Improved mine waste dump planning through integration of geochemical and mineralogical data and mixed integer programming: Reducing acid rock generation from mine waste.

Although the environmental significance of acid rock drainage (ARD) generated from mining wastes is well known, selecting the appropriate ARD management strategy can prove a complicated task. Chemical methods are favored for initial mine waste characterization but using these exclusively can overlook key factors, e.g., mineralogy, which controls the formation and elution of ARD. This paper first presents an ARD waste rock classification developed on Triple Characterization Criteria (TCC) which considers three input parameters: neutralizing potential ratio (NPR), net acid generation (NAG pH), and modal mineralogy weathering index (MMWI) values. Second, a new mixed-integer programming (MIP) model to guide waste dump construction with the dual aim of preventing ARD across the life-of-mine (LOM) and reducing waste rock re-handling, is introduced. Last, the spatial distribution of TCC in a planned waste dump is simulated via geo-statistical techniques to evaluate the MIP model. The proposed waste rock classification and dump planning model has been tested at an iron mine. The results of the MIP modeling and simulation of TCC showed the successful prevention of ARD by achieving large values of TCC (NPR ≥2, NAG pH ≥ 4.5, and MMWI ≥4.7) for dump cells, with the planned mine production maintained. The integrated TCC approach introduced in this study is intended to enable mine operators, at the start of the LOM, to effectively forecast ARD from future waste rock. Further, the MIP model will facilitate development of a mine schedule that optimizes the use of the waste materials based on TCC values. If used correctly, the TCC and MIP model have the potential to enable mine operators to reduce their environmental footprint across the entire LOM.

Correction: The Good Food for Learning Universal Curriculum-Integrated Healthy School Lunch Intervention: Protocol for a Two-Year Matched Control Pre-Post and Case Study.

[This corrects the article DOI: 10.2196/30899.].

The Good Food for Learning Universal Curriculum-Integrated Healthy School Lunch Intervention: Protocol for a Two-Year Matched Control Pre-Post and Case Study.

BACKGROUND: Good nutrition affects children's health, well-being, and learning, and schools offer an important setting to promote healthy behaviors that can last a lifetime. Once children reach school age, they spend more of their waking hours in school than in any other environment. Children's eating habits may be easier to influence than those of adults. In Canada, households with children are more likely to experience food insecurity, and school food programs that are universally available to all children can support the development of healthy eating patterns across groups of varying socioeconomic status. There is a significant gap in the rigorous community-engaged academic research on the impact of school meal programs, especially universal ones. OBJECTIVE: The aim of this population health intervention research is to study the impact of a 2-year universal, curriculum-integrated healthy school lunch program in elementary schools in Saskatoon, Saskatchewan, Canada, on food consumption, dietary quality and food and nutrition-related knowledge, attitudes, and practices. METHODS: This population health intervention study will be conducted in 2 intervention elementary schools matched with 2 control schools. We will collect preintervention data, including objective measurements of food eaten at school and food-related knowledge, attitudes, and behaviors. This will be followed by the intervention itself, along with qualitative case studies of the intervention process in the 2 intervention schools. Then, we will collect postintervention data similar to the preintervention data. Finally, we will finish the data analysis and complete the ongoing sharing of learning from the project. RESULTS: This study was funded in April 2020 but because of the COVID-19 pandemic, data collection did not begin until May 2021. The intervention will begin in September 2021 and end in June 2023, with end point data collection occurring in May and June 2023. The case study research will begin in September 2021 and will be ongoing for the duration of the intervention. CONCLUSIONS: The opportunity we have to systematically and comprehensively study a curriculum-integrated school lunch program, as well as the promising practices for school food programs across Canada, is without precedent. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30899.

Multiple sclerosis incidence rate in southern Iran: a Bayesian epidemiological study.

BACKGROUND: Multiple Sclerosis (MS) remains to be a public health challenge, due to its unknown biological mechanisms and clinical impacts on young people. The prevalence of this disease in Iran is reported to be 5.30 to 74.28 per 100,000-person. Because of high prevalence of this disease in Fars province, the purpose of this study was to assess the spatial pattern of MS incidence rate by modeling both the associations s of spatial dependence between neighboring regions and risk factors in a Bayesian Poisson model, which can lead to the improvement of health resource allocation decisions. METHOD: Data from 5468 patients diagnosed with MS were collected, according to the McDonald's criteria. New cases of MS were reported by the MS Society of Fars province from 1991 until 2016. The association between the percentage of people with low vitamin D intake, smoking, abnormal BMI and alcohol consumption in addition to spatial structure in a Bayesian spatio-temporal hierarchical model were used to determine the relative risk and trend of MS incidence rate in 29 counties of Fars province. RESULTS: County-level crude incidence rates ranged from 0.22 to 11.31 cases per 100,000-person population. The highest relative risk was estimated at 1.80 in the county of Shiraz, the capital of Fars province, while the lowest relative risk was estimated at 0.11 in Zarindasht county in southern of Fars. The percentages of vitamin D supplementation intake and smoking were significantly associated with the incidence rate of MS. The results showed that 1% increase in vitamin D supplementation intake is associated with 2% decrease in the risk of MS and 1% increase in smoking is associated with 16% increase in the risk of MS. CONCLUSION: Bayesian spatio-temporal analysis of MS incidence rate revealed that the trend in the south and south east of Fars province is less steep than the mean trend of this disease. The lower incidence rate was associated with a higher percentage of vitamin D supplementation intake and a lower percentage of smoking. Previous studies have also shown that smoking and low vitamin D, among all covariates or risk factors, might be associated with high incidence of MS.

Development of a MIP model to maximize NPV and minimize adverse environmental impact-a heuristic approach.

Block sequencing is of great importance in an open-pit mining operation. Sequencing is usually performed to maximize the net present value (NPV). Also, from the environmental viewpoint, the sequence of dumping mined materials is of significant value in the sulfide mines. The potential acid-forming (PAF) waste rocks in these mines can seriously damage the environment due to the formation of acid mine drainage (AMD). To prevent the exposition of the PAF materials, it is essential to design suitable block sequencing. For this purpose, encapsulation of the PAF rocks by non-acid forming (NAF) rocks should be considered during waste dumping. However, this method can impose unnecessary re-handling costs. This issue is due to the determination of the waste-dump sequence based on improper block sequencing obtained from the previous models with the NPV maximization strategy. In the present study, a mixed-integer programming (MIP) model is proposed for generating proper block sequencing taking into account the composition of waste rocks. The main objective of the proposed MIP model is to maximize NPV and minimize the destructive environmental effects of PAF materials dumping. The CPLEX solver was applied to solve the proposed model in small datasets. Then, an artificial bee colony (ABC) is implemented to find out optimum block sequencing and waste dumping (BSWD) on a large scale. The proposed approach was examined employing several sets of data. The obtained results were compared with those of the CPLEX solver as a benchmark. An approximate gap of 2% demonstrates the efficiency of the proposed approach.

Measurement Invariance and Psychometric Analysis of Oxford Happiness Inventory Scale across Gender and Marital Status.

BACKGROUND: The Oxford Happiness Inventory (OHI) is a self-report tool to measure happiness. A brief review of previous studies on OHI showed the lack of evaluation of OHI fairness/equivalence in measuring happiness among identified groups. METHODS: To examine the psychometric properties and measurement invariance of the OHI, responses of 500 university students were analyzed using item response theory and ordinal logistic regression (OLR). Relevant measures of effect size were utilized to interpret the results. Differential test functioning was also evaluated to determine whether there is an overall bias at the test level. RESULTS: OLR analysis detected four items across gender and two items across marital status to function differentially. An assessment of effect sizes implied negligible differences for practical considerations. CONCLUSIONS: This study was a significant step towards providing theoretical and practical information regarding the assessment of happiness by presenting adequate evidence regarding the psychometric properties of OHI.

Measurement invariance and psychometric analysis of Kutcher Adolescent Depression Scale across gender and marital status.

BACKGROUND: The Kutcher Adolescent Depression Scale (KADS) has been studied across Canada and some other countries during the past almost 15 years. The scale is a self-report tool to diagnose and monitor clinical depression in adolescents. A brief review of previous studies on KADS showed the lack of evaluation of KADS fairness/equivalence in measuring depression among identified groups. METHODS: To examine the psychometric properties and measurement invariance of the KADS, responses of 407 participants were analyzed using item response theory (IRT) and ordinal logistic regression (OLR). Relevant measures of effect size were utilized to interpret the results. RESULTS: Findings of the parallel factor analysis confirmed unidimensionality of the KADS and the partial credit IRT model found to be the best fitting model for analyzing the scale. OLR analysis detected three items across gender and one item across marital status to function differentially. An assessment of effect sizes implied negligible differences for practical considerations. LIMITATIONS: A note of caution is necessary with respect to interpreting results of measurement invariance across Gender. The sample analyzed in this study was predominantly female and this might have affected our findings. A similar analysis with a more balanced sample is recommended. CONCLUSIONS: This study was a significant step towards providing theoretical and practical information regarding the assessment of depression among adolescents by presenting adequate evidence regarding the psychometric properties of KADS-11. Future studies may look at different methods for assessing invariance and different groups for strengthening conclusions with respect to the KADS.

Association between demographic and radiographic characteristics of the schneiderian membrane and periapical and periodontal diseases using cone-beam computed tomography scanning: A retrospective study.

Background. This study was undertaken to assess the pathological and spatial associations between periapical and periodontal diseases of the maxillary first molars and thickening of maxillary sinus mucosa with cone-beam computed tomography. Methods. A total of 132 CBCT images of subjects 20‒60 years of age were evaluated retrospectively. The patients' sex and age and demographic and pathologic findings of the maxillary sinus in the first molar area were recorded, graded and analyzed. Results. Approximately 59% of patients were male and 41% were female, with no significant difference in the thickness of schneiderian membrane between males and females. Based on the periapical index scoring, the highest frequency was detected in group 1. Based on the results of ANOVA, there were no significant differences in the frequencies of endodontic‒periodontal lesions and an increase in schneiderian membrane thickness. There were significant relationships between periapical and periodontal infections (P<0.001) and schneiderian membrane thickness. Furthermore, a significant relationship was detected between the thickness of the schneiderian membrane and the distance between the sinus floor and the root apices (P=0.38). Conclusion. A retrospective inspection of CBCT imaging revealed that periapical lesions and periodontal infections in the posterior area of the maxilla were associated with thickening of the schneiderian membrane. In addition, there was a significant relationship between the location of maxillary posterior teeth, i.e. the thickness of bone from the root apex to the maxillary sinus floor, and schneiderian membrane thickness.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data.

BACKGROUND: The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. METHODS: The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. RESULTS: Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. CONCLUSIONS: The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

The Sound Access Parent Outcomes Instrument (SAPOI): Construction of a new instrument for children with severe multiple disabilities who use cochlear implants or hearing aids.

OBJECTIVE: To report on the Phase 2 development of the Sound Access Parent Outcomes Instrument (SAPOI), a new instrument focused on formalizing outcomes that parents of children with severe multiple disabilities (SMD) who use amplification prioritize as important. METHODS: Phase 2 of this project involved item selection and refinement of the SAPOI based on (a) Phase 1 study participant input, (b) clinical specialist feedback, and (c) test-retest instrument reliability. Phase 1 participant responses were utilized to construct a draft version of the SAPOI. Next, clinical specialists examined the instrument for content validity and utility and instrument reliability was examined through a test-retest process with parents of children with SMD. RESULTS: The draft SAPOI was constructed based on Phase 1 participant input. Clinical specialists supported content validity and utility of the instrument and the inclusion of 19 additional items across four categories, namely Child Affect, Child Interaction, Parent Well-being, and Child's Device Use. The SAPOI was completed twice at one-month intervals by parents of children with SMD to examine instrument reliability across the four categories (Child Affect, Child Interaction, Parent Well-being, and Child's Device Use). Instrument reliability was strong-to-excellent across all four sections. DISCUSSION: The SAPOI shows promise as a much-needed addition to the assessment battery currently used for children with SMD who use cochlear implants and hearing aids. It provides valuable information regarding outcomes resulting from access to sound in this population that currently used assessments do not identify.

Context transfer in reinforcement learning using action-value functions.

This paper discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this paper, implies knowledge transfer between source and target tasks that share the same environment dynamics and reward function but have different states or action spaces. In other words, the agents learn the same task while using different sensors and actuators. This requires the existence of an underlying common Markov decision process (MDP) to which all the agents' MDPs can be mapped. This is formulated in terms of the notion of MDP homomorphism. The learning framework is Q-learning. To transfer the knowledge between these tasks, the feature space is used as a translator and is expressed as a partial mapping between the state-action spaces of different tasks. The Q-values learned during the learning process of the source tasks are mapped to the sets of Q-values for the target task. These transferred Q-values are merged together and used to initialize the learning process of the target task. An interval-based approach is used to represent and merge the knowledge of the source tasks. Empirical results show that the transferred initialization can be beneficial to the learning process of the target task.