Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of sampling volume on the probability density function of steady state concentration

In recent years, statistical theory has been used to compute the ensemble mean and variance of solute concentration in aquifer formations with second‐order stationary velocity fields. The merit of accurately estimating the mean and variance of concentration, however, remains unclear without knowing the shape of the probability density function (pdf). In a setup where a conservative solute is continuously injected into a domain, the concentration is bounded between zero and the concentration value in the injected solution. At small travel distances close to the fringe of the plume, an observation point may fall into the plume or outside, so that the statistical concentration distribution clusters at the two limiting values. Obviously, this results in non‐Gaussian pdf's of concentration. With increasing travel distance, the lateral plume boundaries are smoothed, resulting in increased probability of intermediate concentrations. Likewise, averaging the concentration in a larger sampling volume, as typically done in field measurements, leads to higher probabilities of intermediate concentrations. We present semianalytical results of concentration pdf's for measurements with point‐like or larger support volumes based on stochastic theory applied to stationary media. To this end, we employ a reversed auxiliary transport problem, in which we use analytical expressions for first and second central spatial lateral moments with an assumed Gaussian pdf for the uncertainty of the first lateral moment and Gauss‐like shapes in individual cross sections. The resulting concentration pdf can be reasonably fitted by beta distributions. The results are compared to Monte Carlo simulations of flow and steady state transport in 3‐D heterogeneous domains. In both methods the shape of the concentration pdf changes with distance to the contaminant source: Near the source, the distribution is multimodal, whereas it becomes a unimodal beta distribution far away from the contaminant source. The semianalytical and empirical pdf's differ slightly, which we contribute to the numerical artifacts in the Monte Carlo simulations but also to hard assumptions made in the semianalytical approach. Our results imply that geostatistical techniques for interpolation and other statistical inferences based on Gaussian distributions, such as kriging and cokriging, may be feasible only far away from the contaminant source. For calculations near the source, the beta‐like distribution of concentration should be accounted for.
Mg-Al Layered Double Hydroxide Nano-Carrier for Controlled Release of anti-inflammatory Drug

Layered double hydroxides (LDHs), have been known for many decades as a catalyst and ceramic precursors, traps for anionic pollutants, and additives for polymers. Recently, their successful synthesis on the nanometer scale opened up a whole new field for their application in nanomedicine. Here we report the efficacy of Mg1-xAlx (NO3) x (OH)2 LDH nanoparticles as a carrier and for controlled release of one of the non-steroidal anti-inflammatory drugs (NSAID), sodium salicylate. Mg1-xAlx (NO3)x(OH)2.nH2O nanoparticles were synthesized using co-precipitation method from an aqueous solution of Mg(NO3)2.6H2O and Al(NO3)3.9H2O. Salicylate was intercalated in the interlayer space of Mg-Al LDH after suspending nanoparticles in 0.0025(M) HNO3 and 0.75 (M) NaNO3 solution and using anion exchange method under N2 atmosphere. The shift in the basal planes like (003) and (006) to lower 2θ value in the XRD plot of intercalated sample confirmed the increase in basal spacing in LDH, which is because of intercalation of salicylate into the interlayer space of LDH. FTIR spectroscopy of SA-LDH nano hybrid revealed a red shift in the frequency band of carboxylate group in salicylate indicating an electrostatic interaction between cationic LDH sheet and anionic drug. Differential thermal analysis of LDH-SA nanohybrid indicated higher thermal stability of salicylate in the intercalated form into LDH as compared to its free state.DLS studies showed a particle size distribution between 30-60 nm for pristine LDH whereas salicylate intercalated LDH exhibited a particle size distribution between 40-80 nm which is ideal for its efficacy as a superior carrier for drugs and biomolecules.The cumulative release kinetic of salicylate from MgAl-LDH–SA hybrids in phosphate buffer saline (PBS) at pH 7.4 showed a sustained release of salicylate up to 72 h. The drug release kinetic closely resembled first order release kinetics through a combination of drug diffusion and dissolution of LDH under physiological conditions.The hemocompatibility tests performed on the samples showed that Mg Al LDH was compatible with human blood. Cytotoxicity of LDH-
A meta-analysis of the effects of numerical competency development on achievement: Recommendations for mathematics educators

ABSTRACT This meta-analysis examines the effects of numerical competency development in mathematics classrooms. An exhaustive search of the quantitative literature yielded 17 studies with 39 effect sizes. The overall mean effect size, d = 0.88 (p < 0.05), indicates that there is a large positive summary effect of numerical competency development on mathematics achievement. The large overall effect size is complementary to empirical benchmarks for the average annual gains in mathematics knowledge across K–12 grade levels. Results suggest that numeracy and number sense are more effective than math fact fluency with regard to developing numerical competence. Subsequently, the majority of numerical competency studies were conducted in the early elementary grades. The results also indicate that the effect sizes are reduced drastically after second grade. The article concludes with explicit implications for mathematics teachers and researchers to support the evolution of numerical competency instruction in U.S. schools.
Design of the Cooling System of Diesel Locomotive

This paper mainly expounds the locomotive cooling system functions, composition and main components. On the function of the locomotive cooling system and plays an important role in the locomotive has a preliminary understanding. Then expounds several kinds of commonly used cooling technology, and basic working principle of numerous kinds of cooling technology and related role makes a simple elaboration. The former mainly expounds the process more research of the radiator.
Identification of Hybrid Okra Seeds Based on Near-Infrared Hyperspectral Imaging Technology

Near-infrared (874–1734 nm) hyperspectral imaging technology combined with chemometrics was used to identify parental and hybrid okra seeds. A total of 1740 okra seeds of three different varieties, which contained the male parent xiaolusi, the female parent xianzhi, and the hybrid seed penzai, were collected, and all of the samples were randomly divided into the calibration set and the prediction set in a ratio of 2:1. Principal component analysis (PCA) was applied to explore the separability of different seeds based on the spectral characteristics of okra seeds. Fourteen and 86 characteristic wavelengths were extracted by using the successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS), respectively. Another 14 characteristic wavelengths were extracted by using CARS combined with SPA. Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) were developed based on the characteristic wavelength and full-band spectroscopy. The experimental results showed that the SVM discriminant model worked well and that the correct recognition rate was over 93.62% based on full-band spectroscopy. As for the discriminative model that was based on characteristic wavelength, the SVM model based on the CARS algorithm was better than the other two models. Combining the CARS+SVM calibration model and image processing technology, a pseudo-color map of sample prediction was generated, which could intuitively identify the species of okra seeds. The whole process provided a new idea for agricultural breeding in the rapid screening and identification of hybrid okra seeds.
Analisis Kadar Siklamat Dengan Metode Kromatografi Cair Kinerja Tinggi Pada Minuman Jajanan Sekolah Di Kota Palu

Siklamat adalah pemanis buatan yang diproses secara kimiawi. Siklamat tidak boleh dipakai pada hasil pangan untuk bayi, anak batita, ibu hamil serta ibu menyusui. Batas maksimum penggunaan Siklamat adalah 0-11 mg/kg berat badan. Tujuan penelitian untuk mengetahui kadar siklamat pada minuman jajanan sekolah di Kota Palu, Penelitian ini menggunakan metode observasi di 8 (delapan) lokasi di Kota Palu pada tanggal 8-24 Agustus 2018. Analisis kadar Siklamat di Balai Pengawas Obat dan Makanan di Palu. Sampel sebanyak 20 minuman jajajan diperoleh dengan cara accidental sampling. Metode analisis dengan kromatografi cair kinerja tinggi (KCKT). Hasil penelitian menunjukkan bahwa kadar siklamat pada minuman jajanan sekolah di Kota Palu yang melebihi ambang batas perka BPOM < 350 mg/Kg sebanyak 35% dengan kadar 514,63 hingg 2963,43 mg/Kg. Disarankan agar melakukan penelitan lebih lanjut tentang pengetahuan, sikap dan perilaku penjaja minuman dilokasi yang melebihi ambang batas perka BPOM <350 mg/Kg serta edukasi tentang gerakan masyarakat sadar pangan
Ameliorating tomato productivity and water-use efficiency under water salinity.

Salinity affects plant growth and productivity through its osmotic effect, a toxicity of salt ions, and changes in soil physical and chemical properties. This work aims to accelerate root development, hence increasing the plant's ability to absorb more nutrients from the soil i n order to avoid the deleterious effects of salinity though using starter solutions and humic acid. Four starter solutions (SS); SS 1: control, SS2: 200-200-200 (1:1:1), SS3: 150-300-150 (1:2:1) and SS4: 100- 400-100 (1:4:1) mg l -1 of N-P2O5-K2O and three rates of humic acid (HA); 0, 750 and 1500 mg l -1 , as well as their interactions, were studied on tomato plants irrigated with saline water (EC = 3.8). Tomato plants receiving SS 3 recorded highest mean values of leaf area, root and stem dry matter, fruit mas s (161.8 g), fruit yield ha -1 (115.5 ton ha -1 ), and water use efficiency (16.0 kg m -3 ), as well as caused a reduction in fruit quality (firmness, total soluble solid , dry matter, pH, and the EC. While, tomato plants receiving SS 4 achieved the highest leaf and total dry matter per plant, the number of fruit clusters per plant(6.7), the percentage of fruit yield in 1 -2 picks (59.9%), fruit dry matter and fruit EC. Increasing HA rate up to 1500 mg l -1 led to significantly increased leaf area, total dry matter , number of fruits per plant(37.3), fruit mass (138.3 g), yield ha -1 (103.0 ton ha -1 ) and WUE (14.3 kg m -3 ) traits compared to control treatment. However, application of HA at rate 750 mg l -1 gave the highest mean values of stem dry matter, fruit number cl usters per plant, and fruit firmness. Dual application of SS 3 with HA at 750 mg l -1 achieved the best results in alleviating the deleterious effects of salinity stress on tomato plants. This was evidenced by maximum leaf area, fruit number clusters per pla nt (7.2), fruit mass (180.3 g), fruit yield (140.63 ton ha -1 ), and WUE (19.5 kg m -3 ). While application of SS 2 + HA at 1500
Beyond the excised ensemble: modelling elliptic curve L-functions with random matrices

The ‘excised ensemble’, a random matrix model for the zeros of quadratic twist families of elliptic curve L-functions, was introduced by Dueñez et al (2012 J. Phys. A: Math. Theor. 45 115207) The excised model is motivated by a formula for central values of these L-functions in a paper by Kohnen and Zagier (1981 Invent. Math. 64 175–98). This formula indicates that for a finite set of L-functions from a family of quadratic twists, the central values are all either zero or are greater than some positive cutoff. The excised model imposes this same condition on the central values of characteristic polynomials of matrices from SO ( 2 N ) ? > . Strangely, the cutoff on the characteristic polynomials that results in a convincing model for the L-function zeros is significantly smaller than that which we would obtain by naively transferring Kohnen and Zagier’s cutoff to the SO ( 2 N ) ? > ensemble. In this current paper we investigate a modification to the excised model. It lacks the simplicity of the original excised ensemble, but it serves to explain the reason for the unexpectedly low cutoff in the original excised model. Additionally, the distribution of central L-values is ‘choppier’ than the distribution of characteristic polynomials, in the sense that it is a superposition of a series of peaks: the characteristic polynomial distribution is a smooth approximation to this. The excised model did not attempt to incorporate these successive peaks, only the initial cutoff. Here we experiment with including some of the structure of the L-value distribution. The conclusion is that a critical feature of a good model is to associate the correct mass to the first peak of the L-value distribution.
DETECTION OF PERSONS IN MLS POINT CLOUDS USING IMPLICIT SHAPE MODELS

In this paper we present an approach for the detection of persons in point clouds gathered by mobile laser scanning (MLS) systems. The approach consists of a preprocessing and the actual detection. The main task of the preprocessing is to reduce the amount of data which has to be processed by the detection. To fulfill this task, the preprocessing consists of ground removal, segmentation and several filters. The detection is based on an implicit shape models (ISM) approach which is an extension to bag-of-words approaches. For this detection method, it is sufficient to work with a small amount of training data. Although in this paper we focus on the detection of persons, our approach is able to detect multiple classes of objects in point clouds. Using a parameterization of the approach which offers a good compromise between detection and runtime performance, we are able to achieve a precision of 0.68 and a recall of 0.76 while having a average runtime of 370ms per single scan rotation of the rotating head of a typical MLS sensor.
LOFAR reveals the giant: A low-frequency radio continuum study of the outflow in the nearby FR I radio galaxy 3C 31

We present a deep, low-frequency radio continuum study of the nearby Fanaroff-Riley class I (FR I) radio galaxy 3C 31 using a combination of LOw Frequency ARray (LOFAR; 30-85 and 115-178 MHz), Very Large Array (VLA; 290-420 MHz), Westerbork Synthesis Radio Telescope (WSRT; 609 MHz) and Giant Metre Radio Telescope (GMRT; 615 MHz) observations. Our new LOFAR 145-MHz map shows that 3C 31 has a largest physical size of 1.1 Mpc in projection, which means 3C 31 now falls in the class of giant radio galaxies. We model the radio continuum intensities with advective cosmic-ray transport, evolving the cosmic-ray electron population and magnetic field strength in the tails as functions of distance to the nucleus. We find that if there is no in-situ particle acceleration in the tails, then decelerating flows are required that depend on radius r as v ∝ rβ (β ≈ −1). This then compensates for the strong adiabatic losses due to the lateral expansion of the tails. We are able to find self-consistent solutions in agreement with the entrainment model of Croston & Hardcastle, where the magnetic field provides ≈1/3 of the pressure needed for equilibrium with the surrounding intra-cluster medium (ICM). We obtain an advective time-scale of ≈190 Myr, which, if equated to the source age, would require an average expansion Mach number M ≈ 5 over the source lifetime. Dynamical arguments suggest that instead, either the outer tail material does not represent the oldest jet plasma or else the particle ages are underestimated due to the effects of particle acceleration on large scales.
1 AIR PASSENGER DUTY AND OUTBOUND TOURISM DEMAND FROM THE UK

On the 1 st of November 1994, an Air Passenger Duty (APD) was introduced in the UK and since this tax continues to be controversial. This paper examines the effect the ADP on UK outbound tourism demand for ten international destinations. An autoregressive distributed lag model is developed and income, price and tax elasticities are estimated. The income and price elasticities obtained, ranged between 0.36 and 4.11 and -0.05 and -2.02 respectively. The estimated tax elasticities suggest that the implementation of APD had a negative effect on UK outbound travel for five destinations and demand is inelastic to changes in taxes although the magnitudes vary across destinations. The general message is that although the stated objective of APD is to reduce travel and associated carbon emissions, the effectiveness of APD, however, has been marginal; travellers are prepared to pay more in the main to maintain their demand.
Staggered-Grid Finite Difference Method with Variable-Order Accuracy for Porous Media

The numerical modeling of wave field in porous media generally requires more computation time than that of acoustic or elastic media. Usually used finite difference methods adopt finite difference operators with fixed-order accuracy to calculate space derivatives for a heterogeneous medium. A finite difference scheme with variable-order accuracy for acoustic wave equation has been proposed to reduce the computation time. In this paper, we develop this scheme for wave equations in porous media based on dispersion relation with high-order staggered-grid finite difference (SFD) method. High-order finite difference operators are adopted for low-velocity regions, and low-order finite difference operators are adopted for high-velocity regions. Dispersion analysis and modeling results demonstrate that the proposed SFD method can decrease computational costs without reducing accuracy.
BAYESIAN ANALYSIS OF RADIOCARBON DATES

If radiocarbon measurements are to be used at all for chronological purposes, we have to use statistical methods for calibration. The most widely used method of calibration can be seen as a simple application of Bayesian statistics, which uses both the information from the new measurement and information from the 14C calibration curve. In most dating applications, however, we have larger numbers of 14C measurements and we wish to relate those to events in the past. Bayesian statistics provides a coherent framework in which such analysis can be performed and is becoming a core element in many 14C dating projects. This article gives an overview of the main model components used in chronological analysis, their mathematical formulation, and examples of how such analyses can be performed using the latest version of the OxCal software (v4). Many such models can be put together, in a modular fashion, from simple elements, with defined constraints and groupings. In other cases, the commonly used "uniform phase" models might not be appropriate, and ramped, exponential, or normal distributions of events might be more useful. When considering analyses of these kinds, it is useful to be able run simulations on synthetic data. Methods for performing such tests are discussed here along with other methods of diagnosing possible problems with statistical models of this kind.
River Restoration Effects on Steelhead Populations in the Manistee River, Michigan: Analysis Using an Individual-Based Model

Abstract The Manistee River, Michigan, watershed includes two dams as well as residential and agricultural development, and the river itself contains a sizeable population of steelhead Oncorhynchus mykiss that supports a valuable recreational fishery. Restoration of the Manistee River and its flow regime may improve steelhead habitat and the fishery. We developed an individual-based model of steelhead in the Manistee River to assess the population effects of changes in the number of spawners, water discharge from Tippy Dam, and water temperature. The model follows steelhead from spring spawning to the end of the growing season in early fall and depicts the river environment as a series of cells that vary in dimension, water velocity, and substrate. Simulated water discharge, temperature, and prey availability changed daily based on observations from Tippy Dam. Empirically based models describe individual steelhead fry and parr foraging and growth. In the model, steelhead select habitats and maximize indiv.
Socio-technical Evolution and Migration in Software Ecosystems

Open source software ecosystems are formed by software projects that are developed and evolve together in the same environment [1]. Considering that most open source projects today are no longer developed in isolation [2], the research community has recently shifted its attention to software ecosystems [3]. Examples of software ecosystems include package distributions for programming languages (e.g., CRAN, CPAN, RubyGems, npm, PyPI) or operating systems (e.g., Ubuntu, Debian), and mobile app stores. A significant part of many of these ecosystems is developed through GitHub, a portal for distributed versioning allowing developers to create and fork projects, link these projects via dependencies, and collaborate through a pull-based development process [4]–[6]. Developing software in such a way is an inherently social activity, involving the interaction, communication and collaboration of multiple contributors to the same project and across interdependent projects. It is also an inherently technical activity, involving the creation, generation and modification of a multitude of software artefacts such as source code, documentation, tests, metadata, and many more. The socio-technical evolution dynamics of software ecosystems is an emerging research subject [7]–[9], but current studies mainly focus on temporary changes of the ecosystem. For example, an analysis of temporary changes will consider a contributor who becomes temporarily inactive but continues to contribute later on. In contrast, this paper focuses on permanent changes in the ecosystem and measures their effect on the ecosystem’s evolution. For example, a contributor may decide to leave the ecosystem, causing turnover in the projects he is contributing to, and perhaps leading to abandoned projects or files. The degree of turnover and abandonment may be indicative of quality problems in projects or in the ecosystem as a whole.
Ionospheric electric field variations during a geomagnetic storm simulated by a coupled magnetosphere ionosphere thermosphere (CMIT) model

A coupled magnetosphere ionosphere thermosphere (CMIT 2.0) model has been developed. It is capable of self‐consistently calculating global ionospheric electric fields that include the imposed magnetospheric convection field, neutral wind dynamo and penetration electric fields. The CMIT 2.0 simulated ionospheric F2 region ion vertical drift velocities at the magnetic equator were compared with those measured by ground‐based instruments during the April 2–5, 2004, storm. CMIT 2.0 captured the temporal variations seen in the measurements during both the quiet and active periods. These temporal variations corresponded mainly to the variations in the high latitude electric fields driven by changes in solar wind conditions. CMIT 2.0, however, overestimated the magnitudes of the variations of the vertical drifts. In addition, CMIT 2.0 simulated the observed pre‐reversal enhancement well. This enhancement was driven mostly by the neutral wind dynamo.