Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations between RASSF1A promoter methylation and NSCLC: a meta-analysis of published data.

BACKGROUND RASSF1A has been reported to be a candidate tumor suppressor in non-small cell lung cancer (NSCLC). However, the association between RASSF1A promoter methylation and NSCLC remains unclear, particularly in regarding links to clinicopathologic features. METHODS Eligible studies were identified through searching PubMed, EMBASE, Cochrane Library and China National Knowledge Infrastructure (CNKI) databases. Studies were pooled and odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated. Funnel plots were also performed to evaluate publication bias. RESULTS Nineteen studies involving 2,063 cases of NSCLC and 1,184 controls were included in this meta-analysis. A significant association was observed between RASSF1A methylation and NSCLC in the complete data set (OR = 19.42, 95% CI: 14.04- 26.85, P < 0.001). Pooling the control tissue subgroups (heterogeneous/autologous) gave pooled ORs of 32.4 (95% CI, 12.4-84.5) and 17.7 (95% CI, 12.5-25.0) respectively. Racial subgroup (Caucasian/Asian) analysis gave pooled ORs of 26.6 (95% CI, 10.9-64.9) and 20.9 (95% CI, 14.4-30.4) respectively. The OR for RASSF1A methylation in poorly-differentiated vs. moderately/well-differentiated NSCLC tissues was 1.88 (95% CI, 1.32- 2.68, P<0.001), whereas there were no significant differences in RASSF1A methylation in relation to gender, pathology, TNM stage and smoking behavior among NSCLC cases. CONCLUSION This meta-analysis suggests a significant association between RASSF1A methylation and NSCLC, confirming the role of RASSF1A as a tumor suppressor gene. Large-scale and well-designed case-control studies are needed to validate the associations identified in the present meta-analysis.
Synthetic aperture confocal imaging

Confocal microscopy is a family of imaging techniques that employ focused patterned illumination and synchronized imaging to create cross-sectional views of 3D biological specimens. In this paper, we adapt confocal imaging to large-scale scenes by replacing the optical apertures used in microscopy with arrays of real or virtual video projectors and cameras. Our prototype implementation uses a video projector, a camera, and an array of mirrors. Using this implementation, we explore confocal imaging of partially occluded environments, such as foliage, and weakly scattering environments, such as murky water. We demonstrate the ability to selectively image any plane in a partially occluded environment, and to see further through murky water than is otherwise possible. By thresholding the confocal images, we extract mattes that can be used to selectively illuminate any plane in the scene.
Huskie Commons Huskie

Snakes represent a sizable fraction of vertebrate biodiversity, but until recently, data on their demography have been sparse. Consequently, generalizations regarding patterns of variation are weak and the potential for population projections is limited. We address this information gap through an analysis of spatial and temporal variation in demography (population size, annual survival, and realized population growth) of the Lake Erie Watersnake, Nerodia sipedon insularum
Integral-equation methods for inhomogeneous elliptic partial differential equations in complex geometry

Over the last several decades, integral-equation methods have emerged as powerful tools for the solution of the homogeneous partial differential equations of mathematical physics, including the Laplace, Helmholtz and Maxwell equations. By using the methods of potential theory, boundary value problems can be recast as boundary integral equations, reducing the dimensionality of the problem by one and permitting geometrically flexible discretization. Combined with suitable fast algorithms, this has led to optimal or nearly optimal complexity solvers in a variety of important application areas. For inhomogeneous, variable coefficient and nonlinear equations, there is no corresponding reduction in dimensionality, since the interior of the domain needs to be discretized and integral-equation methods appear to be less natural. They lead to dense linear systems of equations, while direct discretization of the partial differential equation leads to a sparse system of the same size. In this thesis, we present a new collection of integral-equation methods for inhomogeneous partial differential equations including the Poisson, modified Helmholtz, and modified Stokes equations that are of optimal computational complexity, while fully adaptive, high order accurate and easy to use even in complex geometry. For this, we have combined fast methods for computing the volume integral operators of potential theory, with new quadrature methods for layer potentials, and a new method for smooth function extension from arbitrarily-shaped domains. Unlike finite difference and finite element discretization of the governing partial differential equation, the only unknowns in the formulation lie on the domain boundary, so that there is still an effective reduction in dimensionality in terms of the size of the linear system which needs to be solved. The interior degrees of freedom are
Induction and polynomial networks

Induction plays a major role in a wide variety of application domains. Because of this broad range of applicability a variety of approaches have been suggested and employed to discover general models from data. A key goal in these approaches is to perform well on data not seen during the model construction process. This paper surveys the variety of techniques available for induction and categorizes them by their degree of automation. The authors then examine in more detail polynomial networks which are induction methods that grew out of cybernetics and early neural network research. The authors conclude the paper with suggested directions for continued work in polynomial networks.
How to Train Your Energy-Based Model for Regression - Supplementary Material

In this supplementary material, we provide additional details and results. It consists of Appendix A Appendix D. Appendix A contains a detailed algorithm for our employed prediction strategy. Further experimental details are provided in Appendix B for 1D regression, and in Appendix C for object detection. Lastly, Appendix D contains details and further results for the visual tracking experiments. Note that equations, tables, figures and algorithms in this supplementary document are numbered with the prefix "S". Numbers without this prefix refer to the main paper.
Intergenerational Mobility: Evidence from Pakistan Panel Household Survey

This paper, using data from Pakistan Panel Household Survey 2010, finds evidence for higher (lower) intergenerational immobility (mobility) for Pakistan. The results from transition matrix and regression analysis suggest that the educational, occupational and income status of the son is mostly determined by the socio-economic position of the father.
Efficient viewshed computation on terrains in external memory

Nowadays, a huge volume of data about terrains is available and generally, the data can not be completely stored in computer’s internal memory. So, many GIS applications require efficient algorithms to manipulate the data externally. One of these applications is the viewshed computation that consists in obtain the visible points from a given point p. In this paper, we present an efficient algorithm to compute the viewshed on terrains stored in external memory. In most practical cases (when the observer’s radius of interest is smaller than the terrain size), the algorithm complexity is O(scan(n2)) where n2 is the number of points in a n × n DEM and scan(n2) is the minimum number of I/O operations required to read n2 contiguous items stored in external memory. Also, as shown in the results, our algorithm outperforms the known algorithms described in the literature.
On Non-Intrusive Workload-Aware Database Replication

Performance and high-availability are the crucial factors in the development of nowadays distributed database systems. Both of these challenges are commonly addressed by means of the same technique, database replication. The overall throughput of the system is increased by leveraging parallel computation on different sites, and in case of replica failures, availability is improved by redirecting requests to operational replicas. However, providing transparent database replication is not an easy task. Although database replicas should be as independent of each other as possible for performance and availability reasons, some synchronization is required to provide data consistency. This thesis is about non-intrusive (or middleware) database replication protocols. More specifically, this thesis focuses on the development of practical replication protocols that use off-the-shelf database engines, take advantage of group communication primitives, cope with failures of system components, behave correctly, and, by exploiting the specific characteristics of the application, achieve high performance. In the first part of this thesis we address the following problem: non-intrusive database replication protocols cannot obtain fine-grained information about transactions due to limited access to the database engine internals. We make three contributions in this part. The first contribution is the Multiversion Database State Machine, a middleware extension of the Database State Machine, a kernelbased replication approach. The Multiversion Database State Machine assumes predefined, parameterized transactions. The particular data items accessed by a transaction depend on the transaction’s type and the parameters provided by the application program when the transaction is instantiated. The second contribution of this thesis is a technique to bypass the extraction and propagation of readsets and writesets in non-intrusive replication protocols. We present the SQL Inspector, a tool capable to automatically identify conflicting transactions before their actual execution by partially parsing them. The performance of the Multiversion Database State Machine can be further improved if transactions execute at carefully chosen database sites. Thus, the third contribution of this thesis is
Achievable Rates of Underwater Acoustic OFDM Systems over Highly Dispersive Channels

Unlike the capacity of other channels, the capacity of the shallow water UAC channel has been seldomly addressed. Motivated by recent results in information theory, this paper investigates achievable rates of underwater acoustic OFDM systems. We consider channels where time and frequency dispersion is high enough that (i) neither the transmitter nor the receiver can have a priori knowledge of the channel state information, and (ii) intersymbol/intercarrier interference (ISI/ICI) cannot be neglected in the information theoretic treatment.
QCD corrections to top quark pair production at hadron colliders

Top quark physics is one of the cornerstones of the research programme at the LHC. Due to its uniquely large mass, the top quark is an excellent probe of the mechanism of mass generation and of several new physics scenarios involving new heavy resonances, non-standard Higgs sectors or flavour changing neutral currents. At hadron colliders top quarks are dominantly produced in top-antitop pairs through QCD interactions. Thanks to its unprecedented centre-of-mass energy and luminosity, the LHC is producing top quark pairs at rates of millions every year, enabling production and decay rates to be measured inclusively and differentially with a high accuracy. In order to extract precise values of the top quark mass and couplings, and in order to maximise the potential to detect possible signals of physics beyond the Standard Model, these very precise measurements must be matched with similarly accurate theoretical predictions. The required theoretical accuracy can only be achieved by including QCD radiative corrections up to NNLO. In this thesis we present the results of ongoing work towards a fully differential calculation for top pair production at NNLO in perturbative QCD. We present an extension of the antenna subtraction method that enables the extraction and cancellation of all infrared singularities which are found at intermediate stages of fixed-order calculations for reactions with massive fermions. Employing this method, we construct subtraction terms for hadronic top pair production at NLO, and for several partonic processes contributing to the double real and real-virtual corrections to top pair production at NNLO.
PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms using Fully Convolutional Neural Networks

Cardiovascular diseases are one of the most severe causes of mortality, taking a heavy toll of lives annually throughout the world. The continuous monitoring of blood pressure seems to be the most viable option, but this demands an invasive process, bringing about several layers of complexities. This motivates us to develop a method to predict the continuous arterial blood pressure (ABP) waveform through a non-invasive approach using photoplethysmogram (PPG) signals. In addition we explore the advantage of deep learning as it would free us from sticking to ideally shaped PPG signals only, by making handcrafted feature computation irrelevant, which is a shortcoming of the existing approaches. Thus, we present, PPG2ABP, a deep learning based method, that manages to predict the continuous ABP waveform from the input PPG signal, with a mean absolute error of 4.604 mmHg, preserving the shape, magnitude and phase in unison. However, the more astounding success of PPG2ABP turns out to be that the computed values of DBP, MAP and SBP from the predicted ABP waveform outperforms the existing works under several metrics, despite that PPG2ABP is not explicitly trained to do so.
Enhanced Deep Learning Framework for Cow Image Segmentation

 Abstract — The applications of deep learning to livestock farming have in recent years gained wide acceptance from the computer vision community due to the continuous achievement of its applications to agricultural tasks. Moreover, the essentiality of deep learning is its practicality in detecting, segmenting, and classifying video and image objects without which precision livestock farming would have been impossible. However, the applications of most of the state-of-the-art models of deep learning to multiple cow objects image segmentation are not accurate and cannot generate colorimetric information due to poor pre-processing mechanism inherent in the associated methods and unequal training of their backbone layers. To overcome the above-mentioned limitations, an enhanced deep learning framework of Mask Region-based Convolutional Neural Network (Mask R-CNN) based on Generalized Color Fourier Descriptors (GCFD) is proposed. The enhanced model produced 0.93 mean Average Precision (mAP). The result shows the performance capability of the proposed framework over the state-of-the-art models for cow image segmentation.
UvA-DARE ( Digital Academic Repository ) Fast Radio Burst Discovered in the Arecibo Pulsar ALFA Survey

Recent work has exploited pulsar survey data to identify temporally isolated, millisecond-duration radio bursts with large dispersion measures (DMs). These bursts have been interpreted as arising from a population of extragalactic sources, in which case they would provide unprecedented opportunities for probing the intergalactic medium; they may also be linked to new source classes. Until now, however, all so-called fast radio bursts (FRBs) have been detected with the Parkes radio telescope and its 13-beam receiver, casting some concern about the astrophysical nature of these signals. Here we present FRB 121102, the first FRB discovery from a geographic location other than Parkes. FRB 121102 was found in the Galactic anti-center region in the 1.4 GHz Pulsar Arecibo L-band Feed Array (ALFA) survey with the Arecibo Observatory with a DM = 557.4 ± 2.0 pc cm−3, pulse width of 3.0 ± 0.5 ms, and no evidence of interstellar scattering. The observed delay of the signal arrival time with frequency agrees precisely with the expectation of dispersion through an ionized medium. Despite its low Galactic latitude (b = −0. ◦2), the burst has three times the maximum Galactic DM expected along this particular line of sight, suggesting an extragalactic origin. A peculiar aspect of the signal is an inverted spectrum; we interpret this as a consequence of being detected in a sidelobe of the ALFA receiver. FRB 121102’s brightness, duration, and the inferred event rate are all consistent with the properties of the previously detected Parkes bursts. Key word: pulsars: general Online-only material: color figures
Quantifying Diapir Ascent Velocities in Power‐Law Viscous Rock Under Far‐Field Stress: Integrating Analytical Estimates, 3D Numerical Calculations and Geodynamic Applications

Diapirism is crucial for heat and mass transfer in many geodynamic processes. Understanding diapir ascent velocity is vital for assessing its significance in various geodynamic settings. Although analytical estimates exist for ascent velocities of diapirs in power‐law viscous, stress weakening fluids, they lack validation through 3D numerical calculations. Here, we improve these estimates by incorporating combined linear and power‐law viscous flow and validate them using 3D numerical calculations. We focus on a weak, buoyant sphere in a stress weakening fluid subjected to far‐field horizontal simple shear. The ascent velocity depends on two stress ratios: (a) the ratio of buoyancy stress to characteristic stress, controlling the transition from linear to power‐law viscous flow, and (b) the ratio of regional stress associated with far‐field shearing to characteristic stress. Comparing analytical estimates with numerical calculations, we find analytical estimates are accurate within a factor of two. However, discrepancies arise due to the analytical assumption that deviatoric stresses around the diapir are comparable to buoyancy stresses. Numerical results reveal significantly smaller deviatoric stresses. As deviatoric stresses govern stress‐dependent, power‐law viscosity, analytical estimates tend to overestimate stress weakening. We introduce a shape factor to improve accuracy. Additionally, we determine characteristic stresses for representative mantle and lower crustal flow laws and discuss practical implications in natural diapirism, such as sediment diapirs in subduction zones, magmatic plutons or exhumation of ultra‐high‐pressure rocks. Our study enhances understanding of diapir ascent velocities and associated stress conditions, contributing to a thorough comprehension of diapiric processes in geology.
Improvement of Escherichia coli production strains by modification of the phosphoenolpyruvate : sugar phosphotransferase system

This peer-reviewed article was published immediately upon acceptance. It can be downloaded, printed and distributed freely for any purposes (see copyright notice below). Articles in Microbial Cell Factories are listed in PubMed and archived at PubMed Central. For information about publishing your research in Microbial Cell Factories or any BioMed Central journal, go to http://www.microbialcellfactories. com/info/instructions/ For information about other BioMed Central publications go to http://www.biomedcentral. com/
Human granulocyte colony‐stimulating factor receptors in acute myelogenous leukemia

Abstract: Human granulocyte colony‐stimulating factor (G‐CSF) receptors on human acute leukemia cells were investigated using human G‐CSF iodolabeled by the lactoperoxidase method. Among various human leukemic cell lines, only cells of myelogenous lineage including HL‐60, THP‐1 and U937 had one type of high‐affinity receptor for G‐CSF, as shown by Scatchard analysis. Fresh leukemia cells from 19 patients with acute myelogenous leukemia (AML) were then studied. Specific receptors for G‐CSF were demonstrated on blast cells in all 19 cases, the mean number of G‐CSF receptors per AML cell ranging from 95 to 1436. G‐CSF receptors on AML cells appeared to be a single affinity type, although some variations were observed. The mean number of G‐CSF receptors on leukemic cells from patients with either FAB M3 or FAB M2 was greater than that of cells from patients with Ml (p < 0.01, p < 0.10, respectively). Moreover, the mean number of receptors for G‐CSF on CD13‐and CD34‐positive AML cells was higher than that on CD13‐negative and CD34‐positive AML cells (p < 0.01), and the mean number of G‐CSF receptors on CD7‐positive AML cells was lower than that for CD7‐negative AML cells (p < 0.10). Since the FAB classification and surface phenotypes reflect maturation stages, our findings indicate that the distribution of G‐CSF receptors, even on AML cells, may be related to the maturation process.
Public Health Service Task Force Recommendations for Use of Antiretroviral Drugs in Pregnant HIV-1-Infected Women for Maternal Health and Interventions to Reduce Perinatal HIV-1 Transmission in the United States

285. 91. ACOG technical bulletin. Preconceptional care. Number 205--May 1995. American College of Obstetricians and Gynecologists. Int J Gynaecol Obstet. 1995 Aug; 50(2):201-7. 92. Burns DN, Landesman S, Muenz LR, et al. Cigarette smoking, premature rupture of membranes and vertical transmission of HIV-1 among women with low CD4 levels. J Acquir Immune Defic Syndr Hum Retrovirol, 1994. 7(7):718-26. 93. Turner BJ, Hauck WW, Fanning R, Markson LE. Cigarette smoking and maternal-child HIV transmission. J Acquir Immune Defic Syndr Human Retrovirol, 1997. 14(4):327-37. 94. Rodriguez EM, Mofenson LM, Chang BH, et al. Association of maternal drug use during pregnancy with maternal HIV culture positivity and perinatal HIV transmission. AIDS, 1996. 10(3):273-82. 95. Bulterys M, Landesman S, Burns DN, et al. Sexual behavior and injection drug use during pregnancy and vertical transmission of HIV-1. J Acquir Immune Defic Syndr Human Retrovirol, 1997.
Determination of selection criteria with correlation and path coefficient analysis in chickpea (Cicer Arietinum L.) Breeding

The experiment was conducted at College Farm, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, to estimate the selection criteria following correlation and path coefficient analysis in 50 genotypes of chickpea (Cicer arietinum L.). seed yield per plant was manifested positive and significant correlation with primary branches per plant, secondary branches per plant, plant height, number of pods per plant, number of seeds per pod, harvest index and 100 seed weight, indicated that these attributes were mainly influencing the seed yield in chickpea. The path analysis revealed that harvest index, secondary branches per plant, plant height, protein content, 100 seed weight and days to maturity affecting directly the seed yield per plant. Therefore, emphasis should be given to the development of chickpea lines with more number of primary and secondary branches per plant, more number of seed per pod, boldness and on high harvest index to improve seed yield per plant. Path analysis showed relatively high values of residual effect (0.721) indicating that there are other traits not recorded in the research, which may significantly be involved.
Mathematical Actions, Mathematical Objects, and Mathematical Induction

Proof by mathematical induction is arguably the most difficult proof technique for students to master. We explain this difficulty within an action-object framework. Specifically, we report on results from clinical interviews with two mathematics majors in which the first author administered tasks designed to elucidate each student’s understanding of logical implications as mental objects. We found that the framework explains much of the difficulty inherent in proof by induction, even the students’ struggles with hidden quantifiers.