Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Surgery for Asymptomatic Primary Tumors in Unresectable Stage IV Colorectal Cancer

There are still debates regarding the appropriate primary treatment policy for asymptomatic primary colorectal lesions in cases of unresectable metastatic colorectal cancer. Even though there are patients with asymptomatic primary tumors when starting chemotherapy, those patients may still undergo surgery due to complications related to primary tumors in the middle of chemotherapy; therefore, controversy exists regarding surgical resection of primary colorectal lesions in cases where symptoms are absent when making a diagnosis. Thus, based on the published literature, we discuss opinions that prefer first-line surgery for primary tumors as well as opinions favoring first-line chemotherapy for treating unresectable synchronous metastatic colorectal cancer. Although the upfront chemotherapy including targeted agents is suggested as an effective treatment in recent years, the first line surgery has been a preferred treatment for decades. The first line surgery is beneficial to prolong the survival duration given the retrospective analysis of randomized trial data. So far, no prospective comparison study has only focused on the first-line treatment modality; thus, future clinical studies focusing on the survival duration and the quality of life should be performed as soon as possible. Furthermore, at this point, multidisciplinary team approaches would be helpful in finding the appropriate therapy. Regardless of symptoms, the performance status and the tumor burden should be taken into consideration as well. In case of surgical resection, minimally invasive surgery, such as laparoscopic surgery, is recommended.
Automated Analysis of Privacy Requirements for Mobile Apps

Mobile apps have to satisfy various privacy requirements. App publishers are often obligated to provide a privacy policy and notify users of their apps’ privacy practices. But how can we tell whether an app behaves as its policy promises? In this study we introduce a scalable system to help analyze and predict Android apps’ compliance with privacy requirements. Our system is not only intended for regulators and privacy activists, but also meant to assist app publishers and app store owners in their internal assessments of privacy requirement compliance. Our analysis of 17,991 free apps shows the viability of combining machine learning-based privacy policy analysis with static code analysis of apps. Results suggest that 71% of apps that lack a privacy policy should have one. Also, for 9,050 apps that have a policy, we ﬁnd many instances of potential inconsistencies between what the app policy seems to state and what the code of the app appears to do. Our results suggest that as many as 41% of these apps could be collecting location information and 17% could be sharing such with third parties without disclosing so in their policies. Overall, it appears that each app exhibits a mean of 1.83 inconsistencies.
Effect of Virtual Reality on Cognition in Stroke Patients

Objective To investigate the effect of virtual reality on the recovery of cognitive impairment in stroke patients. Method Twenty-eight patients (11 males and 17 females, mean age 64.2) with cognitive impairment following stroke were recruited for this study. All patients were randomly assigned to one of two groups, the virtual reality (VR) group (n=15) or the control group (n=13). The VR group received both virtual reality training and computer-based cognitive rehabilitation, whereas the control group received only computer-based cognitive rehabilitation. To measure, activity of daily living cognitive and motor functions, the following assessment tools were used: computerized neuropsychological test and the Tower of London (TOL) test for cognitive function assessment, Korean-Modified Barthel index (K-MBI) for functional status evaluation, and the motricity index (MI) for motor function assessment. All recruited patients underwent these evaluations before rehabilitation and four weeks after rehabilitation. Results The VR group showed significant improvement in the K-MMSE, visual and auditory continuous performance tests (CPT), forward digit span test (DST), forward and backward visual span tests (VST), visual and verbal learning tests, TOL, K-MBI, and MI scores, while the control group showed significant improvement in the K-MMSE, forward DST, visual and verbal learning tests, trail-making test-type A, TOL, K-MBI, and MI scores after rehabilitation. The changes in the visual CPT and backward VST in the VR group after rehabilitation were significantly higher than those in the control group. Conclusion Our findings suggest that virtual reality training combined with computer-based cognitive rehabilitation may be of additional benefit for treating cognitive impairment in stroke patients.
Characterization of Virus-Encoded RNA Interference Suppressors in Caenorhabditis elegans

ABSTRACT In fungi, plants, and invertebrates, antiviral RNA interference (RNAi) directed by virus-derived small interfering RNAs (siRNAs) represents a major antiviral defense that the invading viruses have to overcome in order to establish infection. As a counterdefense mechanism, viruses of these hosts produce diverse classes of proteins capable of suppressing the biogenesis and/or function of viral siRNAs. This RNA-directed viral immunity (RDVI) in the nematode Caenorhabditis elegans is known to exhibit some unique features. Currently, little is known about viral suppression of RNAi in C. elegans. Here, we show that ectopic expression of the B2 protein encoded by Flock House virus (FHV) suppresses RNAi induced by either long double-stranded RNA (dsRNA) or an FHV-based replicon and facilitates the natural infection of C. elegans by Orsay virus but is not active against RNA silencing mediated by microRNAs. We report the development of an assay for the identification of viral suppressor of RNAi (VSR) in C. elegans based on the suppression of a viral replicon-triggered RDVI by ectopic expression of candidate proteins. No VSR activity was detected for either of the two Orsay viral proteins proposed previously as VSRs. We detected, among the known heterologous VSRs, VSR activity for B2 of Nodamura virus but not for 2b of tomato aspermy virus, p29 of fungus-infecting hypovirus, or p19 of tomato bushy stunt virus. We further show that, unlike that in plants and insects, FHV B2 suppresses worm RDVI mainly by interfering with the function of virus-derived primary siRNAs.
Journal of Visual Languages & Computing Automatic Visualisation of Metro Maps

We investigate the new problem of automatic metro map layout. In general, a metro map consists of a set of lines which have intersections or overlaps. We define a set of aesthetic criteria for good metro map layouts and present a method to produce such layouts automatically. Our method uses a variation of the spring algorithm with a suitable preprocessing step. The experimental results with real world data sets show that our method produces good metro map layouts quickly.
The Comparison of the Amount of Methionine Supply by Different Rumen-Protected Methionine Sources

Bioavailability of three rumen protected Methionine (Met) sources with different protection methods (Mepron M85, Evonik Industries, Germany; Methioplus, Soda Nutrition, Italy and Methilock, Tehrandaneh Co. Iran) were evaluated in 2 experiments with 6 canulated non-lactating Holstein cows. In experiment 1, the ruminal in situ and mobile bag techniques were used for assessing ruminal degradability and intestinal digestibility of Met from the protected Met sources. The rate of disappearance of Met from Mepron M85 was lower than Methioplus (2.94 vs. 5.73 % h). Mepron M85 had more resistance to ruminal degradation than Methioplus (82.78 vs. 68.51%), but the higher intestinal digestibility of Methioplus resulted in similar amounts of available Met for two products. Because of high washing out loss from in situ bags, ruminal degradation was not estimated for Methilock. In the second experiment, Met availability was assayed by the blood Met response after 5 days feeding each product in comparison to pretreatment levels utilizing a 3×3 Latin square design. Three Met sources increased blood Met concentration significantly after 5 days feeding (37.5, 52.23 and 44.39% for Methilock, Mepron and Methioplus respectively). Results of the present study showed that the three RPM sources increased blood Met concentration. This study also suggests that the in situ method may not adequately characterize the availability of rumen protected amino acids, especially those of small particle size.
A Robust Algorithm for Eye-Diagram Analysis

We present a new method for analyzing eye diagrams that always provides a unique solution by making use of a robust, least-median-of-squares (LMS) location estimator. In contrast to commonly used histogram techniques, the LMS procedure is insensitive to outliers and data distributions. Our motivation for developing this algorithm is to create an independent, benchmark method that is both amenable to a thorough uncertainty analysis and can function as a comparison tool since no standardized industry algorithms currently exist. Utilizing this technique, we calculate the fundamental parameters of an eye diagram, namely the one and zero levels, and the time and amplitude crossings. With these parameters determined, we can derive various performance metrics, such as extinction ratio and root-mean-square jitter, and perform eye-mask alignment. In addition to describing our algorithm in detail, we compare results computed with this method to those of a commercial oscilloscope, and obtain excellent agreement. Finally, we suggest new definitions of eye height and eye width that are more robust than those that are commonly used.
Assessment of Snow Atmosphere Forcing During Central Idaho Atmospheric Rivers

Atmospheric Rivers (AR) are globally occuring weather features and the primary mechanism through which water vapor moves from the tropics and subtropics towards the mid-latitudes, doing so at rates comparable to the world’s largest terrestrial rivers. AR that encounter mountains often cause extreme precipitation in the form of rain and snow, high winds, and flooding in many watersheds. They account for as much as 20-30% of cool season precipitation in the central Idaho Mountains. In the Northern Hemisphere, seasonal snow cover during Winter and Spring months is the most variable land surface component in space and time, and acts on the fluxes of energy and mass into the atmospheric system. To date, there has been little effort to understand how the land surface snow cover states prior to and during the arrival of ARs, acting on the surface mass and energy balance, impact the onset, extent, and evolution of precipitation accumulation during AR events. Using a high resolution coupled land-atmosphere model, I examine the sensitivity of the precipitation regime and atmospheric energy balance to an ensemble of realistic snowcover states during a March 1998 AR case study in central Idaho. The results indicate that snow cover forcing 1) causes reductions of shortwave radiation and sensible heating that are balanced by atmpospheric energy transport, 2) increases atmospheric static stability, and 3) modifies the distributions of total accumulated precipitation by as much as 10mm.
Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

AbstractWater management activities modify water fluxes at the land surface and affect water resources in space and time. Conventional understanding on the role of water management suggests that regulated river flow would be less sensitive to future climate conditions than natural flow in terms of the absolute changes in mean monthly flows. In this study the authors evaluate such an assumption by redefining sensitivity as the difference in the emergence of changes in cumulative distribution functions (CDFs) of future regulated and natural flows in response to climate change with respect to their respective historical regulated and natural flow conditions. The emergence of changes (shift in CDFs) in natural and regulated river flow regimes across the western United States from simulations driven by multiple climate models and scenarios were compared. Forty percent of Hydrologic Unit Codes 4 (HUC4s) over the western United States might perceive such a shift in seasonal regulated flow earlier than they would.
DNA barcoding of eight North American coregonine species

Coregonine fishes have a circumpolar distribution in the Arctic and sub‐Arctic Northern Hemisphere. This subfamily of Salmonidae consists of three genera: Prosopium, Stenodus and Coregonus, including over 30 species. Many species overlap spatially and are difficult to distinguish based on morphological characteristics, especially as larvae or juveniles. Here we present a method for rapid and cost‐effective species identification for representatives of the three genera based on sequence variation at the mitochondrial cytochrome c oxidase subunit I gene (COI). We examined eight species common to North America with distributional overlap in Alaska. Mean pairwise sequence divergence for all eight species was 7.04% and ranged from 0.46% to 14.23%. This sequence variation was used to develop a genetic assay based on restriction fragment length polymorphism. In a blind test, this assay provided correct species assignment for 48 of 49 individuals representing all eight species. The single incorrect assignment may reflect hybridization between two closely related species. This DNA barcode‐based assay promises to aid fishery managers and researchers by providing a cost‐effective alternative to large‐scale sequence analysis for identification of North American coregonine fishes.
GIS and Matlab modelling of criteria pollutants, a study of lower Onitsha basin during rains

The study of air pollutants SO 2 , NO 2 and PM 10 in lower Onitsha basin, a densely populated city was performed using GPS and Matlab modeling. The pollutants were studied in nine specific locations for 3 months of rains over 3 consecutive years with each georeferenced. The Matlab pollution model was generated by integrating the spatial database and measured pollution attributes database using a polynomial expression. SO 2 highest concentration (141 µg/m 3 ) peaked in Upper Iweka at sampling point 1 before dispersing to lower concentrated regions in Awada and Resthouse. NO 2 peaked at 207 µg/m 3 in Upper Iweka at sampling point 3 and driven by wind towards Borromeo area to very low concentration of 38 ug/m3. The PM 10 peaked in Upper Iweka (180 µg/m 3 ) and driven by rains towards Borromeo before increasing again in concentration levels at Awada. The AQI showed that SO 2 pollutants had acceptable air quality at all sampling points while NO 2 and PM 10 air quality affected sensitive groups. SO 2 concentration levels exceeded
Investigation on Random Distribution of Fibres in Cement Composites

The problem of homogenous distribution of fibres in a cast element always occurs with application of concrete mixes modified by fibres. Past research has proven that the size of an element influences the direction of fibres in the concrete mix. If the depth of a given piece is not much greater than the fibres' length, in the majority of cases they are positioned horizontally. The lack of regularity and directional reorientation of fibres during technological processes causes some difficulties, linked with expected random distribution in the concrete mass. The analysis of the impacted this randomness on workability and strength parameters of concrete is investigated for normal and self-compacting concretes. In this paper an analysis is presented in which cross-sections of concrete beams with steel fibres are closely examined.
Regional lobar atrophy predicts memory impairment in multiple sclerosis.

BACKGROUND AND PURPOSE In recent studies, measures of whole brain atrophy were strongly correlated with neuropsychological testing, explaining more variance than measures of lesion burden in patients with multiple sclerosis. The relationship between regional lobar atrophy and cognitive impairment is yet to be examined. We endeavored to assess the clinical significance of regional lobar atrophy in multiple sclerosis. METHODS In a cross-sectional study, we evaluated 31 patients with multiple sclerosis with brain MR imaging and neuropsychological testing. Impairment was determined by comparison with demographically matched healthy controls. MR imaging generated measures of lesion burden (fluid-attenuated inversion recovery hyperintense volume), general atrophy (brain parenchymal fraction), central atrophy (lateral ventricle volume), and lobar atrophy (regional brain parenchymal fraction of frontal, temporal, parietal, and occipital lobes in each hemisphere). Neuropsychological testing emphasized measures of processing speed and memory, because these are commonly affected in multiple sclerosis. RESULTS Patients with multiple sclerosis showed significant atrophy and impairment on all neuropsychological tests. Regional atrophy accounted for the most variance in all regression models predicting memory performance. Left temporal atrophy was the primary predictor of auditory/verbal memory (partial r's = 0.55-0.61), and both left and right temporal atrophy predicted visual/spatial memory performance (partial r's = 0.51-0.67). Models predicting learning consistency retained frontal lobe atrophy measures (partial r's = 0.44-0.68). Central and general atrophy measures were the primary predictors in modeling processing speed (partial r's = 0.42-0.64). CONCLUSION Regional atrophy accounts for more variance than lesion burden, whole brain atrophy, or lateral ventricle volume in predicting multiple sclerosis-associated memory dysfunction.
RETURNS TO SCHOOLING IN ITALY : OLS , IV and Gender Differences

The conventional wisdom in the literature is that OLS estimates of returns to schooling are biased and inconsistent due to endogeneity in the schooling variable (Griliches 1977). A recent solution to this endogeneity problem has been found in identifying exogenous sources of variation in schooling to build a new set of instrumental variables for years of education attained (Angrist and Krueger 1991; Card 1998). The aim of this paper is to apply new instrumental variables estimation to Italian data using the Bank of Italy data set Indagine sui bilanci della famiglie nell’anno 1991. IV estimation results suggest a downward bias in OLS estimates. Moreover the extent of the bias is asymmetric in regard to gender: OLS estimates indicate the usual hierarchy i.e. female returns higher than male returns (Lucifora 1994; Blau-Kahn 1992) whereas IV estimates suggest an opposite hierarchy in the point estimates.
Stochastic viscosity solution for stochastic PDIEs with nonlinear Neumann boundary condition

This paper is an attempt to extend the notion of viscosity solution to nonlinear stochastic partial differential integral equations with nonlinear Neumann boundary condition. Using the recently developed theory on generalized backward doubly stochastic differential equations driven by a L\'evy process, we prove the existence of the stochastic viscosity solution, and further extend the nonlinear Feynman-Kac formula.
On efficient power allocation modeling in virtualized uplink 3GPP-LTE systems

In order to accommodate mobile users' consumed power with the rapid increase of multimedia-rich mobile data, additional network capacities with optimized power allocation scheduling algorithms should be deployed. Motivated by the fundamental requirement of extending the mobile devices' battery utilization time per charge, this work formulates the optimized power allocation problem in a virtualized scheme considered in the third generation partnership project-long term evolution (3GPP-LTE) uplink (UL) systems. The proposed framework efficiently shares the evolved nodeB's dedicated physical radio resources blocks of service providers having different requirements under dynamic channel conditions. The objective is to minimize the total transmission energy for all users subject to exclusive and contiguous allocation, maximum transmission power, and rate constraints. Two algorithms are developed. A binary integer programming (BIP)-based algorithm is used to solve a simplified version of the problem. A heuristic algorithm is also presented that approaches the BIP-based algorithm's performance. Simulation results show that the proposed framework offers a remarkable transmission power reduction in the virtualized scenario as compared to the non-sharing one.
Unsupervised feature selection under perturbations: meeting the challenges of biological data

MOTIVATION Feature selection methods aim to reduce the complexity of data and to uncover the most relevant biological variables. In reality, information in biological datasets is often incomplete as a result of untrustworthy samples and missing values. The reliability of selection methods may therefore be questioned. METHOD Information loss is incorporated into a perturbation scheme, testing which features are stable under it. This method is applied to data analysis by unsupervised feature filtering (UFF). The latter has been shown to be a very successful method in analysis of gene-expression data. RESULTS We find that the UFF quality degrades smoothly with information loss. It remains successful even under substantial damage. Our method allows for selection of a best imputation method on a dataset treated by UFF. More importantly, scoring features according to their stability under information loss is shown to be correlated with biological importance in cancer studies. This scoring may lead to novel biological insights.
Computing Bayes-Nash Equilibria through Support Enumeration Methods in Bayesian Two-Player Strategic-Form Games

The computation of equilibria in games is a challenging task. The literature studies the problem of finding Nash equilibria with complete-information games in depth, but not enough attention is paid to searching for equilibria in Bayesian games. Customarily, these games are reduced to complete information games and standard algorithms for computing Nash equilibria are employed. However, no work studied how these algorithms perform with Bayesian games. In this paper we focus on two-player strategic-form games. We show that the most efficient algorithm for computing Nash equilibria with GAMUT data (i.e., Porter-Nudelman-Shoham) is inefficient with Bayesian games, we provide an extension, and we experimentally evaluate its performance.
Word Sense Disambiguation Using Sense Examples Automatically Acquired from a Second Language

We present a novel almost-unsupervised approach to the task of Word Sense Disambiguation (WSD). We build sense examples automatically, using large quantities of Chinese text, and English-Chinese and Chinese-English bilingual dictionaries, taking advantage of the observation that mappings between words and meanings are often different in typologically distant languages. We train a classifier on the sense examples and test it on a gold standard English WSD dataset. The evaluation gives results that exceed previous state-of-the-art results for comparable systems. We also demonstrate that a little manual effort can improve the quality of sense examples, as measured by WSD accuracy. The performance of the classifier on WSD also improves as the number of training sense examples increases.