Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic relevance of β-catenin expression in T2-3N0M0 esophageal squamous cell carcinoma.

AIM To study the expression of β-catenin in esophageal squamous cell carcinoma (ESCC) at stage T2-3N0M0 and its relation with the prognosis of ESCC patients. METHODS Expression of β-catenin in 227 ESCC specimens was detected by immunohistochemistry (IHC). A reproducible semi-quantitative method which takes both staining percentage and intensity into account was applied in IHC scoring, and receiver operating characteristic curve analysis was used to select the cut-off score for high or low IHC reactivity. Then, correlation of β-catenin expression with clinicopathological features and prognosis of ESCC patients was determined. RESULTS No significant correlation was observed between β-catenin expression and clinicopathological parameters in terms of gender, age, tumor size, tumor grade, tumor location, depth of invasion and pathological stage. The Kaplan-Meier survival curve showed that the up-regulated expression of β-catenin indicated a poorer post-operative survival rate of ESCC patients at stage T2-3N0M0 (P = 0.004), especially of those with T3 lesions (P = 0.014) or with stage IIB diseases (P = 0.007). Multivariate analysis also confirmed that β-catenin was an independent prognostic factor for the overall survival rate of ESCC patients at stage T2-3N0M0 (relative risk = 1.642, 95% CI: 1.159-2.327, P = 0.005). CONCLUSION Elevated β-catenin expression level may be an adverse indicator for the prognosis of ESCC patients at stage T2-3N0M0, especially for those with T3 lesions or stage IIB diseases.
Resistance Mechanisms to Arsenicals and Antimonials

Salts and organic derivatives of arsenic and antimony are quite toxic. Living organisms have adapted to this toxicity by the evolution of resistance mechanisms. Both prokaryotic and eukaryotic cells develop resistance when exposed to arsenicals or antimonials. In the case of bacteria resistance is conferred by plasmid-encoded arsenical resistance (ars) operons. The genes and gene products of the ars operon of the clinically-isolated conjugative R-factor R773 have been identified and their mechanism of action elucidated. The operon encodes an ATP-driven pump that extrudes arsenite and antimonite from the cells. The lowering of their intracellular concentration results in resistance. Arsenate resistance results from the action of the plasmid-encoded arsenate reductase that reduces arsenate to arsenite, which is then pumped out of the cell.
Contribution of vertebral deformities to chronic back pain and disability

Among 2992 white women aged 65–70 years recruited from population‐based listings, we measured radiographic vertebral dimensions of T5–L4 and calculated ratios of heights: anterior/posterior, mid/posterior, and posterior/posterior of either adjacent vertebra. The degree of deformity for each vertebra was analyzed in terms of the number of standard deviations (SD) that ratio differed from the mean ratio calculated for the same vertebral level in this population. We correlated the severity of each woman's worst vertebral deformity with back pain, back disability in six activities of daily living, and height loss since age 25. Only 39.4% of the cohort had no vertebral deformity; 10.2% had a deformity ≥ 4 SD. Vertebral deformities < 4 SD below the mean were not associated with increased back pain, disability, or loss of height. In contrast, women whose deformity was ≥ 4 SD had a 1.9 (95% CI, 1.5–2.4) times higher risk of moderate to severe back pain and a 2.6 (95% CI, 1.7–3.9) times higher risk of disability involving the back; they were also 2.5 (95% CI, 2.0–3.2) times more likely to have lost ≥ 4 cm in height. All three types of vertebral deformity (wedge, end plate, and crush) were equally associated with these outcomes. Multiple deformities < 4 SD did not increase the likelihood of these three outcomes, but multiple deformities >≥ 4 SD tended to be associated with increased back pain, disability, and height loss. This large cross‐sectional study suggests that vertebral deformities cause substantial pain, disability, or loss of height only if vertebral height ratios fall 4 SD below the normal mean. Much back pain could not be attributed to vertebral deformities, suggesting other causes.
Fuzzy neural network-based robust adaptive control for dynamic positioning of underwater vehicles with input dead-zone

This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural Network (DRFNN) with feedback loops is employed to approximate the unknown portion of the controller, which can greatly reduce the number of neural network inputs. A fuzzy logic dead-zone compensator is designed to cope with the unknown dead-zone characteristics of actuators. The upper bounds of the approximation errors and disturbances of the network, which are often used in existing works, are not necessary in this paper due to the presentation of a special robust compensator. Stability analysis is conducted according to the Lyapunov theorem, and the tracking error is proved to converge to zero. Simulation results indicate that the proposed controller demonstrates good performance.
High performance virtual reality distributed electronic commerce: application for the furniture and ceramics industries

This paper presents an e-commerce tool that extends the conventional online store with a new section called room planner, a web application which is embedded in the virtual store. It allows the specification of the geometry of the room, placement of the objects and selection of the point of view. Then a realistic picture of the scene can be obtained. This functionality is very suitable for the furniture and ceramics sectors. In order to generate the images a parallel radiosity illumination algorithm has been implemented, which can be used in low-cost platforms such as a cluster of PCs, so that these technologies are affordable also for SMEs.
Flood disaster monitoring and evaluation in China

Abstract China frequently experiences natural disasters, of which flooding is the most serious. How to monitor and control natural disasters, assess damage, and provide relief is the most urgent problem for the Chinese government and disaster experts. A national integrated system using remote sensing, geographic information systems, the Global Positioning System, and other technology for monitoring and evaluating flood disasters has been assembled and tried out for 3 years. The system has played an important role in flood mitigation during the trial and has become a key part of the flood management system at China's National Flood Control Headquarters. This paper presents an overview of the system and its use in China.
Boron Deficiency in Trifoliate Orange Induces Changes in Pectin Composition and Architecture of Components in Root Cell Walls

Boron (B) is a micronutrient indispensable for citrus and B deficiency causes a considerable loss of productivity and quality in China. However, studies on pectin composition and architecture of cell wall components in trifoliate orange roots under B deficiency condition are not sufficient. In this study, we investigated the alteration in pectin characteristics and the architecture of cell wall components in trifoliate orange [Poncirus trifoliata (L.) Raf. ] roots under B starvation. The results showed that B-deficient roots resulted in a significant enlargement of root tips and an obvious decrease in cell wall B and uronic acid content in Na2CO3-soluble pectin compared with B-adequate roots. Meanwhile, they showed a decrease of 2-keto-3-deoxyoctanoic acid in CDTA-soluble and Na2CO3-soluble pectin in cell walls, while the degree of methylation (DM) of CDTA-soluble pectin was significantly increased under B deficiency. Transmission electron microscope (TEM) micrographs of B deficient plants showed a distinct thickening of the cell walls, with the thickness 1.82 times greater than that of control plant roots. The results from Fourier-transform infrared spectroscopy (FTIR) showed that B deficiency changed the mode of hydrogen bonding between protein and carbohydrates (cellulose and hemicellulose). The FTIR spectra exhibited a destroyed protein structure and accumulation of wax and cellulose in the cell walls under B starvation. The 13C nuclear magnetic resonance (13C-NMR) spectra showed that B starvation changed the organic carbon structure of cell walls, and enhanced the contents of amino acid, cellulose, phenols, and lignin in the cell wall. The results reveal that the swelling and weakened structural integrity of cell walls, which induced by alteration on the network of pectin and cell wall components and structure in B-deficient roots, could be a major cause of occurrence of the rapid interruption of growth and significantly enlarged root tips in trifoliate orange roots under B-insufficient condition.
Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal

The SLEUTH model (slope, landuse, exclusion, urban extent, transportation and hillshade), formerly called the Clarke Cellular Automaton Urban Growth Model, was developed for and tested on various cities in North America, including Washington, DC, and San Francisco. In contrast, this research calibrated the SLEUTH model for two European cities, the Portuguese metropolitan areas of Lisbon and Porto. The SLEUTH model is a cellular automaton model, developed with predefined growth rules applied spatially to gridded maps of the cities in a set of nested loops, and was designed to be both scaleable and universally applicable. Urban expansion is modeled in a modified two-dimensional regular grid. Maps of topographic slope, land use, exclusions, urban extents, road transportation, and a graphic hillshade layer form the model input. This paper examines differences in the model’s behavior when the obviously different environment of a European city is captured in the data and modeled. Calibration results are included and interpreted in the context of the two cities, and an evaluation of the model’s portability and universality of application is made. Questions such as scalability, sequential multistage optimization by automated exploration of model parameter space, the problem of equifinality, and parameter sensitivity to local conditions are explored. The metropolitan areas present very different spatial and developmental characteristics. The Lisbon Metropolitan Area (the capital of Portugal) has a mix of north Atlantic and south Mediterranean influences. Property is organized in large patches of extensive farmland comprised of olive and cork orchards. The urban pattern of Lisbon and its environs is characterized by rapid urban sprawl, focused in the urban centers of Lisbon, Oeiras, Cascais Setúbal, and Almada, and by intense urbanization along the main road and train lines Computers, Environment and Urban Systems
Diseño e Implementación de un Taller de Programación de Juegos Digitales con Scratch como Apoyo a Fundamentos de Programación

Habilidades relacionadas con los fundamentos de la programacion deben ser desarrollados por todos los estudiantes de los primeros semestres de cursos relacionados con la informatica. Sin embargo, las altas tasas de desercion tambien se identifican en este periodo. Actividades didacticas en las que los estudiantes desarrollen sus propios artefactos digitales, tales como los juegos digitales, pueden aumentar la motivacion de los estudiantes para aprender y aplicar conocimientos de programacion de una manera mas tangible. En este articulo se describe el desarrollo y aplicacion de un taller de diseno de juego para apoyar un curso de Fundamentos de programacion dirigida a los estudiantes de la carrera de Ingenieria Informatica en una universidad chilena. Los resultados indican un aumento considerable en las tasas de aprobacion de los estudiantes que se inscribieron en el curso por primera vez.
Scheduler activations for interference-resilient SMP virtual machine scheduling

The wide adoption of SMP virtual machines (VMs) and resource consolidation present challenges to efficiently executing multi-threaded programs in the cloud. An important problem is the semantic gaps between the guest OS and the hypervisor. The well-known lock-holder preemption (LHP) and lock-waiter preemption (LWP) problems are examples of such semantic gaps, in which the hypervisor is unaware of the activities in the guest OS and adversely deschedules virtual CPUs (vCPUs) that are executing in critical sections. Existing studies have focused on inferring a high-level semantic state of the guest OS to aid hypervisor-level scheduling so as to avoid the LHP and LWP problems. In this work, we find a reverse semantic gap - the guest OS is oblivious of the scheduling events at the hypervisor, leaving the potential of addressing the LHP and LWP problems in the guest OS unexploited. Inspired by scheduler activations (SAs) in hybrid threading, we proposed interference-resilient scheduling (IRS), a guest-hypervisor coordinated approach to enhancing load balancing in the guest. IRS informs the guest OS before vCPU preemption happens at the hypervisor to activate in-guest load balancing. As such, critical threads on preempted vCPUs can be migrated to other running vCPUs so that the LHP and LWP problems are all alleviated. Experimental results with Xen and Linux guests show as much as 42%, 43%, and 46% performance improvement for parallel programs with blocking, spinning synchronizations, and multithreaded server workloads, respectively.
No exit? The effect of health status on dissatisfaction and disenrollment from health plans.

OBJECTIVE To examine the implications of serious and chronic health problems on the willingness of enrollees to switch health plans if they are dissatisfied with their current arrangements. DATA SOURCE A large (20,283 respondents) survey of employees of three national corporations committed to the model of managed competition, with substantial enrollment in four types of health plans: fee-for-service, prepaid group practice, independent practice associations, and point-of-service plans. STUDY DESIGN A set of logistic regression models are estimated to determine the probability of disenrollment, if dissatisfied, controlling for the influence on satisfaction and disenrollment of age, race, education, family income and size, gender, marital status, mental health status, pregnancy, duration of employment and enrollment in the plan, number of alternative plans, and HMO penetration in the local market. Separate coefficients are estimated for enrollees with and without significant physical health problems. Additional models are estimated to test for the influence of selection effects as well as alternative measures of dissatisfaction and health problems. DATA COLLECTION Data were collected through a mailed survey with a response rate of 63.5 percent; comparisons to a subsample administered by telephone showed few differences. PRINCIPAL FINDINGS In group/staff model HMOs and point-of-service plans, only 12-17 percent of the chronically ill enrollees who were so dissatisfied when surveyed that they intended to disenroll actually left their plan in the next open enrollment period. This compared to 25-29 percent of the healthy enrollees in these same plans, who reported this level of dissatisfaction and 58-63 percent of the enrollees under fee-for-service insurance. CONCLUSIONS Switching plans appears to be significantly limited for enrollees with serious health problems, the very enrollees who will be best informed about the ability of their health plan to provide adequate medical care. These effects are most pronounced in plans that have exclusive contracts with providers. We conclude that disenrollment provides only weak safeguards on quality for the sickest enrollees and that reported levels of dissatisfaction and disenrollment represent inaccurate signals of plan performance.
Generalized Linear Latent Variable Models with Flexible Distribution of Latent Variables

Abstract. We consider a semi‐nonparametric specification for the density of latent variables in Generalized Linear Latent Variable Models (GLLVM). This specification is flexible enough to allow for an asymmetric, multi‐modal, heavy or light tailed smooth density. The degree of flexibility required by many applications of GLLVM can be achieved through this semi‐nonparametric specification with a finite number of parameters estimated by maximum likelihood. Even with this additional flexibility, we obtain an explicit expression of the likelihood for conditionally normal manifest variables. We show by simulations that the estimated density of latent variables capture the true one with good degree of accuracy and is easy to visualize. By analysing two real data sets we show that a flexible distribution of latent variables is a useful tool for exploring the adequacy of the GLLVM in practice.
Clustering Startups Based on Customer-Value Proposition

K-means clustering is a popular unsupervised learning technique for grouping closely related data points. This project utilizes K-means to group together startups by text description into related working industry. Additional techniques such as dimensionality reduction via singular-value decomposition are implemented to reduce the space of the feature set and document-term matrix and improve speed and efficiency of the algorithm. This paper also presents a novel metric for measuring the error of K-means clustering in a reduced dimensionality space.
Uptake of oxytetracycline, sulfamethoxazole and ketoconazole from fertilised soils by plants

This study was performed to investigate the potential for a set of two antibiotics and one antifungal compound to be taken up from the soil by plants. Plants are used for animal or human consumption, and so the measured concentrations in the plant material will be used to model potential human exposure to these compounds. The uptake by two types of plants (grass and watercress) from two types of soil was studied. The compounds used for these experiments were sulfamethoxazole, oxytetracycline and ketoconazole at concentrations of 5 and 10 mg kg−1 in the soil. The compounds of interest were extracted out of the plant matrix by applying accelerated solvent extraction. Analyses were carried out by a LC–MS/MS. From the results, it was concluded that the plant materials used for this study were able to take up sulfamethoxazole and ketoconazole when the soil was contaminated with these compounds at a concentration ranging from 5 to 10 mg kg−1. Sulfamethoxazole was detected in all samples, at levels ranging from 7 to 21 µ kg−1 for grass and 4 to 7.5 µ kg−1 for watercress. For ketoconazole, the results showed low absorption. Oxytetracycline was not detected in any sample. A partition-limited model approach was applied for the comparison of experimental and estimated data, and the relationship between physicochemical properties of the compounds and plant uptake was highlighted.
Displacement co-occurrence statistics for binary digital images

Displacement co-occurrence is used to describe the spatial dependence relationships of binary digital images, which in turn are used for disconnectedness detection and texture analysis. A ‘‘m-points-and-M-cells’’ model, in particular, is used to study onedimensional displacement co-occurrence statistics, which then is used for row-wise and column-wise two-dimensional image analysis. A compact state is used to characterize a case for aggregating pixels into a connected region, resulting in a regular straight-line distribution of the displacement co-occurrence histogram. An image pattern is described by a scattering state that usually yields an irregular histogram distribution. With reference to the compact state’s histogram, the vector norms of the scattering states’ histograms can be used to characterize the image’s disconnectedness feature. A connected line along horizontal or vertical orientations results in zero vector norms, and therefore, the nonzero vector norm indicates the presence of disconnectedness. The displacement cooccurrence histogram is invariant under translation, and shear deformation. Using a ‘‘W-points-and-MXN-lattice’’ model and the concept of rectangular rectification, any binary pattern can be considered as one of its scattering states. Two-dimensional displacement co-occurrence matrices yield the statistics of twodimensional displacement configurations, and can be used in texture analysis.
Protein Z G 79 A polymorphism in Turkish pediatric cerebral infarct patients

Objective: Protein Z (PZ) plays an enhancer role in coagulation as an anticoagulant. In this study G79A polymorphism was investigated in Turkish pediatric stroke patients. Material and Methods: Ninety-one pediatric stroke patients with cerebral ischemia and 70 control subjects were analyzed for PZ G79A and also factor V Leiden (FVL) and prothrombin (PT) mutations. Results: PZ 79 ‘A’ allele in homozygous state was found in five patients (5.5%), while it was found in only one control subject (1.4%), and it appeared to be a risk factor for pediatric ischemia [OR=3.94 (0.44-35.1)]. When patients and controls who had FVL and PT carriers were excluded, AA genotype carried a risk [OR=3.88 (0.41-36.5)]. In addition, plasma PZ levels were measured in 21 stroke patients and 52 controls. Plasma PZ levels were not different between stroke patients (501,0 ngml-1 ± 158,3 ngml-1) and controls (447,3 ngml-1 ± 166,0 ngml-1). However, the plasma levels of PZ were decreased in patients with AA genotype. This is the first study in which G79A polymorphism was investigated in Turkish pediatric stroke patients Conclusion: Our data showed that carrying 79 AA genotype could be a genetic risk factor for cerebral infarct in pediatric patients. (Turk J Hematol 2008; 25: 133-5)
MGRO Recognition Algorithm-Based Artificial Potential Field for Mobile Robot Navigation

This paper describes a novel recognition algorithm which includes mean filter, Gaussian filter, Retinex enhancement method, and Ostu threshold segmentation method (MGRO) for the navigation of mobile robots with visual sensors. The approach includes obstacle visual recognition and navigation path planning. In the first part, a three-stage method for obstacle visual recognition is constructed. Stage 1 combines mean filtering and Gaussian filtering to remove random noise and Gauss noise in the environmental image. Stage 2 increases image contrast by using the Retinex enhancement method. Stage 3 uses the Ostu threshold segmentation method to achieve obstacle feature extraction. A navigation method based on the auxiliary visual information is constructed in the second part. The method is based on the artificial potential field (APF) method and is able to avoid falling into local minimum by changing the repulsion field function. Experimental results confirm that obstacle features can be extracted accurately and the mobile robot can avoid obstacles safely and arrive at target positions correctly.