Miracle-dz/UniFAR-FTUs huggingface dataset:
Survival Outcomes of Patients with Follicular Lymphoma after Relapse or Progression: A Single-Center Real-World Data Analysis

Background Follicular lymphoma (FL) is considered incurable because remission and relapse are common. Although various salvage treatment options have been proposed, there is no consensus on treatment strategy for FL patients who failed primary treatment. Methods This single-center study analyzed postevent overall survival (OS) among 70 patients who experienced relapse or progression after rituximab-containing immunochemotherapy according to type of salvage treatment and nature of relapse or progression. Results Of 70 patients, 42 experienced progression of disease within 24 months (POD24), and six showed disease progression during first-line treatment. Large-cell transformation was found in nine patients with POD24. At the median follow-up of 104 months (95% CI: 90-118 months), POD24 patients experienced significantly worse OS than patients without POD24, and postevent OS was not satisfactory after conventional salvage chemotherapy because the majority of patients relapsed or progressed. However, autologous stem cell transplantation (ASCT) after the first relapse resulted in survival prolongation in patients with POD24. Half of the patients (34/67, 51%) participated in at least one clinical trial during treatment after first relapse, and patients participating in at least one clinical trial irrespective of line of treatment tended to experience better survival. Conclusions Relapsed or refractory FL patients showed various clinical courses and treatment outcomes according to relapse or progression. Consolidation treatment with ASCT and active participation to clinical trials might prolong survival duration, especially in POD24 cases.
Improving Winter Wheat Photosynthesis, Nitrogen Use Efficiency, and Yield by Optimizing Nitrogen Fertilization

Wheat is the third most producing crop in China after maize and rice. In order to enhance the nitrogen use efficiency (NUE) and grain yield of winter wheat, a two-year field experiment was conducted to investigate the effect of different nitrogen ratios and doses at various development stages of winter wheat (Triticum aestivum L.). A total of five N doses (0, N75, N150, N225, and N300 kg ha−1) as main plots and two N ratios were applied in split doses (50%:50% and 60%:40%, referring to 50% at sowing time and 50% at jointing stage, 50% at sowing time + 50% at flowering stage, 50% at sowing time + 50% at grain filling stage, and 60% + 40% N ratio applied as a 60% at sowing time and 40% at jointing stage, 60% at sowing time and 40% at flowering stage, and 60% at sowing time and 40% at grain filling stage in subplots). The results of this study revealed that a nitrogen dose of 225 kg ha−1 significantly augmented the plant height by 27% and above ground biomass (ABG) by 24% at the grain filling stage, and the leaf area was enhanced by 149% at the flowering stage under 60 + 40% ratios. Furthermore, the N225 kg ha−1 significantly prompted the photosynthetic rate by 47% at the jointing and flowering stages followed by grain filling stage compared to the control. The correlation analysis exhibited the positive relationship between nitrogen uptake and nitrogen content, chlorophyll, and dry biomass, revealing that NUE enhanced and ultimately increased the winter wheat yield. In conclusion, our results depicted that optimizing the nitrogen dose (N225 kg/ha−1) with a 60% + 40% ratio at jointing stage increased the grain yield and nitrogen utilization rate.
External Force Estimation of the Industrial Robot Based on the Error Probability Model and SWVAKF

This study proposes an external force estimation method based on the error probability model and a sliding window variational adaptive Kalman filter (SWVAKF) for the problem of industrial robot external force estimation. A probability model with a normal distribution was provided, in which the covariance was linearly related to the joint velocity to address the uncertainty in the estimation error of the friction model. A normal distribution probability model was presented to address the time-varying characteristics of the contact external force when the robot interacts with the environment, in which the covariance of the derivative term of the external force was linearly related to the estimated external force. The robot interaction process was dynamically modeled using generalized momentum and external force as state variables, friction estimation deviation and external force derivative term as random interference, and generalized momentum with normally distributed noise as the measurement output. The parameters of the probability model of random interference items were determined by analyzing the experimental data of system identification, and the covariance related to joint velocity and external force was obtained. A set of adaptive scale factors related to the joint velocity and estimated force change rate when the robot interacts with the environment is proposed, and then the error covariance estimated based on the error probability model and the SWVAKF algorithm is fused by the adaptive scale factor, and a covariance of friction deviation and external force derivative term in the robot interaction process and an external force estimation method were provided. Experimental results reveal that the proposed method reduces the root-mean-square (RMS) error by 17.07% compared to the standard Kalman external force estimation method and has a better external force estimation effect.
Partitioned Methods for Multifield Problems: Exercise 1: Iterative Methods for Linear Systems

Convergence Rates Download the Jacobi and SOR implementations from the “Semesterapparat”. Demonstrate their convergence rates by plotting the relative error ||x − x||2 ||x||2 over the number of performed iterations (the reference solution x shall be got by a Gaussian elimination). For the SOR do the plotting for four reasonable values of ω and confirm quantitatively the results of the spectral radius computations.
Adaptive integral terminal super‐twisting with finite‐time convergence for an unmanned surface vehicle under disturbances

This article proposes a robust trajectory tracking controller for underactuated unmanned surface vehicles under disturbances. An adaptive integral terminal super‐twisting algorithm is designed for guidance and control, following a cascade strategy. The properties of such algorithm include practical finite‐time (PFT) convergence, robustness against bounded disturbances/uncertainties with unknown boundaries, and chattering attenuation via adaptive gains. A stability analysis is addressed to prove the PFT stability of the overall system. Moreover, the vehicle is subject to wind, waves, and water currents disturbance models to verify the robustness with numerical simulations. Furthermore, real‐time experiments under an extra payload and environmental perturbations with unknown boundaries validate the performance with a prototype. Finally, a comparison against the adaptive super‐twisting algorithm with conventional sliding surface further demonstrates the advantages of the proposed scheme.
On the use of Machine Learning Approaches for the Early Classification in Network Intrusion Detection

Current intrusion detection techniques cannot keep up with the increasing amount and complexity of cyber attacks. In fact, most of the traffic is encrypted and does not allow to apply deep packet inspection approaches. In recent years, Machine Learning techniques have been proposed for post-mortem detection of network attacks, and many datasets have been shared by research groups and organizations for training and validation. Differently from the vast related literature, in this paper we propose an early classification approach conducted on CSE-CIC-IDS2018 dataset, which contains both benign and malicious traffic, for the detection of malicious attacks before they could damage an organization. To this aim, we investigated a different set of features, and the sensitivity of performance of five classification algorithms to the number of observed packets. Results show that ML approaches relying on ten packets provide satisfactory results.
On the world cognizability

The paper gives a few examples of the phenomena that will never be understood by the mankind. The first example is the physics at the scales of $\sim 10^{-33}$ cm where the gravitation interaction becomes strong, sales at the very beginning of the Big Bang. It argues that the mankind will never establish the laws that controls the events at these scales. Further, it is supposed that the time dependence of the entropy, which determine the direction of the time arrow, originates at the same time scale and, thus, the nature of the time arrow will be never established either. Finally, I conjecture that the brain cells are controlled by quantum computer with the very large (or even infinite) number of degenerate states. An external observation destroys this degeneracy, leading to impossibility to understand the mechanism of the conscience.
Branching law for finite subgroups of 3 ℂ$\mathbf {SL}_3\mathbb {C}$ and McKay correspondence

Given $\Gamma$ a finite subgroup of $\mathbf{SL}_3\mathbb{C}$, we determine how an arbitrary finite dimensional irreducible representation of $\mathbf{SL}_3\mathbb{C}$ decomposes under the action of $\Gamma$. To the subgroup $\Gamma$ we attach a generalized Cartan matrix $C_\Gamma$. Then, inspired by B. Kostant, we decompose the Coxeter element of the Kac-Moody algebra attached to $C_\Gamma$ as a product of reflections of a special form, thereby suggesting an algebraic form for the McKay correspondence in dimension 3.
A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates

We develop a novel unified randomized block-coordinate primal-dual algorithm to solve a class of nonsmooth constrained convex optimization problems, which covers different existing variants and model settings from the literature. We prove that our algorithm achieves and convergence rates in two cases: merely convexity and strong convexity, respectively, where k is the iteration counter and n is the number of block-coordinates. These rates are known to be optimal (up to a constant factor) when n = 1. Our convergence rates are obtained through three criteria: primal objective residual and primal feasibility violation, dual objective residual, and primal-dual expected gap. Moreover, our rates for the primal problem are on the last-iterate sequence. Our dual convergence guarantee requires additionally a Lipschitz continuity assumption. We specify our algorithm to handle two important special cases, where our rates are still applied. Finally, we verify our algorithm on two well-studied numerical examples and compare it with two existing methods. Our results show that the proposed method has encouraging performance on different experiments.
Study of the winter 2005 Antarctica polar vortex

During winter and springtime, the flow above Antarctica at high altitude (upper troposphere and stratosphere) is dominated by the presence of a vortex centered above the continent. It lasts typically from August to November. This vortex is characterized by a strong cyclonic jet centered above the polar high. In a recent study of our group (Hagelin et al. 2008) of four different sites in the Antarctic internal plateau (South Pole, Dome C, Dome A and Dome F), it was made the hypothesis that the wind speed strength in the upper atmosphere should be related to the distance of the site to the center of the Antarctic polar vortex. This high altitude wind is very important from an astronomical point of view since it might trigger the onset of the optical turbulence and strongly affect other optical turbulence parameters. What we are interested in here is to localize the position of the minimum value of the wind speed at high altitude in order to confirm the hypothesis of Hagelin et al. (2008).
Review and Analysis of Electro-Magnetohydrodynamic Flow and Heat Transport in Microchannels

This paper aims to develop a review of the electrokinetic flow in microchannels. Thermal characteristics of electrokinetic phenomena in microchannels based on the Poisson–Boltzmann equation are presented rigorously by considering the Debye–Hückel approximation at a low zeta potential. Several researchers developed new mathematical models for high electrical potential with the electrical double layer (EDL). A literature survey was conducted to determine the velocity, temperature, Nusselt number, and volumetric flow rate by several analytical, numerical, and combinations along with different parameters. The momentum and energy equations govern these parameters with the influences of electric, magnetic, or both fields at various preconditions. The primary focus of this study is to summarize the literature rigorously on outcomes of electrokinetically driven flow in microchannels from the beginning to the present. The possible future scope of work highlights developing new mathematical analyses. This study also discusses the heat transport behavior of the electroosmotically driven flow in microchannels in view of no-slip, first-order slip, and second-order slip at the boundaries for the velocity distribution and no-jump, first-order thermal-slip, and second-order thermal-slip for the thermal response under maintaining a uniform wall-heat flux. Appropriate conditions are conferred elaborately to determine the velocity, temperature, and heat transport in the microchannel flow with the imposition of the pressure, electric, and magnetic forces. The effects of heat transfer on viscous dissipation, Joule heating, and thermal radiation envisage an advanced study for the fluid flow in microchannels. Finally, analytical steps highlighting different design aspects would help better understand the microchannel flow’s essential fundamentals in a single document. They enhance the knowledge of forthcoming developmental issues to promote the needed study area.
A novel stochastic vibration-based algorithm for electromagnetic leakage detection

In the safety detection of the current electromagnetic leakage of electronic equipment, weak leakage signal frequencies are easily missed, involving other problems. This paper presents a new algorithm connecting with stochastic vibrating electromagnetic leakage detection, which uses the principle of stochastic vibration to enhance the leak signal strength and reduce the noise strength by migrating the noise signal energy from the original signal to the leak signal, thus solving the problem arising from leak detection of spectrum. The algorithm is implemented by frequency shifting, a new genetic algorithm and segmented biostability to overcome the shortcomings in the traditional bistatic random algorithm. This paper demonstrates the effectiveness of the method in electromagnetic leakage detection through experiments and simulations.
The mediating role of work stress in the relationship between work engagement and turnover intention

This study investigated the relationship between work engagement and turnover intention in the context of health sector employees and the mediating role of work stress in the relationship between these two variables. A questionnaire was applied to 350 healthcare workers in Erzincan, Turkey, to obtain the data. Analysis of Moment Structures (AMOS) and Statistical Package for the Social Sciences (SPSS) package applications was used to analyse the data obtained in the research. The study concluded that work engagement was significantly and negatively related to work stress and turnover intention, and work stress was significantly and positively related to turnover intention. Furthermore, the study determined that work stress has a mediating role in the relationship between work engagement and turnover intention.
Measurement of the lifetimes of B meson mass eigenstates

In this dissertation, we present the results of the average lifetime measurements in B J/4K +, Bd -+ J/K* '°, and B J/¢ decays, as well as the results of a time-dependent angular analysis of Bd J/K* '° and B J/q decays. The time-dependent angular analysis of Bs -+ J/V)X allows the extraction of separate lifetimes for the mass eigenstates, B} and B', in the BS-B system. The two life8 ' times are combined to extract the width difference, Ar FL FH = 1/rBL 1/TBH, between the two eigenstates. This quantity is extremely useful for over-constraining the Unitarity Triangle and thereby inferring if CP violation in the quark sector is entirely explained within the Standard Model. From 258 ± 15 pb-1 of data collected by CDF up to February 13, 2004, we obtain a wealth of results, most importantly: TB. (1.659 0.033 +0008) Ps ~~~~~~-0.008 p TBd (1.549 0.051 +0.007) ps -d -0.008/ TB =(1.05 +6 0.16 02)ps -0.13 TBH = (2.07 +0.58 ± 0.03)ps -0.46 Ar = (0.46 ± 0.18 0.01)ps' Several f the results obtained here are currently the best of their kind, and in some cases they are unique measurements. We devote special attention to these, in particular Alt. Thesis Supervisor: Christoph M. E. Paus Title: Associate Professor
Singularity-Free Collapse through Local Inflation

In common relativistic models of gravitational collapse, the interior experiences a bubble-like local inflation, allowing radii to diverge rather than converge toward a singularity. This proves a conjecture of Shatskiy. At the horizon, the solution locally resembles the neck of a wormhole from the exterior to the interior. The implied limiting curvature is at the horizon not the Planck level.
Optical Properties of Graphene-like Two Dimensional Silicene

We study optical properties of two dimensional silicene using density functional theory based calculations. Our results on optical response property calculations show that they strongly depend on direction of polarization of light, hence the optical absorption spectra are different for light polarized parallel and perpendicular to plane of silicence. The optical absorption spectra of silicene possess two major peaks: (i) a sharp peak at 1.74 eV due to transition from pi to pi* states and (ii) a broad peak in range of 4-10 eV due to excitation of sigma states to conduction bands. We also investigate the effect of external influences such as (a) transverse static electric field and (b) doping of hydrogen atoms (hydrogenation) on optical properties of silicene. Firstly, with electric field, it is observed that band gap can be opened up in silicene at Fermi level by breaking the inversion symmetry. We see appreciable changes in optical absorption due to band gap opening. Secondly, hydrogenation in silicene strongly modifies the hybridization and our geometry analysis indicates that the hybridization in silicene goes from mixture of sp^2 + sp^3 to purely sp^3. Therefore, there is no pi electron present in the system. Consequently, the electronic structure and optical absorption spectra of silicene get modified and it undergoes a transition from semi-metal to semiconductor due to hydrogenation.
The Interaction Effect of Laser Irradiation and 6-Benzylaminopurine Improves the Chemical Composition and Biological Activities of Linseed (Linum usitatissimum) Sprouts

Simple Summary Recently, novel food processing technologies have been used for the quality improvement of fruits and vegetables. Laser light application and 6-benzylaminopurine (BAP) priming are known to be promising approaches to improve the nutritional values of plants. In this study, we carried out novel food processing technologies using laser light and 6-benzylaminopurine (BAP) priming for the quality improvement of linseed sprouts. The combined treatments improved the accumulation of minerals, vitamins, and amino acids and enhanced the N-metabolism. Moreover, the application of both treatments combined enhanced the antioxidant capacity by increasing fatty acids, phenols, and flavonoids, as well as antimicrobial activity. Abstract Even though laser light (LL) and 6-benzylaminopurine (BAP) priming are well-known as promising strategies for increasing the growth and nutritional value of several plants, no previous studies have investigated their synergistic effect. Herein, we investigated the effects of laser light, 6-benzylaminopurine (BAP) priming, and combined LL-BAP treatment on the nutritional value, chemical composition, and the biological activity of Linum usitatissimum sprouts. The fresh weight, leaf pigments, primary and secondary metabolites, enzymes, and antimicrobial activities were determined. A substantial enhancement was observed in the growth characteristics and leaf pigments of laser-irradiated and BAP-primed sprouts. Furthermore, the combined treatments improved the accumulation of minerals, vitamins, and amino acids, and also enhanced the N-metabolism more than LL or BAP alone. Furthermore, the combined priming boosted the antioxidant capacity by increasing the contents of fatty acids, phenols, and flavonoids. Antimicrobial activity and the highest increase in bioactive compounds were recorded in linseed sprouts simultaneously treated with LL and BAP. This work suggests that priming L. usitatissimum sprouts with laser light and BAP is a promising approach that can improve the nutritional value and health-promoting impacts of L. usitatissimum sprouts.
MULTI-INSTRUMENT X-RAY OBSERVATIONS OF THERMONUCLEAR BURSTS WITH SHORT RECURRENCE TIMES

Type I X-ray bursts from low-mass X-ray binaries result from a thermonuclear runaway in the material accreted onto the neutron star. Although typical recurrence times are a few hours, consistent with theoretical ignition model predictions, there are also observations of bursts occurring as promptly as 10 minutes or less after the previous event. We present a comprehensive assessment of this phenomenon using a catalog of 3387 bursts observed with the BeppoSAX/WFCs and RXTE/PCA X-ray instruments. This catalog contains 136 bursts with recurrence times of less than 1 hr, that come in multiples of up to four events, from 15 sources. Short recurrence times are not observed from the so-called ultra-compact binaries, indicating that hydrogen-burning processes play a crucial role. As far as the neutron star spin frequency is known, these sources all spin fast at over 500 Hz; the rotationally induced mixing may explain burst recurrence times of the order of 10 minutes. Short recurrence time bursts generally occur at all mass accretion rates where normal bursts are observed, but for individual sources the short recurrence times may be restricted to a smaller interval of accretion rate. The fraction of such bursts is roughly 30%. We also report the shortest known recurrence time of 3.8 minutes.
Influence of Clouds on UV Irradiance at Ground Level and Backscattered Exittance

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Introduction to the special issue on the fusion of domain knowledge with data for decision support

Statistics and machine learning are data-oriented tasks in which domain models are induced from data. The bulk of research in these fields concentrates on inducing models from data archived in computer databases; however, for many problem domains, human expertise forms an essential part of the corpus of knowledge needed to construct models of the domain. The discipline of knowledge engineering has focused on encoding the knowledge of experts in a form that can be encoded into computational models of a domain. At present, knowledge engineering and machine learning remain largely separate disciplines, yet, in many fields of endeavor, substantial human expertise exists alongside data archives. When both data and domain knowledge are available, how can these two resources effectively be combined to construct decision support systems?