Miracle-dz/UniFAR-FTUs huggingface dataset:
Increase the Efficiency of Dispersive Liquid-Liquid Microextraction (DLLME) and its Use for the Determination of Lead (II) in Aqueous Solutions

A simple, sensitive, and greener method for green extraction and preconcentration of lead from aqueous media and further assay by UV-Vis spectrophotometer has been developed using 1,5 diphenylthiocarbazone (dithizone). Several factors of dispersive liquid-liquid microextraction (DLLME) including the type and volume of extraction and dispersive solvents, shaking time, the concentration of dithizone as a complexing agent, and pH were optimized. Under optimum selected conditions, the limit of detection (LOD), the limit of quantification (LOQ), the linearity range, the relative standard deviation (RSD), and the Enrichment factor (EF) of the proposed method were obtained at 0.007 ppm, 0.025 ppm, 0.01-0.1 ppm, 4.3% (n = 3) and 40, respectively. This proposed method was successfully applied in the analysis of three synthetic water samples and good spiked recoveries over the range of 96.0–98.5% were obtained.
The Effect of the Bacterial Biofertilizer Azotobacter and Gibberellic Acid Solution and Kinetin in Germination of Guava Seeds (Psidium guajava L.)

The study was carried out in the College of Agriculture - University of Kerbala at the beginning of September of the year 2022, according to a factorial experiment with a completely randomized block design, to study the effect of bacterial biofertilizer Azotobacter, and a solution of gibberellic acid in three concentrations (0, 150 and 300 mg. L-1), and a solution of kinetin in three concentrations (0, 25 and 50 mg. L-1) in germination of guava seeds (Psidium guajava L.), the results showed that the single effect of the biological fertilizing agent was superior in the all studied characteristic, except for the characteristic of germination energy after ten days compared to the control treatment. As for gibberellic acid, the concentration (300 mg. L-1) gave it the highest significant increase in all the studied traits compared to the control treatment. Also, the treatment of seeds with kinetin excelled, as the concentration (50 mg. L-1) recorded the highest significant difference in all the studied traits, compared to the control treatment, which recorded the lowest rate.
Image Compression Using Hand Designed and Lifting Based Wavelet Transforms

In this paper an attempt has been made to analyse different wavelet techniques for image compression. Both hand-designed and lifting based wavelets are considered. Hand designed wavelets considered in this work are Haar wavelet, Daubechie wavelet, Biorthognal wavelet, Demeyer wavelet, Coiflet wavelet and Symlet wavelet. Lifting based wavelet transforms considered are 5/3 and 9/7. Wide range of images, including both color and gray scale images were considered. These wavelet transforms are used to compress the test images competitively by using Set Partitioning In Hierarchical Trees (SPIHT) algorithm and by incorporating lifting concepts. Set Partitioning In Hierarchical Trees is a new advanced algorithm based on wavelet transform which is gaining attention due to many potential commercial applications in the area of image compression. These algorithms resulted in practical advantages, such as, superior low bit rate performance, bit-level compression, progressive transmission by pixel, accuracy and resolution . The SPIHT coder is also a highly refined version of the EZW algorithm and is a powerful image compression algorithm, that produces an embedded bit stream form, in which the best reconstructed images shows a significant perceptual improvement as well as an increased PSNR.
A Transmission Strategy for Hyperbolic Internal Waves of Small Width

Semilinear hyperbolic problems with source terms piecewise smooth and discontinuous across characteristic surfaces yield similarly piecewise smooth solutions. If the discontinuous source is replaced with a smooth transition layer, the discontinuity of the solution is replaced by a smooth internal layer. In this paper we describe how the layer structure of the solution can be computed from the layer structure of the source in the limit of thin layers. The key idea is to use a transmission problem strategy for the problem with the smooth internal layer. That leads to an ansatz different from the obvious candidates. The obvious candidates lead to overdetermined equations for correctors. With the transmission problem strategy we compute infinitely accurate expansions. §
Who Is Really Interested in Mathematics? An Investigation of Lower Secondary Students' Mathematical Role Models.

Declining participation rates in advanced mathematics courses and STEM-related occupations has been an issue in Australia for some time, particularly for females. As students continue to disengage with mathematics and complain about its usefulness, it is important to explore what we can do to stem the tide of departing students. One area worthy of investigation is students’ interest in mathematics including whether they are able to name a mathematical role model in their lives. Forty-three students in Years 7 to 9 from three schools were asked to name people they knew who were interested in mathematics. There was a strong bias towards male figures (44 to 17), particularly fathers and male peers.
Zerebrale Sehstörungen

Storungen visueller Wahrnehmungsleistungen zählen zu den häufigeren Funktionsbeeinträchtigungen nach erworbener Hirnschädigung; betroffen sein können sowohl einzelne (z.B. Farbwahrnehmung) als auch komplexe Wahrnehmungsleistungen (z.B. visuelles Erkennen). Eine Schädigung der postchiasmatischen Sehbahn bzw. des striãren Kortex führt zu den bekannten homonymen Gesichtsfeldstorungen. Beeintrachtigungen der Farbwahrnehmung und des visuellen Erkennens finden sich nach okzipitotemporaler Schadigung, während Störungen der visuellen Raumwahrnehmung einschlielThch der Steuerung der räumlichen Aufmerksamkeit typischerweise nach okzipitoparietaler Schadigung auftreten. Die in Einzelfällen beobachtbaren selektiven Ausfälle oder Storungen visueller Leistungen weisen auf eine funktionelle Spezialisierung des visuellen Kortex auch beim Menschen hin. Aufgrund der wichtigen Rolle der visuellen Wahrnehmung für viele Alltagsleistungen kommt der Diagnostik und Behandlung zerebral bedingter Sehstörungen besondere Bedeutung zu.
Validation of MODIS collection 6 FPAR/LAI in the alpine grassland of the Northern Tibetan Plateau

ABSTRACT Leaf area index (LAI) and fractional photosynthetically active radiation absorbed by vegetation (FPAR) are two important parameters in global carbon cycling. Ground measured LAI (LAIG) and calculated FPAR (FPARG) using LAIG were compared with three MODIS Collection 6 FPAR/LAI products (i.e. MOD15A2H derived from the Terra MODIS; MYD15A2H derived from the Aqua MODIS; and MCD15A2H derived from the combination of Terra MODIS and Aqua MODIS) in the alpine grasslands of the Northern Tibetan Plateau. MODIS FPAR/LAI showed significant positive correlations with FPARG/LAIG (coefficient of determination, R2 = 0.48–0.82). MOD15A2H, MYD15A2H and MCD15A2H LAI overestimated LAIG by 17%, 46% and 55% for fenced areas, and by 10%, 53% and 34% for open grazed areas, respectively. MOD15A2H, MYD15A2H and MCD15A2H FPAR overestimated FPARG by 24%, 37% and 44% for fenced areas and by 20%, 35% and 35% for open grazed areas, respectively. Our findings implied that Terra MODIS FPAR/LAI had the highest accuracy among the three MODIS FPAR/LAI products. The accuracies of MODIS FPAR/LAI also varied with land use types.
CLT for mass distribution of toral Laplace eigenfunctions

We study the fine scale $L^2$-mass distribution of toral Laplace eigenfunctions with respect to random position, in 2 and 3 dimensions. In 2d, under certain flatness assumptions on the Fourier coefficients and generic restrictions on energy levels, both the asymptotic shape of the variance is determined and the limiting Gaussian law is established, in the optimal Planck-scale regime. In 3d the asymptotic behaviour of the variance is analysed in a more restrictive scenario ("Bourgain's eigenfunctions"). Other than the said precise results, lower and upper bounds are proved for the variance, under more general flatness assumptions on the Fourier coefficients.
Search for Dark Matter with the CRESST Experiment

The CRESST experiment uses scintillating crystals to search for weakly interacting Dark Matter particles. This work deals with the analysis of data attained. Dominant sources of the recorded background spectra are identified. Dependencies of the scintillation light yield on position and type of the particle interaction are presented. A new method is developed to determine the optimum acceptance region, and a consistent framework to calculate a limit is given.
Müssen die Ernährungsempfehlungen für die Ballaststoffaufnahme geändert werden?

Zusammenfassung: Fuchs et al. kamen 1999 in einer neuen Analyse der 1Nurses Health Studya, einer prospektiven Kohortenstudie der Harvard-Universität mit über 88 757 Krankenschwestern, ähnlich wie schon in den Vorläuferstudien zu dem Schluss, dass die Gesamtballaststoffaufnahme und kolorektales Karzinomrisiko epidemiologisch nicht assoziiert sind. Diese Beobachtung eines Nulleffektes ist nicht konsistent mit experimentellen Arbeiten, die für eine tumorpräventive Wirkung der Ballaststoffe plausible Mechanismen beschrieben. Jedoch sind für die verschiedenen Ballaststoffe in Lebensmitteln auch unterschiedliche Tumorgenesewirkungen im Tiermodell bekannt. Bei der gesundheitlichen Bewertung der Ballaststoffaufnahme spielen neben Krebserkrankungen auch andere Krankheitsbilder eine Rolle. In der Regel ist z. B. eine Ernährung mit einem hohen Ballaststoffgehalt mit einem niedrigeren koronaren Herzkrankheitsrisiko bzw. mit einer reduzierten Mortalität an Herzinfarkt verbunden. Die Arbeit von Fuchs et al. sollte als ein Hinweis verstanden werden, die Ballaststoffhypothese weiter zu differenzieren und einer ernsthaften wissenschaftlichen Untersuchung zu unterziehen.
Improved Support Vector Machine Using Multiple SVM-RFE for Cancer Classification

Support Vector Machine (SVM) is a machine learning method and widely used in the area of cancer studies especially in microarray data. Common problem related to the microarray data is that the size of genes is essentially larger than the number of sample. Although SVM is capable in handling large number of genes, better accuracy of classification can be obtained using small number of gene subset. This research proposed Multiple Support Vector Machine- Recursive Feature Elimination (MSVM-RFE) as a gene selection to identify the small number of informative genes. This method is implemented in order to improve the performance of SVM during classification. The effectiveness of the proposed method has been tested on two different datasets of gene expression which are leukemia and lung cancer. In order to see the effectiveness of the proposed method, some methods such as Random Forest and C4.5 Decision Tree are compared in this paper. The result shows that this MSVM-RFE is effective in reducing the number of genes in both datasets thus providing a better accuracy for SVM in cancer classification.
A new double‐sided substrate‐integrated waveguide slot array antenna for 5G applications

A double‐sided substrate‐integrated waveguide (SIW) slot antenna with stripline feed, as 4‐by‐4 SIW slot array antenna, operating in millimeter‐waves bands is proposed. The whole antenna and feeding system are fabricated on a single substrate with 2 dielectric layers and 3 copper layers, which takes some advantage, such as, small size, low profile, low cost, and 2 radiation direction propagations. The design process and experimental results are presented. The prototypes can be used in dual band frequency ranges, 25 and 28 GHz, with 8 dBi gain and 63° for half power beamwidth in both sides, front and back antenna sides, and 2 GHz bandwidth. Thus, this component can be applied for 5G indoor environments.
CMOS-compatible optical AND, OR, and XOR gates using voltage-induced free-carrier dispersion and stimulated Raman scattering

We present a theoretical model for two high-throughput optical logic methodologies, using voltage-induced free-carrier dispersion and stimulated Raman scattering based Zeno switching. Increased computational throughput is achieved by accessing higher switching speeds, optimizing the use of space, and by using multiple wavelengths for parallel processing. The condition of CMOS compatibility is maintained to take advantage of the high-volume, low-cost manufacturing potential of the industry and to help lower each design's spatial footprint (enabled by the high refractive index contrast of silicon-on-insulator waveguides and resonators). Each design is made with the potential of higher-order operations in mind; for their use must not only stand alone, but must also have the ability to incorporate into future all-optical or optoelectronic computational devices.
Contributions to Hysteresis in Magnetocaloric Materials

Hysteresis is detrimental to the refrigeration cooling cycle efficiency and yet many of the magnetocaloric materials under consideration as solid state refrigerants possess this property. This article discusses some aspects related to the factors leading to hysteresis in real materials. In the absence of high quality single crystals, determining the intrinsic energy cost associated with the transformation between metastable phases is an experimental challenge. We describe a micro‐calorimetric method that provides valuable insight into intrinsic behavior with the sensitivity to measure micro‐crystallites. We show that there is no correlation between the strength of first order character and magnitude of hysteresis between material families. We review some of the extrinsic factors which contribute to the hysteresis in real materials particularly those that can be accounted for using local imaging techniques such as scanning Hall probe microscopy. We discuss a number of mechanisms by which the extrinsic hysteretic properties of a material can be modified.
Self-Adaptive Framework for Efficient Stream Data Classification on Storm

In this era of big data, stream data classification which is one of typical data stream applications has become more and more significant and challengeable. In these applications, it is obvious that data classification is much more frequent than model training. The ratio of stream data to be classified is rapid and time-varying, so it is an important problem to classify the stream data efficiently with high throughput. In this paper, we first analyze and categorize the current data stream machine learning algorithms according to their data structures. Then, we propose stream data classification topology (SDC-Topology) on Storm. For the classification algorithms based on the matrix, we propose self-adaptive stream data classification framework (SASDC-Framework) for efficient stream data classification on Storm. In SASDC-Framework, all the data sets arriving at the same unit time are partitioned into subsets with the nearly best partition size and processed in parallel. To select the nearly best partition size for the stream data sets efficiently, we adopt bisection method strategy and inverse distance weighted strategy. Extreme learning machine, which is a fast and accurate machine learning method based on matrix calculating, is used to test the efficiency of our proposals. According to evaluation results, the throughputs based on SASDC-Framework are 8–35 times higher than those based on SDC-Topology and the best throughput is more than 40000 prediction requests per second in our environment.
Conformal invariance in conditioned stochastic particle systems

We consider space-time correlations in generic one-dimensional stochastic interacting particle systems with short-range interactions that undergo a fluctuation with an atypically activity of particle jumps or reactions or spin flips. We briefly review the approach in the framework of the quantum Hamiltonian formalism and present examples where the dynamics during such large fluctuations is governed not by the typical stationary dynamics, but by ballistic universality classes with dynamical exponent z=1 that are described unitary conformally invariant field theories with central charge c. For reaction–diffusion and spin flip dynamics we identify critical points (a) in the Ising universality class with c=1/2, and (b) in the universality class of the three-states Potts model with c=4/5. For the Ising universality class we obtain a universal scaling form for the generating function of cumulants of the jump activity. For repulsive driven diffusive systems with one conservation law the regime of an atypically high current or hopping activity is generically conformally invariant with central charge c=1.
Spielt eine erhöhte Fruktoseaufnahme und dadurch bedingte Hyperurikämie bei der Genese des meta− bolischen Syndroms eine Rolle? Do Elevated Fructose Intake and Fructose−Induced Hyperuricemia Play a Role in the Genesis of Metabolic Syndrome?

New research findings from the USA confirm a possible effect of elevated fructose intake on the development of obesity and the related hyper− tension and dyslipidemia. The possible mecha− nisms of the metabolic impact of fructose and uric acid in the multifactorial genesis of meta− bolic syndrome are, therefore, discussed in an overview. Hyperuricemia is associated with high blood pressure and other disorders of metabolic syndrome. High fructose consumption can lead not only to hyperuricemia but also to hypertrigly− ceridemia. In this context, endothelial dysfunc− tion takes on key importance as a common bio− chemical mechanism for these disorders of the metabolic syndrome. Uric acid inhibits the bio− availability of nitrogen oxide (NO) in the vascular endothelium. It can activate inflammatory cells by releasing pro−inflammatory mediators there− by increasing the atherogenic risk. The hypothe− sis advanced in animal experiments that uric acid is an independent risk factor in the onset of primary hypertension is backed by clinical stud− ies on the impact of uric acid−reducing drugs. Comprehensive epidemiological studies and cli− nical trials show, more particularly, that asymp− tomatic hyperuricemia (> 4 mg/dl) should also be taken into account when predicting vascular complications. Further prospective intervention studies are, however, necessary in order to deter− mine whether uric acid should be included as a diagnostic criterion in the definition of metabolic syndrome. There is also a need for research into from what dose onwards and under what accom− panying circumstances fructose increases the uric acid and lipid levels and promotes the for− mation of advanced glycation end products (AGEs) and modified lipoproteins as well as the resulting oxidative stress. The indications from animal experiments and clinical trials that endo− thelial damage to the foetus caused by the elevat−
Substructures in large graphs

The first problem we address concerns Hamilton cycles. Suppose G is a large digraph in which every vertex has in- and outdegree at least |G|/2. We show that G contains every orientation of a Hamilton cycle except, possibly, the antidirected one. The antidirected case was settled by DeBiasio and Molla. Our result is best possible and improves on an approximate result by Haggkvist and Thomason. We then investigate the random greedy F-free process which was initially studied by Erdős, Suen and Winkler and by Spencer. This process greedily adds edges without creating a copy of F, terminating in a maximal F-free graph. We provide an upper bound on the number of hyperedges at the end of this process for a large class of hypergraphs. The remainder of this thesis focuses on F-decompositions, i.e., whether the edge set of a graph can be partitioned into copies of F. We obtain the best known bounds on the minimum degree which ensures a K\(_r\)-decomposition of an r-partite graph, with applications to Latin squares. Lastly, we find exact bounds on the minimum degree for a large graph to have a C\(_2\)\(_k\)-decomposition where k≠3. In both cases, we assume necessary divisibility conditions are satisfied.
Soft-tissue Driven Craniomaxillofacial Surgical Planning

In CMF surgery, the planning of bony movement to achieve a desired facial outcome is a challenging task. Current bone driven approaches focus on normalizing the bone with the expectation that the facial appearance will be corrected accordingly. However, due to the complex non-linear relationship between bony structure and facial soft-tissue, such bone-driven methods are insufficient to correct facial deformities. Despite efforts to simulate facial changes resulting from bony movement, surgical planning still relies on iterative revisions and educated guesses. To address these issues, we propose a soft-tissue driven framework that can automatically create and verify surgical plans. Our framework consists of a bony planner network that estimates the bony movements required to achieve the desired facial outcome and a facial simulator network that can simulate the possible facial changes resulting from the estimated bony movement plans. By combining these two models, we can verify and determine the final bony movement required for planning. The proposed framework was evaluated using a clinical dataset, and our experimental results demonstrate that the soft-tissue driven approach greatly improves the accuracy and efficacy of surgical planning when compared to the conventional bone-driven approach.
Learning and Evaluating Human Preferences for Conversational Head Generation

A reliable and comprehensive evaluation metric that aligns with manual preference assessments is crucial for conversational head video synthesis methods development. Existing quantitative evaluations often fail to capture the full complexity of human preference, as they only consider limited evaluation dimensions. Qualitative evaluations and user studies offer a solution but are time-consuming and labor-intensive. This limitation hinders the advancement of conversational head generation algorithms and systems. In this paper, we propose a novel learning-based evaluation metric named Preference Score (PS) for fitting human preference according to the quantitative evaluations across different dimensions. PS can serve as a quantitative evaluation without the need for human annotation. Experimental results validate the superiority of Preference Score in aligning with human perception, and also demonstrate robustness and generalizability to unseen data, making it a valuable tool for advancing conversation head generation. We expect this metric could facilitate new advances in conversational head generation. Project page: https://github.com/dc3ea9f/PreferenceScore.
Real-Time Detection of Local No-Arbitrage Violations

This paper focuses on the task of detecting local episodes involving violation of the standard It\^o semimartingale assumption for financial asset prices in real time that might induce arbitrage opportunities. Our proposed detectors, defined as stopping rules, are applied sequentially to continually incoming high-frequency data. We show that they are asymptotically exponentially distributed in the absence of Ito semimartingale violations. On the other hand, when a violation occurs, we can achieve immediate detection under infill asymptotics. A Monte Carlo study demonstrates that the asymptotic results provide a good approximation to the finite-sample behavior of the sequential detectors. An empirical application to S&P 500 index futures data corroborates the effectiveness of our detectors in swiftly identifying the emergence of an extreme return persistence episode in real time.