Using Artificial Intelligence techniques to predict intrinsic compressibility characteristic of Clay

Reconstituted clays have often provided the basis for the interpretation and modelling of the properties of natural clays. The term “intrinsic” was introduced to describe a clay remoulded or reconstituted at moisture content up to 1.5 times its liquid limit and consolidated one-dimensionally. In order to circumvent the difficulties of measuring an intrinsic constant called “intrinsic compressibility index” (C*c), a machine learning (ML) approach using traditional non-parametric tree-based and meta-heuristic ensembles was adopted in this study. Results indicated that tree-ensembles namely random decision forest (RDF) and boosted decision tree (BDT) performed better in C*c prediction (average R2 of 0.84 and root mean square error, RMSE of 0.51) compared to stand-alone models. However, models’ hyper parameters combined meta-heuristically, produced the highest accuracy (average R2 of 0.90 and root mean square error, RMSE of 0.34). The greatest capacity to distinguish between positive and negative soil classes (average accuracy of 0.95, precision and recall of 0.86) were demonstrated by meta-ensembles in multinomial classification

Strength Predictive Modelling of Soils Treated with Calcium-Based Additives Blended with Eco-Friendly Pozzolans—A Machine Learning Approach

Abstract: The unconfined compressive strength (UCS) of a stabilised soil is a major mechanical parameter in understanding and developing geomechanical models, and it can be estimated directly by either lab testing of retrieved core samples or remoulded samples. However, due to the effort, high cost and time associated with these methods, there is a need to develop a new technique for predicting UCS values in real time. An artificial intelligence paradigm of machine learning (ML) using the gradient boosting (GB) technique is applied in this study to model the unconfined compressive strength of soils stabilised by cementitious additive-enriched agro-based pozzolans. Both ML regression and multinomial classification of the UCS of the stabilised mix are investigated. Rigorous sensitivity-driven diagnostic testing is also performed to validate and provide an understanding of the intricacies of the decisions made by the algorithm. Results indicate that the well-tuned and optimised GB algorithm has a very high capacity to distinguish between positive and negative UCS categories (‘firm’, ‘very stiff’ and ‘hard’). An overall accuracy of 0.920, weighted recall rates and precision scores of 0.920 and 0.938, respectively, were produced by the GB model. Multiclass prediction in this regard shows that only 12.5% of misclassified instances was achieved. When applied to a regression problem, a coefficient of determination of approximately 0.900 and a mean error of about 0.335 were obtained, thus lending further credence to the high performance of the GB algorithm used. Finally, among the eight input features utilised as independent variables, the additives seemed to exhibit the strongest influence on the ML predictive modelling

The Effect Of Actellic 25 Ec On Mineral Composition On Cured Fresh Water Fish: Heterobranchus longifilis, Heterotis niloticus And Chrysichthys nigrodigitatus

A study to evaluate the effects of the preservative, Actellic 25 EC solution, on the mineral composition of the three freshwater fish species was carried out. Pieces of fish (samples) were analysed for mineral composition before and after traditional smoke drying and smoke drying after Actellic treatment. The investigations were carried out using fresh water fish, Heterobranchus longifilis, Heterotis niloticus and Chrysichthys nigrodigitatus. The result showed that Actellic 0.03 % solution greatly reduced the sodium content of the smoked dried fish species. Furthermore, Actellic 25 EC eroded the magnesium (Mg) content of C. nigrodigitatus and also reduced slightly the naturally high iron content of H. longifilis, H. niloticus and C. nigrodigitatus. The implications of these results are discussed. Keywords: Actellic, Mineral, Freshwater fishAnimal Research International Vol. 1 (2) 2004 pp. 86-8

Viability of calcinated wastepaper sludge ash geopolymer in the treatment of road pavement subgrade materials

Problematic ground conditions constituted by weak or expansive clays are commonly encountered in construction projects and require some form of chemical treatment such as lime and cement to re-engineer their performance. However, in the light of the adverse effects of these traditional additives on the climate, alternative eco-friendlier materials are now sourced. In the current study, the viability of calcinated wastepaper sludge ash geopolymer in enhancing the engineering behaviour of a problematic site condition is evaluated. A highly expansive clay (HEC) constituted with a blend of kaolinite and bentonite clays is treated with calcinated wastepaper sludge ash (CPSA) geopolymer. Activation of the precursor is actualised at room temperature using a combination of NaOH and Na2SiO3 at various activator to soil+binder ratios (AL/P), and molarity (M). The mechanical, microstructural, and mineralogical characteristics of the treated clay were investigated through unconfined compressive strength (UCS), swell, water absorption, SEM, and EDX analysis. The performance of the stabilised samples was then compared with the requirements for road subgrade and subbase materials and that of OPC and lime-GGBS treatment. The results showed that CPSA-geopolymer enhanced the engineering properties of the treated clay better than traditional binders (OPC and Iime-GGBS). UCS improvement of 220% was observed in the CPSA-stabilised soil over that of OPC-treated ones, while the swell potential and water absorption were drastically reduced by over 95 and 97% respectively after 28-day soaking. The SEM and EDX results showed improved crystallisation of earth-metal-based cementitious flakes (NASH) with increasing CPSA, molarity, and AL/P ratios, which enhanced the inter-particle bonds with simultaneous reduction in porosity. The modified characteristics of the stabilised materials meet the requirements for pavement subgrades. Further, the equivalent carbon emission (CO2-e) from the stabilised materials were also evaluated and compared with that of traditional binders. The results also showed that CPSA-geopolymer had lower CO2-e at higher subgrade strengths than OPC, making it more eco-friendly. Therefore, wastepaper sludge, a common landfill waste from paper recycling is a viable geopolymer precursor that could be utilised in enhancing the engineering properties of subgrade and sub-base materials for road and foundation construction

Affine group representation formalism for four dimensional, Lorentzian, quantum gravity

Within the context of the Ashtekar variables, the Hamiltonian constraint of four-dimensional pure General Relativity with cosmological constant, $\Lambda$, is reexpressed as an affine algebra with the commutator of the imaginary part of the Chern-Simons functional, $Q$, and the positive-definite volume element. This demonstrates that the affine algebra quantization program of Klauder can indeed be applicable to the full Lorentzian signature theory of quantum gravity with non-vanishing cosmological constant; and it facilitates the construction of solutions to all of the constraints. Unitary, irreducible representations of the affine group exhibit a natural Hilbert space structure, and coherent states and other physical states can be generated from a fiducial state. It is also intriguing that formulation of the Hamiltonian constraint or Wheeler-DeWitt equation as an affine algebra requires a non-vanishing cosmological constant; and a fundamental uncertainty relation of the form $\frac{\Delta{V}}{}\Delta {Q}\geq 2\pi \Lambda L^2_{Planck}$ (wherein $V$ is the total volume) may apply to all physical states of quantum gravity.Comment: 13 pages. Revised versio

Design and construction of a Cherenkov imager for charge measurement of nuclear cosmic rays

A proximity focusing Cherenkov imager called CHERCAM, has been built for the charge measurement of nuclear cosmic rays with the CREAM instrument. It consists of a silica aerogel radiator plane across from a detector plane equipped with 1,600 1" diameter photomultipliers. The two planes are separated by a ring expansion gap. The Cherenkov light yield is proportional to the charge squared of the incident particle. The expected relative light collection accuracy is in the few percents range. It leads to an expected single element separation over the range of nuclear charge Z of main interest 1 < Z < 26. CHERCAM is designed to fly with the CREAM balloon experiment. The design of the instrument and the implemented technical solutions allowing its safe operation in high altitude conditions (radiations, low pressure, cold) are presented.Comment: 24 pages, 19 figure

Methods for managing miscarriage:a network meta-analysis

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:The objectives of this review are:• to estimate the relative effectiveness and safety profiles for methods of management of miscarriage;• to provide a ranking of the available methods according to their effectiveness and safety profile

Endoparasites of Bucks Raised under Intensive and Semi-Intensive System

An investigation was carried out on bucks in intensive and semi-intensive systems of management. A total of sixteen (16) bucks (male goats) were randomly purchased for the study. The animals were divided into four groups of four animals per treatment and fed Panicum maximum, Gliricidia sepium for Treatment 1 while Treatment 2 were fed Panicum maximum, Gliricidia sepium plus concentrates. Those in T3 were fed concentrate and allowed to graze and T4 were fed Panicum maximum and were also allowed to forage. The result showed significant difference (P&lt;0.05) in infestations of strongyles amongst the treatments

MHC-class-II are expressed in a subpopulation of human neural stem cells in vitro in an IFN gamma-independent fashion and during development

This work was supported by grants from Great Ormond Street Hospital Children’s Charity, Newlife Foundation, the Antony Nolan Trust, a studentship to CAG from Consejo Nacional de Ciencia y Tecnologia (CONACyT) and Instituto Jaliscience de la Juventud (IJJ), Mexico and GOSH NIHR Biomedical Research Centre. The human embryonic and fetal material was provided by the Human Developmental Biology Resource (http://hdbr.org) jointly funded by the Medical Research Council (grant G070089) and The Wellcome Trust (grant GR082557)

A Biodiverse Rich Environment Does Not Contribute to a Better Diet: A Case Study from DR Congo

The potential of biodiversity to increase and sustain nutrition security is increasingly recognized by the international research community. To date however, dietary assessment studies that have assessed how biodiversity actually contributes to human diets are virtually absent. This study measured the contribution of wild edible plants (WEP) to the dietary quality in the high biodiverse context of DR Congo. The habitual dietary intake was estimated from 2 multiple-pass 24 h dietary recalls for 363 urban and 129 rural women. All WEP were collected during previous ethnobotanical investigations and identified and deposited in the National Botanical Garden of Belgium (BR). Results showed that in a high biodiverse region with precarious food security, WEP are insufficiently consumed to increase nutrition security or dietary adequacy. The highest contribution came from Dacryodes edulis in the village sample contributing 4.8% of total energy intake. Considering the nutrient composition of the many WEP available in the region and known by the indigenous populations, the potential to increase nutrition security is vast. Additional research regarding the dietary contribution of agricultural biodiversity and the nutrient composition of WEP would allow to integrate them into appropriate dietary guidelines for the region and pave the way to domesticate the most interesting WEP