Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling

Fractal/multifractal modeling is a widely used geomathematical approach to capturing different populations in geochemical mapping. The rationale of this methodology is based on empirical frequency density functions attained from global or local distributions. This approach is quite popular because of its simplicity and versatility; it accounts for the frequency and spatial distribution of geochemical data considering self-similarity across a range of scales. Using this technique for detection of geochemical anomalies in scarce data, however, is problematic and can lead to systematic bias in the characterization of the underlying populations. In this paper, an innovative technique is presented that provides good results without a priori assumptions. A simulation approach is adopted for fractal analysis by generating different possible distribution scenarios for the variable under study to reveal the underlying populations that are frequently hidden due to lack of data. The proposed technique is called the global simulated size–number method, and it is validated in a case study with two synthetic datasets and another case study with real dataset from the Ushtagan gold deposit in northeast Kazakhstan.Nazarbayev Universit

Categorization of Mineral Resources Based on Different Geostatistical Simulation Algorithms: A Case Study from an Iron Ore Deposit

Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)- simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al2O3) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard

Geostatistical Simulation of Cross-Correlated Variables: a Case Study through Cerro Matoso Nickel-Laterite Deposit

Geostatistical methods have been increasingly used as powerful techniques for predicting spatial attributes and modelling the uncertainty of predictions in un-sampled locations, especially through multi-element deposits. Independent Gaussian simulation constructs precise outputs over each variable, in most cases by simulating using the multi-Gaussian assumption. However, this approach does not consider the underlying correlations between the variables. Spatial uncertainty can also be quantified by co-simulation, where the relationship of the co-regionalized variables is accounted for and the spatial relationships between variables are reproduced. In this study, we apply the two aforementioned approaches (independent simulation and co-simulation) for modelling two correlated elements (Fe & MgO) at Cerro Matoso S.A. Nickel laterite deposit located in Colombia. Results show that co-simulation provides a reasonable outcome in regards to the correlation coefficient parameter and relative error as expected.Nazarbayev University, School of Mining and Geoscience

Multivariate Mapping of Heavy Metals Spatial Contamination in a Cu–Ni Exploration Field (Botswana) Using Turning Bands Co-simulation Algorithm

With a mining-driven economy, Botswana has experienced increased geochemical exploration of minerals around existing mining towns. The mining and smelting of copper and nickel around Selibe-Phikwe in the Central Province are capable of releasing heavy metals including Pb, Fe, Mn, Co, Ni and Cu into the soil environments, thereby exposing humans, plants and animals to health risks. In this study, turning bands co-simulation, a multivariate geostatistical algorithm, was presented as a tool for spatial uncertainty quantification and probability mapping of cross-correlated heavy metals (Co, Mn, Fe and Pb) risk assessment in a semiarid Cu–Ni exploration field of Botswana. A total of 1050 soil samples were collected across the field at a depth of 10 cm in a grid sampling design. Rapid elemental concentration analysis was done using an Olympus Delta Sigma portable X-ray fluorescence device. Enrichment factor, geoaccumulation index and pollution load index were used to assess the potential risk of heavy metals contamination in soils. The partially heterotopic nature of the dataset and strong correlations among the heavy metals favors the use of co-simulation instead of independent simulation in the probability mapping of heavy metal risks in the study area. The strong correlation of Co and Mn to iron infers they are of lithogenic origin, unlike Pb which had weak correlation pointing to its source in the area being of anthropogenicsource. Manganese, Co and Fe show low enrichment, whereas Pb had high enrichment suggesting possible lead pollution. We, however, recommend that speciation of Pb in the soils rather than total concentration should be ascertained to infer chances of possible bioaccumulation, and subsequent health risk to human by chronic exposure.Nazarbayev University through Faculty Development Competitive Research Grants for 2018–2020 under Contract No. 090118FD5336

Assessing heterotopic searching strategy in hierarchical cosimulation for modeling the variables with inequality constraints

A hierarchical sequential Gaussian cosimulation method is applied in this study for modeling the variables with an inequality constraint in the bivariate relationship. An algorithm is improved by embedding an inverse transform sampling technique in the second simulation to reproduce bivariate complexity and accelerate the process of cosimulation. A heterotopic simple cokriging (SCK) is also proposed, which introduces two moving neighborhoods: single and multiple searching strategies in both steps of the hierarchical process. The proposed algorithm is tested over a real case study from an iron deposit where iron and aluminum oxide shows a strong bivariate dependency as well as a sharp inequality constraint. The results showed that the proposed hierarchical cosimulation with a multiple searching strategy provides satisfying results compared to the case when a single searching strategy is employed. Moreover, the proposed algorithm is compared to the conventional hierarchical cosimulation, which does not implement the inverse transform sampling integrated into the second simulation. The proposed methodology successfully reproduces inequality constraint, while conventional hierarchical cosimulation fails in this regard. However, it is demonstrated that the proposed methodology requires further improvement for better reproduction of global statistics (i.e., mean and standard deviation)

GEOSTATISTICAL MODELING OF HETEROGENEOUS GEO-CLUSTERS IN A COPPER DEPOSIT INTEGRATED WITH MULTINOMIAL LOGISTIC REGRESSION: AN EXERCISE ON RESOURCE ESTIMATION

Resource estimation is the main and primary step in the development of a mining project. Principally, it is necessary to first identify the geological domains through boreholes, model them at unsampled locations, and then evaluate the grade(s) of interest inside each built domain. The traditional determination of these categorical domains over the sampling points is suboptimal as it considers mostly-one or two variables from core logging. This leads to the neglect of the influence of other significant variables. To circumvent the problem of estimation domain identification, spatially dependent clustering machine learning algorithms can be of great help in detecting such domains. However, one problem that may appear when using these techniques is that the resulting geo-domains (geo-clusters) obtained by the clustering technique might be heterogeneous and show a non-stationary property. The reason is that the aim of these spatially dependent techniques is to produce compact and spatially contiguous clusters, which are well suited to establishing non-stationary geo-domains. This makes the procedure of modelling challenging as it necessitates the use of advanced geostatistical techniques to propagate the heterogeneous geo-clusters at unsampled locations. An algorithm is presented in this study that employs a non-stationary sequential indicator simulation paradigm to model such complex variability of heterogeneous geo-clusters. Since the spatial trends of underlying geoclusters are required in this simulation method, in this study, we propose the use of multinomial logistic regression to infer these trends. The algorithm was tested using an actual case study from a porphyry copper deposit in Iran, where Cu, Mo, Au, Rock Quality Designation (RQD), mineralization zones, alteration types, and rock types were employed to identify and spatially model the heterogeneous geo-domains in the entire deposit. The results were compared with a conventional sequential indicator simulation where no trend was used. An examination of the resulting maps using several evaluation criteria including visual inspection of the realizations, probability maps, reproduction of proportion of each geo-cluster, connectivity measures, and trend analysis, showed that the findings of the proposed algorithm were superior in modelling heterogeneous geo-domains

Perceived Stress among Undergraduate Dental Students in Relation to Gender, Clinical Training and Academic Performance

Cilj: Ovo istraživanje usmjereno je na procjenu uočenog stresa i njegovih izvora među studentima dodiplomskog studija dentalne medicine Sveučilišta Jazan u Saudijskoj Arabiji. Materijali i metode: U ovoj presječnoj studiji podatci su prikupljeni DES upitnikom. Ukupan rezultat stresa i rezultati po pojedinim područjima opisani su i analizirani različitim čimbenicima grupiranja – prema spolu, godini studija, bračnom stanju i prosjeku ocjena (GPA). Rezultati: Ukupno 366 studenata dentalne medicine pristalo je sudjelovati u ovom istraživanju. Među njima je bilo 57 posto žena. Ukupan DES iznosio je 1,67 ± 0,45. Studentice i oženjeni studenti pokazali su veći stres od svojih kolega. Stres se znatno povećavao na višim godinama studija. Suprotno tomu, pokazatelji stresa bili su niži kod sudionika s visokim GPA-om. Višestruke linearne regresijske analize pokazale su stupanj studija i spol kao važne neovisne determinante ukupnoga DES-a i većine područja stresa. Obje ove odrednice objasnile su 41 posto varijabilnosti u DES bodovima. Zaključak: DES među studentima dentalne medicine Sveučilišta Jazan umjeren je i neznatno povećan. Veći je među ženama i znatno se povećava na višim godinama studija. No studenti s višim GPA-om pokazali su nižu razinu stresa. Kliničko značenje: Smanjenje i/ili ublažavanje stresa među studentima dentalne medicine pozitivno će utjecati na njihov uspjeh u učenju, što će rezultirati boljim upravljanjem i brigom o pacijentu.Aim: This study aimed at evaluating the perceived stress and its sources among undergraduate dental students at Jazan University, Saudi Arabia. Materials and Methods: In this cross-sectional study, the data were collected using the DES questionnaire. The overall score of stress and scores by individual domains were described and analyzed by different grouping factors: gender, study level, marital status and GPA. Results: A total of 366 dental students agreed to take a part in this study. Up to 57% of the participants were females. The overall DES score was 1.67 ± 0.45. Female students and married students scored higher stress levels than their counterparts. Stress increased significantly among students as their educational level increased. Inversely, the stress levels were lower in participants with high GPA. Multiple linear regression analyses revealed that “Study level” and “Gender” were significant independent determinants of overall DES and, also, most of the stress domains. Forty one percent of the variability in DES score can be explained by these determinants. Conclusion: DES among dental students in Jazan University is moderate and slightly higher. It is higher among females and increases significantly with study progression. However, students who had higher GPA showed lower levels of stress. Clinical significance: Reduction and/or relief of stress among dental students will reflect positively on persistence and academic achievement, which will lead to better management and care of patients

Perceived Stress among Undergraduate Dental Students in Relation to Gender, Clinical Training and Academic Performance

Cilj: Ovo istraživanje usmjereno je na procjenu uočenog stresa i njegovih izvora među studentima dodiplomskog studija dentalne medicine Sveučilišta Jazan u Saudijskoj Arabiji. Materijali i metode: U ovoj presječnoj studiji podatci su prikupljeni DES upitnikom. Ukupan rezultat stresa i rezultati po pojedinim područjima opisani su i analizirani različitim čimbenicima grupiranja – prema spolu, godini studija, bračnom stanju i prosjeku ocjena (GPA). Rezultati: Ukupno 366 studenata dentalne medicine pristalo je sudjelovati u ovom istraživanju. Među njima je bilo 57 posto žena. Ukupan DES iznosio je 1,67 ± 0,45. Studentice i oženjeni studenti pokazali su veći stres od svojih kolega. Stres se znatno povećavao na višim godinama studija. Suprotno tomu, pokazatelji stresa bili su niži kod sudionika s visokim GPA-om. Višestruke linearne regresijske analize pokazale su stupanj studija i spol kao važne neovisne determinante ukupnoga DES-a i većine područja stresa. Obje ove odrednice objasnile su 41 posto varijabilnosti u DES bodovima. Zaključak: DES među studentima dentalne medicine Sveučilišta Jazan umjeren je i neznatno povećan. Veći je među ženama i znatno se povećava na višim godinama studija. No studenti s višim GPA-om pokazali su nižu razinu stresa. Kliničko značenje: Smanjenje i/ili ublažavanje stresa među studentima dentalne medicine pozitivno će utjecati na njihov uspjeh u učenju, što će rezultirati boljim upravljanjem i brigom o pacijentu.Aim: This study aimed at evaluating the perceived stress and its sources among undergraduate dental students at Jazan University, Saudi Arabia. Materials and Methods: In this cross-sectional study, the data were collected using the DES questionnaire. The overall score of stress and scores by individual domains were described and analyzed by different grouping factors: gender, study level, marital status and GPA. Results: A total of 366 dental students agreed to take a part in this study. Up to 57% of the participants were females. The overall DES score was 1.67 ± 0.45. Female students and married students scored higher stress levels than their counterparts. Stress increased significantly among students as their educational level increased. Inversely, the stress levels were lower in participants with high GPA. Multiple linear regression analyses revealed that “Study level” and “Gender” were significant independent determinants of overall DES and, also, most of the stress domains. Forty one percent of the variability in DES score can be explained by these determinants. Conclusion: DES among dental students in Jazan University is moderate and slightly higher. It is higher among females and increases significantly with study progression. However, students who had higher GPA showed lower levels of stress. Clinical significance: Reduction and/or relief of stress among dental students will reflect positively on persistence and academic achievement, which will lead to better management and care of patients

Research priority setting related to older adults: a scoping review to inform the Cochrane-Campbell Global Ageing Partnership work programme.

OBJECTIVE: To explore and map the findings of prior research priority-setting initiatives related to improving the health and well-being of older adults. DESIGN: Scoping review. DATA SOURCES: Searched MEDLINE, EMBASE, AgeLine, CINAHL and PsycINFO databases from January 2014 to 26 April 2021, and the James Lind Alliance top 10 priorities. ELIGIBILITY CRITERIA: We included primary studies reporting research priorities gathered from stakeholders that focused on ageing or the health of older adults (≥60 years). There were no restrictions by setting, but language was limited to English and French. DATA EXTRACTION AND SYNTHESIS: We used a modified Reporting Guideline for Priority Setting of Health Research (REPRISE) guideline to assess the transparency of the reported methods. Population-intervention-control-outcome (PICO) priorities were categorised according to their associated International Classification of Health Interventions (ICHI) and International Classification of Functioning (ICF) outcomes. Broad research topics were categorised thematically. RESULTS: Sixty-four studies met our inclusion criteria. The studies gathered opinions from various stakeholder groups, including clinicians (n=56 studies) and older adults (n=35), and caregivers (n=24), with 75% of the initiatives involving multiple groups. None of the included priority-setting initiatives reported gathering opinions from stakeholders located in low-income or middle-income countries. Of the priorities extracted, 272 were identified as broad research topics, while 217 were identified as PICO priorities. PICO priorities that involved clinical outcomes (n=165 priorities) and interventions concerning health-related behaviours (n=59) were identified most often. Broad research topics on health services and systems were identified most often (n=60). Across all these included studies, the reporting of six REPRISE elements was deemed to be critically low. CONCLUSION: Future priority setting initiatives should focus on documenting a more detailed methodology with all initiatives eliciting opinions from caregivers and older adults to ensure priorities reflect the opinions of all key stakeholder groups

Subcutaneous Injection of Allogeneic Adipose-Derived Mesenchymal Stromal Cells in Psoriasis Plaques: Clinical Trial Phase I

Objective: Mesenchymal stromal cells (MSCs) play immunomodulatory role in various autoimmune diseases. Previouspre-clinical and clinical studies have shown that MSCs could be a therapeutic modality for psoriasis. However, themechanisms of treatment and its possible side effects are under investigation. In this study, the safety and probableefficacy of injecting allogeneic adipose-derived mesenchymal stromal cells (ADSCs) in psoriatic patients were evaluated.Materials and Methods: In this phase I clinical study with six months of follow-up, total number of 1×106 or 3×106cells/cm2 of ADSCs were injected into the subcutaneous tissue of each plaque as a single dose in three males and twofemales (3M/2F) with a mean age of 32.8 ± 8.18. The primary outcome was safety. Changes in clinical and histologicalindexes, the number of B and T lymphocytes in local and peripheral blood, and serum levels of inflammatory cytokineswere assessed. Paired t test was used to compare variables at two time points (baseline and six months after injection)and repeated measures ANOVA test was utilized for variables at three time points in follow-up visits.Results: No major adverse effects such as burning, pain, itching, or any systemic side effects were observed followingADSCs injection, and the lesions showed slight to considerable improvement after injection. The mRNA expressionlevels of pro-inflammatory factors were reduced in the dermis of the patients after injection. The increased expressionlevel of Foxp3 transcription factor in the patient blood samples suggested modulation of inflammation after ADMSCsadministration. Six months after the intervention, no major side effects were reported, but skin thickness, erythema, andscaling of the plaques, as well as the PASI score, were decreased in majority of patients.Conclusion: Our study suggested that ADSC injection could be considered as a safe and effective therapeuticapproach for psoriatic plaques (registration number: IRCT20080728001031N24)