Miracle-dz/UniFAR-FTUs huggingface dataset:
IGFBP1hiWNT3Alo Subtype in Esophageal Cancer Predicts Response and Prolonged Survival with PD-(L)1 Inhibitor

Simple Summary The lack of precision biomarkers hinders the development of individualized immunotherapy for esophageal cancer (ESCA) patients. The activation of WNT signaling has proved to be associated with the primary resistance to immunotherapy. Therefore, our study aims to develop efficient biomarkers based on WNT signaling to guide ESCA immunotherapy. In the TCGA cohort with 196 cases and our BJCH cohort with 95 cases, we successfully constructed an IGFBP1hiWNT3Alo signature and validated its correlation with the poor prognosis of ESCA patients. Moreover, in 2 GEO cohorts with a total of 68 cases and our BJIM cohort with 21 cases, we verified that IGFBP1hiWNT3Alo ESCA patients had a good response and prognosis with immunotherapy. Our findings indicate that the IGFBP1hiWNT3Alo signature was a potential immunotherapeutic biomarker for ESCA. Abstract PD-(L)1 inhibitor could improve the survival of locally advanced esophageal cancer (ESCA) patients, but we cannot tailor the treatment to common biomarkers. WNT signaling activation was associated with primary resistance to immunotherapy. In this study, we used our two clinical cohorts (BJCH n = 95, BJIM n = 21) and three public cohorts to evaluate and verify a new immunotherapeutic biomarker based on WNT signaling in ESCA patients. Our findings showed that WNT signaling-related genes stratified TCGA patients into Cluster 1, 2, and 3, among which, Cluster 3 had the worst prognosis. The most up- and down-regulated genes in Cluster 3 were IGFBP1 and WNT3A. Further analysis validated that IGFBP1hiWNT3Alo ESCA patients had significantly poor RFS and OS in the TCGA and BJCH cohorts. Interestingly, IGFBP1hiWNT3Alo patients had a good response and prognosis with immunotherapy in three independent cohorts, exhibiting better predictive value than PD-L1 expression (signature AUC = 0.750; PD-L1 AUC = 0.571). Moreover, IGFBP1hiWNT3Alo patients may benefit more from immunotherapy than standard treatment (p = 0.026). Immune cell infiltration analysis revealed a significant increase in DC infiltration in IGFBP1hiWNT3Alo patients post-immunotherapy (p = 0.022), which may enhance immune response. The IGFBP1hiWNT3Alo signature could predict patients who benefited from PD-(L)1 inhibitor treatment and may serve as a biomarker in ESCA.
As Scales Become Separated: Lectures on Effective Field Theory

These lectures aim to provide a pedagogical introduction to the philosophical underpinnings and technical features of Effective Field Theory (EFT). Improving control of $S$-matrix elements in the presence of a large hierarchy of physical scales $m \ll M$ is emphasized. Utilizing $\lambda \sim m/M$ as a power counting expansion parameter, we show how matching an ultraviolet (UV) model onto an EFT makes manifest the notion of separating scales. Renormalization Group (RG) techniques are used to run the EFT couplings from the UV to the infrared (IR), thereby summing large logarithms that would otherwise reduce the efficacy of perturbation theory. A variety of scalar field theory based toy examples are worked out in detail. An approach to consistently evolving a coupling across a heavy particle mass threshold is demonstrated. Applying the same method to the scalar mass term forces us to confront the hierarchy problem. The summation of a logarithm that lacks explicit dependence on an RG scale is performed. After reviewing the physics of IR divergences, we build a scalar toy version of Soft Collinear Effective Theory (SCET), highlighting many subtle aspects of these constructions. We show how SCET can be used to sum the soft and collinear IR Sudakov double logarithms that often appear for processes involving external interacting light-like particles. We conclude with the generalization of SCET to theories of gauge bosons coupled to charged fermions. These lectures were presented at TASI 2018.
Exploring the relationship between personalized feedback models, learning design and assessment outcomes

Abstract The increasing use of technology in education has brought new opportunities for the systematic collection of student data. Analyzing technology-mediated trace data, for example, has enabled researchers to bring new insights into student learning processes and the factors involved to support learning and teaching. However, many of these learning analytic studies have drawn conclusions from limited data sets that are derived from a single course or program of study. This impacts the generalizability of noted outcomes and calls for research on larger institutional data sets. The institutional adoption and analysis of learning technology can provide deeper insights into a wide range of learning contexts in practice. This study focused on examining how instructors used the learning tool, OnTask, to provide personalized feedback for students in large classes. We collected usage data from 99 courses and 19,385 students to examine how the instructors customized feedback to different groups of students. The findings reveal that there is a significant association between the topics of feedback and students with different performance. The results also demonstrated that instructors most frequently provided feedback related to student assessment. The study emphasizes the importance of teacher and student feedback literacy for creating effective feedback loops.
How Does Social and Work Life Change for Fathers of Children With Cancer?

Caring for a child with cancer greatly affects fathers’ social lives, with fathers experiencing conflicts between work demands and their desire to be with their sick child. To date, fathers’ unique experiences of caring for a child with cancer remain poorly understood. This study aimed to understand the impact of a child’s cancer diagnosis on the social and work relationships of their father through in-depth interviews with 20 Korean fathers of a child with cancer within 5 years of the diagnosis. Thematic analysis yielded five themes related to how a child’s cancer diagnosis affected the father’s relationships at work and in social situations: (a) shifting priorities, (b) changes in work, (c) support and struggles at work, (d) not being social out of guilt, and (e) pent-up stress. Overall, the findings highlight that fathers experienced conflicting roles and constraints in social relationships after their child’s cancer diagnosis. This should be considered when developing and implementing social services for families with children diagnosed with cancer.
A Numerical Study of Relativistic Fluid Collapse

We investigate the dynamics of self-gravitating, spherically-symmetric distributions of fluid through numerical means. In particular, systems involving neutron star models driven far from equilibrium in the strong-field regime of general relativity are studied. Hydrostatic solutions of Einstein's equations using a stiff, polytropic equation of state are used for the stellar models. Many of the scenarios we examine involve highly-relativistic flows that require improvements upon previously published numerical methods to simulate. Here our particular focus is on the physical behavior of the coupled fluid-gravitational system at the threshold of black hole formation--so-called black hole critical phenomena. To investigate such phenomena starting from conditions representing stable stars, we must drive the star far from its initial stable configuration. We use one of two different mechanisms to do this: setting the initial velocity profile of the star to be in-going, or collapsing a shell of massless scalar field onto the star. Both of these approaches give rise to a large range of dynamical scenarios that the star may follow. These scenarios have been extensively surveyed by using different initial star solutions, and by varying either the magnitude of the velocity profile or the amplitude of the scalar field pulse. In addition to illuminating the critical phenomena associated with the fluid collapse, the resulting phase diagram of possible outcomes provides an approximate picture of the stability of neutron stars to large, external perturbations that may occur in nature.
Comparison Analysis of CNN, SVC and Random Forest Algorithms in Segmentation of Teeth X-Ray Images

In dental diagnosis, rapid identification of dental complications from radiographs requires highly experienced medical professionals. Occasionally, depending exclusively on a expert's judgement could lead to changes in diagnosis, that could eventually lead to difficult treatment. Although fully automatic diagnostic tools aren’t still anticipated, image pattern recognition has grown into decision support, opening with discovery of teeth and its constituents on X-ray images. Dental discovery is a topic of study for more than previous two decades, depending primarily on threshold and region-based strategies. In this study, we proposed segmentation based Teeth X-Ray images using a couple of machine learning algorithms as well as deep learning algorithms i.e., Support Vector Classifier (SVC), Random Forest algorithm and Convolutional Neural network (CNN) which would help us in accurate identification and classification. This article also presents a comprehensive comparison between these Algorithms.
The Role of The Electron Energy Balance in Plasma Thruster Instabilities

Using the fluid equations of Hall thruster plasma we analyze the influence of the electron energy balance on the stability of ion sound modes. For frequencies lower than ωc = 107 s−1 the gains and losses in the source term are approximately equal, thus the temperature can be in principle determined in terms of other dependent variables. This permits to reduce the number of equations. It appears however, that the new system can have complex characteristics in some regions. This in turn implies instability of certain modes with frequencies lower than ωc. Using the fluid equations of Hall thruster plasma we analyze the influence of the electron energy balance on the stability of ion sound modes. For frequencies lower than ωc = 107 s−1 the gains and losses in the source term are approximately equal, thus the temperature can be in principle determined in terms of other dependent variables. This permits to reduce the number of equations. It appears however, that the new system can have complex characteristics in some regions. This in turn implies instability of certain modes with frequencies lower than ωc.
What Aspects of Galaxy Environment Matter?

We determine what aspects of the density field surrounding galaxies most affect their properties. For Sloan Digital Sky Survey galaxies, we measure the group environment, meaning the host group luminosity and the distance from the group center (hereafter "groupocentric distance"). For comparison, we measure the surrounding density field on scales ranging from 100 h-1 kpc to 10 h-1 Mpc. We use the relationship between color and group environment to test the null hypothesis that only the group environment matters, searching for a residual dependence of properties on the surrounding density. Generally, red galaxies are slightly more clustered on small scales (~100-300 h-1 kpc) than the null hypothesis predicts, possibly indicating that substructure within groups has some importance. At large scales (>1 h-1 Mpc), the actual projected correlation functions of galaxies are biased at less than the 5% level with respect to the null hypothesis predictions. We exclude strongly the converse null hypothesis: that only the surrounding density (on any scale) matters. These results generally encourage the use of the halo model description of galaxy bias, which models the galaxy distribution as a function of host halo mass alone. We compare these results to proposed galaxy formation scenarios within the cold dark matter cosmological model.
A modified CoRoT detrend algorithm and the discovery of a new planetary companion

We presentMCDA, a modification of the COnvectionROtation and planetary Transits (CoRoT) detrend algorithm (CDA) suitable to detrend chromatic light curves. By means of robust statistics and better handling of short-term variability, the implementation decreases the systematic light-curve variations and improves the detection of exoplanets when compared with the original algorithm. All CoRoT chromatic light curves (a total of 65 655) were analysed with our algorithm. Dozens of new transit candidates and all previously known CoRoT exoplanets were rediscovered in those light curves using a box-fitting algorithm. For three of the new cases, spectroscopicmeasurements of the candidates’ host stars were retrieved from the ESO Science Archive Facility and used to calculate stellar parameters and, in the best cases, radial velocities. In addition to our improved detrend technique, we announce the discovery of a planet that orbits a 0.79+0.08 −0.09 R star with a period of 6.718 37 ± 0.000 01 d and has 0.57+0.06 −0.05 RJ and 0.15 ± 0.10MJ. We also present the analysis of two cases in which parameters found suggest the existence of possible planetary companions
Laboratory experiments on fronts

Abstract We describe a laboratory model of an upwelling front in a two-layer stratification. In the model the interface between the two layers slopes upwards toward a vertical boundary (or coastline) and can intersect the free surface to produce a front. Fluid motion in each layer is density driven and, in the undisturbed state, is in quasi-geostrophic balance. The front is observed to be unstable to (ageostrophic) disturbances with an along-front wavelength proportional to the Rossby radius of deformation. At very large amplitudes these unstable waves form closed circulations. However, in contrast to the behaviour of fronts far from vertical boundaries, where cyclone-anticyclone vortex pairs are formed, the presence of the coastline inhibits formation of anticyclonic eddies in the upper layer and enhances cyclonic rings of upper layer fluid which lie above cyclonic eddies in the lower layer. The cyclones move away from the vertical boundary and (as is also the case when no vertical boundary is present) t.
⁸⁷Rubidium Bose-Einstein condensates : machine construction and quantum Zeno experiments

This thesis details construction of a new apparatus for the production of 87Rb Bose-Einstein condensates and a subsequent quantum Zeno effect experiment. An experimental apparatus for producing large Bose-Einstein condensates of 87Rb is described in detail. A high flux thermal atomic beam is decelerated by a Zeeman slower and is then captured and cooled in a magneto-optical trap. The atoms are then transfered into a cloverleaf style Ioffe-Pritchard magnetic trap and cooled to quantum degeneracy with radio frequency induced forced evaporation. Condensates containing up to 20 million atoms can be produced every few minutes. The quantum Zeno effect is the suppression of transitions between quantum states by frequent measurement. Oscillation between two ground hyperfine states of a magnetically trapped 87Rb Bose-Einstein condensate, externally driven at a transition rate ωR, was substantially suppressed by destructively measuring one of the levels with resonant optical scattering. While an ideal continuous measurement will stop the transition, any real measurement method will occur at a finite rate. The suppression of the transition rate in the two level system was quantified for pulsed measurements with a time between pulses δt and weak continuous measurements with a scattering rate γ. We observe that the weak continuous measurements exhibit the same suppression in the transition rate as the pulsed measurements when γδt = 3.60(0.43). This is in agreement with the previously predicted value of 4. Increasing the measurement frequency suppressed the transition rate to 0. 005ωR. Thesis Supervisor: Wolfgang Ketterle Title: John D. MacArthur Professor of Physics Thesis Supervisor: David E. Pritchard Title: Cecil and Ida Green Professor of Physics
Response to Horton and Dewdney

There are some points in the reply of Horton et al. [this http URL] to my comment [quant-ph/0202140] on their paper [quant-ph/0103114] which I cannot let stand without a response. I provide here some clarification of how much I proved about the set of points where their law of motion is ill-defined.
Dislocation nucleation mechanisms during nanoindentation of concentrated FeNiCr alloys: unveiling the effects of Cr through molecular simulations

Fe-based alloys with high chromium and nickel concentrations are very attractive for efficient energy production in extreme operating conditions. We perform molecular dynamics (MD) simulations of nanoindentation on fcc FeNiCr multicomponent materials. Equiatomic FeNi, Fe55Ni19Cr26, and Fe74Ni8Cr18 are tested by using established interatomic potentials and similar conditions, for the elucidation of key dislocation nucleation mechanisms and interactions. Generally, we find that the presence of Cr in these alloys reduces the mobility of prismatic dislocation loops, and increases their area, regardless of crystallographic orientation. Dislocation nucleation and evolution is tracked during mechanical testing as a function of nanoindentation strain and Kocks–Mecking continuum modeling displays good agreement with MD findings. Furthermore, the analysis of geometrically necessary dislocations (GNDs) is consistent with the Ma–Clarke’s model at depths lower than 1.5 nm. The presence of Cr leads to a decrease of the GND density with respect to Cr-less FeNi samples, thus we find that Cr is critically responsible of increasing these alloys’ hardness. Post-indentation impression maps indicate that Ni–Fe–Cr compositions display strain localization and hardening due to high Cr concentration.
Interpretable Disease Name Estimation based on Learned Models using Semantic Representation Learning of Medical Terms

: This paper describes a method for constructing a learned model for estimating disease names using semantic representation learning for medical terms and an interpretable disease-name estimation method based on the model. Experiments were conducted using old and new electronic medical records from Toyama University Hospital, where the data distribution of disease names differs signiﬁcantly. The F1-score of the disease name estimation was improved by about 10 points compared with the conventional method using a general word semantic vector dictionary with a faster linear SVM. In terms of the interpretability of the estimation, it was conﬁrmed that 70% of the disease names could provide higher-level concepts as the basis for disease name estimation. As a result of the experiments, we conﬁrmed that both interpretability and accuracy for disease name estimation are possible to some extent.
Magnetic field in a young circumbinary disk

Context. Polarized continuum emission at millimeter-to-submillimeter wavelengths is usually attributed to thermal emission from dust grains aligned through radiative torques with the magnetic field. However, recent theoretical work has shown that under specific conditions polarization may arise from self-scattering of thermal emission and by radiation fields from a nearby stellar object. Aims. We use multi-frequency polarization observations of a circumbinary disk to investigate how the polarization properties change at distinct frequency bands. Our goal is to discern the main mechanism responsible for the polarization through comparison between our observations and model predictions for each of the proposed mechanisms. Methods. We used the Atacama Large Millimeter/submillimeter Array to perform full polarization observations at 97.5 GHz (Band 3), 233 GHz (Band 6) and 343.5 GHz (Band 7). The ALMA data have a mean spatial resolution of 28 AU. The target is the Class I object BHB07-11, which is the youngest object in the Barnard 59 protocluster. Complementary Karl G. Jansky Very Large Array observations at 34.5 GHz were also performed and revealed a binary system at centimetric continuum emission within the disk. Results. We detect an extended and structured polarization pattern that is remarkably consistent between the three bands. The distribution of polarized intensity resembles a horseshoe shape with polarization angles following this morphology. From the spectral index between Bands 3 and 7, we derived a dust opacity index β ~ 1 consistent with maximum grain sizes larger than expected to produce self-scattering polarization in each band. The polarization morphology and the polarization levels do not match predictions from self-scattering. On the other hand, marginal correspondence is seen between our maps and predictions from a radiation field model assuming the brightest binary component as main radiation source. Previous molecular line data from BHB07-11 indicates disk rotation. We used the DustPol module of the ARTIST radiative transfer tool to produce synthetic polarization maps from a rotating magnetized disk model assuming combined poloidal and toroidal magnetic field components. The magnetic field vectors (i.e., the polarization vectors rotated by 90°) are better represented by a model with poloidal magnetic field strength about three times the toroidal one. Conclusions. The similarity of our polarization patterns among the three bands provides a strong evidence against self-scattering and radiation fields. On the other hand, our data are reasonably well reproduced by a model of disk with toroidal magnetic field components slightly smaller than poloidal ones. The residual is likely to be due to the internal twisting of the magnetic field due to the binary system dynamics, which is not considered in our model.
Early Effects of Improved Mood on Propensity for Emotional Eating During the Physical Activity-only Phase of a Community-Based Behavioral Treatment for Obesity in Women with High Mood Disturbance

Weight loss beyond the short term is problematic for individuals with obesity. Especially for women, emotional eating is one of the greatest barriers and might require attention early in a behavioral weightloss program. Physical activity-associated mood improvement may be associated with reduced emotional eating. Women with obesity volunteered for a community-based weight-management treatment. Effects associated with the initial 10 weeks, which focused on behavioral support of physical activity (prior to addressing eating behavior change), were assessed. Groups were designated based on whether participants’ high total mood disturbance (TMD) scores reduced to a normal level (n = 45) or remained high (n = 27). Although significant overall improvements in emotional eating were found, F(1, 70) = 22.80, p < . 001, its change scores did not significantly differ by group, F(1, 70) = 0.82, p = . 370. Using aggregated data, the prediction of reduction in emotional eating by lowered TMD scores was not statistically significant. Adding change in self-efficacy for controlled eating into Step 2 of the regression model significantly increased the explained variance to R2 = . 10, p = . 014, with group not being a significant contributor when added in Step 3. TMD reduction was significantly predicted by increase in physical activity, β = -. 23, p = . 028, and completion of at least 3 bouts/week, rpb = -. 22, p= . 015. Because physical activity-related reductions in negative mood and increases in self-efficacy were associated with reduced emotional eating, viability for those behavioral factors as early treatment targets were signaled.