOS (DTMOS) configuration of EDFinFET using the available body terminal to individual transistors. The DTMOS configuration reduces LER-based variability by 90% and overall variability by 59%. It also has excellent subthreshold slope (SS) and gives 43% higher ION compared with FinFETs. Meanwhile, EDFinFET shows poorer SS and lower ION than FinFET due to single gate control. However, it is capable of multiple VT, which leads to circuit level power optimization.
On Stability in the Presence of Analog Erasure Channel Between the Controller and the Actuator

Consider a discrete-time networked control system, in which the controller has direct access to noisy measurements of the output of the plant. However, information flows from the controller to the actuator via a channel that features Bernoulli erasure events. If an erasure occurs, the channel outputs an erasure symbol; otherwise, it transmits a real finite-dimensional vector. We determine necessary and sufficient conditions for the stabilizability of an unstable linear time-invariant finite-dimensional plant. Given a minimal state-space representation for the plant, the necessary and sufficient conditions for stabilizability are expressed in terms of the probability of erasure at the channel and of the spectral radius of the one-step state transition matrix. There are two main results in the technical note. The first result shows that if the actuator has processing capabilities, then the necessary and sufficient conditions for stabilizability remain unchanged with or without acknowledgements from the actuator to the controller. The second result shows that the stabilizability conditions are identical for two types of actuators: (Type I) Processing at the actuator has access to the plant's model; (Type II) Processing at the actuator uses a universal algorithm that does not depend on the model of the plant. Thus, neither the knowledge of the model of the plant at the actuator, nor the presence of acknowledgements from the actuator to the controller, can be used to alter or relax the necessary and sufficient conditions for stabilizability.
Correlations between user voting data, budget, and box office for films in the internet movie database

The Internet Movie Database (IMDb) is one of the most‐visited websites in the world and the premier source for information on films. Similar to Wikipedia, much of IMDb's information is user contributed. IMDb also allows users to voice their opinion on the quality of films through voting. We investigate whether there is a connection between user voting data and economic film characteristics. We perform distribution and correlation analysis on a set of films chosen to mitigate effects of bias due to the language and country of origin of films. Production budget, box office gross, and total number of user votes for films are consistent with double‐log normal distributions for certain time periods. Both total gross and user votes are consistent with a double‐log normal distribution from the late 1980s onward while for budget it extends from 1935 to 1979. In addition, we find a strong correlation between number of user votes and the economic statistics, particularly budget. Remarkably, we find no evidence for a correlation between number of votes and average user rating. Our results suggest that total user votes is an indicator of a film's prominence or notability, which can be quantified by its promotional costs.
Finding a minimum circuit in a graph

Finding minimum circuits in graphs and digraphs is discussed. An almost minimum circuit is a circuit which may have only one edge more than the minimum. An <italic>0(n<supscrpt>2</supscrpt>)</italic> algorithm is presented to find an almost minimum circuit. The straightforward algorithm for finding a minimum circuit has an <italic>0(ne)</italic> behavior. It is refined to yield an <italic>0(n<supscrpt>2</supscrpt>)</italic> average time algorithm. An alternative method is to reduce the problem of finding a minimum circuit to that of finding a triangle in an auxiliary graph. Three methods for finding a triangle in a graph are presented. The first has an <italic>0(e<supscrpt>3/2</supscrpt>)</italic> worst case bound (<italic>(n)</italic> for planar graphs); the second takes <italic>0(n<supscrpt>5/3</supscrpt>)</italic> time on the average; the third has an <italic>0(n<supscrpt>log7</supscrpt>)</italic> worst case behavior. For digraphs, recent results of Bloniarz, Fisher and Meyer are used to obtain an algorithm with <italic>0(n<supscrpt>2</supscrpt>logn)</italic> average behavior.
Origins of the Highly Ionized Gas along the Line of Sight toward HD 116852

We present Hubble Space Telescope Imaging Spectrograph (HST/STIS) and Far Ultraviolet Spectroscopic Explorer (FUSE) observations of high ion interstellar ultraviolet absorption along the sight line to HD 116852. At a distance of 4.8 kpc, HD 116852 is an O9 III star lying in the low Galactic halo, -1.3 kpc from the plane of the Galaxy in the direction l = 304. °9, b = -16. °1. The sight line passes underneath the Sagittarius-Carina and the Norma-Centaurus spiral arms. The STIS E140H grating observations provide high-resolution (FWHM ≈ 2.7 km s-1) spectra of the resonance doublets of Si IV, C IV, and N V. These data are complemented by medium-resolution (FWHM ≈ 20 km s-1) FUSE spectra of O VI. The integrated logarithmic column densities are log N(Si IV) = 13.60 ± 0.02, log N(C IV) = 14.08 ± 0.03, log N(N V) = 13.34, and log N(O VI) = 14.28 ± 0.01. We find evidence for three distinct types of highly ionized gas present in the data. First, two narrow absorption components are resolved in the Si IV and C IV profiles, at approximate LSR velocities of -36 and -10 km s-1 . These narrow components appear to be produced in gas associated with the Norma and Sagittarius spiral arms, at approximate z-distances of -1.0 and -0.5 kpc, respectively. The temperature of the gas in these narrow components, as implied by their b-values, suggests that the gas is photoionized. The ratio of C IV to Si IV in these narrow components is low compared to the Galactic average. Second, we detect an intermediate-width component in C IV and Si IV, at 17 km s-1, which we propose could arise at the conductive interface at the boundary between a low column density neutral or weakly ionized cloud and the surrounding hot medium. Finally, a broad collisionally ionized component of gas responsible for producing the smooth N V and O VI profiles is observed; such absorption is also present to a lesser degree in the profiles of Si IV and C IV. The broad O VI absorption is observed at a velocity displaced from the broad C IV component by almost 20 km s-1, an amount large enough to suggest that the two ions may not coexist in the same physical location. If these two ions do exist together, then the ratio N(C IV)/N(O VI) is too low to be consistent with turbulent mixing layer models, but could be explained by radiative cooling or conductive heating models. Combining our results with high resolution observations of four other sight lines from the literature, we find an average C IV component frequency of 1.0 ± 0.25 kpc-1.
Good IPOs draw in bad: Inelastic banking capacity in the primary issue market †

In this paper, we model the eect of labor market constraints on the Initial Public Oering (IPO) activity of investment banks. We posit that identifying project quality requires specialized screening labor that takes time to train. Positive shocks to economy’s production frontier stimulate new equity issues. At this higher level of demand, screening labor costs must rise to clear the labor market. This results in underwriters optimally reducing screening quality, in the process encouraging firms with sub-marginal projects to also apply, further straining the screening labor market. In equilibrium, underpricing can be quite significant both because of lower quality screening and because of its role in lowering the quality of the applicant pool. Our model’s predictions are consistent with empirical results such as positive correlation between issue volume and underpricing, reduced information search per project during hot markets, and the persistence of high issue volume in the face of increased underpricing.
The relationship between hypotension, cerebral flow, and the surgical field during endoscopic sinus surgery

Hypotensive anesthesia is often used in endoscopic sinus surgery (ESS) to improve surgical visibility; however, its safety and efficacy in this role are yet to be justified. This study aimed to evaluate the effect of hypotensive anesthesia on both real‐time middle cerebral artery blood flow velocity (Vmca) and the severity of surgical bleeding in patients undergoing ESS.
Vibrotactile Targeting in Multimodal Systems: Accuracy and Interaction

Tactile displays to enhance virtual and real environments are becoming increasingly common. Extending previous studies, we explored spatial localization of individual sites on a dense tactile array worn on the observer’s trunk, and their interaction with simultaneously-presented visual stimuli in an isomorphic display. Stimuli were composed of individual vibratory sites on the tactile array or projected flashes of light. In all cases, the task for the observer was to identify the location of the target stimulus, whose modality was defined for that session. In the multimodal experiment, observers were also required to identify the quality of a stimulus presented in the other modality (the "distractor"). Overall, performance was affected by the location of the target within the array. Having to identify the quality of a simultaneous stimulus in the other modality reduced both target accuracy and response time, but these effects did not seem to be a function of the relative location of the distractor.
Mental Health Learning Needs Assessment: Competency-Based Instrument for Best Practice

A learning needs assessment focused on psychiatric/mental health nursing competency development is a central component of nursing education in specialty mental health nursing practice. The provision of education for mental health nursing relies on the underlying assumption that the learning needs of experienced mental health nurses have been assessed and educational programs implemented to address educational needs for competency in professional practice. Few professional learning needs assessments have been developed to identify learning needs in mental health nursing practice. The majority of available professional learning needs assessments focus on medical nursing practice applications rather than the psychosocial aspects of a mental health assessment. The mental health field addresses very different assessment criteria such as knowledge of suicide assessment and therapeutic interventions. The purpose of this article is to present and describe the process of developing a learning needs assessment focused on competency development for the specialty practice of mental health nursing that addresses and resolves complex learning needs.
Privacy-enhanced Biometric Hamming Distance Classification

is a very effective way of verifying a person's identity, but it also raises privacy concerns. Because biometrics can never be changed, they should be kept private. Therefore it is important that biometric data is always encrypted when stored on a database. There exist many ways to encrypt biometric data, but often the data has to be decrypted before it can be compared. If somehow the data can be compared while encrypted, it is not necessary to decrypt the data in the process. In this research, a very simple and lightweight approach is introduced to compare biometric data while it stays encrypted. It uses a 'somewhat homomorphic encryption' scheme, implemented with the open-source library HElib to compute the Hamming distance in the encrypted domain. This implementation is then evaluated and analyzed. We focus on the iris biometrics for our evaluation. It is found that the implementation works, but that the encryption, computation and decryption of an iris scan takes almost 10 minutes, which is a very poor performance. Recommendations for the future are done to make it perform better. This approach can open up the way to a more private and secure way of doing an iris scan comparison. However, we also learned about the limitations of our system in terms of privacy and security.
Big biology meets microclimatology: defining thermal niches of ectotherms at landscape scales for conservation planning.

Temperature profoundly affects ecology, a fact ever more evident as the ability to measure thermal environments increases and global changes alter these environments. The spatial structure of thermalscapes is especially relevant to the distribution and abundance of ectothermic organisms, but the ability to describe biothermal relationships at extents and grains relevant to conservation planning has been limited by small or sparse data sets. Here, we combine a large occurrence database of >23 000 aquatic species surveys with stream microclimate scenarios supported by an equally large temperature database for a 149 000-km mountain stream network to describe thermal relationships for 14 fish and amphibian species. Species occurrence probabilities peaked across a wide range of temperatures (7.0-18.8°C) but distinct warm- or cold-edge distribution boundaries were apparent for all species and represented environments where populations may be most sensitive to thermal changes. Warm-edge boundary temperatures for a native species of conservation concern were used with geospatial data sets and a habitat occupancy model to highlight subsets of the network where conservation measures could benefit local populations by maintaining cool temperatures. Linking that strategic approach to local estimates of habitat impairment remains a key challenge but is also an opportunity to build relationships and develop synergies between the research, management, and regulatory communities. As with any data mining or species distribution modeling exercise, care is required in analysis and interpretation of results, but the use of large biological data sets with accurate microclimate scenarios can provide valuable information about the thermal ecology of many ectotherms and a spatially explicit way of guiding conservation investments.
The association between cancer incidence and family income: analysis of Korean National Health Insurance cancer registration data.

BACKGROUND Economic status is known to be directly or indirectly related to cancer incidence since it affects accessibility to health-related social resources, preventive medical checkups, and lifestyle. This study investigates the relationship between cancer incidence and family income in Korea. METHODS Using the Korean National Health Insurance cancer registration data in 2009, the relationship between their family income class and cancer risk was analyzed. The age-standardized incidence rates of the major cancers were calculated for men and women separately. After adjusting for age, residential area, and number of family members, cancer risks for major cancers according to family income class were estimated using a logistic regression model. RESULTS In men, the risk of stomach cancer for Income Class 5 (lowest) was 1.12 times (95% CI 1.02-1.23) higher than that of Income Class 1 (highest), for lung cancer 1.61 times (95% CI 1.43- 1.81) higher, for liver cancer 1.22 times (95% CI 1.08-1.37) higher, and for rectal cancer 1.37 times higher (95% CI 1.18-1.59). In women, the risk of stomach cancer for Income Class 5 was 1.22 times higher (95% CI 1.08-1.37) than that for Income Class 1, while for cervical cancer it was 2.47 times higher (95% CI 2.08- 2.94). In contrast, in men, Income Class 1 showed a higher risk of thyroid cancer and prostate cancer than that of Income Class 5, while, in women the same was the case for thyroid cancer. CONCLUSIONS The results show the relationship between family income and cancer risk differs according to type of cancer.
Using Discourse Signals for Robust Instructor Intervention Prediction

We tackle the prediction of instructor intervention in student posts from discussion forums in Massive Open Online Courses (MOOCs). Our key finding is that using automatically obtained discourse relations improves the prediction of when instructors intervene in student discussions, when compared with a state-of-the-art, feature-rich baseline. Our supervised classifier makes use of an automatic discourse parser which outputs Penn Discourse Treebank (PDTB) tags that represent in-post discourse features. We show PDTB relation-based features increase the robustness of the classifier and complement baseline features in recalling more diverse instructor intervention patterns. In comprehensive experiments over 14 MOOC offerings from several disciplines, the PDTB discourse features improve performance on average. The resultant models are less dependent on domain-specific vocabulary, allowing them to better generalize to new courses.