Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Accuracy of Generalized Inferences from Comparison Group Studies

Background: Various studies have examined bias in impact estimates from comparison group studies (CGSs) of jobs training programs and in education, where results are benchmarked against randomized trials. The usual question addresses levels of and conditions for bias as well as strategies for reducing bias when the estimand is the impact for those who participated in the program. Objectives: This article extends the framework to situations where results from CGSs are generalized to untreated inference populations. The methodology is explained and demonstrated using results from two multisite trials in education. Research Design: Multisite trials are used to generate CGS-based impact estimates that are evaluated against site-specific experimental benchmarks. Strategies for reducing bias are evaluated. Subjects: Students in grades K-3 in 79 schools in Tennessee; students in grades 4-8 in 82 schools in Alabama. Measures: Grades K-3 SAT reading and math scores; grades 4-8 SAT10 reading scores. Results: Using CGS-based program impact estimates with untreated inference populations leads to bias from: differences between compared groups in average performance, differences between them in program impact, and covariation between average performance and impact. In both studies, the first bias had greater magnitude, but both were substantial compared to the average impact. Conclusion: Decision makers who extrapolate CGS results to untreated inference populations in their jurisdictions should be aware of potential for bias from both selection and effect heterogeneity. Moderator effects may give insight into and account for the latter; however, even accounting for effects of confounders and moderators, substantial bias may remain.
Cardiac implantable electrical devices in women

Clinical trials have demonstrated the benefits of cardiac implantable electrical devices, which include pacemakers, implantable cardioverter‐defibrillators (ICDs), and cardiac resynchronization therapy (CRT), with respect to key clinical outcomes and survival. Women more often require permanent pacing for sick sinus syndrome, whereas atrioventricular block is more common in men. Women appear to have a higher incidence of complications with pacemaker implantation, as well as with ICD and CRT implantation. The indications for ICDs and CRT do not have any distinctions based on sex, and outcomes are comparable in men and women. In fact, women often seem to have better outcomes with CRT compared with men. Despite the demonstrated benefits of these devices, ICDs and CRT are underutilized in women. In this review, we explore sex differences in utilization, outcomes, and complications with pacemakers, ICDs, and CRT.
Generation of Realistic Amorphous Al2O3 And ZrO2 Samples By Hybrid Classical and First-Principle Molecular Dynamics Simulations

The rapid scaling of complementary metal oxide semiconductor (CMOS) technology requires substituting the traditional gate oxide, SiO2, with highdielectrics, which can maintain the same capacitance with much lower leakage current. Amorphous aluminum and zirconium oxides (a-Al2O3 and a-ZrO2) are leading candidates for such highgate oxide materials on Ge. Ge is one of a few semiconductors that offer significantly higher hole mobility than silicon and is being extensively investigated for p-channel high-k MOSFETs. (1-3).
Distributed planning and scheduling for enhancing spacecraft autonomy

1. ABSTRACT In an autonomous operating mode of a spacecraft, operators will communicate only high-level goals and deadlines directly to the spacecraft. The spacecraft will then perform its own planning and scheduling, decomposing a goal into a set of sub-goals to be achieved with onboard subsystems and/or in cooperation with other spacecraft in the environment. Here we present this distributed approach to onboard planning and scheduling that helps a spacecraft function as an autonomous agent. Such an agent’s domain knowledge of tasks and their components are manifested through a hierarchical language taking into account spacecraft operational aspects and resource constraints. The task decentralization problem is solved by the use of the hierarchical knowledge structures, and the resource optimization problem is addressed by its explicit representation within the model. The reasoning performed by an agent for the required planning and scheduling tasks is based on a constraint propagation paradigm. A limited-scope Java prototype is developed and demonstrated using space-based scenarios involving onboard sensors and a satellite constellation. We are specifically targeting our effort to enhance the planning and scheduling capability of NASA’s proposed Remote Agent architecture. 2. INTRODUCTION Spacecraft autonomy [4] has the potential for effecting significant cost savings in mission operations by reducing the need for dedicated ground staff. In an autonomous operating mode, operators will communicate only highlevel goals and deadlines directly to the spacecraft. The spacecraft will then perform its own planning and scheduling, decomposing a goal into a set of sub-goals to be achieved in cooperation with other spacecraft within the constellation. The term ‘planning’ refers to the generation of activities that satisfy a current set of goals [2]. For example, a planning process to satisfy the request for an image generates activities such as slewing the camera to the correct orientation, activating the camera shutter, and transmitting the captured image. The term ‘schedule’ is an association of these specific activities with particular times by satisfying constraints: for example, slewing should be performed before the shutter action. The onboard spacecraft subsystems must execute these time-sensitive activities autonomously to achieve the goals. If none of the subsystems of the spacecraft is capable of executing an activity then cooperation from another spacecraft within the constellation is required to get the activity executed to achieve the overall goal. In addition to serving these payload-oriented functions, planning and scheduling are also necessary to achieve goals generated to ensure safe spacecraft on-orbit operations. The onboard planner assumes a domain model containing an explicit representation of spacecraft subsystems, tasks, goals, and the norms, under which they operate. These norms are a set of flight rules and constraints that are represented in a highlevel syntax.
Some Properties of topological pressure on cellular automata

This paper investigates the ergodicity and the power rule of the topological pressure of a cellular automaton. If a cellular automaton is either leftmost or rightmost premutive (due to the terminology given by Hedlund [Math.~Syst.~Theor.~3, 320-375, 1969]), then it is ergodic with respect to the uniform Bernoulli measure. More than that, the relation of topological pressure between the original cellular automaton and its power rule is expressed in a closed form. As an application, the topological pressure of a linear cellular automaton can be computed explicitly.
The prognostic value of long non coding RNAs in non small cell lung cancer: A meta-analysis

Background Reports have demonstrated the prognostic function of long non-coding RNAS (lncRNAS) in patients with cancer. However, their prognostic functions in non small cell lung cancer (NSCLC) remain controversial. We therefore performed a meta-analysis on six lncRNAs (PVT1, AFAP1-AS1, LINC01133, ANRIL, MEG3 and UCA1) to clarify their prognostic roles in NSCLC. Results Thirty-six studies involving 6267 patients with NSCLC and 34 lncRNAs were included. Of the listed lncRNAs, 20 were shown to negatively affect patients' overall survival while the high expression of 13 lncRNAs indicated better survival outcomes. Materials and Methods The log-rank p value and Kaplan–Meier survival curves of survival outcomes were extracted for hazard ratio (HR) calculation. Survival outcomes were measured by overall survival (OS) and event free survival (EFS) which were then analyzed by calculating pooled hazard ratios. The heterogeneity was detected by Q statistic and I-squared statistic. Conclusions The abnormal expression of lncRNAs may significantly affect NSCLC patients' survival and may serve as a novel predictive factor for prognosis of NSCLC patients.
Negative to positive lymph node ratio is a superior predictor than traditional lymph node status in stage III colorectal cancer

Negative lymph node counts has recently attracted attention as a prognostic indicator in colorectal cancer (CRC). But little is known about prognostic significance of negative to positive lymph node ratio (NPR) in CRC. Our aim was to determine impact of NPR on oncological outcomes in patients with stage III CRC. This retrospective study included 2,256 patients with stage III CRC under curative resection at Fudan university Shanghai cancer center. Kaplan-Meier methods and multivariable Cox regression models were built for the analysis of survival outcomes and risk factors. Accuracy of the NPR was assessed with the Harrell's concordance-index(C-index). X-tile program identified 2.38 or 0.55/2.38 as the optimal cutoff value for NPR to divide the cohort into high/low risk or high/middle/low risk subsets in terms of CRC cause specific survival (CCSS). In a multivariate analysis, NPR was significant independent prognostic factors for CCSS (P<0.05), notably, N classification was not an independently prognostic factor (P>0.05). Further analysis found NPR could give detailed prognostic classification for both N1 and N2 stage (P<0.05). Interestingly, patients in N2+ NPR >2.38 stage have similar survival outcome with N1+ NPR >2.38 stage (χ2=0.030, P=0.863), and better than those at N1+ NPR ≤2.38 and N2+ NPR ≤2.38 stage (P<0.001). The TNNPRM stage was more accurate for predicting CCSS (C-index = 0.659) than current TNM stage system(C-index = 0.628) (P<0.001). Collectively, NPR was an independent prognostic factor for stage III CRC patients, it could provide more accurate prognostic information than the current node stage system.
Cucurbitacin B exerts anti-cancer activities in human multiple myeloma cells in vitro and in vivo by modulating multiple cellular pathways

Cucurbitacin B (CuB), a triterpenoid compound isolated from the stems of Cucumis melo, has long been used to treat hepatitis and hepatoma in China. Although its remarkable anti-cancer activities have been reported, the mechanism by which it achieves this therapeutic activity remains unclear. This study was designed to investigate the molecular mechanisms by which CuB inhibits cancer cell proliferation. Our results indicate that CuB is a novel inhibitor of Aurora A in multiple myeloma (MM) cells, arresting cells in the G2/M phase. CuB also inhibited IL-10-induced STAT3 phosphorylation, synergistically increasing the anti-tumor activity of Adriamycin in vitro. CuB induced dephosphorylation of cofilin, resulting in the loss of mitochondrial membrane potential, release of cytochrome c, and activation of caspase-8. CuB inhibited MM tumor growth in a murine MM model, without host toxicity. In conclusion, these results indicate that CuB interferes with multiple cellular pathways in MM cells. CuB thus represents a promising therapeutic tool for the treatment of MM.
Chemical Composition of Laurencia obtusa Extract and Isolation of a New C15-Acetogenin

A new C15-acetogenin, sagonenyne (20), exhibiting an unusual single tetrahydropyran ring was isolated from an ethyl acetate extract of Laurencia obtusa collected on the Corsican coastline. Its structure was established by detailed NMR spectroscopic analysis, mass spectrometry, and comparison with literature data. Twenty-three known compounds were identified in the same extract by means of column chromatography steps, using a 13C-NMR computer aided method developed in our laboratory. In addition to sesquiterpenes, which represent the main chemical class of this extract, diterpenes, sterols, and C15-acetogenins were identified. The crude extract was submitted to a cytotoxicity assay and was particularly active against THP-1 cells, a human leukemia monocytic cell line.
System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation

Recently, consumer applications have dramatically created the demand for low-cost and compact gyroscopes. Therefore, on the basis of microelectromechanical systems (MEMS) technology, many gyroscopes have been developed and successfully commercialized. A MEMS gyroscope consists of a MEMS device and an electrical circuit for self-oscillation and angular-rate detection. Since the MEMS device and circuit are interactively related, the entire system should be analyzed together to design or test the gyroscope. In this study, a MEMS vibratory gyroscope is analyzed based on the system dynamic modeling; thus, it can be mathematically expressed and integrated into a circuit simulator. A behavioral simulation of the entire system was conducted to prove the self-oscillation and angular-rate detection and to determine the circuit parameters to be optimized. From the simulation, the operating characteristic according to the vacuum pressure and scale factor was obtained, which indicated similar trends compared with those of the experimental results. The simulation method presented in this paper can be generalized to a wide range of MEMS devices.
Termination for direct sums of left-linear complete term rewriting systems

A term rewriting system is called complete if it is confluent and terminating. We prove that completeness of TRSs is a modular property (meaning that it stays preserved under direct sums), provided the constituent TRSs are left-linear. Here, the direct sum R 0 ? R, is the union of TRSs R 0 , R 1 with disjoint signature. The proof hinges crucially upon the (non)deterministic collapsing behavior of terms from the sum TRS.
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods

We consider the problem of estimating the values of a function over $n$ nodes of a $d$-dimensional grid graph (having equal side lengths $n^{1/d}$) from noisy observations. The function is assumed to be smooth, but is allowed to exhibit different amounts of smoothness at different regions in the grid. Such heterogeneity eludes classical measures of smoothness from nonparametric statistics, such as Holder smoothness. Meanwhile, total variation (TV) smoothness classes allow for heterogeneity, but are restrictive in another sense: only constant functions count as perfectly smooth (achieve zero TV). To move past this, we define two new higher-order TV classes, based on two ways of compiling the discrete derivatives of a parameter across the nodes. We relate these two new classes to Holder classes, and derive lower bounds on their minimax errors. We also analyze two naturally associated trend filtering methods; when $d=2$, each is seen to be rate optimal over the appropriate class.
On the representation error in data assimilation

Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology. In addition to a theoretical framework, examples from application areas of satellite data assimilation, ocean reanalysis and atmospheric chemistry data assimilation are provided. Diagnosing representation‐error statistics as well as their use in state‐of‐the‐art data assimilation systems is discussed within a consistent framework.
Investigation of Effects of Friction Stir Welding Parameters on Bending Behavior of AA7075-T6

The influence of tool rotation speed and welding speed on the bending strength of the friction stir welding (FSW) of AA7075-T6 were investigated in this study. The experimental results shown that, the joint is fabricated successfully with a properly good bending strength when the ratio of rotational speed to weld speed is in range from 4.0÷10.0 rev/mm. The grain size rise when the ratio of rotational speed to weld speed or the rotation speed is increased. Most of the bending specimens are fractured when bending angle reaches 90 except the regime of 4.0 rev/min. Furthermore, the temperature and hardness distribution in and around the welded zone were considered and discussed. Keywords—Friction stir welding; bending strength; aluminum alloy AA7075-T6; microstructure; temperature and hardness distribution
Sliding-mode and proportional-resonant based control strategy for three-phase grid-connected LCL-filtered VSI

A sliding-mode and proportional-resonant based control strategy for three-phase grid-connected LCL-filtered voltage source inverter (VSI) is proposed. The generation of three-phase capacitor voltage references is essential in the proposed control strategy. Although the reference capacitor voltage for a specific phase can be generated by adding the measured grid voltage for that phase with the voltage drop on the grid-side inductor caused by the reference grid current, the computation of the voltage drop on the inductor requires a derivative operation which is not preferred in a control algorithm. Therefore, a proportional-resonant (PR) controller is employed to generate the three-phase reference capacitor voltages. The consequence of using PR controller is that the need for using the derivative operation is eliminated. The PR controller offers another advantage regarding the ability to track ac quantities with zero steady-state error. In addition, the equation for the optimum sliding coefficient is derived analytically. Computer simulation results are presented and reported to validate the proposed control approach.
THE EFFECT OF COBALT NAPHTHENATE AND 2-BENZOYLBENZOIC ACID ON UV-DEGRADATION OF LDPE

The effect of cobalt naphthenate and 2-benzoylbenzoic acid on UV-photooxidative degradation of low density polyethylene have been studied. Sheets of these samples were prepared from polyethylene and different concentrations of cobalt naphthenate and 2-benzoylbenzoic acid then these samples were UV-irradiated. Changes in the carbonyl index, tensile strength, elongation at break, crystallinity and density were measured to monitor the degradation. The measurements were done before and after UV-irradiation at every 30-day interval for 90 days. The results show that the UVirradiation affects the rate of degradation of LDPE with increasing the concentration of the cobalt naphthenate and 2-benzoylbenzoic acid. The increasing rate of degradation is more obvious for the increased concentration of cobalt naphthenate and also the time of irradiation, but the rate of degradation is decreased by incorporation of 2benzoylbenzoic acid.
Some Practical Considerations for the Use of Localized Hyperthermia in the Treatment if Cancer

AbstractPractical considerations in the selection and administration of microwave and RF induced hyperthermia in the treatment of various tumors are discussed. A thorough knowledge of the thermal properties of the tumor and its environment is required for the establishment of an effective therapeutic regimen. Examples of clinical observations illustrate the patients’ general tolerance to the therapy and highlight the problems presented by some special cases. Possible ways of avoiding adverse effects during localized microwave induced heating of superficial tumors and RF heating of deep seated tumors are described.
University of Groningen Deep Support Vector Machines for Regression Problems

In this paper we describe a novel extension of the support vector machine, called the deep support vector machine (DSVM). The original SVM has a single layer with kernel functions and is therefore a shallow model. The DSVM can use an arbitrary number of layers, in which lower-level layers contain support vector machines that learn to extract relevant features from the input patterns or from the extracted features of one layer below. The highest level SVM performs the actual prediction using the highest-level extracted features as inputs. The system is trained by a simple gradient ascent learning rule on a min-max formulation of the optimization problem. A two-layer DSVM is compared to the regular SVM on ten regression datasets and the results show that the DSVM outperforms the SVM.
(No) influence of continuous integration on the commit activity in GitHub projects

A core goal of Continuous Integration (CI) is to make small incremental changes to software projects, which are integrated frequently into a mainline repository or branch. This paper presents an empirical study that investigates if developers adjust their commit activity towards the above-mentioned goal after projects start using CI. We analyzed the commit and merge activity in 93 GitHub projects that introduced the hosted CI system Travis CI, but have previously been developed for at least one year before introducing CI. In our analysis, we only found one non-negligible effect, an increased merge ratio, meaning that there were more merging commits in relation to all commits after the projects started using Travis CI. This effect has also been reported in related work. However, we observed the same effect in a random sample of 60 GitHub projects not using CI. Thus, it is unlikely that the effect is caused by the introduction of CI alone. We conclude that: (1) in our sample of projects, the introduction of CI did not lead to major changes in developers' commit activity, and (2) it is important to compare the commit activity to a baseline before attributing an effect to a treatment that may not be the cause for the observed effect.
Autonomous reinforcement of behavioral sequences in neural dynamics

We introduce a dynamic neural algorithm called Dynamic Neural (DN) SARSA(λ) for learning a behavioral sequence from delayed reward. DN-SARSA(λ) combines Dynamic Field Theory models of behavioral sequence representation, classical reinforcement learning, and a computational neuroscience model of working memory, called Item and Order working memory, which serves as an eligibility trace. DN-SARSA(λ) is implemented on both a simulated and real robot that must learn a specific rewarding sequence of elementary behaviors from exploration. Results show DN-SARSA(λ) performs on the level of the discrete SARSA(λ), validating the feasibility of general reinforcement learning without compromising neural dynamics.