Miracle-dz/UniFAR-FTUs huggingface dataset:
Ideational Coherence Reconstruction in E-C Translation Teaching—A Sample Study on Xu Chi’s Version “Walden”

This paper is a tentative endeavor to apply a new functional discourse analysis mode to translation teaching and study, intending to find out what kind of coherence features the translator represents in the version, and how those coherence features as well as the significance of the coherence reconstruction are reconstructed by analyzing the translation sample from the levels of ideational coherence. The significance of this paper lies in that it may shed a new light on the application of discourse coherence to translation teaching and study.
A Truth Serum for Large-Scale Evaluations

A major challenge in obtaining large-scale evaluations, e.g., product or service reviews on online platforms, labeling images, grading in online courses, etc., is that of eliciting honest responses from agents in the absence of verifiability. We propose a new reward mechanism with strong incentive properties applicable in a wide variety of such settings. This mechanism has a simple and intuitive output agreement structure: an agent gets a reward only if her response for an evaluation matches that of her peer. But instead of the reward being the same across different answers, it is inversely proportional to a popularity index of each answer. This index is a second order population statistic that captures how frequently two agents performing the same evaluation agree on the particular answer. Rare agreements thus earn a higher reward than agreements that are relatively more common. In the regime where there are a large number of evaluation tasks, we show that truthful behavior is a strict Bayes-Nash equilibrium of the game induced by the mechanism. Further, we show that the truthful equilibrium is approximately optimal in terms of expected payoffs to the agents across all symmetric equilibria, where the approximation error vanishes in the number of evaluation tasks. Moreover, under a mild condition on strategy space, we show that any symmetric equilibrium that gives a higher expected payoff than the truthful equilibrium must be close to being fully informative if the number of evaluations is large. These last two results are driven by a new notion of an agreement measure that is shown to be monotonic in information loss. This notion and its properties are of independent interest.
Tournament limits: Degree distributions, score functions and self-converseness

Motivated by known results for finite tournaments, we define and study the score functions of tournament kernels and the degree distributions of tournament limits. Our main theorem completely characterises those distributions that appear as the degree distribution of some tournament limit and those functions that appear as the score function of some tournament kernel. We also show that only the uniform distribution can be realised as the outdegree distribution of a unique tournament limit. Finally we define self-converse tournament limits and kernels and characterise their degree distributions and score functions.
SKIN CANCER EXPERT SYSTEM USING FRACTAL DIMENSION

There are many characteristics that differentiate normal moles (nevi) from melanomas. Fractal measures like fractal dimension and lacunarity are widely-used for the analysis of textures, or any images with self-similar content. However, all the existing approaches are defined for one dimensional signals or binary images with extension to grey-scale images. We proposed a novel approach, in combination to the probabilistic algorithm for the computation of the fractal dimension and lacunarity. Our method was used the boundary irregularity, which can be quantified using fractal dimension. In this work, fractal dimension of normal moles and melanoma was computed using the box counting method. We used this approach for the evaluation of the skin lesions, in case of psoriasis. The efficacy of these new descriptors was tested on a data set of 800 skin lesions, composed by 85 melanomas and nevi. The result showed the high accuracy of the developed GUI for melanoma detection. Keywords- melanoma; skin cancer; fractal; cancer detection; fractal dimension.
An Efficient Fake Biometric Detection Technique Exploiting Structural Similarity Index

In this paper, we propose a novel image quality assessment (IQA) based on an Improved Structural Similarity (ISSIM) which considers the spatial distributions of image structures. The existing structural similarity (SSIM) metric, which deals with structure loss based on statistical moments, i.e., the mean and variance, represents mainly the luminance change in pixels rather than describing the spatial distribution. However, the human visual system (HVS) is highly adapted to extract structures with regular spatial distributions. In the proposed document, we work with a self-comparision based procedure to illustrate the spatial distribution of image structures. Then, combining with the statistical characters, we improve the structural similarity based quality metric. Investigational outcome exhibit that IQA metric is more reliable with human sensitivity than SSIM metric. The investigative outcomes obtained from publicly available data sets of fingerprint, iris, and 2D face, illustrate that the proposed method is highly efficient compared with other modern approaches and that the analysis of the general image quality of real biometric data sets reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.
Magnetohydrodynamic and thermal analysis of PbLi flows in poloidal channels with flow channel insert for the EU-DCLL blanket

Magnetohydrodynamic (MHD) processes are known to be critically important for the dual coolant lithium lead (DCLL) breeding blanket (BB) concept. In order to minimize the MHD pressure drop in the European DCLL blanket design, the liquid metal breeder (PbLi) is decoupled electrically from the ferritic–martensitic structure (EUROFER) using insulating ceramic-based flow channel inserts (FCIs). The impact of the FCI on the velocity profile and the pressure drop in the DCLL front poloidal channels is studied. Two-dimensional momentum and induction equations for fully developed flows are solved numerically using the ANSYS-Fluent simulation platform under DCLL-relevant conditions (, ). Velocity and pressure drop in the PbLi flows have been computed first for a channel without FCI and then for three possible alumina-based FCI design: two types of sandwich FCI and one naked FCI. In order to analyze thermal effects in the blanket, the obtained velocity profiles are used as inputs to solve the 3D energy equation. The computations of the temperature distribution in the DCLL poloidal front channel with a prototypical exponentially varying heat generation profile are obtained using convective boundary conditions. Results show the effect of the FCI and MHD phenomena on heat transfer.
A review: Morphological, physiological, biochemical and molecular plant responses to water deficit stress

--------------------------------------------------------ABSTRACT------------------------------------------------------------In the conditions of changing climate, plants are continuously subject to several biotic and abiotic stresses. Among these stresses, drought is one of the most severe abiotic stress which threats crops production and yield. Crops demonstrate various morphological, physiological, biochemical and molecular responses under water stress. This review describes some aspects of drought induced changes in morphological, physiological, biochemical and molecular changes in plants. Drought triggers a wide variety of plant responses, ranging from cellular metabolism to changes in growth development including roots, shoots and final yield. Moreover, understanding the biochemical and molecular responses to drought is essential for perception of plant resistance mechanisms to water-limited conditions. The sections of this review deal with plant responses including root growth, transpiration, photosynthesis, phenotypical flexibility, accumulation of solutes and expression of some genes and proteins for improving the tolerance to the drought stress.
A combined scheme of generalized finite difference method and Krylov deferred correction technique for highly accurate solution of transient heat conduction problems

This paper presents a numerical framework for the highly accurate solutions of transient heat conduction problems. The numerical framework discretizes the temporal direction of the problems by introducing the Krylov deferred correction (KDC) approach, which is arbitrarily high order of accuracy while remaining the computational complexity same as in the time‐marching of first‐order methods. The discretization by employing the KDC method yields a boundary value problem of the inhomogeneous modified Helmholtz equation at each time step. The meshless generalized finite difference method (GFDM) or meshless finite difference method (MFDM), a meshless method, is then applied to the solution of resulting boundary value problems at each time step. Six numerical experiments in one‐, two‐, and three‐dimensional cases show that the proposed hybrid KDC‐GFDM scheme allows big time step size for a long‐time dynamic simulation and has a great potential for the problems with complex boundaries. In addition, some comparisons are also presented between the present method, the COMSOL software, and the GFDM with implicit Euler method.
Fourier series of functions involving higher-order ordered Bell polynomials

Abstract In 1859, Cayley introduced the ordered Bell numbers which have been used in many problems in number theory and enumerative combinatorics. The ordered Bell polynomials were defined as a natural companion to the ordered Bell numbers (also known as the preferred arrangement numbers). In this paper, we study Fourier series of functions related to higher-order ordered Bell polynomials and derive their Fourier series expansions. In addition, we express each of them in terms of Bernoulli functions.
A slab waveguide source for discontinuous Galerkin time-domain methods

An essential device in opto-electronics is the optical waveguide. In the following we present a way to incorporate a waveguide field source into numerical time-domain simulations via the total field/scattered field technique. In particular, we develop a method by which we introduce a Gaussian light-pulse with the real eigenmodes of a slab waveguide into the nodal discontinuous Galerkin time-domain scheme.
Turbulent heat transport in TOKAM3X edge plasma simulations

The recent version of the 3D fluid code TOKAM3X, including self‐consistent variation of both electron and ion temperature, is used to investigate the properties of energy turbulent structures and heat transport. We also make a comparison with the results of the isothermal equivalent simulation. The studied regime is an L‐mode‐like regime where both particle and heat transport are dominated by turbulence with Γturb/Γtot > 80% and the turbulence features are found to be similar in isothermal and anisothermal models. However, the presence of a significant shear at the separatrix in the anisothermal version modifies the penetration length of turbulent structures into the scrape‐off layer, and seems to trigger the appearance of a sharper gradient at the separatrix, reminiscent of the narrow feature observed in the experiment.
Adaptive Fuzzy Fault-Tolerant Tracking Control of Uncertain Nonlinear Time-Varying Delay Systems

This paper investigates the problem of fuzzy-approximation-based adaptive fault-tolerant (FT) tracking control for uncertain nonlinear time-varying delay systems with nonaffine nonlinear faults. Compared with the existing results, the proposed control scheme avoids the use of the Lyapunov–Krasovskii functional, which relaxes the restriction on the derivative of unknown time-varying delay ( ${\dot \tau (t)< 1}$ ). By utilizing the finite covering lemma and fuzzy logic systems (FLSs), the considered time-varying delay system is transformed into novel switched nonlinear system with known constant delays. In addition, the nonaffine nonlinear faults make the control design more complicated. To overcome the difficulty, the fault function is decoupled by utilizing the mean-value theorem. In the design procedure, the problem of unknown control gain and control direction is produced. To solve this problem, the Nussbaum-type function is introduced. Combined backstepping technique with FLSs, an adaptive approximation FT tracking control scheme is proposed. Finally, the developed control method ensures that all the closed-loop signals are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin. A simulation example is presented to illustrate the effectiveness of the developed control scheme.
Subspace clustering algorithms for mineral mapping

The application of drill core hyperspectral data in exploration campaigns is receiving great interest to obtain a general overview of a mineral deposit. However, the main approach to the investigation of such data is by visual interpretation, which is subjective and time consuming. To address this issue, recently, the use of machine learning techniques is proposed for the analysis of this data. For drill core samples that for which only very little prior knowledge is often available, applying classification algorithms which are supervised learning methods is very challenging. In this paper, we suggest to use clustering (unsupervised) methods for mineral mapping, which are similar to classification but no predefined class labels are needed. To handle mapping of the very highly mixed pixels in drill core hyperspectral data, we propose to use advance subspace clustering methods, in which pixels are assumed to lie in a union of low-dimensional subspaces. We conduct a comparative study and evaluate the performance of two well-known subspace clustering methods, i.e., sparse subspace clustering (SSC) and low rank representation (LRR). For the experiments, we acquired VNIR-SWIR hyperspectral data and applied scanning electron microscopy based Mineral Liberation Analysis (MLA) for two drill core samples. MLA is a high resolution imaging technique that allows detailed mineral charactrisition. We use the high-resolution MLA image as a reference to analyse the clustering results. Qualitative analysis of the obtained clustering maps indicate that the subspace clustering methods can accurately map the available minerals in the drill core hyperspectral data, especially in comparison to the traditional k-means clustering method.
Erstdiagnostik - Belastungs-EKG: Zwischen Qualität und Evidenz

Die bildgebende Diagnostik in der Kardiologie hat mit Echokardiographie, CT-Diagnostik und Kernspintechnik in den letzten Jahren große Fortschritte gemacht. Vor allem die Belastungsun-tersuchung mittels Ultraschall ist zum neuen Standard geworden. Dennoch hat sich in der Praxis das Belastungs-EKG als Verfahren der Erstdiagnostik behauptet. Durch Verbesserung der Qualität und unter Beachtung der Evidenz lassen sich die Gütekriterien, insbesondere der Vor-hersagegenauigkeit, deutlich verbessern. Im Folgenden werden kritische Anmerkungen und einige Beispiele zur Qualitätssteigerung und Erhöhung der Aussagekraft des Belastungs-EKGs vorgestellt. Die aktualisierte Liste der Indikationen nach evidenz-basierten Kriterien werden tabellarisch aufgelistet. Eine kritische Bewertung unter Beachtung der laufenden neuen Er-kenntnisse wird angemahnt.
GLASGOW COMA SCALE (GCS), TEKANAN DARAH DAN KADAR HEMOGLOBIN SEBAGAI PREDIKTOR KEMATIANPADA PASIEN CEDERA KEPALA

The number of incidence and mortality of patients with traumatic brain injury (TBI) is high, so it is called for better service, on the other hand healthcare care facilities, particularly bed of intensive care unit (ICU) limited. So often the hospital should perform a selection against patients. Mortality predictors can be used as tool for selection. The aims of this research is to gain a predictive model of mortality in isolativeTBI patients using a standardized examination in Emergency Department. Design of this study is a observational study with prospective approach. Respondents totaled 49 person by consecutive sampling. The results of this research show that there is a correlation between all the independence variables with mortality of the patient.GCS (p<0,001, r=0,732), TDS (p=0,005, r=0,420), MAP (p=0,005, r=0,429), Hb (p=0,048, r=0,272). The result of logistic regression showed that GCS is the most dominant factor related to patient mortality is GCS (p=0,002, correlation coefisient = - 0,906). Keywords : Traumatic brain injury, mortality predictor, GCS, components of GCS
Topics in Many-valued and Quantum Algebraic Logic

Introduced by C.C. Chang in the 1950s, MV algebras are to many-valued ( Lukasiewicz) logics what boolean algebras are to two-valued logic. More recently, effect algebras were introduced by physicists to describe quantum logic. In this thesis, we begin by investigating how these two structures, introduced decades apart for wildly different reasons, are intimately related in a mathematically precise way. We survey some connections between MV/effect algebras and more traditional algebraic structures. Then, we look at the categorical structure of effect algebras in depth, and in particular see how the partiality of their operations cause things to be vastly more complicated than their totally defined classical analogues. In the final chapter, we discuss coordinatization of MV algebras and prove some new theorems and construct some new concrete examples, connecting these structures up (requiring a detour through the world of effect algebras! ) to boolean inverse semigroups.
Traumaspezifische Behandlungstechniken

Traumaspezifische Behandlungstechni− ken verfolgen das Ziel, die traumatische Stress− und Symptombelastung zu redu− zieren und die Dissoziation traumatischer Erinnerungen aufzuheben. Es können Techniken der traumaspezifischen Stabi− lisierung und Techniken der Traumabear− beitung zur Anwendung kommen. Zur Reduktion der traumaassozierten Symp− tomatik, zur Verbesserung der Fähigkeit zur Emotionsregulierung und zur Distan− zierung von traumatischem Erleben sind traumaspezifische Stabilisierungstechni− ken von großer Bedeutung. Diese um− fassen Techniken der Aufmerksamkeits− umfokussierung, imaginative Distanzie− rungstechniken und ressourcenaktivie− rende Techniken. Eine Integration der dissoziierten traumatischen Erinnerun− gen in den biografischen Kontext der Lebensgeschichte erfordert den Einsatz traumabearbeitender (traumakonfronta− tiver) Verfahren. Verfahren mit gesicher− ter Wirksamkeit sind EMDR und kogni− tiv−behaviorale Expositionsverfahren. Ein traumakonfrontatives Vorgehen ist an strikte Indikationskriterien gebunden. Äußere Sicherheit, psychische Stabilität und eine gestärkte Fähigkeit zur Emo− tionsregulierung sind unverzichtbare Voraussetzungen.
Integrated Readout at the Quantum-Classical Interface of Semiconductor Qubits

Quantum computing promises to deliver uniquely powerful information processing machines, by exploiting the quantum phenomena of superposition and entanglement. In solid-state systems, there has been significant progress in the isolation and control of the fundamental units needed to build such machines, known as qubits. However, scaling-up the number of qubits to the point where sophisticated algorithms can be performed presents considerable experimental challenges. In particular, it is becoming increasingly apparent that a new class of tools will be required to interface between fragile quantum systems, and the classical readout and control hardware of the outside world. This thesis presents experimental investigations towards the development of a scalable readout architecture for semiconductor qubit platforms. Fast readout of a GaAs-AlGaAs double quantum dot in the few-electron regime is first demonstrated via an embedded dispersive gate sensor (DGS), alleviating the burden of requiring separate charge sensors for every qubit. The sensitivity and bandwidth of this technique are extracted and benchmarked against well-established readout methods. Dispersive gate sensing of
OPTIMAL CONTROL PROBLEM FOR A SEIR TYPE MODEL OF EBOLA EPIDEMICS

A Susceptible, Exposed, Infectious, and Recovered (SEIR) type control model describing the Ebola epidemic in a population of constant size is considered over a ﬁxed time interval. This model is an extension of the well-known SEIR model and is more suitable to the study of the control mechanism of Ebola epidemics. Along with the traditional SEIR compartments, this model contains an isolated infectious compartment representing the number of infected and exposed individuals that have been isolated from the susceptible individuals. The model has two intervention controls reﬂecting efforts to protect susceptible individuals from infected and exposed individuals. Additionally,there are two control functions that deﬁne efforts for the detection and isolation of infected and exposed individuals. The minimization problem of the sum of total fractions of infected and exposed individuals and total weighted costs of control constraints over a given time interval is stated. For the analysis of the corresponding optimal controls, the Pontryagin maximum principle is used. Accordingly, the controls are bang-bang functions determined by the corresponding switching functions. In order to estimate the number of zeros of the switching functions, a new approach is proposed based on the analys is of the Cauchy problems for the derivatives of these functions. It is found that theoptimal controls of the original problem have at most one switching. This allows the reduction of the original complex optimal control problem to the solution of a much simpler problem of conditional minimization of a function of three variables. Results of the numerical solution to this problem and their analysis are provided.
A clustering and selection based transfer ensemble model for customer credit scoring

Customer credit scoring is an important concern for numerous domestic and global industries. It is difficult to achieve satisfactory performance by traditional models constructed on the assumption that the training and test data are subject to the same distribution, because the customers usually come from different districts and may be subject to different distributions in reality. This study combines ensemble learning with transfer learning, and proposes a clustering and selection based transfer ensemble (CSTS) model to transfer the instances from related source domains to target domain for assisting in modeling. The experimental results in two customer credit scoring datasets show that CSTE model outperforms two traditional credit scoring models, as well as three existing transfer learning models.