Miracle-dz/UniFAR-FTUs huggingface dataset:
Stable Feature Selection from Brain sMRI

Neuroimage analysis usually involves learning thousands or even millions of variables using only a limited number of samples. In this regard, sparse models, e.g. the lasso, are applied to select the optimal features and achieve high diagnosis accuracy. The lasso, however, usually results in independent unstable features. Stability, a manifest of reproducibility of statistical results subject to reasonable perturbations to data and the model (Yu 2013), is an important focus in statistics, especially in the analysis of high dimensional data. In this paper, we explore a nonnegative generalized fused lasso model for stable feature selection in the diagnosis of Alzheimer's disease. In addition to sparsity, our model incorporates two important pathological priors: the spatial cohesion of lesion voxels and the positive correlation between the features and the disease labels. To optimize the model, we propose an efficient algorithm by proving a novel link between total variation and fast network flow algorithms via conic duality. Experiments show that the proposed nonnegative model performs much better in exploring the intrinsic structure of data via selecting stable features compared with other state-of-the-arts.
Segmentation of point cloud from a 3D LIDAR using range difference between neighbouring beams

Apart from detecting traversable region, an autonomous mobile robot needs to robustly identify different objects in its surroundings. This information it can then use to localize itself, as well as to plan its path. Multi beam laser scanners like Velodyne are now-a-days commonly used to obtain range data of the environment in the form of point clouds. The geometry of laser scanning, particularly the range difference between neighbouring beams has been used by various researchers for the detection of obstacles. In this paper, we exploit the same basic concept in a different form and introduce the notion of an unevenness field that enables easy identification of obstacles in contrast to the ground. Then, we go ahead and use the same unevenness field with modified limits for segmenting point cloud into different objects. Finally, we demonstrate results of segmentation in various environments in our research centre. The conceptual and computational simplicity of this approach, and its effectiveness makes it an attractive method for range image segmentation.
Learning Non-Stationary Dynamic Bayesian Networks

Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional DBN structure learning is that the data are generated by a stationary process, an assumption that is not true in many important settings. In this paper, we introduce a new class of graphical model called a non-stationary dynamic Bayesian network, in which the conditional dependence structure of the underlying data-generation process is permitted to change over time. Non-stationary dynamic Bayesian networks represent a new framework for studying problems in which the structure of a network is evolving over time. Some examples of evolving networks are transcriptional regulatory networks during an organism's development, neural pathways during learning, and traffic patterns during the day. We define the non-stationary DBN model, present an MCMC sampling algorithm for learning the structure of the model from time-series data under different assumptions, and demonstrate the effectiveness of the algorithm on both simulated and biological data.
An Exploratory Study of Trust Dynamics in Work-Oriented Virtual Teams

This study explores trust development and maintenance in temporary, work-oriented virtual teams, and examines the effect of trust on communication and cohesiveness. Results suggest that for work-oriented virtual teams formed on a temporary basis, members swiftly develop calculus-based trust in order to assess the outcomes and costs of maintaining team relationships. Members also rely on prior knowledge to determine other members' competence so that they can make predictions about one another's behaviors. Thus, both calculus-based and knowledge-based trust play accentuating roles in the initial development of work-oriented virtual teams. Identification-based trust also develops swiftly initially, but is relatively insignificant compared to the other two types of trust. Finally, initial trust may correlate to both later communication and later cohesiveness.
Network models that reflect multiplex dynamics

Many of the systems that are traditionally analyzed as complex networks have natural interpretations as multiplex structures. While these formulations retain more information than standard network models, there is not yet a fully developed theory for computing network metrics and statistics on these objects. As many of the structural representations associated to these models can distort the underlying characteristics of dynamical process, we introduce an algebraic method for modeling arbitrary dynamics on multiplex networks. Since several network metrics are based on generalized notions of dynamical transfer, we can use this framework to extend many of the standard network metrics to multiplex structures in a consistent fashion.
[Influence of angiotensin II type 1 receptor gene polymorphism on patients with essential hypertension complicated by brain infarction].

OBJECTIVE To identify the A1166/C polymorphism of angiotensin II type 1 receptor (AT1R) gene in patients with essential hypertension complicated with brain infarction (BI). METHODS AT1R genotyping with polymerase chain reaction-restrictive fragment length polymorphism was performed in 70 normotensive subjects, 72 hypertensive patients without cardio-cerebrovascular diseases(EH-NCCVD) and 70 hypertensive patients with BI. The relationship between the polymorphism of AT1R gene and plasma lipid levels was also studied. RESULTS The frequencies of C allele in the two groups of hypertension were higher than that in the health controls, respectively (P<0.05). But there was no significant difference in the frequency of C allele between the two groups of hypertension. A positive correlation was observed between the lipoprotein(a) and AT1R gene A1166/C polymorphism in hypertensive patients. CONCLUSION AT1R gene contributes to the development of essential hypertensive, but not to the incidence of BI in the hypertensive.
Quantitative Nature of Arabidopsis Responses during Compatible and Incompatible Interactions with the Bacterial Pathogen Pseudomonas syringae Online version contains Web-only data. Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.007591.

We performed large-scale mRNA expression profiling using an Affymetrix GeneChip to study Arabidopsis responses to the bacterial pathogen Pseudomonas syringae. The interactions were compatible (virulent bacteria) or incompatible (avirulent bacteria), including a nonhost interaction and interactions mediated by two different avirulence gene–resistance (R) gene combinations. Approximately 2000 of the ∼8000 genes monitored showed reproducible significant expression level changes in at least one of the interactions. Analysis of biological variation suggested that the system behavior of the plant response in an incompatible interaction was robust but that of a compatible interaction was not. A large part of the difference between incompatible and compatible interactions can be explained quantitatively. Despite high similarity between responses mediated by the R genes RPS2 and RPM1 in wild-type plants, RPS2-mediated responses were strongly suppressed by the ndr1 mutation and the NahG transgene, whereas RPM1-mediated responses were not. This finding is consistent with the resistance phenotypes of these plants. We propose a simple quantitative model with a saturating response curve that approximates the overall behavior of this plant-pathogen system.
Functional Expression of a Bacterial Xylose Isomerase in Saccharomyces cerevisiae

ABSTRACT In industrial fermentation processes, the yeast Saccharomyces cerevisiae is commonly used for ethanol production. However, it lacks the ability to ferment pentose sugars like d-xylose and l-arabinose. Heterologous expression of a xylose isomerase (XI) would enable yeast cells to metabolize xylose. However, many attempts to express a prokaryotic XI with high activity in S. cerevisiae have failed so far. We have screened nucleic acid databases for sequences encoding putative XIs and finally were able to clone and successfully express a highly active new kind of XI from the anaerobic bacterium Clostridium phytofermentans in S. cerevisiae. Heterologous expression of this enzyme confers on the yeast cells the ability to metabolize d-xylose and to use it as the sole carbon and energy source. The new enzyme has low sequence similarities to the XIs from Piromyces sp. strain E2 and Thermus thermophilus, which were the only two XIs previously functionally expressed in S. cerevisiae. The activity and kinetic parameters of the new enzyme are comparable to those of the Piromyces XI. Importantly, the new enzyme is far less inhibited by xylitol, which accrues as a side product during xylose fermentation. Furthermore, expression of the gene could be improved by adapting its codon usage to that of the highly expressed glycolytic genes of S. cerevisiae. Expression of the bacterial XI in an industrially employed yeast strain enabled it to grow on xylose and to ferment xylose to ethanol. Thus, our findings provide an excellent starting point for further improvement of xylose fermentation in industrial yeast strains.
Predictors of rehospitalization and death after a severe exacerbation of COPD.

BACKGROUND Patients who survive a severe exacerbation of COPD are at high risk of rehospitalization for COPD and death. The objective of this study was to determine predictors of these events in a large cohort of Veterans Affairs (VA) patients. METHODS We identified 51,353 patients who were discharged after an exacerbation of COPD in the VA health-care system from 1999 to 2003, and determined the rates of rehospitalization for COPD and death from all causes. Potential risk factors were assessed with univariate and multivariate survival analysis. RESULTS On average, the cohort was elderly (mean age, 69 years), predominately white (78% white, 13% black, 3% other, and 6% unknown), and male (97%), consistent with the underlying VA population. The risk of death was 21% at 1 year, and 55% at 5 years. Independent risk factors for death were age, male gender, prior hospitalizations, and comorbidities including weight loss and pulmonary hypertension; nonwhite race and other comorbidities (asthma, hypertension, and obesity) were associated with decreased mortality. The risk of rehospitalization for COPD was 25% at 1 year, and 44% at 5 years, and was increased by age, male gender, prior hospitalizations, and comorbidities including asthma and pulmonary hypertension. Hispanic ethnicity and other comorbidities (diabetes and hypertension) were associated with a decreased risk of rehospitalization. CONCLUSIONS Age, male gender, prior hospitalizations, and certain comorbid conditions were risk factors for death and rehospitalization in patients discharged after a severe COPD exacerbation. Nonwhite race and other comorbidities were associated with decreased risk.
Using policies for information valuation to justify beliefs

This research presents a belief revision algorithm, based on intuitive policies for information valuation. Policies for valuation of information, based on characteristics of the information and the sources providing it, are delineated as guidelines for algorithm construction. In addition, each policy is traceably incorporated into the belief revision process to provide justification for calculated belief certainties. Finally, since modeling of information source trustworthiness can be complicated, significant effort is devoted to constructing these reputation models. Experimental results show that application of information valuation policies to belief revision yields significant improvement in belief accuracy and precision over no-policy or single-policy belief revision.
Prognostic Value of Clinical and Pathological Features in Chinese Patients with Chromophobe Renal Cell Carcinoma: A 10-Year Single-Center Study

Objective: To evaluate the prognostic significance of clinicopathological features in a large series of Chinese patients with chromophobe renal cell carcinoma (RCC). Materials and Methods: Patients with chromophobe RCC who were treated surgically for renal masses at Chinese PLA General Hospital from 2006 to 2015 were identified. Tissue slides were reviewed to verify diagnoses and collect clinicopathological variables. Cox proportional hazard regression models and the Kaplan-Meier method were performed to evaluate the significance of clinicopathological variables on survival outcomes. Results: A total of 209 patients with chromophobe RCC were enrolled in this study. There were only 13 cancer-specific events, which included 7 local recurrences and 6 metastases. The estimated 5-year and 10-year disease-free survival (DFS) rates were 92.4% and 83.1%, respectively. Univariate analysis indicated that tumor size, 2010 AJCC TNM stage, grade, sarcomatoid differentiation and urinary collecting system invasion were correlated with poor DFS. Multivariate analysis revealed that tumor size, 2010 AJCC TNM stage and grade were independent predictors of DFS. Conclusions: According to this long-term follow-up on a large number of Chinese patients, we found that chromophobe RCC was associated with a very low rate of cancer-specific events (6.2%) and has a better prognosis than clear cell RCC. Tumor size, 2010 AJCC TNM stage and grade were independent prognostic factors in Chinese patients with chromophobe RCC. The presence of these features in a nephrectomy specimen with chromophobe RCC warrants more active surveillance.
Cellular Protein TIA-1 Regulates the Expression of HBV Surface Antigen by Binding the HBV Posttranscriptional Regulatory Element

Objective: To identify T-cell intracellular antigen 1 (TIA-1) interacting with the posttranscriptional regulatory element (PRE) of hepatitis B virus (HBV), and reveal TIA-1 function on HBV gene expression. Methods: In order to demonstrate TIA-1 binding to PRE, electrophoretic mobility shift and RNA and protein pull-down assays were used. The pDM138-PRE reporter system, HepG2.2. 15 cell line and HBs-PRE transient expression cells were adopted to identify TIA-1 function in the HBV life cycle. Results: TIA-1 could directly bind to PRE RNA. The functional binding region of TIA-1 was identified. Functional analysis indicated that TIA-1 could dose-dependently inhibit PRE function in pDM138-PRE system. Down-expression of HBs antigen induced by TIA-1 was detected both in the HepG2.2. 15 cell line and in HBs-PRE transient expression cells. Conclusion: These data demonstrated that TIA-1 inhibits HBs expression by interacting with PRE.
Predicting Behaviors of Basketball Players from First Person Videos

This paper presents a method to predict the future movements (location and gaze direction) of basketball players as a whole from their first person videos. The predicted behaviors reflect an individual physical space that affords to take the next actions while conforming to social behaviors by engaging to joint attention. Our key innovation is to use the 3D reconstruction of multiple first person cameras to automatically annotate each others visual semantics of social configurations. We leverage two learning signals uniquely embedded in first person videos. Individually, a first person video records the visual semantics of a spatial and social layout around a person that allows associating with past similar situations. Collectively, first person videos follow joint attention that can link the individuals to a group. We learn the egocentric visual semantics of group movements using a Siamese neural network to retrieve future trajectories. We consolidate the retrieved trajectories from all players by maximizing a measure of social compatibility&#x2014;the gaze alignment towards joint attention predicted by their social formation, where the dynamics of joint attention is learned by a long-term recurrent convolutional network. This allows us to characterize which social configuration is more plausible and predict future group trajectories.
Bipotential glial precursor cells of the optic nerve express the NG2 proteoglycan

We have studied the expression of the NG2 chondroitin sulfate proteoglycan on bipotential glial precursor cells in cultures of postnatal rat optic nerve. Purified populations of these precursor cells were prepared by panning dissociated optic nerve cells on dishes coated with monoclonal A2B5 antibody. Using immunofluorescence double staining, we found that NG2 was present on almost 95% of the purified A2B5+ precursor cells. The NG2 core protein from optic nerve cells was identified by immune precipitation and PAGE and was found to be identical to the 300,000 Da NG2 core protein from a clonal rat cell line B49. Over a culture period of 5 d in medium containing 10% fetal calf serum, more than 80% of the NG2+ precursor cells acquired the glial fibrillary acidic protein (GFAP), an astrocyte-specific marker. Under these conditions, fewer than 10% of the NG2+ cells expressed galactocerebroside (GC), an oligodendrocyte-specific marker. These GFAP+GC- type II astrocytes continued to express the NG2 antigen for up to 10 d in culture. During a 5 d culture period in hormonally supplemented, serum-free medium, fewer than 15% of the NG2+ cells expressed GFAP, while up to 40% expressed GC. The NG2 antigen continued to be expressed for only a short period of time by these GFAP-GC+ oligodendrocytes, so that mature oligodendrocytes in the cultures became NG2-. These results support our previous suggestion that the NG2 antigen is found on a class of neural cells that can differentiate along more than one pathway.
Work, self, and military life: The experiences of U.S. Air Force wives

This study explores the experiences of U.S. Air Force wives who wish to pursue their own employment while frequently relocating with their military husbands. Previous research has shown that military wives face significant obstacles to maintaining employment, evidenced by lower earnings, and higher rates of unemployment and underemployment compared to the general U.S. female population. While other studies have documented these employment challenges, few researchers have examined the personal experiences of the women who live with them. Through the use of 21 narrative interviews, this research focuses on military wives’ thoughts and feelings about their work-related desires, and the impact to self. The findings from this study are grouped into thoughts and feelings across three domains: working, not working, and being a military spouse. Participants were unanimous in associating positive thoughts and feelings with working and negative thoughts and feelings with not working. Furthermore, participants expressed ambivalence about their military lifestyle of frequent relocation, and identified both positive and negative aspects of this reality. As a result of the data produced in this study, a model of fit is proposed with respect to work, self, and military life. A high degree of fit facilitates a military wife’s ability to preserve her whole self, while lack of fit results in the need to change one’s work or self to adapt, and in some cases result in feelings of despair, depression, and loss of self. This process is influenced by multi-layered gendered roles inherent in marriage, motherhood, and the military.
A study of adoption reunions and self concept in adult adoptees

The primary aim of this study was to examine whether adoptees who had experienced a reunion with a birth relative would score more positively on a measure of self-concept than adoptees who had not experienced a reunion. The Tennessee SelfConcept Scale (Roid & Fitts, 1988) was administered by mailout to adoptees who were members of the Forget Me Not Family Society or the TRIAD Society. A total of 159 adult adoptees participated in the study. Contrary to expectation, the results of the study indicated no differences on self-concept scores between reunited and searching adoptees. In addition, the mean scores of adoptees in this study were within the normal limits reported for the general population. The findings seem to indicate that as a group, adoptees do not differ in self-concept from the general population and also that reunions do not influence the self-concept of adult adoptees.
Do Banks Pass Through Credit Expansions? The Marginal Profitability of Consumer Lending During the Great Recession

We examine the ability of policymakers to stimulate household borrowing and spending during the Great Recession by reducing banks’ cost of funds. Using panel data on 8.5 million U.S. credit card accounts and 743 credit limit regression discontinuities, we estimate the marginal propensity to borrow (MPB) for households with different FICO credit scores. We find substantial heterogeneity, with a $1 increase in credit limits raising total unsecured borrowing after 12 months by 59 cents for consumers with the lowest FICO scores ( 660) while having no effect on consumers with the highest FICO scores (> 740). We use the same credit limit regression discontinuities to estimate banks’ marginal propensity to lend (MPL) out of a decrease in their cost of funds. For the lowest FICO score households, higher credit limits quickly reduce marginal profits, limiting the pass-through of credit expansions to those households. We estimate that a 1 percentage point reduction in the cost of funds raises optimal credit limits by $127 for consumers with FICO scores below 660 versus $2,203 for consumers with FICO scores above 740. We conclude that banks’ MPL is lowest exactly for those households with the highest MPB, limiting the effectiveness of policies that aim to stimulate the economy by reducing banks’ cost of funds.
Biomarkers: Evaluation of Screening for and Early Diagnosis of Hepatocellular Carcinoma in Japan and China

Over the past few decades, the screening for and early diagnosis of hepatocellular carcinoma (HCC) has attracted attention worldwide, and especially in Asian countries such as Japan and China. Such approaches can help detecting HCC at an earlier stage when curable interventions can be offered to achieve long-term disease-free survival for patients. Biomarkers have been used to screen for and diagnose HCC in various countries. In Japan, the combined tests of des-γ-carboxyprothrombin (DCP) and α-fetoprotein (AFP) or Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) have been shown to achieve a high level of sensitivity and specificity. These tests have routinely been used to screen for HCC and are covered by Japan’s national health insurance. Due to the routine practice of screening for HCC among high-risk patients, HCC nodules have been detected in the early stages in more than 60% of patients in Japan. In contrast, although several remarkable advances in the management of HCC have been made in China over the past few decades, most HCC patients still present with advanced-stage disease. AFP is the only serum biomarker that has widely been used to screen for and diagnose HCC in China. In recent years, several molecular biological studies have further investigated the clinical usefulness of DCP, and they have found that it may facilitate the screening for and diagnosis of HCC and assist with the assessment of HCC progression. DCP can serve as a biomarker to detect HCC in an early stage and facilitate definitive treatment. The wide implementation of DCP is expected, especially in China where 55% of HCC cases worldwide live.