ARTICLE | doi:10.20944/preprints202301.0423.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: proportion estimation; linear mixture model; confidence interval; confidence region; photosynthetic vegetation; non-photosynthetic vegetation; soil; Landsat Thematic Mapper
Online: 24 January 2023 (05:56:10 CET)
Many papers in recent years have been devoted to estimating the per pixel proportions of three broad classes of materials (e.g. photosynthetic vegetation, non-photosynthetic vegetation and bare soil) using data from multispectral sensors. Many of these papers use estimation methods based on the linear mixture model. Very few of these papers assess the accuracy of their estimators. I show how to produce confidence intervals (CIs) and joint confidence regions (JCRs) for the proportions associated with various linear mixture models. There are two main models, both of which assume that the coefficients in the model are non-negative. The first model assumes that the coefficients sum to 1. The second does not, but uses rescaling of the estimated coefficients to produce estimated proportions. Three variants of these two models are also analysed. JCRs are shown to be particularly informative, because they are typically better at localising the information than CIs are. The methodology is illustrated using examples from Landsat Thematic Mapper data at 1169 locations across Australia, each of which has associated field observations. There is also discussion about the extent to which the methodology can be extended to hyperspectral data.
ARTICLE | doi:10.20944/preprints202109.0503.v1
Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: mitogenome; transmembrane proteins; substitution matrix; JTT matrix; molecular evolution; partitioned models; mixture models; RY coding; cyto-nuclear discordance
Online: 29 September 2021 (16:57:38 CEST)
Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acids exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution dataset for transmembrane helices from a variety of sampled set of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.
ARTICLE | doi:10.20944/preprints202308.1839.v1
Subject: Engineering, Civil Engineering Keywords: reclaimed asphalt mixture; roundness; road performance
Online: 29 August 2023 (04:22:29 CEST)
Recycled asphalt mixture is a material remixed with old asphalt recycled material (RAP) and new aggregate, and its application is of great significance in environmental protection.Due to the wear and tear of the old asphalt mixture, the road performance of the recycled asphalt mixture will decrease. This paper uses IPP software to obtain the shape characteristics of the old and new aggregates, and found that the roundness of the old aggregate of 9.5mm-16mm is the most serious wear. Therefore, the 30% RAP, and the influence of the roundness of the recycled asphalt mixture on the road performance is studied.
ARTICLE | doi:10.20944/preprints202010.0550.v2
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: expectation maximization (EM) algorithm; finite mixture model; conditional mixture model; regression model; adaptive regressive model (ARM)
Online: 28 October 2020 (11:18:04 CET)
Expectation maximization (EM) algorithm is a powerful mathematical tool for estimating statistical parameter when data sample contains hidden part and observed part. EM is applied to learn finite mixture model in which the whole distribution of observed variable is average sum of partial distributions. Coverage ratio of every partial distribution is specified by the probability of hidden variable. An application of mixture model is soft clustering in which cluster is modeled by hidden variable whereas each data point can be assigned to more than one cluster and degree of such assignment is represented by the probability of hidden variable. However, such probability in traditional mixture model is simplified as a parameter, which can cause loss of valuable information. Therefore, in this research I propose a so-called conditional mixture model (CMM) in which the probability of hidden variable is modeled as a full probabilistic density function (PDF) that owns individual parameter. CMM aims to extend mixture model. I also propose an application of CMM which is called adaptive regressive model (ARM). Traditional regression model is effective when data sample is scattered equally. If data points are grouped into clusters, regression model tries to learn a unified regression function which goes through all data points. Obviously, such unified function is not effective to evaluate response variable based on grouped data points. The concept “adaptive” of ARM means that ARM solves the ineffectiveness problem by selecting the best cluster of data points firstly and then evaluating response variable within such best cluster. In order words, ARM reduces estimation space of regression model so as to gain high accuracy in calculation.
ARTICLE | doi:10.20944/preprints202011.0266.v1
Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: dyadic data; co-occurrence data; attributed dyadic data (ADD); mixture model; conditional mixture model (CMM); regression model
Online: 9 November 2020 (08:48:40 CET)
Dyadic data contains co-occurrences of objects, which is often modeled by finite mixture model which in turn is learned by expectation maximization (EM) algorithm. Objects in traditional dyadic data are identified by names, causing the drawback which is that it is impossible to extract implicit valuable knowledge under objects. In this research, I propose the so-called attributed dyadic data (ADD) in which each object has an informative attribute and each co-occurrence of two objects is associated with a value. ADD is flexible and covers most of structures / forms of dyadic data. Conditional mixture model (CMM), which is a variant of finite mixture model, is applied into learning ADD. Moreover, a significant feature of CMM is that any co-occurrence of two objects is based on some conditional variable. As a result, CMM can predict or estimate co-occurrent values based on regression model, which extends applications of ADD and CMM.
ARTICLE | doi:10.20944/preprints201909.0231.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: mixture distribution; mixture model; high dimensional statistics; nonparametric maximum likelihood; primal-dual interior-point method; adaptive grid
Online: 20 September 2019 (05:17:17 CEST)
In this paper we describe a nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions. Given $N$ independent observations, convexity theory shows that the NPML estimator is discrete with at most $N$ support points. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. The probability of the support points is found by a Primal-Dual Interior-Point method; the location of the support points is found by an Adaptive Grid method. Our method is able to handle high-dimensional and complex multivariate mixture models.An important application is discussed for the problem of population pharmacokinetics and a non-trivial example is treated.Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics.
ARTICLE | doi:10.20944/preprints202211.0512.v1
Subject: Biology And Life Sciences, Endocrinology And Metabolism Keywords: Thyroid hormones; Mixture; Neurodevelopment; Xenopus laevis; EDC
Online: 28 November 2022 (10:44:37 CET)
Thyroid hormones (THs) are essential for normal brain development, influencing neural cell differentiation, migration, and synaptogenesis. Multiple endocrine-disrupting chemicals (EDCs) are found in the environment, raising concern for their potential effects on thyroid hormone signaling and the consequences on neurodevelopment and behavior. While most research on EDCs investigates the effects of individual chemicals, human health may be adversely affected by a mixture of chemicals. Many compounds belonging to a wide range of chemical classes have been identified as EDCs, notably those affecting thyroid hormone signaling. We hypothesized that embryonic exposure to a mixture of chemicals (containing phenols, phthalates, pesticides, heavy metals, perfluorinated -, polychlorinated, and polybrominated compound) commonly found in the human amniotic fluid could lead to altered brain development to assess its effect on thyroid hormone signaling and neurodevelopment in an amphibian model (Xenopus laevis), highly sensitive to thyroid disruption. Newly hatched tadpoles were exposed for eight days to either TH (thyroxine, T4 10nM) or the amniotic mixture (1x concentration) and gene expression was analyzed in the brains of exposed tadpoles using both RT-qPCR and RNA sequencing. Results indicate that whilst some overlap on TH-dependent genes exist, T4 and the mixture have different gene signatures. Immunohistochemistry showed increased proliferation in the brains of T4-treated animals whereas no difference was observed for the amniotic mixture. Further, we demonstrated diminished tadpoles’ motility in response to T4 and mixture exposure. As the individual chemicals composing the mixture are considered safe, these results highlight the importance of examining the effects of mixtures to improve risk assessment
ARTICLE | doi:10.20944/preprints202206.0342.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: mixture experiments; lattice point sets; uniform designs
Online: 27 June 2022 (03:09:12 CEST)
For the symmetrical mixture model and mixture test area, the lattice point set is used to partition, and then the corresponding test statistics can be constructed. In this paper, we first proposes the partition methods under the lattice point sets and obtains several sub-simplexes without common interior points. Furthermore, we present the method for constructing a uniform design on the simplex using the center points of these sub-simplexes. The designs satisfy the uniformity of maximum distance deviation and provide good results for the mean square error deviation. Finally, the uniformity test on the mixture region is considered and illustrated by examples.
ARTICLE | doi:10.20944/preprints202107.0229.v1
Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: HPLC; NSAIDs; Isocratic; Short column; Drug mixture
Online: 9 July 2021 (15:23:57 CEST)
Nonsteroidal anti-inflammatory drugs (NSAIDs), which block the activity of cyclooxygenase (COX) isoenzymes and inhibit the synthesis of prostaglandin, have been used for pain relief. We have developed a method to separate a mixture of three NSAIDs, such as aspirin, paracetamol, and naproxen, using reverse-phase high-performance liquid chromatography (RP-HPLC). An isocratic mobile phase consisting of acidic water and acetonitrile was selected to run at a low flow rate, such as 0.8 mL/min. The mixture of three NSAIDs was injected at a low volume into a C18 column that was 150 mm in length and characterized using a UV detector at 230 nm. We identified three peaks in the chromatogram indicating the three compounds. The elution time of the peaks was less than 10 minutes. To identify multiple peaks on the isocratic flow using a short column, further studies are required regarding the proposed method to generate microfluidic devices for nanoLC.
ARTICLE | doi:10.20944/preprints202102.0458.v1
Subject: Computer Science And Mathematics, Other Keywords: Copula; Vine Copula; Mixture vine copula; Truncation
Online: 22 February 2021 (11:28:49 CET)
Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically, which becomes along with huge computational times and efforts. This situation becomes even much more harder and complicated in the mixture Regular vine models. Incorporating truncation method with mixture Regular vine models will reduce the computation difficulty for the mixture based models. In this paper, tree-by-tree estimation mixture model is joined with the truncation method, in order to reduce the computational time and the number of the parameters that need to be estimated in the mixture vine copula models. A simulation study and a real data applications illustrated the performance of the method. In addition, the real data applications show the affect of the mixture components on the truncation level.
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: mixture experiments; lattice points; pseudo component transformation
Online: 20 August 2020 (08:07:54 CEST)
We consider mixture experiments in which the proportions of the components must be non-negative and their sum must equal one. Thus, the experimental region for a mixture of components is a simplex. Li and Zhang (2017) made the conjecture that the pseudo component transformation of the lattice points in the simplex has a special property. In this paper, we show that this conjecture is not true in general. Furthermore, we refine this conjecture and prove the refined conjecture.
ARTICLE | doi:10.20944/preprints201704.0172.v1
Subject: Chemistry And Materials Science, Metals, Alloys And Metallurgy Keywords: 7075 Aluminum alloy; eutectic mixture; formability; hardness.
Online: 26 April 2017 (18:12:46 CEST)
Strain induced melt activation process (SIMA) creates a globular microstructure which improves the hardness and ultimate tensile stress (UTS) of 7075 aluminum alloys. But, at the grain boundaries of SIMA processed 7075 aluminum alloy, presence of continuous and brittle intermetallic compounds and the eutectic structure result in decreasing mechanical properties, such as elongation, formability and etc. Hence, in order to improve microstructure and formability of 7075 aluminum alloy respect to SIMA process, a new process was done that is called two-step strain induced melt activation (TSSIMA). This process, which has been mentioned in the experimental procedure section, both organized globular structure and significantly modified the microstructure of the alloy compared to that of the SIMA method. It promoted discontinuity and more homogeneity in distribution of the precipitates and, approximately removed the eutectic mixture. Performing the rolling process on the alloy also revealed that it is more effective in formability enhancement in comparison with SIMA process. Also, it increased the hardness of 7075 aluminum alloy respect to that of SIMA process.
ARTICLE | doi:10.20944/preprints202108.0527.v1
Subject: Medicine And Pharmacology, Clinical Medicine Keywords: PSPS; FBSS; chronic pain; health-related quality of life; mixture models analysis; personalized pain management; chronic pain after spinal surgery
Online: 27 August 2021 (15:23:27 CEST)
Persistent Spinal Pain Syndrome Type 2 (PSPS-T2), (Failed Back Surgery Syndrome), dramatically impacts on patient quality of life, as evidenced by Health-Related Quality of Life (HRQoL) assessment tools. However, the importance of functioning, pain perception and psychological status in HRQoL can substantially vary between subjects. Our goal was to extract patient profiles based on HRQoL dimensions in a sample of PSPS-T2 patients and to identify factors associated with these profiles. Two classes were clearly identified using a mixture of mixed effect models from a clinical data set of 200 patients enrolled in “PREDIBACK”, a multicenter observational prospective study including PSPS-T2 patients with 1-year follow-up. We observed that HRQoL was more impacted by functional disability for first class patients (n=136) and by pain perception for second class patients (n=62). Males that perceive their work as physical were more impacted by disability than pain intensity. Lower education level, lack of adaptive coping strategies and higher pain intensity were significantly associated with HRQoL being more impacted by pain perception. The identification of such classes allows for a better understanding of HRQoL dimensions and opens the gate towards optimized health-related quality of life evaluation and personalized pain management.
ARTICLE | doi:10.20944/preprints202310.0317.v1
Subject: Chemistry And Materials Science, Materials Science And Technology Keywords: Kunkur fines; blended cement; mixture design; circular economy
Online: 6 October 2023 (06:18:39 CEST)
Ternary blended cements such as limestone calcined clay cement (LC3) represent a strategic binder type for the mitigation of environmental impact associated with cement production and are estimated to reduce CO2 emissions by about 40% compared to ordinary Portland cement (OPC). In this paper we explore the possibility of producing such ternary blends by utilizing secondary raw materials that may be locally available. Specifically, the primary limestone that is commonly used in LC3 is here substituted by quarry dust obtained by sourcing of “kunkur”, a carbonate-rich sedimentary rock (also known as caliche) that can be locally utilized for the production of ordinary OPC clinker. To optimize the blending proportions of ternary cements consisting of OPC, calcined clay and kunkur fines, a Design of Experiment (DoE) approach was implemented, with the further goal of exploring the possibility of reducing the amount of the OPC fraction to values lower than 50%. The properties of the formulated blends were assessed by a combination of techniques that comprise mechanical strength testing, XRD time-dependent quantitative phase analysis, SEM-EDS microstructural and microchemical analysis. The results suggest that ternary blended cements based on kunkur fines form hydration products, such as hemicarboaluminates, which are also observed in LC3. This shows that such a waste material can potentially be used in sustainable cement blends, however, the presence of kaolinite in the kunkur fines seems to affect the development of strength when compared to both OPC and conventional LC3.
ARTICLE | doi:10.20944/preprints202212.0059.v1
Subject: Biology And Life Sciences, Biology And Biotechnology Keywords: nanocellulose; enzymatic synergism; optimal mixture; CCRD; Colby factor
Online: 5 December 2022 (06:03:10 CET)
A study to produce cellulose nanofibrils (CNF) from Kraft cellulose pulp, an optimal enzyme mixture, was defined using a centroid simplex mixture design. The enzyme blend contains 69% endoglucanase and 31% exoglucanase. The central composite rotational design (CCRD) optimized the CNF production process by achieving a higher crystallinity index. It thus corresponded to a solid loading of 15 g/L and an enzyme loading of 0.974. Using the Segal formula, the crystallinity index (CrI) of CNF was determined by X-ray diffraction to be 80.87%. The average diameter of nanocellulose fibers measured by scanning electron microscopy between 550 - 600 nm for the CNF prepared by enzymatic hydrolysis and between 250 - 300 nm for the CNF produced by enzymatic hydrolysis with the optimal enzyme mixture followed by ultrasonic dispersion. Finally, synergistic interactions between the enzymes involved in nanocellulose production were demonstrated, with Colby factor values greater than one.
ARTICLE | doi:10.20944/preprints201812.0084.v1
Subject: Biology And Life Sciences, Ecology, Evolution, Behavior And Systematics Keywords: mixture toxicity; concentration addition; pesticide; pharmaceuticals; Aliivibrio fischeri
Online: 6 December 2018 (11:08:43 CET)
This work introduced the potential synergistic toxicity of binary mixtures of pesticides and pharmaceuticals, which have been substantially detected in major river basins in South Korea. Different dose-response curve functions were employed in each experimental toxicity dataset for Aliivibrio fischeri. We tested the toxicity of 30 binary mixtures at two effect concentrations: high effect concentration [EC50] and low effect concentration [EC10] ranges. Thus, the toxicological interactions were evaluated at 60 effected concentration data points in total and based on model deviation ratios (MDRs) between predicted and observed toxicity values (e.g., three types of combined effects: synergistic (MDR > 2), additive (0.5 ≤ MDR ≤ 2), and antagonistic (MDR < 0.5)). From the 60 data points, MDRs could not be applied to 17 points, since their toxicities could not be measured. The result showed 48 %-additive (n = 20), 40 %-antagonistic (n = 17), and 12 %-synergistic (n = 6) toxicity effects from 43 binaries (excluding the 17 combinations without MDRs). In this study, EC10 ratio mixtures at a low overall effect range showed a general tendency to have more synergistic effects than the EC50 ratio mixtures at a high effect range. We also found an inversion phenomenon, which detected three binaries of the combination of synergism at low concentrations and additive antagonism at high concentrations.
ARTICLE | doi:10.20944/preprints201709.0083.v1
Subject: Engineering, Civil Engineering Keywords: asphalt mixture; cooling; basic oxygen furnaces (BOF) slag
Online: 18 September 2017 (16:45:41 CEST)
The basic oxygen furnace slag (BOF) was wide used in road construction, but there was a lack of characteristics in different asphalt mixtures. This study investigates the properties of hot-mixed asphalt (HMA) containing stone mastic asphalt (SMA), porous asphalt (PA) and dense-graded BOF as a partial substitution for natural aggregates. The purpose of this study is to evaluate various BOF slag contents in the asphalt mixtures would affect the cooling behavior after compaction. Asphalt mixture specimens contained 0%, 20%, 40% and 60% BOF slag, respectively, as coarse aggregate. Test results showed that BOF slag has a lipophilic property, so it can be adsorbed by asphalt cement, thereby reducing the cost of asphalt. The stability value of all asphalt mixtures increases with the proportion of BOF slag replacement. In addition, the voids in the mineral aggregate (VMA) value variable exhibited significant differences among asphalt mixtures, and could determine the deviation of the cooling trend of asphalt mixtures. Furthermore; it was found that the cooling procedure of the BOF slag used in dense-graded asphalt mixture takes about 100 min, and that the temperature tends to be moderate; however, it took about 120 min of cooling the SMA and PA mixture with BOF slag. In addition, the voids distribution of dense asphalt mixture was not uniform. It would result in various locations of thermal energy temperature on asphalt mixtures that were inconsistent.
ARTICLE | doi:10.20944/preprints201610.0086.v1
Subject: Computer Science And Mathematics, Geometry And Topology Keywords: information geometry; mixture models; log-sum-exp bounds
Online: 20 October 2016 (10:35:57 CEST)
Information-theoretic measures such as the entropy, cross-entropy and the Kullback-Leibler divergence between two mixture models is a core primitive in many signal processing tasks. Since the Kullback-Leibler divergence of mixtures provably does not admit a closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration, approximated, or bounded using various techniques. We present a fast and generic method that builds algorithmically closed-form lower and upper bounds on the entropy, the cross-entropy and the Kullback-Leibler divergence of mixtures. We illustrate the versatile method by reporting on our experiments for approximating the Kullback-Leibler divergence between univariate exponential mixtures, Gaussian mixtures, Rayleigh mixtures, and Gamma mixtures.
ARTICLE | doi:10.20944/preprints202310.1490.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: Mixture exponential; INAR(1) process; CUSUM chart; EWMA chart
Online: 24 October 2023 (07:52:09 CEST)
This paper presents a new discrete counterpart of the mixture exponential distribution by utilizing the survival discretization method. The moment-generating function and associated moment measures are discussed. The distribution’s hazard rate function can assume increasing or decreasing forms, making it adaptable for diverse fields requiring count data modelling. The paper explores four distinct parameter estimation methods and assesses their performance through Monte Carlo simulations. The applicability of this distribution extends to time series analysis, particularly within the framework of the first-order integer-valued autoregressive process. Additionally, the paper explores quality control applications, addressing serial dependence challenges in count data encountered in production and market management. The performance of two distinct control charts, the cumulative sum chart and the exponentially weighted moving average chart, is evaluated for their effectiveness in detecting shifts in the process means under various models. A bivariate Markov chain approach is used to estimate the average run lengths of these charts, offering valuable insights for implementation. Design recommendations for achieving robustness in-control chart applications are provided. The effectiveness of the proposed models and charts is illustrated using a real data, demonstrating their practical superiority.
ARTICLE | doi:10.20944/preprints202309.2090.v1
Subject: Engineering, Transportation Science And Technology Keywords: asphalt mastic; asphalt mixture; flame retardant - smoke suppressant; performance
Online: 30 September 2023 (10:13:04 CEST)
Variety of harmful gases are produced in asphalt mixture after mixing, paving and rolling process. Effective measures must be tak-en to suppress the asphalt pavement in the tunnel due to fire accidents and other toxic gases and fumes, reducing the human health during the construction process. In this study, a flame retardant and smoke suppressant (compound) with Mg(OH)2 as the main component was developed, the flame retardant asphalt mixture and asphalt mastics were prepared to evaluate the flame retard-ant-smoke suppressant properties and performance effects. Firstly, its low and high temperature performances were investigated with the bending beam rheometer (BBR) and dynamic shear rheological (DSR), respectively. Then, the indoor combustion test and the cone calorimeter test were used to evaluate the fire retardant smoke suppression effect of the asphalt mastic. Thirdly, the flame retardant effect of asphalt mastic mixed with the compound was further analyzed by thermogravimetric (TG) test and scanning electron microscopy (SEM). The pyrolysis temperature, mass loss and microscopic state of asphalt surface were used to verify and explain the flame retardant reaction effect and process of the compound. Finally, the asphalt mixture performance was evaluated, as well as the flame retardant smoke suppression effect was verified by asphalt mixture combustion tests. The results showed that the flame retardant smoke suppression time of the flame retardant asphalt mixture was reduced by 66% and the smoke emission area was reduced by 20%. The flame retardant smoke suppression effect of the asphalt mixture was improved by 44%. The flame-retardant and smoke-suppressing compound and the asphalt mixture with the compound prepared in this study meet the asphalt mixture performance and flame retardant smoke suppression function, providing an option for application of fire retardant and smoke-suppressing asphalt pavement materials in tunnels.
REVIEW | doi:10.20944/preprints202304.0614.v1
Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: varietal mixture; evolutionary population; resilient; informal seed system; landrace
Online: 20 April 2023 (07:13:09 CEST)
Crop genetic diversity is most for the long-term sustainable production system. The breeding and production strategies of developing and growing uniform and homogenous varieties have created many different problems. Such populations are static and very sensitive to unpredictable stresses. In Nepal, more than 80% of seed system is informal s which has contributed greatly to creating and maintaining genetic diversity within the field particularly contributing to landrace diversity. This paper aims to assess and present the approaches and advantages of increased crop genetic diversity in the fields. The paper is developed based on experiences of implementing on-farm conservation activities carried out in Nepal since last two decades. Some of the evidences have been derived from on-going evolutionary plant breeding project being implemented in Nepal. The information is supplemented with field assessment, focus group discussion, and literature review. The major approaches to increase crop genetic diversity are evolutionary plant breeding, cultivar mixture, landrace enhancement, informal seed system, bulk method, diversifying the sources, participatory plant breeding, open pollination, etc. EPB and cultivar mixture are very simple and effective approaches to increase crop genetic diversity at field level. The involvement of farmers in these approaches helps to accelerate the population improvement particularly for landraces. The major advantages of increased crop genetic diversity are: seed maintenance by farmers themselves, minimal risk of crop failure, resilience to unpredictable stresses, increased amount of diversified nutrition, production increment each year, ease to produce organically, etc. However, there are some issues and problems associated with mixtures and diverse varieties, for example, not being able to harvest by machine, mature at a different date, difficulty in maintaining seeds and registration, etc. Crop genetic diversity should be considered for a climate-resilient and self-dependent production system. The higher the genetic diversity in farming land, the more chance of getting the multiple benefits in the agriculture system (Vernooy 2022).
ARTICLE | doi:10.20944/preprints202301.0524.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: Matrix variate distribution; Mixture models; EM-algorithm; Penalized likelihood
Online: 28 January 2023 (08:53:19 CET)
In the era of big data with increasingly complex data structures and ever-larger data scales, matrix-type data are becoming highly valued and their applications in the fields of medicine, industry, education, geography, and astronomy are growing in extent. In recent years, significant progress has been made in the practical use of matrix variable t-distribution finite mixture models for handling data in order to address the issues of multi-subgroup structures and long data tails. In this paper, the expectation-maximization (EM) algorithm with penalized maximum likelihood is proposed to resolve the problem of the unbounded nature of the likelihood function applied to the model by considering the degeneracy of the variance-covariance matrix of this model. Our data were analyzed through simulations and real data, and the results demonstrate that our model is effective in both preventing the likelihood function from being unbounded and in ensuring the accuracy of the estimated parameters of the EM algorithm.
ARTICLE | doi:10.20944/preprints201810.0461.v1
Subject: Computer Science And Mathematics, Computer Science Keywords: multi-task; Gaussian processes; cross convolution; spectral mixture; dependency
Online: 22 October 2018 (04:19:00 CEST)
Multi-task Gaussian processes (MTGPs) are a powerful approach for modeling structured dependencies among multiple tasks. Researchers on MTGPs have contributed to enhance this approach in various ways. Current MTGP methods, however, cannot model nonlinear task correlations in a general way. In this paper we address this problem. We focus on spectral mixture (SM) based kernels and propose an enhancement of this type of kernels, called multi-task generalized convolution spectral mixture (MT-GCSM) kernel. The MT-GCSM kernel can model nonlinear task correlations and mixtures dependency, including time and phase delay, not only between different tasks but also within a task at the spectral mixture level. Each task in MT-GCSM has its own generalized convolution spectral mixture kernel (GCSM) with a different number of convolution structures and all spectral mixtures from different tasks are dependent. Furthermore, the proposed kernel uses inner and outer full cross convolution between base spectral mixtures, so that the base spectral mixtures in the tasks are not necessarily aligned. Extensive experiments on synthetic and real-life datasets illustrate the difference between MT-GCSM and other kernels as well as the practical effectiveness of MT-GCSM.
ARTICLE | doi:10.20944/preprints202310.1826.v1
Subject: Engineering, Civil Engineering Keywords: moisture stability; anti-stripping agent; solid waste filler; asphalt mixture
Online: 30 October 2023 (06:36:22 CET)
In recent years, the use of solid waste fillers to partially replace natural fillers in asphalt mixtures to produce high-performance asphalt mixtures has received widespread attention. However, differences in the material properties of solid waste fillers remain a problem for this recycling method. To address this issue, limestone powder in asphalt mixtures was replaced by three solid waste fillers (steel slag powder, tailings powder and calcium carbide slag powder) in this study. The chemical composition of the fillers was first characterized to assess the homogeneity of the material. Then, AC and SMA asphalt mixtures were designed and produced and characterized for wet stability. The results showed that asphalt mixtures with solid waste fillers were superior to LP asphalt mixtures in terms of resistance to water damage, and steel slag powder showed the best improvement in moisture stability of asphalt mixtures. The optimum substitution of solid waste filler for limestone filler was 25%. In addition, the moisture stability of asphalt mixture with limestone filler was significantly improved with the addition of anti-stripping agents. In contrast, the moisture stability of asphalt mixtures with solid waste filler was slightly improved. Solid waste fillers could be used in asphalt mixtures and have a similar function as the anti-stripping agent. In summary, the use of solid waste fillers to replace mineral fillers in asphalt mixtures is a reliable, value-added, recycling option.
ARTICLE | doi:10.20944/preprints202305.0923.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Injury prevention; FMS; depth camera; Gaussian Mixture Model; machine learning
Online: 12 May 2023 (10:21:23 CEST)
Background: Functional Movement Screening (FMS) allows for rapid assessment of an individual’s physical activity level and timely detection of sports injury risk. However, traditional functional movement screening often requires on-site assessment by experts, which is time-consuming and prone to subjective bias. Therefore, the study of automated functional movement screening has become increasingly important. Methods: In this study, we propose an automated assessment method for FMS based on the improved Gaussian Mixture Model (GMM). First, the oversampling of minority samples is conducted, the movement features are manually extracted from the FMS dataset collected with two Azure Kinect depth sensors, then we train the Gaussian mixture model with different scores (1 point, 2 points, 3 points) of feature data separately, finally, we conducted FMS assessment by the Maximum Likelihood estimation. Results: The improved GMM has a higher scoring accuracy (Improved GMM:0.8) compared to other models (Traditional GMM=0.38, Adaboost.M1=0.7, Naïve-Bayes=0.75), and the scoring results of improved GMM have a high level of agreement with the expert scoring (kappa=0.67). Conclusions: The results show that the proposed method based on the improved Gaussian mixture model can effectively perform the FMS assessment task and it is potentially feasible to use depth cameras for FMS assessment.
ARTICLE | doi:10.20944/preprints202102.0019.v1
Subject: Business, Economics And Management, Accounting And Taxation Keywords: dynamic mixture copula; marginal expected shortfall; systemic risk; insurance sector
Online: 1 February 2021 (12:15:01 CET)
In this study, a dynamic mixture copula is used to estimate the marginal expected shortfall in the South African insurance sector. While other studies assumed nonlinear dependence to be static over time, our model capture time-varying nonlinear dependence between institutions and the market. In order to capture time-varying nonlinear dependence, the generalized autoregressive score (GAS) is used to model the dynamic copula parameters. Furthermore, our study implements a ranking that expresses to what degree individual insurers are systemically important in South Africa. We use daily stock return of five South African insurers listed in the Johannesburg Stock Exchange (JSE) from November 13, 2007 to June 15, 2020. We find that Sanlam and Discovery contribute the most to systemic risk, while Santam is found to be the least contributor to the overall systemic risk in the South African insurance sector. Our findings would be of paramount importance for the South African regulators as they would be informed that not only banks are systemically important, but some insurers also are systemically important financial institutions. Hence, stricter regulation of these institutions in the form of higher capital and loss absorbency requirements could be required based on the individual business activities undertaken by the company.
ARTICLE | doi:10.20944/preprints201906.0289.v1
Subject: Engineering, Civil Engineering Keywords: digital fabrication; 3D printing; foam concrete; mixture design; material testing
Online: 28 June 2019 (07:28:09 CEST)
3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.
ARTICLE | doi:10.20944/preprints201807.0012.v1
Subject: Chemistry And Materials Science, Polymers And Plastics Keywords: polyurethane; polyol; Mixture design; Design of experiment; structure-properties relationship
Online: 2 July 2018 (12:52:57 CEST)
Polyurethanes are materials with a strong structure-property relationship. The goal of this research was to study the effect of a polyol blend composition of polyurethanes on its properties using a mixture design and setting mathematic models for each property. Water absorption, hydrolytic degradation, contact angle, tensile stretch, hardness and modulus were studied. Additionally, Thermal stability was studied by thermogravimetric analysis. Area under the curve was used to evaluate the effect of polyol blend composition on thermal stability and kinetics of water absorption and hydrolytic degradation. Least squares were used to calculate the regression coefficients. Models for the properties were significant, and lack of fit was not (P<0.05). Fit statistics suggest both good fitting and prediction. Water absorption, hydrolytic degradation and contact angle were mediated by the hydrophilic nature of the polyols. Tensile strength, modulus and hardness could be regulated by the molecular weight and hydroxyl index of the polyols. Regression of DTG curves from thermal analysis showed improvement of thermal stability with the increase of PCL and PE. An ANOVA test of the model terms demonstrated that three component effects on bulk properties like water absorption, hydrolytic degradation, hardness, tensile strength and modulus, and the PEG*PCL interaction with the contact angle, which is a surface property. Mixture design application allowed for an understanding of the structure-property relationship through mathematic models.
ARTICLE | doi:10.20944/preprints202310.1098.v1
Subject: Engineering, Safety, Risk, Reliability And Quality Keywords: Time diffusion, Mixture inhomogeneity, Deflagration to Detonation Transition, Turbulent jet flame
Online: 17 October 2023 (13:03:44 CEST)
The current study primarily aimed to simulate detonation initiation via turbulent jet flame acceleration in partial-premixed H2-air mixtures. Different vertical concentration gradients were generated by varying the duration of hydrogen injection (referred to as diffusion time) within an enclosed channel filled with air. H2-air mixtures with average hydrogen concentrations of 22.5% (lean mixture) and 30% (near stoichiometric mixture) were investigated at diffusion times of 3, 5, and 60 seconds. Numerical results show that the vertical concentration gradient has a major influence on the early-stage of flame acceleration (FA). In the stratified lean mixture, detonation began in all the diffusion times, and comparing the flame-speed graphs showed that a decrease in the diffusion time and an increase in the mixture inhomogeneity speeded up the flame propagation and the jet flame to detonation transition occurrence in the channel. In the stratified H2-air mixture with an average hydrogen concentration of 30%, transition from a turbulent jet flame to detonation occurred in all the cases, and the mixture inhomogeneity weakened the FA and delayed the detonation initiation.
ARTICLE | doi:10.20944/preprints202310.1028.v1
Subject: Environmental And Earth Sciences, Remote Sensing Keywords: GEDI; laser altimetry, lidar, uncertainty quantification; mixture density network; terrain elevation
Online: 17 October 2023 (12:00:19 CEST)
Early spaceborne laser altimetry mission development starts in pre-phase A design, where diverse ideas are evaluated against mission science requirements. A key challenge is predicting realistic instrument performance through forward modeling at arbitrary spatial scale. Analytical evaluations compromise accuracy for speed, while radiative transfer modeling is not applicable at global scale due to computational expense. Instead of predicting arbitrary properties of a lidar measurement, we develop a baseline theory to predict only the distribution of uncertainty specifically for the terrain elevation retrieval based on terrain slope and fractional canopy cover features through a deep neural network gaussian mixture model, also known as a mixture density network (MDN). Training data was created from differencing geocorrected GEDI L2B elevation measurements with 32 independent reference lidar datasets in the contiguous U.S. from the National Ecological Observatory Network. We trained the MDN and selected hyperparameters based on regional distribution predictive capability. On average, the relative error of equivalent standard deviation of predicted regional distributions was 15.9%, with some anomalies in accuracy due to generalization and insufficient feature diversity and correlation. As an application, we predict the percent of elevation residuals of a GEDI-like lidar within a given mission threshold from 60°S to 78.25°N, which correlate to qualitative understanding of prediction accuracy and instrument performance.
ARTICLE | doi:10.20944/preprints202307.0480.v1
Subject: Physical Sciences, Mathematical Physics Keywords: Tsallis entropy; Many fermion systems; Mixture-degree; Finite temperature; Magic numbers
Online: 7 July 2023 (10:51:53 CEST)
We consider an $N$ fermion system at low temperature $T$ in which we encounter special particle number values $N_m$ exhibiting special traits. These values arise in focusing attention upon the degree of mixture (DM) of the pertinent quantum states. Given the coupling constant of the Hamiltonian, the DMs stay constant for all $N$-values, but experience sudden jumps at the $N_m$. For a quantum state described by the matrix $\rho$, its purity is expressed by $Tr \rho^2$ and then the degree of mixture is given by $1 - Tr \rho^2$, a quantity that coincides with the entropy $S_q$ for $q=2$. Thus, Tsallis entropy of index two faithfully represents the degree of mixing of a state, that is, it measures the extent to which the state departs from maximal purity . Macroscopic manifestations of the degree of mixing can be observed through various physical quantities. Our present study is closely related to properties of many-fermion systemsn that are usually manipulated at zero temperature. Here we wish to study the subject at finite temperature. Gibbs' ensemble is appealed to. Some interesting insights are thereby gained.
ARTICLE | doi:10.20944/preprints202306.1388.v1
Subject: Computer Science And Mathematics, Mathematics Keywords: Genetic algorithm; Multi-objective functions; Missing observation; Mixture experiment; D-efficiency
Online: 20 June 2023 (10:59:20 CEST)
Missing observation is a common problem in scientific and industrial experiments, particularly in a small-scale experiment. They often present significant challenges when experiment repetition is infeasible. In this research, we propose a multi-objective genetic algorithm as a practical alternative for generating optimal mixture designs that remain robust in the face of missing observation. Our algorithm prioritizes designs that exhibit superior D-efficiency while maintaining a high minimum D-efficiency due to missing observation. The focus on D-efficiency stems from its ability to minimize the impact of missing observations on parameter estimates, ensure reliability across the experimental space, and maximize the utility of available data. We study problems with three mixture components where the experimental region is an irregularly shaped polyhedral within the simplex. Our designs have proven to be D-optimal designs, demonstrating exceptional performance in terms of D-efficiency and robustness against missing observations. We provide a well-distributed set of optimal designs derived from the Pareto front, enabling experimenters to select the most suitable design based on their priorities using the desirability function.
ARTICLE | doi:10.20944/preprints202212.0278.v1
Subject: Chemistry And Materials Science, Physical Chemistry Keywords: NMR; shift spectra; wavelet packet transform; automated small molecule mixture analysis
Online: 15 December 2022 (09:00:55 CET)
Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency and / or requirement of prior knowledge. Recently, we have resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.
ARTICLE | doi:10.20944/preprints202104.0064.v1
Subject: Engineering, Automotive Engineering Keywords: recompression Brayton cycle; supercritical carbon dioxide; fluid mixture; solar thermal plant.
Online: 2 April 2021 (13:54:40 CEST)
In this work, an evaluation and quantification of the impact of using mixtures based on Supercritical Carbon Dioxide "s-CO2" (s-CO2/COS, s-CO2/H2S, s-CO2/NH3, s-CO2/SO2) are made as a working fluid in simple and complex recompression Brayton s-CO2 power cycles configurations that have pressure drops in their components. These cycles are coupled to a solar thermal plant with parabolic-trough collector (PTC) technology. The methodology used in the calculation performance is to establish values of the heat recuperator total conductance (UAtotal) between 5 and 25 MW/K. The main conclusion of this work is that the cycle's efficiency has improved due to s-CO2 mixtures as working fluid; this is significant compared to that obtained using the standard fluid (pure s-CO2). Furthermore, a techno-economic analysis is carried out that compares each configuration's costs using pure s-CO2 and a mixture of s-CO2/COS with a molar fraction (70/30) respectively as working fluid where relevant results are obtained. These results show that the best configuration in terms of thermal efficiency and cost is the RCC-RH for pure sCO2 with values of 41.25% and 2811 $/kWe, while for the mixture sCO2/COS, the RCC-2RH configuration with values of 45, 05% and 2621 $/kWe is optimal. Using the mixture costs 6.75% less than if it is used the standard fluid (s-CO2).
TECHNICAL NOTE | doi:10.20944/preprints202011.0038.v1
Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: dyadic data; co-occurrence data; expectation maximization (EM) algorithm; mixture model
Online: 2 November 2020 (12:06:26 CET)
Dyadic data which is also called co-occurrence data (COD) contains co-occurrences of objects. Searching for statistical models to represent dyadic data is necessary. Fortunately, finite mixture model is a solid statistical model to learn and make inference on dyadic data because mixture model is built smoothly and reliably by expectation maximization (EM) algorithm which is suitable to inherent spareness of dyadic data. This research summarizes mixture models for dyadic data. When each co-occurrence in dyadic data is associated with a value, there are many unaccomplished values because a lot of co-occurrences are inexistent. In this research, these unaccomplished values are estimated as mean (expectation) of random variable given partial probabilistic distributions inside dyadic mixture model.
ARTICLE | doi:10.20944/preprints202304.1073.v1
Subject: Biology And Life Sciences, Life Sciences Keywords: cell mixture; deconvolution; immune cells; blood cells; cancer cells; gene signature; bioinformatics
Online: 27 April 2023 (10:34:59 CEST)
In the last two decades many detailed full transcriptomic studies on complex biological samples have been published and included in large gene expression repositories. These studies primarily provide bulk expression signal for each sample, including multiple cell-types mixed within the global signal. The cellular heterogeneity in these mixtures does not allow the activity of specific genes in specific cell types to be identified. Therefore, inferring relative cellular composition is a very powerful tool to achieve a more accurate molecular profiling of complex biological samples. In recent decades, computational techniques have been developed to solve this problem by applying cell deconvolution methods, designed to decompose cell mixtures into their cellular components and calculate the relative proportions of these elements. Some of them, only calculate the cell proportions (supervised methods), while other deconvolution algorithms can also identify the gene signatures specific for each cell type (unsupervised methods). In these work, five deconvolution methods (CIBERSORT, FARDEEP, DECONICA, LINSEED and ABIS) were implemented and used to analyze blood and immune cells, and also cancer cells, in complex mixture samples (using three bulk expression datasets). Our study provides three analytical tools (corrplots, cell-signature plots and bar-mixture plots) that allow a thorough comparative analysis of the cell mixture data. The work indicates that CIBERSORT is a robust method optimized for the identification of immune cell-types, but not as efficient in the identification of cancer cells. We also observed that LINSEED is a very powerful unsupervised method that provides precise and specific gene signatures for each of the five main immune cell-types analyzed: neutrophils and monocytes (in the myeloid lineage), B-cells, NK cells and T-cells (in the lymphoid lineage).
ARTICLE | doi:10.20944/preprints202109.0270.v1
Subject: Engineering, Civil Engineering Keywords: sediments; circular economy; cement; ternary eco-binders; flash calcination method; mixture design
Online: 15 September 2021 (15:25:47 CEST)
CO2 emissions resulting from the production of cement is a major issue, but can be limited by the partial substitution of cement by low-carbon-impact additions. The aim of this study was the formulation of a ternary binder based on ordinary Portland cement (OPC), ground granulated blast-furnace slag (GGBS) and flash-calcined sediment (FCS), a dredged waste which was valorized after applying a new heat treatment: flash calcination. The used materials were physically, chemically and mineralogically characterized. The composition of the formulations was optimized using mixture designs. Five formulations, one reference formulation RM (100% OPC), one binary formulation (50% OPC/50% GGBS), and three ternary formulations with a variable FCS rate (10%, 15%, 20%), were selected and characterized fresh and hardened. Results showed that the incorporation of FCS reduced the workability and increased the density. In addition, a decrease in the initial setting time and the heat of hydration peak were observed. In the hardened state, the formulation containing 10% FCS showed 90-day mechanical strengths superior to that of RM. The use of FCS in ternary binders could reduce the environmental impact by reducing greenhouse gas emissions.
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: Pressure drop; biopolymer; polymer-polymer mixture; synergism; Oil-water flow; Drag reduction
Online: 11 May 2020 (12:58:42 CEST)
The search for lower cost materials that reduce pressure drop in fluid transport systems in oil and gas industries to conserve pumping energy is of paramount importance. Polymers are known to reduce pressure drop in pipeline oil-water flows in a process referred to as drag reduction (DR). The effect of partially hydrolysed polyacrylamide, polyethylene oxide, aloe vera mucilage and their mixtures as drag reducing polymers (DRPs) on pressure gradient (pressure drop; Δp) in pipeline oil-water flows was studied. The experiment was carried out in flow rig with 0.02-m diameter straight unplasticised polyvinylchloride (uPVC) pipe, two centrifugal pumps, control valves and two storage tanks. Tap water (ρ = 997 Kg/m3 and µ = 0.89 cP) and diesel (ρ = 832 Kg/m3 and µ = 1.66 cP) were used as the test fluid at ambient condition. The polymer mixture total concentration (MTC) of 30 and 400 ppm at different mixing proportion, mixture Reynolds number (Remix) and oil input volume were investigated. The results show increase in pressure gradient with increase in oil input volume in both single-phase water flow and oil-water flow before adding drag reducing polymers (DRPs). But Δp decreased after adding DRPs with increase in Reynolds number (Re) or Remix and decrease in the oil-phase Re, vice versa. The results further showed higher reduction in pressure drop by the polymer mixture than in each of the polymer used at the same conditions. The rigidness of the biopolymer was improved by adding synthetic polymers which result to increase in DR efficiency.The search for lower cost materials that reduce pressure drop in fluid transport systems in oil and gas industries to conserve pumping energy is of paramount importance. Polymers are known to reduce pressure drop in pipeline oil-water flows in a process referred to as drag reduction (DR). The effect of partially hydrolysed polyacrylamide, polyethylene oxide, aloe vera mucilage and their mixtures as drag reducing polymers (DRPs) on pressure gradient (pressure drop; Δp) in pipeline oil-water flows was studied. The experiment was carried out in flow rig with 0.02-m diameter straight unplasticised polyvinylchloride (uPVC) pipe, two centrifugal pumps, control valves and two storage tanks. Tap water (ρ = 997 Kg/m3 and µ = 0.89 cP) and diesel (ρ = 832 Kg/m3 and µ = 1.66 cP) were used as the test fluid at ambient condition. The polymer mixture total concentration (MTC) of 30 and 400 ppm at different mixing proportion, mixture Reynolds number (Remix) and oil input volume were investigated. The results show increase in pressure gradient with increase in oil input volume in both single-phase water flow and oil-water flow before adding drag reducing polymers (DRPs). But Δp decreased after adding DRPs with increase in Reynolds number (Re) or Remix and decrease in the oil-phase Re, vice versa. The results further showed higher reduction in pressure drop by the polymer mixture than in each of the polymer used at the same conditions. The rigidness of the biopolymer was improved by adding synthetic polymers which result to increase in DR efficiency.
ARTICLE | doi:10.20944/preprints201809.0588.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: non-mixture model; Fréchet distribution; right censored survival data; maximum likelihood method
Online: 29 September 2018 (07:55:08 CEST)
This paper considers a non-mixture cure model for right censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluate the performance of the method. Comparing with Weibull and exponentiated exponential distributions, the non-mixture Fréchet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.
ARTICLE | doi:10.20944/preprints201807.0530.v1
Subject: Chemistry And Materials Science, Chemical Engineering Keywords: catalytic oxidation; oxide catalysts; C3-C4 mixture; ethylene; propylene; butylenes; heteropoly compound
Online: 27 July 2018 (04:07:12 CEST)
The processing of alkanes (the main components of natural gas) for obtaining of industrially important chemical products is one of the most urgent environmental problems, because the major share of raw materials are burned in torches. Therefore, the main goal of the work is the development of catalysts and conditions for obtaining of important petrochemical products from light alkanes. For the preparation of catalysts, Mo, Cr and Ga oxide catalysts as well as catalysts based on heteropoly compounds, supported on natural materials were used. The catalysts were prepared by the capillary impregnation method and used in oxidative conversion in a flowing unit while varying the process conditions. It has been determined that 5 and 10% MoCrGa catalysts are optimal for obtaining of liquid and gaseous products, and 1% catalyst is more favorable for the synthesis of gaseous products. Supported catalysts from heteropoly acid Н3PW12O40 are highly active in oxidative dehydrogenation and cracking processes, which are concurrent. High activity is caused by dispersity of catalysts, formation of crystal hydrates and amorphous phase of heteropoly acid in a condition of interaction with carrier. Maximum yield of C2H4 - 35.2% at 973 K, C3H6 – 20.0% and C4H8 – 14.3% at 773 К were observed.
ARTICLE | doi:10.20944/preprints202308.0251.v1
Subject: Engineering, Civil Engineering Keywords: Green pavement; Polyethylene Terephthalate; Limestone and Basalt Aggregates; Modified Asphalt mixtures; Mixture properties
Online: 3 August 2023 (05:24:28 CEST)
The global environmental impact of plastic waste is significant, with only 9% being recycled, causing pollution and harming the environment and humans. Due to increased traffic, limited funding, and dwindling natural resources, Jordan's road network is deteriorating rapidly. Pavement performance can be improved through high-quality materials and sustainable construction practices. The research investigates using Polyethylene Terephthalate as a polymer additive in asphalt mixtures to enhance their properties. Basalt and limestone mixtures were applied to asphalt mixtures. The optimal binder content for the control mixture was 4.8% for basalt and 4.93% for limestone. When modified with 10% PET, the basalt mixture showed slightly better stability than the control mix, while higher PET proportions led to reduced strength. PET-modified mixtures consistently displayed higher flows and bulk densities, with a more pronounced impact on the basalt mixture. PET increased the air-void ratio in basalt but had minimal effect on VMA. PET offers economic and environmental advantages, saving 8.4% of the original bitumen cost. As a result, limestone mixture properties, which are inferior to basalt mixture properties, improved significantly compared to basalt mixture properties. PET has the potential to create sustainable and high-performing asphalt mixtures, providing valuable insights for road construction and environmental management.
ARTICLE | doi:10.20944/preprints202304.0521.v1
Subject: Engineering, Civil Engineering Keywords: dynamical properties; dynamic elastic modulus; concrete; mortar; mixture parameters; acoustic test; composite theory
Online: 18 April 2023 (11:09:47 CEST)
This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.
REVIEW | doi:10.20944/preprints202202.0104.v3
Subject: Medicine And Pharmacology, Orthopedics And Sports Medicine Keywords: EMG; muscle; spontaneous electrical activity (SEA); spasm; pain; CMECD protocol; phenoxybenzamine-lidocaine mixture
Online: 28 February 2022 (12:10:27 CET)
: This article was not intended to be a complete report of a standard clinical trial. It is a report of the outcomes of preliminary data for validation of the CMECD procedure (Coletti Method of EMG ChemoDenervation) protocol for the treatment of chronic pain resulting from chronic muscle spasm. Methods are here detailed on how to approach the patient with chronic pain, identify the presence of chronic muscle spasm, undertake the treatment protocol and how to perform the follow up process to confirm that chronic pain secondary to chronic muscle spasm was the accurate diagnosis. Furthermore, this article presents the results of a cohort of more than 90 patients treated by the CMECD procedure regarding location and duration of prior pain, prior treatment strategies, degree of success in resolving pain and duration of relief. Outcome data consisting of patient and staff reporting of specific situations in which the chronic pain treatment was successful has been included to help establish the “believability” of outcome successes and to elucidate the potential life altering effects of successful treatment of chronic pain secondary to chronic muscle spasm. This article will hopefully increase the interest in this treatment protocol and increase the chance that a classical international clinical trial will be undertaken.
ARTICLE | doi:10.20944/preprints202308.0791.v1
Subject: Chemistry And Materials Science, Materials Science And Technology Keywords: hydrogen sulphide; adsorption; fixed-bed column; modelling; spent alkaline batteries; Zn-Mn-oxides mixture
Online: 9 August 2023 (16:23:15 CEST)
Breakthrough curves for the adsorption of H2S using a metal-oxides mixture were predicted using the Bohart-Adams model of fixed bed adsorption. This mixture (ZnMn2O4+ZnO+Mn2O3) came from the processing of an urban waste as spent alkaline batteries were. The H2S adsorption experiments were carried out in a fixed-bed column at 20º C, and under various experimental conditions: gas flow rate, inlet H2S concentration and adsorbent dosage. Curves predicted by the model matched well with experimental data, providing data for the possible scale-up of the system. At the various experimental variables, the efficiency of the column, were also provided in the work. This investigation demonstrated the usefulness of a waste material, like spent alkaline batteries, to provide an adsorbent material to mitigate the problem of the presence of this harmful gas.
ARTICLE | doi:10.20944/preprints202305.1850.v1
Subject: Chemistry And Materials Science, Physical Chemistry Keywords: N,N-dimethylformamid+1-butanol mixture; density; sound velocity; molar heat capacity; excess functions
Online: 26 May 2023 (04:54:35 CEST)
The present paper contains data on the density (ρ), sound velocity (u), specific heat capacity (c_p ) of the mixture of N,N-dimethylformamide + 1-butanol (DMF + BuOH) determined in the entire concentration range of solution and in the temperature range: (293.15–318.15) K. The analysis of thermodynamic functions such as isobaric molar expansion, isentropic and isothermal molar compression, isobaric and isochoric molar heat capacity, as well as their excess functions (〖 E〗_(p,m)^E,〖 K〗_(S,m)^E,〖 K〗_(T,m)^E,〖 C〗_"p,m" ^E,〖 C〗_"V,m" ^E) and also V_m^E was undertaken. The analysis of changes in the physicochemical quantities was based on consideration of the system in an aspect of intermolecular interactions with resulting changes in the mixture structure. The results available in the literature are confusing during the analysis and became the reason for our decision to thoroughly examine the system. What is more, for a system whose components are widely used, there is no information in the literature regarding the heat capacity of the tested mixture, which was also achieved and presented in this publication. The conclusions drawn from so many data allow us to approximate and understand the changes that occur in the structure of the system due to repeatability and consistency of the obtained results
ARTICLE | doi:10.20944/preprints202112.0013.v1
Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: nuclear magnetic resonance; dielectric spectroscopy; water-oil mixture; relaxation characteristic; drill cuttings; West Siberia
Online: 1 December 2021 (12:53:32 CET)
The article is devoted to the topical problem of estimating water content in water-oil mixtures and porous media they saturate, according to low-field NMR relaxometry and dielectric spectroscopy. The aim of the research is to theoretically substantiate and experimentally validate the capability of joint interpretation of data from these methods to acquire information on the filtration-volumetric properties of drill cuttings, relaxation characteristics of oil-containing fluids, water/oil ratio in water-oil mixtures and saturated with them drill cuttings in order to control the composition of liquids produced from boreholes. The studies were carried out on samples of cuttings and oils taken from fields in the northern and Arctic regions of the West Siberian oil-and-gas province. Based on the experimental data obtained, we evaluated the water content in the water-oil mixtures, determined the main NMR parameters of the mixtures in terms of properties of the constituent oils, and specified the parameters and shapes of NMR and complex dielectric permittivity spectra. The NMR method was found to be effective in examining high-viscosity and medium-viscosity oils, while the dielectric spectroscopy method – in the study of light oils; their integration allows obtaining reliable data for all the samples under study. We also showed how the shapes of NMR and complex dielectric permittivity spectra depend on the rheological properties of oil belonging to the mixture.
ARTICLE | doi:10.20944/preprints202105.0374.v1
Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: soil–rock mixture, freezing–thawing interface, shear strength, shear failure surface, particle calculation model
Online: 17 May 2021 (09:34:41 CEST)
With global warming and accelerated degradation of permafrost, the engineering problems caused by the formation of weak zones between the shallow and permafrost layers of soil–rock mixture (S-RM) slopes in permafrost regions have become increasingly prominent. To explore the influence of rock content on the shear strength of the S-RM freezing–thawing interface, the variation in the shear strength for different rock content is studied herein using direct shear tests. In addition, a 3D laser scanner is used for obtaining the topography of the shear failure surface. Combined with the analysis results of the shear band-particle calculation model, the influence of the rock content on the shear strength of the interface is explored. It was found that the impact threshold of the rock content on the interface strength and failure mode is approximately 30%, when the rock content (R) is > 30% and that the shear strength increases rapidly with increasing rock content. When R ≤ 30%, the actual shear plane is similar to waves; when R > 30%, the shear plane appears as gnawing failure. The shear strength of S-RM freezing–thawing interface mainly comes from the bite force and friction between particles. The main reason for the increase in shear strength with increasing rock content is the increase in bite force between particles, which makes the ratio of bite force to friction force approximately 1:1.
ARTICLE | doi:10.20944/preprints202103.0752.v1
Subject: Biology And Life Sciences, Anatomy And Physiology Keywords: Mixture toxicity; Neurotoxicity; Antagonism; Organophosphate; Acetylcholinesterase inhibitors; GABA; Behavior; Risk assessment; Spontaneous movement activity
Online: 31 March 2021 (07:52:05 CEST)
Risk assessment of chemicals is usually conducted for individual chemicals whereas mixtures of chemical are occurring in the environment. Considering that neuroactive chemicals are a group of contaminants that dominate in the environment, it is then imperative to understand the combined effects from mixtures. The commonly used models to predict mixture effects, namely concentration addition (CA) and independent action (IA), are thought suitable for mixtures of similarly or dissimilarly acting components, respectively. For mixture toxicity prediction, one important challenge is to clarify whether to group neuroactive substances based on similar mechanisms of action, e.g. same molecular target or rather similar toxicological response, e.g. hyper- or hypoactivity (effect direction). We addressed this by using the spontaneous tail coiling (STC) of zebrafish embryos, which represents the earliest observable motor activity in the developing neural network, as a model to elucidate the link between mechanism of action and toxicological response. Two questions were asked: 1.) Can the mixture models CA or IA be used to predict combined effects for neuroactive chemical mixtures when the components share a similar mode of action (i.e. hyper- or hypoativity) but show different mechanism of action? 2.) Will a mixture of chemicals where the components show opposing effect directions result in an antagonistic combined effect? Results indicate that mixture toxicity of chemicals such as propafenone and abamectin as well as chlorpyrifos and hexaconazole that are known to show different mechanisms of action but similar effect directions were predictable using CA and IA models. This could be interpreted with the convergence of effects on the neural level leading to either a collective activation or inhibition of synapses. We also found antagonistic effects for mixtures containing substances with opposing effect direction. Finally, we discuss how the STC may be used to amend risk assessment.
ARTICLE | doi:10.20944/preprints201904.0084.v1
Subject: Biology And Life Sciences, Ecology, Evolution, Behavior And Systematics Keywords: abundance; detection; diamondback terrapin; Malaclemys terrapin; monitoring; N-mixture; salt marsh; visual head count
Online: 8 April 2019 (10:55:00 CEST)
Generating a range-wide population status of the diamondback terrapin (Malaclemys terrapin spp.) is challenging due to a combination of species ecology and behavior, and limitations associated with traditional sampling methods. Visual counting of emergent heads offers an efficient, non-invasive and promising method for generating abundance estimates of terrapin populations across broader spatial scales and can be used to explain spatial variation in population size. We conducted repeated visual head count surveys at 38 predetermined sites along the shoreline of Wellfleet Bay in Wellfleet, Massachusetts. We analyzed the count data using a hierarchical modeling framework designed specifically to analyze repeated count data: the so-called N-mixture model. This approach allows for simultaneous modeling of imperfect detection to generate estimates of true terrapin abundance. We found detection probability was lowest when skies were overcast and when wind speed was highest. Site specific abundance varied but we found that abundance estimates were, on average, higher in unexposed sites compared to exposed sites. We demonstrate the utility of pairing visual head counts and N-mixture models as an efficient method for estimating terrapin abundance and show how the approach can be used to identifying environmental factors that influence detectability and distribution.
ARTICLE | doi:10.20944/preprints201901.0299.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: mild cognitive impairment (MCI); speaker recognition; Gaussian Mixture Model (GMM); Universal Background Model (UBM)
Online: 30 January 2019 (05:11:27 CET)
This study aims to develop an elderly care system for improving the interpersonal relationship of the elderly with mild cognitive impairment (MCI) by employing the speaker recognition technique and association functionality of social network platforms. Firstly, the speaker recognition units based on the Gaussian Mixture Model (GMM) and Gaussian Mixture Model-Universal Background Model (GMM-UBM) are implemented to identify the visitor via individual input utterance. After the visitor is identified, the proposed system will be linked to the private database and social network platforms to extract the associated message of two parties. Experimental results indicate that the speaker recognition unit based on GMM-UBM achieves the best performance. Finally, five elderly persons are invited to measure the usability of the proposed system. A questionnaire is used to survey the five elderly persons, and the result indicates that the proposed system is highly potentially applicable in improving the interpersonal relationship of the elderly with MCI.
ARTICLE | doi:10.20944/preprints201710.0030.v1
Subject: Engineering, Mechanical Engineering Keywords: Hamilton’s principle; Nonlinear vibration; Two-phase flow; Critical mixture velocity; Cantilever pipes; Perturbation method
Online: 6 October 2017 (08:31:13 CEST)
This paper studied the nonlinear vibrations of top tensioned cantilevered pipes conveying pressurized steady two-phase flow under thermal loading. The coupled axial and transverse governing partial differential equations of motion of the system were derived based on Hamilton’s mechanics with the centreline assumed to be extensible. Multiple scale perturbation method was used to resolve the governing equations, which resulted to an analytical approach for assessing the natural frequency, mode shape and the nonlinear coupled axial and transverse steady state response of the pipe. The analytical assessment reveals that at some frequencies the system is uncoupled, while at some frequencies a 1:2 coupling exists between the axial and the transverse frequencies of the pipe. Nonlinear frequencies versus the amplitude displacement of the cantilever pipe conveying two-phase flow at super critical mixture velocity for the uncoupled scenario exhibit a nonlinear hardening behaviour, an increment in the void fractions of the two-phase flow resulted to a reduction in the pipe’s transverse vibration frequencies and the coupled amplitude of the system. However, increasing the temperature difference, pressure and the presence of top tension were observed to increase the pipe’s transverse vibration frequencies without a significant change in the coupled amplitude of the system.
ARTICLE | doi:10.20944/preprints202311.0187.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Switch-Transformer; Mixture of Experts (MoE) Mechanism; Sentiment Analysis (SA); Arabic Dialects; 5-polarity, MTL.
Online: 2 November 2023 (14:43:46 CET)
In recent times, models like the Transformer have showcased remarkable prowess in tasks related to natural language processing. However, these models tend to be excessively intricate and demand extensive training. Additionally, while the multi-head self-attention mechanism in the Transformer model aims to capture semantic connections between words in a sequence, it encounters limitations when handling short sequences, thereby limiting its effectiveness in 5-polarity Arabic sentiment analysis tasks. The switch-transformer model has recently emerged as a high-performing alternative. Nevertheless, when these models are trained using single-task learning, they often fall short of achieving exceptional performance and struggle to generate robust latent feature representations, especially when working with compact datasets. This challenge is particularly pronounced in the case of the Arabic dialect, which is considered a low-resource language. Given these constraints, this research introduces a novel approach to sentiment analysis in Arabic text. This method leverages multitask learning in tandem with the switch-transformer shared encoder to enhance model adaptability and refine sentence representation. By introducing a mixture of expert (MoE) mechanism that break down the problem into smaller, more manageable sub-problems, the model becomes adept at handling lengthy sequences and intricate input-output relationships, benefiting both five-point and three-polarity Arabic sentiment analysis tasks. This proposed model effectively discerns sentiment in Arabic dialect sentences. The empirical results highlight the outstanding performance of the suggested model, as evidenced in evaluations on the Hotel Arabic-Reviews Dataset, the Book Reviews Arabic Dataset, and the LARB dataset.
ARTICLE | doi:10.20944/preprints202305.1631.v1
Subject: Environmental And Earth Sciences, Remote Sensing Keywords: blowdowns; crown damage; forest inventory; extreme wind gusts; natural disturbances; spatial resolution; Spectral Mixture Analysis
Online: 23 May 2023 (08:53:39 CEST)
Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in the Amazon. Images from medium-resolution optical satellites (mostly Landsat) combined with extensive field data have allowed researchers to assess patterns of tree mortality and monitor forest recovery over decades of subsequent succession in different regions. Although satellites with high spatial-resolution have become available for the Amazon in the last decade, they have not yet been employed for the mapping and quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November/2015. Remote sensing estimates of tree mortality were produced with Spectral Mixture Analysis and analyzed together with forest inventory data using Generalized Linear Models. Windthrow tree-mortality measured in 3 transects (30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Based on this ground truth, the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3% windthrow tree-mortality, p<0.001). The mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of fit of models showed the opposite pattern, which may reflect the influence of crown damage not accounted for in our field study, and fast-growing regeneration of leaf area. Among the satellites studied, Landsat 8 most accurately captured field observations of variations in tree mortality across the disturbance gradient (i.e., lower under- and/or overestimation from undisturbed to extremely damaged forest). Although satellites with high spatial-resolution can refine estimates of windthrow severity by allowing the quantification of individual tree damage and mortality, our results validate the reliability of Landsat imagery for assessing patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Although high-resolution imagery may improve estimates of tree damage and mortality, these should be validated using field data at compatible scales.
ARTICLE | doi:10.20944/preprints202012.0750.v1
Subject: Engineering, Energy And Fuel Technology Keywords: Solar thermal; flat-plate collector; stagnation; steam range; two-phase mixture model; thermal-hydraulic model.
Online: 30 December 2020 (10:02:25 CET)
Stagnation is the transient state of a solar thermal system under high solar irradiation where the useful solar gain is zero. Both flat-plate collectors with selective absorber coatings and vacuum-tube collectors exhibit stagnation temperatures far above the saturation temperature of the glycol-based heat carriers within the range of typical system pressures. Therefore, stagnation is always associated with vaporization and propagation of vapor into the pipes of the solar circuit. It is therefore essential to design the system in such a way that vapor never reaches components that cannot withstand high temperatures. In this article, a thermal-hydraulic model based on the integral form of a two-phase mixture model and a drift-flux correlation is presented. The model is applicable to solar thermal flat-plate collectors with meander-shaped absorber tubes and selective absorber coatings. Experimental data from stagnation experiments on two systems, which are identical except for the optical properties of the absorber coating, allowed comparison with simulations carried out under the same boundary conditions. The absorber of one system features a conventional highly selective coating, while the absorber of the other system features a thermochromic coating, which exhibits a significantly lower stagnation temperature. Comparison of simulation results and experimental data show good conformity. This model is implemented into an open-source software tool called “THD” for the thermal-hydraulic dimensioning of solar systems. The latest version of THD, updated by the results of this article, enables planners to achieve cost-optimal design of solar thermal systems and to ensure failsafe operation by predicting the steam range under the initial and boundary conditions of worst-case scenarios.
ARTICLE | doi:10.20944/preprints202008.0413.v1
Subject: Engineering, Civil Engineering Keywords: Concrete quality; concrete additive; cross-section; concrete mixture; concrete composition; plastic waste; HDPE; plastic fibre
Online: 19 August 2020 (10:56:00 CEST)
HDPE (high-density polyethene) plastic waste is stronger, harder, and more resistant to high temperatures than other plastics. Using it as an additive in a concrete mixture is one solution to reduce this type of waste. We examined how HDPE-type plastics can be used as an additive material in the manufacture of concrete to improve its hardness, tensile strength and compressive strength. Using 156 samples, we aimed to identify the effect of HDPE plastic fibres on concrete of three qualities; B0, f'c10 MPa (low quality), and f'c25 MPa (medium and high quality). We added four compositions (2.5%, 5%, 10% and 20% by weight of cement) of HDPE plastic fibre to each quality of cement, with HDPE plastic fibre sizes of 1 x 1 cm, 0.5 x 2 cm or 0.25 x 4 cm. We found that the addition of 5% HDPE plastic fibre with a 0.5 x 2 cm cross-sectional shape to the f'c10 MPa concrete gives the best result, with increased tensile and compressive strength of the concrete.
ARTICLE | doi:10.20944/preprints202302.0428.v1
Subject: Biology And Life Sciences, Biology And Biotechnology Keywords: hybrid cheese; faba bean protein; insect protein; desirability-based mixture design; spreadability texture analysis; sensory analysis
Online: 27 February 2023 (01:44:30 CET)
As a result of the growing demand for foods with reduced animal protein content, many new alternative diets are now emerging. Nevertheless, recent studies have shown that the Western population is unprepared for drastic changes and is disinclined to accept foods based on alternative proteins. However, hybrid products might become a good transitional offer. This study used a desirability-based mixture design to model hybrid spreadable cheese analogues (SCAs). The design combined the dairy protein (MPC), Tenebrio molitor (IF) and faba bean (FBP) flours. Nine SCAs with different MPC/FBP/IF ratios were formulated, representing 0, 50 and 100% MPC replacement (7.1% of the formula). Incorporating the IF negatively impacted the desirable texture properties. The FBP flour improved the texture (achieving increased firmness and stickiness and decreased spreadability), but only when combined with MPC. Changing the MPC/FBP/IF ratio affected the colour of SCAs. Sensory analysis showed that hybrid SCAs (≤ 50% MPC) had a more characteristic cheesy flavour than the commercial plant-based reference, and sample C2 had a texture profile similar to the dairy reference. Samples containing IF showed a better flavour profile than the products without IF. The SCAs had higher protein and lower saturated fat, starch and sugar con-tent than commercial analogues.This study demonstrates that the inclusion of alternative proteins can be effective as a strategy to reduce dairy protein content in hybrid product formulations.
ARTICLE | doi:10.20944/preprints202105.0543.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: Blind Source Separation (BSS), Minimum Mean Square Error (MMSE), convolutive mixture, source Prior, generalized Gaussian distribution
Online: 24 May 2021 (08:50:37 CEST)
This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises of two stages named Blind Source Separation (BSS) and De-noising. A hybrid source prior model separates the source signals from the noisy reverberant mixture in the BSS stage. Moreover, we model the low and high-energy components by generalized multivariate Gaussian and super-Gaussian models, respectively. We use Minimum Mean Square Error (MMSE) to reduce noise in the noisy convolutive mixture signal in the de-noising stage. Furthermore, two proposed models investigate the performance gain. In the first model, the speech signal is separated from the observed noisy convolutive mixture in the BSS stage, followed by suppression of noise in the estimated source signals in the de-noising module. In the second approach, the noise is reduced using the MMSE filtering technique in the received noisy convolutive mixture at the de-noising stage, followed by separation of source signals from the de-noised reverberant mixture at the BSS stage. We evaluate the performance of the proposed scheme in terms of signal-to-distortion ratio (SDR) with respect to other well-known multistage BSS methods. The results show the superior performance of the proposed algorithm over the other state-of-the-art methods.
Subject: Engineering, Civil Engineering Keywords: bed load transport; shear Reynolds number; bed-armoring; bed-change; Danube; gravel-sand mixture; 3D CFD modeling
Online: 1 August 2019 (11:12:26 CEST)
In this study, the field measurement-based validation of a novel sediment transport calculation method is presented. River sections with complex bed topography and inhomogeneous bed material composition highlight the need for an improved sediment transport calculation method. The complexity of the morphodynamic features can result in the simultaneous appearance of the gravel and finer sand dominated sediment transport (e.g. parallel bed armoring and siltation) at different regions within a shorter river reach. For the improvement purpose of sediment transport calculation in such complex river beds, a novel sediment transport method was elaborated. The base concept of it is the combined use of two already existing empirical sediment transport models. The method was already validated against laboratory measurements. The major goal of this study is the verification of the novel method with a real river case study. The combining of the two sediment transport models is based on the implementation of a recently presented classification method of the locally dominant sediment transport nature (gravel or sand transport dominates). The results are compared with measured bed change maps. The verification clearly refers to the meaningful improvement in the sediment transport calculation by the novel manner in case of spatially varying bed content.
ARTICLE | doi:10.20944/preprints201807.0215.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: multivariate gaussian mixture model (MVGMM); multivariate linear regression; expectation-maximization imputation; WiFi localization; hidden markov model (HMM)
Online: 12 July 2018 (08:24:06 CEST)
The extensive deployment of wireless infrastructure provides a low-cost way to track mobile users in indoor environment. This paper demonstrates a prototype model of an accurate and reliable room location awareness system in a real public environment, where three typical problems arise. First, a massive number of access points (APs) can be sensed leading to a high-dimensional classification problem. Second, heterogeneous devices record different received signal strength (RSS) levels due to the variations in chip-set and antenna attenuation. Third, APs are not necessarily visible in every scanning cycle leading to missing data. This paper presents a probabilistic Wi-Fi fingerprinting method in a hidden Markov model (HMM) framework for mobile user tracking. Considering the spatial correlation of the signal strengths from multiple APs, a Multivariate Gaussian Mixture Model (MVGMM) is fitted to model the probability distribution of RSS measurements in each cell. Furthermore, the unseen property of invisible AP has been investigated in this research, and demonstrated the efficiency of differentiation between cells. The proposed system is able to achieve comparable localization performance. The filed test results present a reliable 97% localization room level accuracy of multiple mobile users in a real university campus WiFi network without any prior knowledge of the environment.
ARTICLE | doi:10.20944/preprints201712.0108.v1
Subject: Computer Science And Mathematics, Computer Science Keywords: Plant phenotyping, Plant pixel classification, Colour space, , Gaussian mixture model, Earth mover distance, Variance ratio, Plant segmentation.
Online: 15 December 2017 (16:52:23 CET)
Segmentation of a region of interest is an important pre-processing step for many colour image analysis techniques. Similarly segmentation of plant in digital images is an important preprocessing step in phenotying plants by image analysis. In this paper we present an analytical study to statistically determine the suitability of colour space representation of an image to best detect plant pixels and separate them from background pixels. Our hypothesis is that the colour space representation in which the separation of the distributions representing plant pixels and background pixels is maximized would be the best for detection of plant pixels. The two classes of pixels are modelled as a Gaussian mixture model (GMM). In our GM modelling we don't make any prior assumption about the number of Gaussians in the model. Rather a constant bandwidth mean-shift filter is used to cluster the data and the number of clusters and hence the number of Gaussians is automatically determined. Here we have analysed following representative colour spaces like $RGB$, $rgb$, $HSV$, $Ycbcr$ and $CIE-Lab$. This is because these colour spaces represent several other similar colour spaces and also an exhaustive study of all the colour space will be too voluminous. We also analyse the colour space feature from the two-class variance ratio perspective and compare the results of our hypothesis with this metric. The dataset for this empirical study consist of 378 digital images of plants and their manual segmentation. Dataset consist of various species of plants (arabidopsi, tobacco, wheat, rye grass etc.) imaged under different lighting conditions, indoor and outdoor, controlled and uncontrolled background. In results we obtain better segmentation of the plants in $HSV$ colour space, which is supported by its Earth mover distance (EMD) on the GMM distribution of plant and background pixels.
ARTICLE | doi:10.20944/preprints201902.0009.v1
Subject: Engineering, Civil Engineering Keywords: asphalt mixture; low-temperature cracking; Tensile Creep Test (TCT); Bending Beam Creep Test (BBCT); tensile strength; thermal stress;
Online: 1 February 2019 (09:45:08 CET)
Thermal stresses belong to the leading factors that influence low-temperature cracking behavior of asphalt pavements. During winter, when temperature drops to significantly low values, tensile thermal stresses develop as a result of pavement contraction. Creep test methods can be suitable for the assessment of low-temperature properties of asphalt mixtures. To evaluate the influence of creep test methods on the obtained low-temperature properties of asphalt mixtures, three point bending and uniaxial tensile creep tests were applied and the master curves of stiffness modulus were analyzed. On the basis of creep test results, rheological parameters describing elastic and viscous properties of the asphalt mixtures were determined. Thermal stresses were calculated and compared to tensile strength of the material to obtain the failure temperature of the analyzed asphalt mixtures. It was noted that lower strain values of creep curves were obtained for the Tensile Creep Test (TCT) than for the Bending Beam Creep Test (BBCT), especially at lower temperatures. Results of thermal stress calculations indicated that higher reliability was obtained for the viscoelastic Monismith method based on the TCT results than for the simple quasi-elastic solution of Hills and Brien. The highest agreement with the TSRST results was also obtained for the Monismith method based on the TCT results. No clear relationships were noted between the predicted failure temperature and different methods of thermal stress calculations.
ARTICLE | doi:10.20944/preprints202212.0072.v1
Subject: Computer Science And Mathematics, Probability And Statistics Keywords: beta prime distribution; Weibull distribution; mixture representations; information generating function; entropies; order statistics; Monte Carlo simulation; blood cancer disease
Online: 5 December 2022 (09:47:54 CET)
Statistical modeling of lifetime data plays an essential role in a wide range of practical fields, such as health and engineering. There have been a lot of studies done to develop statistical models that can better describe health data than traditional models. For the first time, we pioneer a novel family of continuous probability distributions called the generalized odd beta prime generalized (GOBP-G) family of distributions. The cumulative distribution and probability density functions of the new family are presented. A new generalization of the Weibull distribution called "generalized odd beta prime-Weibull" (GOBPW) is proposed using the pioneered GOBP-G family. The mixture representations of the new distribution are defined and derived. Some formal statistical properties of the GOBPW distribution, such as the moments, moment generating function, incomplete moments, information generating function, entropies, stress-strength function, quantile function, and order statistics, are derived. The estimation of the parameters of the proposed distribution is evaluated using the maximum likelihood estimation approach. Different cancer disease data sets, such as the bladder, head and neck, acute bone, and blood cancers, are used to illustrate the applicability and usefulness of the new model and were compared using several statistical accuracy measures with that of well-established extended Weibull distributions, which are the beta modified Weibull distribution, Kumaraswamy modified Weibull distribution, gamma generalized modified Weibull distribution, gamma log-logistic Weibull distribution, and beta log-logistic Weibull distribution. The results show that the proposed model gives better results than the competitive models. This study could guide the relevant stakeholders in choosing a suitable statistical model for the health data instead of relying on traditional models to enhance decision-making.
ARTICLE | doi:10.20944/preprints201907.0268.v1
Subject: Chemistry And Materials Science, Metals, Alloys And Metallurgy Keywords: slag; metallurgical dust; rolling scale; tails of dressing-works; iron; magnetite; fusion mixture; melting; arc steel-smelting furnace; production efficiency
Online: 24 July 2019 (09:06:41 CEST)
In article questions of development low-waste technologies of processing of steel-smelting slag are considered, gland allowing by extraction and its connections from steel-smelting slag to receive additional raw materials for production became, and the remains to use in building industry. Studying of gravitational methods of enrichment of steel-smelting slag and heat treatment the ore-fuel of pellets is the basis for work. Proceeding from it, in work modern physic-mechanical, chemical and physical and chemical methods of researches (UV-spectroscopy, electronic microscopy, the granulometric analysis) are used.
ARTICLE | doi:10.20944/preprints202306.0132.v1
Subject: Chemistry And Materials Science, Materials Science And Technology Keywords: dispersed titanium and zirconium; mechanical mixture; galvanic replacement; metal systems Ti-Ni and Zr-Ni; core-shell structure, precursors of intermetallics
Online: 2 June 2023 (05:01:36 CEST)
The article focuses on the galvanic replacement synthesis of Ti-Ni and Zr-Ni metal systems with the "core-shell" structure which are potential precursors for intermetallics. The authors defined the effective synthesis parameters and the formation features of polymetallic systems character-ized by granulometric, phase and elemental composition. The X-ray fluorescence and X-ray phase analysis methods showed that the deposition of nickel on dispersed titanium and zirconium leads to the production of test samples with phase composition representing a mechanical mixture of Ni and Ti, Ni and Zr. The method of X-ray fluorescence analysis showed that the presence of hy-drofluoric acid with a 0.5-1.5 M concentration results in the formation of fixed quantitative ratios of elements in the precipitate, which allows the quantitative composition of dispersed systems "titanium - nickel", "zirconium - nickel" to be regulated within a relatively wide range. Scanning electron microscopy proved that all synthesized systems are characterized by a highly porous structure that follows the titanium and zirconium particle surface contour and the presence of spherical nanoscale subunits on the formed particle surface.
ARTICLE | doi:10.20944/preprints202311.1829.v1
Subject: Engineering, Energy And Fuel Technology Keywords: Mineralogy; Mineral Mixture; Surface Complexation Modelling (SCM); Flotation test; Electrostatic pair Linkage; Bond Product (BP); Total Bond Product (TBP); Cation Bridging; Oil Complex; Carboxylate; PHREEQ-C
Online: 29 November 2023 (09:49:41 CET)
Minerals are the chief constituents of rocks and they have varied properties such as surface area, surface charge, site densities etc. Hence, numerous interactions are bound to occur in the reservoir during rock-fluids (i.e., rock, crude oil and brine) interactions. This study seeks to assess the role of mineralogical composition on the wettability of Sandstone Rocks (SR) and Mineral Mixture (MM) using both Surface Complexation Modelling (SCM) and flotation test. From the considered sandstone rocks, both the experimental results and its simulated counterpart revealed that, the SR were preferentially hydrophilic. For the MM, when the mass fraction of the hydrophobic mineral was increased, the affinity of the MM became slightly hydrophobic and vice-versa. For the dominant sandstone reservoir rock minerals with predominantly negatively charged surfaces, negligible oil adsorption took place due the interfacial repulsive forces at the oil-brine and mineral-brine interfaces. For the MM with low calcite content, the wetting preference was influenced by the mineral with prominent surface area. Our developed model portrayed that the main mechanism for oil adhesion onto sandstone minerals was divalent cations bridging. Nonetheless, adhesion of carboxylate (>COO-) onto the illite, montmorillonite and calcite sites also took place with the latter being more pronounced.
ARTICLE | doi:10.20944/preprints202305.2219.v1
Subject: Engineering, Transportation Science And Technology Keywords: pavement friction rating; network level; road safety attributes; hybrid clustering; density-based spatial clustering of applications with noise (DBSCAN); Gaussian mixture model (GMM); Chi-square test
Online: 31 May 2023 (10:38:47 CEST)
Pavement friction plays a crucial role in ensuring the safety of road networks. Accurately assessing friction levels is vital for effective pavement maintenance and management strategies employed by state highway agencies. Traditionally, friction evaluations have been conducted on a case-by-case basis, focusing on specific road sections. However, this approach fails to provide a comprehensive assessment of friction conditions across the entire road network. This paper introduces a hybrid clustering algorithm, namely the combination of density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM), to perform pavement friction performance rating across a statewide road network. A large, safety-oriented dataset is first generated by integrating network friction and vehicle crash data based on the attributes contributing possibly to friction related crashes. One-, two-, and multi-dimensional clustering analyses, respectively, are then performed to rate pavement friction. The Chi-square test is further employed to validate and identify the practical ratings. It is shown that by effectively capturing the hidden, intricate patterns within the integrated, complex dataset and prioritizing friction-related safety attributes, the hybrid clustering algorithm can produce pavement friction ratings that align effectively with the current practices of the Indiana Department of Transportation (INDOT) in friction management.
ARTICLE | doi:10.20944/preprints202307.0519.v1
Subject: Engineering, Bioengineering Keywords: Lung cancer classification; dimensionality reduction; feature selection techniques; STFT; Particle Swarm Optimization; Harmonic Search; Non-Linear Regression; Mixture Model; Convolutional Neural Network (CNN) for Lung Cancer; Microarray gene expression dataset
Online: 7 July 2023 (16:30:59 CEST)
Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.
ARTICLE | doi:10.20944/preprints201809.0548.v1
Subject: Engineering, Civil Engineering Keywords: asphalt mixture; low-temperature cracking; tensile strength; strength reserve; flexural strength; Uniaxial Tension Stress Test (UTST); Thermal Stress Restrained Specimen Test (TSRST); Bending Beam Test (BBT); Semi-Circular Bending Test (SCB);
Online: 27 September 2018 (14:43:05 CEST)
In regions with low-temperature action transverse cracks can appear in asphalt pavements as a result of thermal stresses that exceed the fracture strength of materials used in asphalt layers. To better understand thermal cracking phenomenon, strength properties of different asphalt mixtures were investigated. Four test methods were used to assess the influence of bitumen type and mixture composition on tensile strength properties of asphalt mixtures: tensile strength using the Thermal Stress Restrained Specimen Test (TSRST) and the Uniaxial Tension Stress Test (UTST), flexural strength using the Bending Beam Test (BBT) and fracture toughness using the Semi-Circular Bending Test (SCB). The strength reserve behavior of tested asphalt mixtures was assessed as well. The influence of cooling rate on strength reserve was investigated and correlations between results from different test methods were also analyzed and discussed. It was observed that the type of bitumen is a factor of crucial importance to low-temperature properties of the tested asphalt concretes. This conclusion was proved by all test methods that were used. It was also observed that the level of cooling rate influences the strength reserve and, in consequence, resistance to low-temperature cracking. It was concluded that reasonably good correlations were observed between strength results for the UTST, BBT and SCB test methods.