Voltage-temperature charge verification testing of 34 ampere-hour nickel-cadmium cells

This testing was designed to evaluate various voltage-temperature (V-T) charge curves for use in low-Earth-orbit (LEO) applications of nickel-cadmium battery cells. The trends established relating V-T level to utilizable capacity were unexpected. The trends toward lower capacity at higher V-T levels was predominant in this testing. This effect was a function of the V-T level, the temperature, and the cell history. This effect was attributed to changes occurring in the positive plate. The results imply that for some applications, the use of even lower V-T levels may be warranted. The need to limit overcharge, especially in the early phases of missions, is underlined by this test program

Estimating Risks in Emerging Soil Remediation Technologies

The Department of Energy is focusing a long-term development effort on producing cheaper, safer, and faster state-of-the-art soil remediation technologies. To assist with the management of these innovative technology development projects, ways of quantifiably measuring technical risk were investigated through a detailed literature review. \u27Technical risk\u27 was defined in this study as the combination of the consequences of undesired events and their likelihood. Careful design of the inputs into a technology selection decision support system accounted for the uncertainty in forecasting final characteristics of remediation technologies still in the early phases of R&D. Experts made subjective probability estimates of these cost, schedule, and performance factors. Examination of several measures of final cost and schedule risk focused on communicating the risks inherent in different technological alternatives to the technology manager for operational, not theoretical, use. These risk measures included subjective measures, using utility theory, and objective measures, using variation about an expected value. A new measure was developed, the expected unfavorable deviation, which is similar but superior to the semi-variance as a measure of downside risk. These simple risk measures can be used whenever uncertainty is expressed through probability distributions of cost, schedule, and performance characteristics

A 34 ampere-hour nickel-cadmium minimum trickle charge testing

The current rates used for trickle charging batteries are critical in maintaining a full charge and in preventing an overcharge condition. The importance of the trickle charge rate comes from the design, maintenance and operational requirements of an electrical power system. The results of minimum trickle charge testing performed on six 34 ampere-hour, nickel-cadmium cells manufactured by General Electric are described. The purpose of the testing was to identify the minimum trickle charge rates at temperatures of 15 C and 30 C

Intraduodenal sarcoma recurrence of retroperitoneal origin: an unusual cause for a duodenal obstruction.

Soft tissue sarcomas are uncommon tumors, and intraduodenal soft tissue sarcoma manifestation is even more rare. Only three cases of intraduodenal sarcomas have been reported in the literature thus far. Here, we report a case of an intraduodenal recurrence of a retroperitoneal sarcoma causing bowel obstruction. This unusual recurrence pattern likely relates to the patient's previous resection and radiation treatment, and highlights the benefits, limitations and follow-up strategies after multimodality treatment

Comparison of Estimation Procedures for Multilevel AR(1) Models

To estimate a time series model for multiple individuals, a multilevel model may be used.In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo.Furthermore, we examine the difference between modeling fixed and random individual parameters.To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25), the number of individuals per sample (10 or 25), the mean of the autocorrelation (-0.6 to 0.6 inclusive, in steps of 0.3) and the standard deviation of the autocorrelation (0.25 or 0.40).We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators.The fixed estimators profit slightly more from a higher number of time points than the random estimators.When possible, random estimation is preferred to fixed estimation.The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates).Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures

A tutorial on regression-based norming of psychological tests with GAMLSS

A norm-referenced score expresses the position of an individual test taker in the reference population, thereby enabling a proper interpretation of the test score. Such normed scores are derived from test scores obtained from a sample of the reference population. Typically, multiple reference populations exist for a test, namely when the norm-referenced scores depend on individual characteristic(s), as age (and sex). To derive normed scores, regression-based norming has gained large popularity. The advantages of this method over traditional norming are its flexible nature, yielding potentially more realistic norms, and its efficiency, requiring potentially smaller sample sizes to achieve the same precision. In this tutorial, we introduce the reader to regression-based norming, using the generalized additive models for location, scale, and shape (GAMLSS). This approach has been useful in norm estimation of various psychological tests. We discuss the rationale of regression-based norming, theoretical properties of GAMLSS and their relationships to other regression-based norming models. Based on 6 steps, we describe how to: (a) design a normative study to gather proper normative sample data; (b) select a proper GAMLSS model for an empirical scale; (c) derive the desired normed scores for the scale from the fitted model, including those for a composite scale; and (d) visualize the results to achieve insight into the properties of the scale. Following these steps yields regression-based norms with GAMLSS for a psychological test, as we illustrate with normative data of the intelligence test IDS-2. The complete R code and data set is provided as online supplemental material

The role of hydrothermal activity in the formation of karst-hosted manganese deposits of the Postmasburg Mn Field, Northern Cape Province, South Africa

The Postmasburg Manganese Field (PMF), Northern Cape Province, South Africa, once represented one of the largest sources of manganese ore worldwide. Two belts of manganese ore deposits have been distinguished in the PMF, namely the Western Belt of ferruginous manganese ores and the Eastern Belt of siliceous manganese ores. Prevailing models of ore formation in these two belts invoke karstification of manganese-rich dolomites and residual accumulation of manganese wad which later underwent diagenetic and low-grade metamorphic processes. For the most part, the role of hydrothermal processes and metasomatic alteration towards ore formation has not been adequately discussed. Here we report an abundance of common and some rare Al-, Na-, K- and Ba-bearing minerals, particularly aegirine, albite, microcline, banalsite, sérandite-pectolite, paragonite and natrolite in Mn ores of the PMF, indicative of hydrothermal influence. Enrichments in Na, K and/or Ba in the ores are generally on a percentage level for most samples analysed through bulk-rock techniques. The presence of As-rich tokyoite also suggests the presence of As and V in the hydrothermal fluid. The fluid was likely oxidized and alkaline in nature, akin to a mature basinal brine. Various replacement textures, particularly of Na- and K- rich minerals by Ba-bearing phases, suggest sequential deposition of gangue as well as ore-minerals from the hydrothermal fluid, with Ba phases being deposited at a later stage. The stratigraphic variability of the studied ores and their deviation from the strict classification of ferruginous and siliceous ores in the literature, suggests that a re-evaluation of genetic models is warranted. New Ar-Ar ages for K-feldspars suggest a late Neoproterozoic timing for hydrothermal activity. This corroborates previous geochronological evidence for regional hydrothermal activity that affected Mn ores at the PMF but also, possibly, the high-grade Mn ores of the Kalahari Manganese Field to the north. A revised, all-encompassing model for the development of the manganese deposits of the PMF is then proposed, whereby the source of metals is attributed to underlying carbonate rocks beyond the Reivilo Formation of the Campbellrand Subgroup. The main process by which metals are primarily accumulated is attributed to karstification of the dolomitic substrate. The overlying Asbestos Hills Subgroup banded iron formation (BIF) is suggested as a potential source of alkali metals, which also provides a mechanism for leaching of these BIFs to form high-grade residual iron ore deposits

Practical guidance for applying the ADNEX model from the IOTA group to discriminate between different subtypes of adnexal tumors.

All gynecologists are faced with ovarian tumors on a regular basis, and the accurate preoperative diagnosis of these masses is important because appropriate management depends on the type of tumor. Recently, the International Ovarian Tumor Analysis (IOTA) consortium published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, the first risk model that differentiates between benign and four types of malignant ovarian tumors: borderline, stage I cancer, stage II-IV cancer, and secondary metastatic cancer. This approach is novel compared to existing tools that only differentiate between benign and malignant tumors, and therefore questions may arise on how ADNEX can be used in clinical practice. In the present paper, we first provide an in-depth discussion about the predictors used in ADNEX and the ability for risk prediction with different tumor histologies. Furthermore, we formulate suggestions about the selection and interpretation of risk cut-offs for patient stratification and choice of appropriate clinical management. This is illustrated with a few example patients. We cannot propose a generally applicable algorithm with fixed cut-offs, because (as with any risk model) this depends on the specific clinical setting in which the model will be used. Nevertheless, this paper provides a guidance on how the ADNEX model may be adopted into clinical practice

Psychogenic periodic fever

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