Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy analysis of empirical bismuth quadruple therapy, high-dose dual therapy, and resistance gene-based triple therapy as a first-line Helicobacter pylori eradication regimen – An open-label, randomized trial

Abstract This research aimed to evaluate the eradication efficacy, safety, and gastrointestinal symptom relief rates of empirical bismuth quadruple therapy, high-dose dual therapy, and resistance gene-based triple therapy in primary eradication patients in Yangzhou, China. It also investigated the possible factors influencing the success of different Helicobacter pylori eradication regimens. A single-center, prospective, open-label, randomized controlled study was performed from December 2020 and October 2021, in which 255 patients with H. pylori infection were assigned in a 1:1:1 ratio to the three different groups. Our results showed that high-dose dual therapy (91.0%, 71/78) and resistance gene-based triple therapy (94.9%, 75/79) achieved eradication rates and compliance equivalent to those of empirical bismuth quadruple therapy (85.3%, 64/75) in the per-protocol analysis, while high-dose dual therapy had lower rates of adverse events (11.5%, 9/78, P < 0.05), fewer side effects, and greater safety. Most patients’ gastrointestinal discomfort symptoms improved after eradication of H. pylori. Poor compliance (P < 0.05) and antibiotic resistance (P < 0.05) were risk factors for the efficacy of H. pylori eradication. Therefore, the appropriate regimen can be individualized for eradication therapy in clinical practice according to the patient’s resistance and tolerance to the drug.
Ethno-Medicinal and Therapeutic Applications of Natural Anthraquinones: Recent Trends and Advancements

Pharmacological Uses of Certain Anthraquinones Traditional and ethno-medicinal use of plants enforces a holistic approach towards human health by wittily utilizing the synergistic potency of the bioactive compounds. Quinones are unique molecules with several therapeutic properties that lead them as most vital compound in pharmaceutical system. They can easily undergo reduction reaction paving the path for many biological processing. This class of molecules helps in treatment of several chronic ailments. Many of the drugs in Ayurvedic formulations and/or modern medicinal sectors are having one or more types of quinone groups as a major bio-active compound. However these aforementioned properties of quinones make them unique and versatile. The biochemical knowledge of these compounds is necessary to understand their physiological and toxicological properties. Amongst all quinones found naturally, anthraquinones are one of its kinds due to wide spectrum utilization in several drug formulations. In this review a brief detail of six unique yet ethno-botanically and pharmacologically versatile quinone compounds are depicted with their natural resources, structural characterization and ethno-pharmacological activities. The gathered information regarding the above mentioned bio-active compounds would be helpful in identification and isolation of these compounds from a wide range of natural sources with structural characterization and pharmacological potency. These data would be pivotal in their precise identification for further use in both Ayurvedic and modern drug formulation sectors thereby lessening the threat status of the frequently used rare, endangered and threatened plants.
Multiple model adaptive control for switched linear systems: A two‐layer switching strategy

In this paper, the multiple model adaptive control scheme is first introduced into a class of switched systems. A switched multiple model adaptive control scheme is proposed to improve the transient behavior by resetting the controller parameters. Firstly, a finite‐time parameter identification model is presented, which greatly reduces the number of identification models. Secondly, a two‐layer switching strategy is constructed. The outer layer switching mechanism is to ensure the stability of the switched systems. The inner layer switching mechanism is to improve the transient behavior. Then, by using the constructed jumping multiple Lyapunov functions, the proposed adaptive control scheme guarantees that all the closed‐loop system signals remain bounded and the state tracking error converges to a small ball whose radius can be made arbitrarily small by appropriately choosing the design parameter. Finally, a practical example about model reference adaptive control of an electrohydraulic system using multiple models is given to demonstrate the validity of the main results.
CR-Lasso: Robust cellwise regularized sparse regression

Cellwise contamination remains a challenging problem for data scientists, particularly in research fields that require the selection of sparse features. Traditional robust methods may not be feasible nor efficient in dealing with such contaminated datasets. We propose CR-Lasso, a robust Lasso-type cellwise regularization procedure that performs feature selection in the presence of cellwise outliers by minimising a regression loss and cell deviation measure simultaneously. To evaluate the approach, we conduct empirical studies comparing its selection and prediction performance with several sparse regression methods. We show that CR-Lasso is competitive under the settings considered. We illustrate the effectiveness of the proposed method on real data through an analysis of a bone mineral density dataset.
Thermoacoustic Riemann Solver Finite Volume Method With Application To Turbulent Premixed Gas Turbine Combustion Instability

This thesis describes the development, verification, and validation of a three-dimensional time-domain thermoacoustic solver. The purpose of the solver is to predict the frequencies, modeshapes, linear growth rates, and limit cycle amplitudes for combustion instability modes in gas turbine combustion chambers. The treatment of mean density gradients was found to be vital to the success of frequency and modeshape predictions due to the sharp density gradients that occur across deflagration waves. In order to treat mean density gradients with physical fidelity, a non-conservative finite volume method based on the wave propagation approach to the Riemann problem is applied. For modelling unsteady heat release, user input flexibility is maximized using a virtual class hierarchy within the OpenFOAM C++ library. Unsteady heat release based on time lag models are demonstrated. The solver gives accurate solutions compared with analytical methods for one-dimensional cases involving mean density gradients, cross-sectional area changes, uniform mean flow, arbitrary impedance boundary conditions, and unsteady heat release in a one-dimensional Rijke tube. The solver predicted resonant frequencies within 1% of the analytical solution for these verification cases, with the dominant component of the error coming from the finite time interval over which the simulation is performed. The linear growth rates predicted by the solver for the Rijke tube verification were within 5% of the theoretical values, provided that numerical dissipation effects were controlled. Finally, the solver is then used to predict the frequencies and limit cycle amplitudes for two lab scale experiments in which detailed acoustics data are available for comparison. For experiments at the University of Melbourne, an empirical flame describing function was provided. The present simulation code predicted a limit cycle of 0.21 times the mean pressure, which was in close agreement with the estimate of 0.25 from the experimental data. The experiments at Purdue University do not yet have an empirical flame model, so a general vortex-shedding model is proposed on physical grounds. It is shown that the coefficients of the model can be tuned to match the limit cycle amplitude of the 2L mode from the experiment with the same accuracy as the Melbourne case. The code did not predict the excitation of the 4L mode, therefore it is concluded that the vortex-shedding model is not sufficient and must be supplemented with additional heat release models to capture the entirety of the physics for this experiment.
Cutaneous B‐cell lymphomas: 2023 update on diagnosis, risk‐stratification, and management

Approximately one‐fourth of primary cutaneous lymphomas are B‐cell derived and are generally classified into three distinct subgroups: primary cutaneous follicle center lymphoma (PCFCL), primary cutaneous marginal zone lymphoma (PCMZL), and primary cutaneous diffuse large B‐cell lymphoma, leg type (PCDLBCL, LT).
A simple model for self-propulsion of microdroplets in surfactant solution

We propose a simple active hydrodynamic model for the self-propulsion of a liquid droplet suspended in micellar solutions. The self-propulsion of the droplet occurs by spontaneous breaking of isotropic symmetry and is studied using both analytical and numerical methods. The emergence of self-propulsion arises from the slow dissolution of the inner fluid into the outer micellar solution as filled micelles. We propose that the surface generation of filled micelles is the dominant reason for the self-propulsion of the droplet. The flow instability is due to the Marangoni stress generated by the non-uniform distribution of the surfactant molecules on the droplet interface. In our model, the driving parameter of the instability is the excess surfactant concentration above the critical micellar concentration which directly correlates with the experimental observations. We consider various low-order modes of flow instability and show that the first mode becomes unstable through a supercritical bifurcation and is the only mode contributing to the swimming of the droplet. The flow fields around the droplet for these modes and their combined effects are also discussed.
Argumentative Segmentation Enhancement for Legal Summarization

We use the combination of argumentative zoning [1] and a legal argumentative scheme to create legal argumentative segments. Based on the argumentative segmentation, we propose a novel task of classifying argumentative segments of legal case decisions. GPT-3.5 is used to generate summaries based on argumentative segments. In terms of automatic evaluation metrics, our method generates higher quality argumentative summaries while leaving out less relevant context as compared to GPT-4 and non-GPT models.
Considerations for master protocols using external controls.

There has been an increasing use of master protocols in oncology clinical trials because of its efficiency to accelerate cancer drug development and flexibility to accommodate multiple substudies. Depending on the study objective and design, a master protocol trial can be a basket trial, an umbrella trial, a platform trial, or any other form of trials in which multiple investigational products and/or subpopulations are studied under a single protocol. Master protocols can use external data and evidence (e.g. external controls) for treatment effect estimation, which can further improve efficiency of master protocol trials. This paper provides an overview of different types of external controls and their unique features when used in master protocols. Some key considerations in master protocols with external controls are discussed including construction of estimands, assessment of fit-for-use real-world data, and considerations for different types of master protocols. Similarities and differences between regular randomized controlled trials and master protocols when using external controls are discussed. A targeted learning-based causal roadmap is presented which constitutes three key steps: (1) define a target statistical estimand that aligns with the causal estimand for the study objective, (2) use an efficient estimator to estimate the target statistical estimand and its uncertainty, and (3) evaluate the impact of causal assumptions on the study conclusion by performing sensitivity analyses. Two illustrative examples for master protocols using external controls are discussed for their merits and possible improvement in causal effect estimation.
Connectedness of approximate weak efficient sets for the set-vector equilibrium problem

In this paper, a scalarization result of approximate weak efficient solution for a set-vector equilibrium problem (SVEP) is given. With this scalarization result, the connectedness of ε -weak efficient sets for the SVEP is proved under some suitable conditions in real Hausdorff topological vector spaces. The main results presented in this paper improve and generalize some known results in the literature [6,7,10]. 1.Introduction Vector equilibrium problems were first introduced by Blum and Oettli, It is well known that several problems such as vector optimization problems, fixed point problems, vector variational problems, and Nash economic equilibrium problems can be studied as particular cases of vector equilibrium problems. Vector equilibrium problems research mainly includes the existence of the solution, the stability of the solution sets, sensitivity analysis, topological properties of the set of solutions etc. The solution of the connectedness is an important aspect of topological properties, because it provides the possibility of continuously moving from one solution to any other solution. Recently, Lee et al. [2],Cheng [3] have studied the connectedness of weak efficient solutions set for vector variational inequalities in finite dimensional Euclidean space. Gong [4-6] has studied the connectedness of the various solutions set for VEPs in infinite dimension space. Chen et al. [7] studied the connectedness and the compactness of the weak efficient solutions set for set-valued VEPs and the set-valued vector Hartman-Stampacchia variational inequalities in normed linear space. Gong and Yao [8] have studied the connectedness of the set of efficient solutions for generalized systems. Zhong et al. [9] have studied the connectedness and path-connectedness of solutions set for symmetric VEPs. Chen et al. [10] studied the connectedness of approximate solutions set for vector equilibrium problems in Hausdorff topological vector spaces . and Chen Bin et al have studied the connected of the single value of vector equilibrium problems. This paper inspired by the paper[6,7,10],studies the connectedness and compactness of approximate weak efficient sets for the set-valued vector equilibrium problem under different conditions ,thus promoting the conclusion of paper[6,7,10] 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016) © 2016. The authors Published by Atlantis Press 751
Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference

We introduce a synthetic dataset called Sentences Involving Complex Compositional Knowledge (SICCK) and a novel analysis that investigates the performance of Natural Language Inference (NLI) models to understand compositionality in logic. We produce 1,304 sentence pairs by modifying 15 examples from the SICK dataset (Marelli et al., 2014). To this end, we modify the original texts using a set of phrases modifiers that correspond to universal quantifiers, existential quantifiers, negation, and other concept modifiers in Natural Logic (NL) (MacCartney, 2009). We use these phrases to modify the subject, verb, and object parts of the premise and hypothesis. Lastly, we annotate these modified texts with the corresponding entailment labels following NL rules. We conduct a preliminary verification of how well the change in the structural and semantic composition is captured by neural NLI models, in both zero-shot and fine-tuned scenarios. We found that the performance of NLI models under the zero-shot setting is poor, especially for modified sentences with negation and existential quantifiers. After fine-tuning this dataset, we observe that models continue to perform poorly over negation, existential and universal modifiers.
Dynamics of Temporal Difference Reinforcement Learning

Reinforcement learning has been successful across several applications in which agents have to learn to act in environments with sparse feedback. However, despite this empirical success there is still a lack of theoretical understanding of how the parameters of reinforcement learning models and the features used to represent states interact to control the dynamics of learning. In this work, we use concepts from statistical physics, to study the typical case learning curves for temporal difference learning of a value function with linear function approximators. Our theory is derived under a Gaussian equivalence hypothesis where averages over the random trajectories are replaced with temporally correlated Gaussian feature averages and we validate our assumptions on small scale Markov Decision Processes. We find that the stochastic semi-gradient noise due to subsampling the space of possible episodes leads to significant plateaus in the value error, unlike in traditional gradient descent dynamics. We study how learning dynamics and plateaus depend on feature structure, learning rate, discount factor, and reward function. We then analyze how strategies like learning rate annealing and reward shaping can favorably alter learning dynamics and plateaus. To conclude, our work introduces new tools to open a new direction towards developing a theory of learning dynamics in reinforcement learning.
Influence of modulation periods on the tribological behavior of Si/a-C: H multilayer film

A series of Si/a-C: H multilayer films with different modulation periods were fabricated on stainless steel and silicon substrates by radio-frequency magnetron sputtering. The influence of the modulation period on the structure, morphology, mechanical properties and tribological behaviors in different environments (air, simulated acid rain, and NaCl solution) was investigated. The results show that the content of the sp2 hybrid carbon, surface roughness and hardness of the multilayer film increased firstly and then decreased with the decreased modulation period. Furthermore, the combination of the sublayer agrees well with the formation of the SiC crystal at the interface. Interestingly, the films show quite substantially different tribological properties in various test environments. The lowest friction coefficient is 0.2 for the S1 film in air. However, the lowest friction coefficient can reach 0.13 in solution. Importantly, the tribological behavior of the multilayer film is mainly determined by its hardness, as well as surface roughness in air while it is closely related with modulation period and interface structure in solution.
Hybrid Synchronization of n-scroll Chaotic Chua Circuits using Adaptive Backstepping Control Design with Recursive Feedback

In this paper, the hybrid synchronization is investigated for n-scroll chaotic Chua circuit (Wallace et al. (2001)) using adaptive backstepping control design based on recursive feedback control. Our theorems on hybrid synchronization for n-scroll chaotic Chua circuits are established using Lyapunov stability theory. The adaptive backstepping control links the choice of Lyapunov function with the design of a controller and guarantees global stability performance of strict-feedback chaotic systems. The adaptive backstepping control maintains the parameter vector at a predetermined desired value. The adaptive backstepping control method is effective and convenient to synchronize and estimate the parameters of the chaotic systems. Mainly, this technique gives the flexibility to construct a control law and estimate the parameter values. Numerical simulations are also given to illustrate and validate the synchronization results derived in this paper.
SHAP@k: Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features

The SHAP framework provides a principled method to explain the predictions of a model by computing feature importance. Motivated by applications in finance, we introduce the Top-k Identification Problem (TkIP) (and its ordered variant TkIP- O), where the objective is to identify the subset (or ordered subset for TkIP-O) of k features corresponding to the highest SHAP values with PAC guarantees. While any sampling-based method that estimates SHAP values (such as KernelSHAP and SamplingSHAP) can be trivially adapted to solve TkIP, doing so is highly sample inefficient. Instead, we leverage the connection between SHAP values and multi-armed bandits (MAB) to show that both TkIP and TkIP-O can be reduced to variants of problems in MAB literature. This reduction allows us to use insights from the MAB literature to develop sample-efficient variants of KernelSHAP and SamplingSHAP. We propose KernelSHAP@k and SamplingSHAP@k for solving TkIP; along with KernelSHAP-O and SamplingSHAP-O to solve the ordering problem in TkIP-O. We perform extensive experiments using several credit-related datasets to show that our methods offer significant improvements of up to 40× in sample efficiency and 39× in runtime.
New class of entropy-power-based uncertainty relations

We use the concept of entropy power to introduce a new one-parameter class of information-theoretic uncertainty relations. This class constitutes an infinite hierarchy of uncertainty relations, which allows to determine the shape of the underlying information-distribution function by measuring the relevant entropy powers. The efficiency of such uncertainty relations in quantum mechanics is illustrated with two examples: superpositions of two squeezed states and the Lévy-type heavy-tailed wave function. Improvement over both the variance-based and Shannon entropy based uncertainty relations is demonstrated in both these cases.
Complexity results for matching cut problems in graphs without long induced paths

In a graph, a (perfect) matching cut is an edge cut that is a (perfect) matching. Matching Cut (MC), respectively, Perfect Matching Cut (PMC), is the problem of deciding whether a given graph has a matching cut, respectively, a perfect matching cut. The Disconnected Perfect Matching problem (DPM) is to decide if a graph has a perfect matching that contains a matching cut. Solving an open problem recently posed in [Lucke, Paulusma, Ries (ISAAC 2022), and Feghali, Lucke, Paulusma, Ries (arXiv:2212.12317)], we show that PMC is NP-complete in graphs without induced 14-vertex path $P_{14}$. Our reduction also works simultaneously for MC and DPM, improving the previous hardness results of MC on $P_{19}$-free graphs and of DPM on $P_{23}$-free graphs to $P_{14}$-free graphs for both problems. Actually, we prove a slightly stronger result: within $P_{14}$-free graphs, it is hard to distinguish between (i) those without matching cuts and those in which every matching cut is a perfect matching cut, (ii) those without perfect matching cuts and those in which every matching cut is a perfect matching cut, and (iii) those without disconnected perfect matchings and those in which every matching cut is a perfect matching cut. Moreover, assuming the Exponential Time Hypothesis, none of these problems can be solved in time $2^{o(n)}$ for $n$-vertex $P_{14}$-free input graphs. We also consider the problems in graphs without long induced cycles. It is known that MC is polynomially solvable in graphs without induced cycles of length at least 5 [Moshi (JGT 1989)]. We point out that the same holds for DPM.