A New Method for Computation of Axial Flux Permanent Magnet Synchronous Machine Inductances under Saturated Condition

Accurate computing of the saturated inductances of Permanent Magnet Synchronous Machine (PMSM) is very important during the design process. In this paper, a new method is presented based on the B-H characteristic of the stator material and unsaturated inductances formulations. This method is used to calculate the saturated inductances of the axial flux PMSM. The synchronous inductance and all of the leakage inductances can be calculated using this method. Two motors with different slot/pole combinations are selected as the case studies. The effectiveness and accuracy of the method is confirmed by 3D Finite Element Analysis (FEA). This method can be extended to other types of electric machines comprising multi-phase winding in their armature such as induction motors and other types of synchronous motors

The Use of ROC Analysis for the Qualitative Prediction of Human Oral Bioavailability from Animal Data

PURPOSE: To develop and evaluate a tool for the qualitative prediction of human oral bioavailability (F(human)) from animal oral bioavailability (F(animal)) data employing ROC analysis and to identify the optimal thresholds for such predictions. METHODS: A dataset of 184 compounds with known F(human) and F(animal) in at least one species (mouse, rat, dog and non-human primates (NHP)) was employed. A binary classification model for F(human) was built by setting a threshold for high/low F(human) at 50%. The thresholds for high/low F(animal) were varied from 0 to 100 to generate the ROC curves. Optimal thresholds were derived from ‘cost analysis’ and the outcomes with respect to false negative and false positive predictions were analyzed against the BDDCS class distributions. RESULTS: We successfully built ROC curves for the combined dataset and per individual species. Optimal F(animal) thresholds were found to be 67% (mouse), 22% (rat), 58% (dog), 35% (NHP) and 47% (combined dataset). No significant trends were observed when sub-categorizing the outcomes by the BDDCS. CONCLUSIONS: F(animal) can predict high/low F(human) with adequate sensitivity and specificity. This methodology and associated thresholds can be employed as part of decisions related to planning necessary studies during development of new drug candidates and lead selection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11095-013-1193-2) contains supplementary material, which is available to authorized users

Forecasting for Social Good

Forecasting plays a critical role in the development of organisational business strategies. Despite a considerable body of research in the area of forecasting, the focus has largely been on the financial and economic outcomes of the forecasting process as opposed to societal benefits. Our motivation in this study is to promote the latter, with a view to using the forecasting process to advance social and environmental objectives such as equality, social justice and sustainability. We refer to such forecasting practices as Forecasting for Social Good (FSG) where the benefits to society and the environment take precedence over economic and financial outcomes. We conceptualise FSG and discuss its scope and boundaries in the context of the "Doughnut theory". We present some key attributes that qualify a forecasting process as FSG: it is concerned with a real problem, it is focused on advancing social and environmental goals and prioritises these over conventional measures of economic success, and it has a broad societal impact. We also position FSG in the wider literature on forecasting and social good practices. We propose an FSG maturity framework as the means to engage academics and practitioners with research in this area. Finally, we highlight that FSG: (i) cannot be distilled to a prescriptive set of guidelines, (ii) is scalable, and (iii) has the potential to make significant contributions to advancing social objectives.Comment: 28 pages, 6 figure

Physicochemical characteristic of Penaeus indicus ponds in coastal area of Gorgan Bay (Mazandaran province)

A series of studies were conducted to evaluate the possibility to culture Penaeus indicus in coastal area of Gorgan bay concerning the proper climate potential of Behshahr zone during summer till autumn 2000. Thirty two water samples were collected from four shrimp ponds for further laboratory studies to measure some physicochemical parameters such as: temperature, pH, salinity, transparency, nitrogen, phosphorus, D.O. according to the Russian Standard (1988). As a result, the range of water temperature, pH, salinity and trasparency were 24.5-29.0°C, 8.02-8.18, 31.5-43.5 ppt and 21-50cm, respectively and the fluctuation concentration of D.O, NH^+4, NO^-2, PO4^-3 were 3.8-9.5 ml/l, 0.0022-0.015, 0.0021-0.1210 and 0.0145-0.3710 mg/l, respectively. As a conclusion, this shrimp species can be easily adopted with different climate, so this region is suitable for shrimp culture as view point of temperature and salinity. For demonstration of this issue, the semi-intensive shrimp culture has been successful. Also the toxic material such as ammonia and nitrite did not show any restriction for shrimp culture

Microscopic Enteritis; Clinical Features and Correlations with Symptoms

Aim: To assess the clinical characteristic of CD as well as correlation of symptoms and the degrees of intestinal mucosal lesions in Iranian children. Background: Microscopic Enteritis (Marsh 0-II) is associated with malabsorption. Patients and methods: From August 2005 to September 2009, 111 cases with malabsorption and classical gastrointestinal symptoms were evaluated. Results: The mean (±SD) age of children with CD was 4.9±3.5 years (range, 6 month - 16 years) and the mean duration of symptoms was 8 ± 20.5 months. 50 cases (45%) were female and 61 cases (55%) were male. The most common clinical presentation was failure to thrive in 72%, chronic diarrhea in 65.8% and Iron deficiency anemia in 59.5%. Sensitivity of EMA was 100% in patients with Marsh IIIb and Marsh IIIc. EMA was also positive in 77% of cases with Marsh 0, 18% in Marsh I, 44% in Marsh II and 81.8% in patients with Marsh IIIa. Conclusion: Histopathology did not reflect the severity of gluten sensitivity. This would suggest that the degree of intestinal mucosal damage might not be a reliable prognostic factor. Significant symptoms can be present with minor histological change on biopsy

MEOW: - Automatic Evolutionary Multi-Objective Concealed Weapon Detection

X-ray screening is crucial for ensuring safety and security in crowded public areas. However, X-ray operators are often overwhelmed by the sheer amount of potential threats to assess; thus, current computer vision-aided systems are designed to alleviate theseworkloads. In this study, we focus on a key, unresolved challenge for developing such automatic X-ray screening systems: the direct application of existing avant garde computer vision approaches does not necessarily yield satisfactory results in the X-ray medium, hindering the effectiveness of current screening systems. To overcome this drawback, we propose a novel automated machine learning (AutoML) multi-objective approach for neural architecture search (NAS) for concealed weapon detection (MEOW). We benchmark MEOW with the state-of-the-art in two comprehensive scenarios in threat identification: SIXray (a popular, massive X-ray dataset) and Residuals (a proprietary, unpublished dataset provided by our industry partners). MEOW consist of the coalescence of two new components: First, we design a heuristic technique to strongly reduce the high computational cost of neuroevolutionary search while preserving a high performance such that it can be effectively used in real-time industrial settings. Second, we devise a novel ensemble approach for combining multiple discovered architectures simultaneously. Leveraging these two characteristics, MEOW outperforms the state-of-the-art while keeping the NAS overhead to a minimum. More broadly, our results suggest that AutoML has a strong potential for security applications

Whole-organism phenotypic screening methods used in early-phase anthelmintic drug discovery

Diseases caused by parasitic helminths (worms) represent a major global health burden in both humans and animals. As vaccines against helminths have yet to achieve a prominent role in worm control, anthelmintics are the primary tool to limit production losses and disease due to helminth infections in both human and veterinary medicine. However, the excessive and often uncontrolled use of these drugs has led to widespread anthelmintic resistance in these worms - particularly of animals - to almost all commercially available anthelmintics, severely compromising control. Thus, there is a major demand for the discovery and development of new classes of anthelmintics. A key component of the discovery process is screening libraries of compounds for anthelmintic activity. Given the need for, and major interest by the pharmaceutical industry in, novel anthelmintics, we considered it both timely and appropriate to re-examine screening methods used for anthelmintic discovery. Thus, we reviewed current literature (1977-2021) on whole-worm phenotypic screening assays developed and used in academic laboratories, with a particular focus on those employed to discover nematocides. This review reveals that at least 50 distinct phenotypic assays with low-, medium- or high-throughput capacity were developed over this period, with more recently developed methods being quantitative, semi-automated and higher throughput. The main features assessed or measured in these assays include worm motility, growth/development, morphological changes, viability/lethality, pharyngeal pumping, egg hatching, larval migration, CO2- or ATP-production and/or enzyme activity. Recent progress in assay development has led to the routine application of practical, cost-effective, medium- to high-throughput whole-worm screening assays in academic or public-private partnership (PPP) contexts, and major potential for novel high-content, high-throughput platforms in the near future. Complementing this progress are major advances in the molecular data sciences, computational biology and informatics, which are likely to further enable and accelerate anthelmintic drug discovery and development