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Accurate coal seam identification is crucial in coal mining to prevent resource wastage and potential damage to coal seams from misplaced explosives. The current industry standard involves drilling past the seam and refilling the hole, a resource-intensive process. Manual seam detection is error-prone, and geophysical logging, performed for only a subset of drill holes, is costly and time-consuming. Monitor-While-Drilling (MWD) data captures drill response metrics like rotary speed and torque, influenced by local geology. These MWD measurements offer insights into geology, including hardness and rock type; They can be used for real-time rock recognition using advanced artificial intelligence techniques. This study focuses on developing tools for precise coal recognition and identification of the top of coal seams using MWD data. Several Machine Learning classifiers are employed, each providing unique data interpretations, and their results are integrated into a more reliable prediction. An artificial neural network is used for rock density regression, which is then used to correct depth offset between geophysical loggings and drill MWD data. The research demonstrates that MWD data can enable real-time coal seam identification, reducing the reliance on time-consuming and expensive geophysical logging. The integrated model accurately identifies the top of coal seams within a ± 20 cm margin. [ABSTRACT FROM AUTHOR]

In this paper, a mixed integer programming model for solving the short term planning problem in surface mining is presented. This model will establish the sequence of mining for a period ranging from days to several months. This involves determining which blocks of the geological model will be extracted and in what order, indicating the movement of the shovels and meeting the production capacity of equipment. To reduce the computation time, four sets of strategies are proposed. [ABSTRACT FROM AUTHOR]

A training image free, high-order sequential simulation method is proposed herein, which is based on the efficient inference of high-order spatial statistics from the available sample data. A statistical learning framework in kernel space is adopted to develop the proposed simulation method. Specifically, a new concept of aggregated kernel statistics is proposed to enable sparse data learning. The conditioning data in the proposed high-order sequential simulation method appear as data events corresponding to the attribute values associated with the so-called spatial templates of various geometric configurations. The replicates of the data events act as the training data in the learning framework for inference of the conditional probability distribution and generation of simulated values. These replicates are mapped into spatial Legendre moment kernel spaces, and the kernel statistics are computed thereafter, encapsulating the high-order spatial statistics from the available data. To utilize the incomplete information from the replicates, which partially match the spatial template of a given data event, the aggregated kernel statistics combine the ensemble of the elements in different kernel subspaces for statistical inference, embedding the high-order spatial statistics of the replicates associated with various spatial templates into the same kernel subspace. The aggregated kernel statistics are incorporated into a learning algorithm to obtain the target probability distribution in the underlying random field, while preserving in the simulations the high-order spatial statistics from the available data. The proposed method is tested using a synthetic dataset, showing the reproduction of the high-order spatial statistics of the sample data. The comparison with the corresponding high-order simulation method using TIs emphasizes the generalization capacity of the proposed method for sparse data learning., (© The Author(s) 2021.)

The present work proposes a new high-order simulation framework based on statistical learning. The training data consist of the sample data together with a training image, and the learning target is the underlying random field model of spatial attributes of interest. The learning process attempts to find a model with expected high-order spatial statistics that coincide with those observed in the available data, while the learning problem is approached within the statistical learning framework in a reproducing kernel Hilbert space (RKHS). More specifically, the required RKHS is constructed via a spatial Legendre moment (SLM) reproducing kernel that systematically incorporates the high-order spatial statistics. The target distributions of the random field are mapped into the SLM-RKHS to start the learning process, where solutions of the random field model amount to solving a quadratic programming problem. Case studies with a known data set in different initial settings show that sequential simulation under the new framework reproduces the high-order spatial statistics of the available data and resolves the potential conflicts between the training image and the sample data. This is due to the characteristics of the spatial Legendre moment kernel and the generalization capability of the proposed statistical learning framework. A three-dimensional case study at a gold deposit shows practical aspects of the proposed method in real-life applications., (© The Author(s) 2019.)

Multiple-point simulations have been introduced over the past decade to overcome the limitations of second-order stochastic simulations in dealing with geologic complexity, curvilinear patterns, and non-Gaussianity. However, a limitation is that they sometimes fail to generate results that comply with the statistics of the available data while maintaining the consistency of high-order spatial statistics. As an alternative, high-order stochastic simulations based on spatial cumulants or spatial moments have been proposed; however, they are also computationally demanding, which limits their applicability. The present work derives a new computational model to numerically approximate the conditional probability density function (cpdf) as a multivariate Legendre polynomial series based on the concept of spatial Legendre moments. The advantage of this method is that no explicit computations of moments (or cumulants) are needed in the model. The approximation of the cpdf is simplified to the computation of a unified empirical function. Moreover, the new computational model computes the cpdfs within a local neighborhood without storing the high-order spatial statistics through a predefined template. With this computational model, the algorithm for the estimation of the cpdf is developed in such a way that the conditional cumulative distribution function (ccdf) can be computed conveniently through another recursive algorithm. In addition to the significant reduction of computational cost, the new algorithm maintains higher numerical precision compared to the original version of the high-order simulation. A new method is also proposed to deal with the replicates in the simulation algorithm, reducing the impacts of conflicting statistics between the sample data and the training image (TI). A brief description of implementation is provided and, for comparison and verification, a set of case studies is conducted and compared with the results of the well-established multi-point simulation algorithm, filtersim. This comparison demonstrates that the proposed high-order simulation algorithm can generate spatially complex geological patterns while also reproducing the high-order spatial statistics from the sample data.

A pilot-scale demonstration of surfactant-enhanced aquifer remediation (SEAR) was conducted during the summer of 2000 at the Bachman Road site in Oscoda, MI. Part two of this two-part paper describes results from partitioning and nonpartitioning tracer tests, SEAR operations, and post-treatment monitoring. For this field test, 68 400 L of an aqueous solution of 6% (wt) Tween 80 were injected to recover tetrachloroethene-nonaqueous phase liquid (PCE-DNAPL) from a shallow, unconfined aquifer. Results of a nonreactive tracer test, conducted prior to introducing the surfactant solution, demonstrate target zone sweep and hydraulic control, confirming design-phase model predictions. Partitioning tracer test results suggest PCE-DNAPL saturations of up to 0.74% within the pilot-scale treatment zone, consistent with soil core data collected during site characterization. Analyses of effluent samples taken from the extraction well during SEAR operations indicate that a total of 19 L of PCE and 95% of the injected surfactant were recovered. Post-treatment monitoring indicated that PCE concentrations at many locations within the treated zone were reduced by as much as 2 orders of magnitude from pre-SEAR levels and had not rebounded 450 days after SEAR operations ceased. Pilot-scale costs ($365 900) compare favorably with design-phase cost estimates, with approximately 10% of total costs attributable to the intense sampling density and frequency. Results of this pilot-scale test indicate that careful design and implementation of SEAR can result in effective DNAPL mass removal and a substantial reduction in aqueous concentrations within the treated source zone under favorable geologic conditions

A pilot-scale demonstration of surfactant-enhanced aquifer remediation (SEAR) was conducted in July 2000 at the Bachman Road site located in Oscoda, MI. The Bachman aquifer is a shallow, relatively homogeneous, unconfined aquifer formation composed primarily of sandy glacial outwash with relatively low organic carbon content (0.02 wt %). A 6 wt % aqueous solution of Tween 80 (a nonionic, food-grade surfactant) was flushed through a localized dense nonaqueous phase liquid (DNAPL) source zone to recover approximately 19 L of tetrachloroethene (PCE). Post-treatment monitoring revealed PCE concentrations were reduced by up to 2 orders of magnitude within the source zone, and there was no evidence of concentration rebound after more than 450 d. Concentrations of PCE dechlorination products (trichloroethene, cis-1,2-dichloroethene) 450 d after SEAR operations ceased were more than 2 orders of magnitude greater than pretreatment values, suggesting stimulation of native dechlorination activity. Post-treatment monitoring detected increased concentrations of volatile fatty acids generated from the fermentation of residual-level Tween 80 surfactant. These field data suggest that Tween 80 not only induced and maintained anaerobiosis but also provided reducing equivalents to reductively dechlorinating populations present in the oligotrophic Bachman aquifer. Experience from this site supports application of staged treatment strategies that couple SEAR and microbial reductive dechlorination to enhance mass removal and reduce contaminant mass flux emanating from treated source zones.

Lung injury is a frequent consequence of oxygen (O2) therapy administered to newborns and adults with respiratory distress. Acute exposure to hyperoxia results in a well-described pathophysiologic response in the lungs. Because inflammation is an important component of pulmonary O2 toxicity, we have an interest in identifying the inflammatory mediators that increase during hyperoxia. Platelet-endothelial cell adhesion molecule-1 (PECAM-1), a member of the immunoglobulin superfamily that is expressed at the junctions between endothelial cells, is essential to the transendothelial migration of leukocytes. We hypothesized that increased expression of PECAM-1 occurs in pulmonary endothelial cells during hyperoxic lung injury. Adult mice were exposed to 100% O2 for up to 96 h. We analyzed PECAM-1 expression by RNA blot hybridization, in situ hybridization, and immunohistochemistry. A increase in PECAM-1 mRNA was seen as soon as 2 d of hyperoxia relative to unexposed control mice. PECAM-1 mRNA and protein were found in endothelial cells of both large and small arteries. The expression of PECAM-1 in capillary vessels was further confirmed using in situ hybridization at the electron microscope level. This increase in PECAM-1 expression coincided with the appearance of leukocytes in lung tissue. These observations suggest that PECAM-1 expression is a relatively early step in the inflammation cascade, and intervention at this phase may be critical to the prevention of further damage.

Unlabelled: Fetal tracheal occlusion (TO) has been shown to lead to lung hyperplasia in various animal models, and this procedure has already been carried out in human fetuses with congenital diaphragmatic hernia (CDH). However, the authors previously showed that TO caused a decrease in type II pneumocytes., Purpose: The aim of this study is to examine the effects of TO and release on type II pneumocytes., Method: To was carried out with a Swan Ganz or Fogarty catheter in fetal sheep at 116 to 118 days of gestation. TO was maintained for 2 weeks followed by deflation of the balloon for 1 week before delivery, in group 1; in group 2, TO was maintained for 19 days and released 2 days before delivery. Group 3 consisted of previously reported animals who had TO maintained until birth. Unoperated twins served as controls. All specimens were analyzed using the surfactant protein C (SP-C) mRNA as a specific marker for type II pneumocytes. We used Northern Blot and in situ hybridization techniques to quantify total SP-C and the density of type II cells. Electron microscopy (EM) was also used to evaluate and quantitate type II cells., Results: TO resulted in significant lung growth in all groups. In situ hybridization and Northern Blot analysis showed that there was a complete recovery of type II cells in group 1 versus controls. Quantitative EM analysis confirmed these findings. In group 2 the number of type II cells was decreased but there was an increase in SP-C content per type II cell versus group 3., Conclusion: Lung growth after TO appears to occur at the expense of type II cell differentiation. This effect is reversible with the release of TO before birth in this animal model.

It was previously shown that tracheal obstruction accelerated fetal lung growth and eventually reversed the pulmonary hypoplasia in experimental diaphragmatic hernia. We have successfully developed a reversible tracheal obstruction technique in fetal sheep using balloon occlusion and showed that 3 wk of obstruction induced significant lung growth of the same magnitude as the tracheal ligation. The purpose of this study was to examine the effects of 1 and 3 wk of tracheal occlusion on the alveolar cell population with specific attention to the type II pneumocytes. We first showed that 1 wk of occlusion induced a significant increase in lung weight and in alveolar surface area. We then used the surfactant protein C (SP-C) mRNA as a specific marker of differentiated type II pneumocytes. Total RNA was isolated from fetal sheep lung with or without tracheal occlusion, and Northern blots were hybridized with a cDNA probe specific for the sheep SP-C. The results show a dramatic decrease in SP-C mRNA expression (8.8-fold, p < 0.01). In situ hybridization showed a marked decrease in the density of cells expressing SP-C, as well as the amount of SP-C mRNA expressed by the cells. The effect was present as early as 1 wk of occlusion. The sparseness of type II pneumocytes was further confirmed by electron microscopy. We thus conclude that tracheal obstruction causes a profound decrease in the number of type II pneumocytes in the lungs. Given the crucial role of type II pneumocytes in surfactant production, we could speculate that, if tracheal occlusion is able to accelerate lung growth, the final product is probably surfactant-deficient.

Since the original descriptions of the radiologic appearance of implantable cardiac defibrillators by Lurie et al. [1] and Goodman et al. [2] in 1985, rapid growth has occurred in the complexity and variety of models available. Originally, all devices were surgically placed in or on the pericardium. Now, some devices are inserted by intravascular catheters with part of the device buried in the chest wall, avoiding the need for thoracotomy. Initially, these devices were used as defibrillators for treatment of tachyarrythmia and ventricular fibrillation. Now they serve as pacemakers for both tachy- and bradyarrhythmias and can act as cardioverters or defibrillators if required. Radiologists must be familiar with the appearances of these devices as their use becomes more widespread. In this article, the electrophysiology of these devices is briefly reviewed and the typical radiologic appearances are presented along with common radiologically recognizable complications.

The role of the biliary pathway in the homeostasis of the vitamin D3 (D3) group of compounds is poorly understood. The purpose of the studies was to investigate the biliary excretion pattern of materials derived from the parent compound D3 and from the hormone 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) during constant iv infusion, and to probe the influence of 1,25(OH)2D3 pretreatment on the excretion into the bile of D3-derived materials. Under anesthesia, the bile duct, duodenum (for bile replacement), and jugular veins were cannulated. The experiments were then carried out in fully awake rats with access to food and water ad libitum during a period of 6 h. Data indicate that before steady state was reached, biliary excretion of 1,25(OH)2[3H]D3 was much more important than that of [14C]D3 with bile/plasma concentration ratios above 1 in 1,25(OH)2[3H]D3-infused animals from the 15th-60th min of infusion compared to ratios between 0.12-0.40 in [14C]D3-infused rats (P less than 0.0001); this led to a cumulative excretion 6.3-fold higher after 1,25(OH)2[3H]D3 than after [14C]D3 administration, with 3.9 +/- 0.4% and 0.6 +/- 0.1% of the dose being recovered into the bile during the first hour of excretion. However, once stable plasma concentrations were reached, the rate of excretion of the two compounds became similar, with bile/plasma concentration ratios of 0.64 +/- 0.02 and 0.70 +/- 0.02 (P greater than 0.05), and plasma bile clearance of 26.4 +/- 1.0 and 25.7 +/- 1.7 microliters/min.kg for 1,25(OH)2[3H]D3 and [14C]D3, respectively (P greater than 0.05). During that period, the MCR of 1,25(OH)2D3 was estimated to be 118.3 +/- 10.5 microliters/min.kg. On the other hand, 1,25(OH)2D3 pretreatment as constant ip infusion (14 pmol/24 h for 6 days) significantly increased bile flow [1,25(OH)2D3 treated, 44.9 +/- 1.6 microliters/min.kg; untreated, 36.6 +/- 0.5 microliters/min.kg, P less than 0.01)], leading to significant increases in the plasma bile clearance of [14C]D3-derived compounds early in the course of the study (P less than 0.004) in the presence of similar bile/plasma concentration ratios in the two groups. During the steady state phase of investigation, however, bile/plasma concentration ratios became lower in 1,25(OH)2D3-than in placebo-treated animals (P less than 0.05), but due to the 1,25(OH)2D3-mediated increase in bile flow, similar plasma bile clearances were observed in both groups.(ABSTRACT TRUNCATED AT 400 WORDS)

Recent studies indicate the adherence of many patients with rheumatoid arthritis (RA) to their treatment regimens is poor. Management of this problem depends on identification of noncompliant patients, followed by interventions to increase their level of adherence. In this study, 63 patients with RA receiving salicylate drugs completed a questionnaire during an outpatient visit. The questionnaire contained items believed to be predictive of future compliance, including patient self-predictions regarding future compliance, ratings of behavior in similar situations and barriers to compliance, such as ease of transportation to the clinic. Compliance was estimated via a salicylate assay that was taken during a subsequent outpatient appointment. Multivariate analyses of our data revealed that significant predictions could be made regarding future compliance, with 75% of the noncompliant patients correctly identified. Variables contributing significantly included behavioral self-predictions and a measure of current behavior in similar situations, as assessed by a salicylate assay that was collected during the 1st outpatient visit.

Two hundred and eight adults who requested outpatient treatment at a community mental health center were asked to complete brief questionnaires immediately prior to and after their first therapy session. Questionnaires contained items that pertained to self-predicted length of stay in psychotherapy, situational barriers to regular attendance, and past behavior in similar situations (e.g., appointment-keeping with other health care professionals). Therapists also were asked to make predictions with regard to client length of stay. Questionnaire data were analyzed via a series of double cross-validated multiple regression and discriminant function equations, and results indicated that client and therapist predictions of length of stay in therapy were the most stable and consistent correlates of attendance behavior.