Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Falls and Fear of Falling with Mortality in Korean Adults: The Dong-gu Study

This study evaluated the association between falls and the fear of falling (FOF) with the risk of all-cause mortality in Korean adults. The study enrolled 4,386 subjects aged 50 years and over who participated in the Dong-gu Study. Falls in the past year were categorized as yes or no. Injurious falls were defined as falls that resulted in fractures, head injuries, sprains or strains, bruising or bleeding, or other unspecified injuries. FOF was classified as low or high. The associations of falls and fall-related characteristics with mortality were assessed using Cox proportional hazards models. The average follow-up was 7.8 years. During this period, 255 men and 146 women died. In a fully adjusted model, falls in the past year were not associated with an increased risk of all-cause mortality (hazard ratio [HR] 1.16, 95% confidence interval [CI] 0.85–1.58), but a history of injurious falls was associated with an increased risk of mortality (HR 1.36, 95% CI 1.04–1.79). Compared with subjects without a FOF, subjects who were moderately or very afraid of falling had a higher mortality rate (HR 1.26, 95% CI 0.97–1.63). In conclusion, injurious falls and a high FOF increased the risk of all-cause mortality in Koreans. This study suggests that injurious falls and FOF can predict mortality in the general population.
Transforming growth factor-β3 relation with osteoporosis and osteoporotic fractures

Background: The high socioeconomic impact of osteoporosis and osteoporotic fracture is due to their high mortality, morbidity, and disease-related costs. Nowadays, bone mineral density (BMD) is a comparatively expensive way to diagnose and follow up patients with osteoporosis. Transforming growth factor-β3 (TGF-β3) is a protein categorized into cytokines. Some previous in vitro studies showed TGF-β3 effects on osteocytes and bone formation. Therefore, we conducted this study to find if there is any significant relationship between TGF-β3 and BMD results. Materials and Methods: This was an analytical cross-sectional study conducted in 2017. We included individuals who had been referred from their physicians to undergo BMD dual-energy X-ray absorptiometry. Blood samples were taken from 150 participants for measuring TGF-β3 with ELISA method. Results: The mean ± standard deviation of TGF-β3 serum level was 79 ± 30.8 pg/ml (minimum 41 pg/ml and maximum 210 pg/ml). There was a statistically significant and direct proportional relationship between TGF-β3 and T-score as a marker for the diagnosis and follow-up of osteoporosis and osteoporotic fracture (P = 0.001) (Pearson's correlation = +0.95). Conclusion: There was a significant relationship between TGF-β3 serum level and BMD. TGF-β3 serum level may be used as a marker for the diagnosis and follow-up of osteoporosis and osteoporotic fracture.
A substitute to xylene in deparaffinization and clearing prior to coverslipping in histopathology

INTRODUCTION: Deparaffinization and clearing prior to coverslipping are important steps in all staining methods in histopathology. Xylene is the most commonly used agent worldwide. However, xylene is toxic. We evaluated safer alternative dewaxing and clearing agents prior to coverslipping in a histopathology laboratory. MATERIALS AND METHODS: Thirteen different fresh surgical tissues were cut into two halves. One half processed using xylene and the other half processed using UltraClear™. Five groups were designed. For each Group of A, B, C, and D, 100 slides were cut from xylene-processed blocks. For Group E, 100 slides were cut from UltraClear™-processed blocks. Group A is the standard method. Group B evaluates UltraClear™ as a dewaxing agent only. Group C evaluates UltraClear™ as a clearing agent prior to coverslipping only. Group D evaluates UltraClear™ as both dewaxing and clearing agents prior to coverslipping. Group E evaluates UltraClear™ as both dewaxing and clearing agents prior to coverslipping. Six parameters were evaluated: nuclear staining, cytoplasmic staining, cell morphology, clarity of staining, uniformity of staining, and cost. RESULTS: Groups B, C, and D showed 79% (P = 0.054), 83% (P = 0.221), and 80% (P = 0.079) adequacy when compared with Group A (89%), respectively. However, Group E showed only 76% (P = 0.016) adequacy. UltraClear™ is more expensive than xylene. CONCLUSION: UltraClear™ is a promising dewaxing agent. It is also a good clearing agent for use prior to coverslipping in histopathology laboratory. Cost-benefit balance between safety of laboratory workers, good quality staining, and cost-effective strategy needs to be further studied.
Effectiveness of adjuvant chemotherapy in patients with Stage II colorectal cancer: A multicenter retrospective study

Background: Adjuvant chemotherapy (ACT) for patients with Stage II colorectal cancer (CRC) is an area of controversy in oncology. International guidelines recommend the use of ACT in patients with specific high-risk features. This study aimed to investigate the effectiveness of ACT in improving survival in patients with and without high-risk features. Materials and Methods: A total of 225 patients with Stage II CRC who underwent primary tumor resection were included in this study. Patients with one or more high-risk features including T4 tumor, poor differentiation, lymphovascular invasion, perineural invasion, bowel obstruction, local perforation, positive resection margins, or suboptimal lymph node sampling (fewer than 12 nodes) were classified as high risk. The survival analysis was performed between patients who only received curative surgery and those received single-agent (5-fluorouracil [5-FU] and leucovorin [LV] or capecitabine) or multiagent ACT (oxaliplatin and 5-FU + LV or oxaliplatin and capecitabine). Results: The 5-year overall survival (OS) rate was 88.4%, and the 5-year disease-free survival (DFS) rate was 80.4%. The 5-year OS and DFS rates improved insignificantly with ACT (89.8% vs. 81.2%, P = 0.59 and 81.3% vs. 74.6%, P = 0.41, respectively); however, multiagent ACT results to inferior 5-year OS and DFS compared to single-agent ACT (82.1 vs. 92.8%, P = 0.14 and 70.1% vs. 86%, P = 0.07, respectively). ACT was associated with insignificant improved OS and DFS in both high-risk and low-risk groups, but high-risk patients who received multiagent ACT had a significant inferior OS and DFS in comparison with those received single-agent ACT. T4 tumor and obstruction were independent poor prognostic factors affecting OS and DFS. Conclusion: In our population, the improvement of OS and DFS with ACT was not statistically significant in high-risk and low-risk patients with Stage II CRC.
A new characterization of stabilizing cycles for switched linear systems

Characterization of stabilizing switching signals in terms of infinite walks constructed by concatenating cycles on the underlying directed graph of a switched system that satisfy certain conditions, is a well-known technique in the literature. This paper deals with a new characterization of these cycles for stability of switched linear systems. We employ properties of the subsystem matrices and mild assumption on the admissible switches between the subsystems to characterize stabilizing cycles. In contrast to prior works, detection of our stabilizing cycles does not involve design of Lyapunov-like functions and storage of sets of scalars prior to the application of a cycle detection algorithm. As a result, our techniques offer improved numerical tractability. We also present an algorithm to detect our stabilizing cycles on the underlying directed graph of a switched system.
Generalized Momentum-Based Methods: A Hamiltonian Perspective

We take a Hamiltonian-based perspective to generalize Nesterov's accelerated gradient descent and Polyak's heavy ball method to a broad class of momentum methods in the setting of (possibly) constrained minimization in Euclidean and non-Euclidean normed vector spaces. Our perspective leads to a generic and unifying nonasymptotic analysis of convergence of these methods in both the function value (in the setting of convex optimization) and in norm of the gradient (in the setting of unconstrained, possibly nonconvex, optimization). Our approach relies upon a time-varying Hamiltonian that produces generalized momentum methods as its equations of motion. The convergence analysis for these methods is intuitive and is based on the conserved quantities of the time-dependent Hamiltonian.
M2G1G2 white blood cell flag by three-part automated hematology analyzer: A hint to dengue infection in appropriate clinical context

BACKGROUND: Automated hematology analyzers often generate many flags which can provide important clues to the underlying hematological abnormality. Although pathologists are generally well versed in recognizing the importance of flags indicating potential leukemic blasts, their utility in hinting toward infectious etiology, especially during epidemics, is less well known. We analyzed any abnormal flags generated by a three-part automated hematology analyzer in serologically confirmed cases of dengue. MATERIALS AND METHODS: The study included 28 patients diagnosed with serologically confirmed dengue infection. The venous samples were run on ABX Miros-60 three-part hematology analyzer. The complete blood count data and any abnormal flags were noted and correlated with peripheral blood film findings in all patients. RESULTS: An abnormal white blood cell (WBC) flag was noted in all 28 patients, including two in whom all other hematological parameters were within normal limits. In 26 (93%) patients, M2G1G2 WBC flag was noted while the samples of the remaining two patients generated M2G1 and L1M2G1G2 WBC flags, respectively. CONCLUSION: An abnormal WBC flag, when correlated in appropriate clinical context, especially during a dengue outbreak, can aid in targeting the cohort of patients who will require immediate referral for serological confirmation.
Model selection for contextual bandits

We introduce the problem of model selection for contextual bandits, where a learner must adapt to the complexity of the optimal policy while balancing exploration and exploitation. Our main result is a new model selection guarantee for linear contextual bandits. We work in the stochastic realizable setting with a sequence of nested linear policy classes of dimension $d_1 < d_2 < \ldots$, where the $m^\star$-th class contains the optimal policy, and we design an algorithm that achieves $\tilde{O}(T^{2/3}d^{1/3}_{m^\star})$ regret with no prior knowledge of the optimal dimension $d_{m^\star}$. The algorithm also achieves regret $\tilde{O}(T^{3/4} + \sqrt{Td_{m^\star}})$, which is optimal for $d_{m^{\star}}\geq{}\sqrt{T}$. This is the first model selection result for contextual bandits with non-vacuous regret for all values of $d_{m^\star}$, and to the best of our knowledge is the first positive result of this type for any online learning setting with partial information. The core of the algorithm is a new estimator for the gap in the best loss achievable by two linear policy classes, which we show admits a convergence rate faster than the rate required to learn the parameters for either class.
AutoSlim: Towards One-Shot Architecture Search for Channel Numbers

We study how to set channel numbers in a neural network to achieve better accuracy under constrained resources (e.g., FLOPs, latency, memory footprint or model size). A simple and one-shot solution, named AutoSlim, is presented. Instead of training many network samples and searching with reinforcement learning, we train a single slimmable network to approximate the network accuracy of different channel configurations. We then iteratively evaluate the trained slimmable model and greedily slim the layer with minimal accuracy drop. By this single pass, we can obtain the optimized channel configurations under different resource constraints. We present experiments with MobileNet v1, MobileNet v2, ResNet-50 and RL-searched MNasNet on ImageNet classification. We show significant improvements over their default channel configurations. We also achieve better accuracy than recent channel pruning methods and neural architecture search methods. Notably, by setting optimized channel numbers, our AutoSlim-MobileNet-v2 at 305M FLOPs achieves 74.2% top-1 accuracy, 2.4% better than default MobileNet-v2 (301M FLOPs), and even 0.2% better than RL-searched MNasNet (317M FLOPs). Our AutoSlim-ResNet-50 at 570M FLOPs, without depthwise convolutions, achieves 1.3% better accuracy than MobileNet-v1 (569M FLOPs). Code and models will be available at: this https URL
Constraints on axion-like particles with different magnetic field models from the PKS 2155–304 energy spectrum

Axion-like particles (ALPs) are a promising kind of dark matter candidate particle that are predicted to couple with photons in the presence of magnetic fields. The oscillations between photons and ALPs traveling in the magnetic fields have been used to constrain ALP properties. In this work, we obtain some new constraints on the ALP mass ma and the photon-ALP coupling constant g with two different magnetic field models through TeV photons from PKS 2155–304. The first is the discrete-φ model in which the magnetic field has the orientation angle φ that changes discretely and randomly from one coherent domain to the next, and the second is the linearly-continuous-φ model in which the magnetic field orientation angle φ varies continuously across neighboring coherent domains. For the discrete-φ model, we can obtain the best constraints on the ALP mass m1 = ma/(1\ neV) = 0.1 and on the photon-ALP coupling constant g11 = g/(10−11 GeV−1) = 5. The reasonable range of the ALP mass m1 is 0.08 ∼ 0.2 when g11 = 5, and the only reasonable value of the photon-ALP coupling constant is g11 = 5 when m1 = 0.1. For the linearly-continuous-φ model, we can obtain the best constraints on the ALP mass m1 = 0.1 and on the photon-ALP coupling constant g11 = 0.7. The reasonable range of the ALP mass m1 is 0.05 ∼ 0.4 when g11 = 0.7, and the reasonable range of the photon-ALP coupling constant g11 is 0.5 ∼ 1 when m1 = 0.1. All of the results are consistent with the upper bound (g < 6.6 × 10−11 GeV−1, i.e., g11 < 6.6) set by the CAST experiment.
Diagonally Dominant Principal Component Analysis

Abstract We consider the problem of decomposing a large covariance matrix into the sum of a low-rank matrix and a diagonally dominant matrix, and we call this problem the “diagonally dominant principal component analysis (DD-PCA). ” DD-PCA is an effective tool for designing statistical methods for strongly correlated data. We showcase the use of DD-PCA in two statistical problems: covariance matrix estimation and global detection in multiple testing. Using the output of DD-PCA, we propose a new estimator for estimating a large covariance matrix with factor structure. Thanks to a nice property of diagonally dominant matrices, this estimator enjoys the advantage of simultaneous good estimation of the covariance matrix and the precision matrix (by a plain inversion). A plug-in of this estimator to linear discriminant analysis and portfolio optimization yields appealing performance in real data. We also propose two new tests for testing the global null hypothesis in multiple testing when the z-scores have a factor covariance structure. Both tests first use DD-PCA to adjust the individual p-values and then plug in the adjusted p-values to the higher criticism (HC) test. These new tests significantly improve over the HC test and compare favorably with other existing tests. For computation of DD-PCA, we propose an iterative projection algorithm and an ADMM algorithm. Supplementary materials for this article are available online.
Modelling accretion disc emission with generalized temperature profile and its effect on AGN spectral energy distribution

The broadband spectral energy distribution (SED) of Active Galactic Nuclei (AGN) is investigated for a well-selected sample composed of $23$ Seyfert 1 galaxies observed simultaneously in the optical/UV and X-ray bands with the Neil Gehrels {\it Swift} Observatory. The optical to UV continuum spectra are modeled, for the first time, with emission from an accretion disk with a generalized radial temperature profile, in order to account for the intrinsic spectra which are found to be generally redder than the model prediction of the standard Shakura-Sunyaev disk (SSD) ($F_\nu\propto\nu^{+1/3}$). The power-law indices of the radial temperature profile ($T_{\rm eff}(R)\propto R^{-p}$, $R$ is the radius of the accretion disk) are inferred to be $p=0.5$ -- $0.75$ (a median of $0.63$), deviating from the canonical $p=0.75$ for the SSD model as widely adopted in previous studies. A marginal correlation of a flatter radial temperature profile (a smaller $p$ value) with increasing the Eddington ratio is suggested. Such a model produces generally a lower peak of accretion disk emission and thus a smaller bolometric luminosity in some of the AGN, particularly those with high Eddington ratios, than that based on the SSD model by a factor of several. The broadband SED, the bolometric correction factors and their dependence on some of the AGN parameters are re-visited. We suggest that such non-standard SSD disks may operate in AGN and are at least partly responsible for the reddened optical/UV spectra as observed. One possible explanation for these flattened temperature profiles is the mass loss process in form of disk winds/outflows.
At What Level Should One Cluster Standard Errors in Paired Experiments, and in Stratified Experiments with Small Strata?

In paired experiments, the units included in the randomization, e.g. villages, are matched into pairs, and then one unit of each pair is randomly assigned to treatment. We conducted a survey of papers that used paired randomized experiments in economics. To estimate the treatment effect, researchers usually regress their outcome on a treatment indicator and pair fixed effects, and cluster standard errors at the unit-of-randomization level, namely, at the village level in our example. We show that the variance estimator in this regression may be severely downward biased: under constant treatment effect, its expectation is equal to 1/2 of the true variance. Using that variance estimator may lead researchers to substantially overreject the null of no treatment effect. Instead, we argue that researchers should cluster their standard errors at the pair level.
Fallback Accretion-powered Supernova Light Curves Based on a Neutrino-driven Explosion Simulation of a 40 M⊙ Star

We present synthetic light curves (LCs) of fallback-powered supernovae based on a neutrino-driven explosion of a 40 zero-metallicity star with significant fallback accretion onto a black hole that was previously simulated by Chan et al. until shock breakout. Here, we investigate the LC properties of the explosion after shock breakout for various fallback models. Without extra power from fallback accretion, the LC is that of an SN IIP with a plateau magnitude of around −14 mag and a plateau duration of 40 days. With extra power for the LC from fallback accretion, however, we find that the transient can be significantly more luminous. The LC shape can be SN 1987A-like or Type IIP-like, depending on the efficiency of the fallback engine. If the accretion disk forms soon after the collapse and more than 1% of the accretion energy is released as the central engine, fallback accretion-powered supernovae become as luminous as superluminous supernovae. We suggest that Type II superluminous supernovae with broad hydrogen features could be related to such hydrogen-rich supernovae powered by fallback accretion. In the future, such superluminous supernovae powered by fallback accretion might be found among the supernovae from the first stars in addition to pair-instability supernovae and pulsational pair-instability supernovae.
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off

Reducing the precision of weights and activation functions in neural network training, with minimal impact on performance, is essential for the deployment of these models in resource-constrained environments. We apply mean-field techniques to networks with quantized activations in order to evaluate the degree to which quantization degrades signal propagation at initialization. We derive initialization schemes which maximize signal propagation in such networks and suggest why this is helpful for generalization. Building on these results, we obtain a closed form implicit equation for $L_{\max}$, the maximal trainable depth (and hence model capacity), given $N$, the number of quantization levels in the activation function. Solving this equation numerically, we obtain asymptotically: $L_{\max}\propto N^{1.82}$.
Outcomes of Bilateral Adrenalectomy in Cushing's Syndrome

Context: The literature on outcomes of bilateral adrenalectomy (BADx) in Cushing's syndrome (CS) is scant. Aims: The aim of this study is to analyze the short- and long-term outcomes of patients who underwent BADx and to compare the outcomes among different etiologies of CS. Settings and Design: This is a retrospective analysis of patients who underwent BADx for CS at our center between 2005 and 2018. Materials and Methods: In all, 33 patients were studied for clinical outcomes, survival rates, and long-term complications. Statistical Analysis: All analyses were performed with SPSS software (version 21.0). Results: The mean age at surgery was 39.33 ± 15.67 years. The primary etiology for CS was Cushing's disease (CD) in 42.42%, ectopic source in 36.36%, primary pigmented nodular adrenocortical disease (PPNAD) in 12.12%, and adrenocorticotrophin hormone–independent macronodular adrenal hyperplasia (AIMAH) in 9.09% of patients. The median follow-up time was 72.77 months. Improvement in hypertension and diabetes status after surgery was seen in 78% and 76.19% of patients, respectively. Proximal myopathy improved in 68% of patients. Nelson's syndrome and adrenal crisis were seen in 21.4% of patients each on long-term follow-up. Total mortality after BADx was 33.3%. Mortality in the first 30 days after surgery was seen in five patients (15.15%). Higher cortisol levels at presentation and age more than 40 years were predictors of mortality. Among the Cushing's subtypes, PPNAD had the best prognosis followed by CD. Perioperative Infections were a major cause of mortality. Conclusion: BADx is an effective treatment for CS especially in patients with PPNAD and CD but carries a significant mortality rate too.
Automated Video Game Testing Using Synthetic and Humanlike Agents

In this article, we present a new methodology that employs tester agents to automate video game testing. We introduce two types of agents—synthetic and humanlike—and two distinct approaches to create them. Our agents are derived from Sarsa and Monte Carlo tree search (MCTS) but focus on finding defects, while traditional game-playing agents focus on maximizing game scores. The synthetic agent uses test goals generated from game scenarios, and these goals are further modified to examine the effects of unintended game transitions. The humanlike agent uses test goals extracted by our proposed multiple greedy-policy inverse reinforcement learning (MGP-IRL) algorithm from tester trajectories. MGP-IRL captures multiple policies executed by human testers. We use our agents to produce test sequences, and run the game with these sequences. At each run, we use an automated test oracle to check for bugs. We analyze the proposed method in two parts—we compare the success of humanlike and synthetic agents in bug finding, and we evaluate the similarity between humanlike agents and human testers. We collected 427 trajectories from human testers using the General Video Game Artificial Intelligence (GVG-AI) framework and created three games with 12 levels that contain 45 bugs. Our experiments reveal that humanlike and synthetic agents compete with human testers’ bug finding performances. Moreover, we show that MGP-IRL increases the humanlikeness of agents while improving the bug finding performance.