ИЗУЧЕНИЕ ФЛОТАЦИОННЫХ СВОЙСТВ НОВЫХ СОБИРАТЕЛЕЙ ПРИ ОБОГАЩЕНИИ ШЕЕЛИТ-СУЛЬФИДНЫХ РУД

The article studies flotation properties of BTF-1552, IMA-206, and IMA-I413 alkali metal dialkyldithiophosphate samples. The article estimates beneficiation indices when using the reagent M-TF and its mixture with IMA-I413 and xanthogenate. On the basis of undertaken studies it was found that application of the mixture of IMA-I413 collectors with butyl xanthate at the ratio of 5 : 1 and the feed ratio of 20 + 5 g/t made it possible to increase the extraction into the copper concentrate: Cu by 0,79 %, Au by 4,1 % and Ag by 2,4, while the sulfide concentrate yield decreased by a factor of 2. The disadvantage of this reagent composition is the increase in As content in the copper concentrate by 0,67 %. Of all tested dialkyldithiophosphate samples, the best incremental indices of copper and noble metals recovery were obtained when using the BTF-1552collector. The extraction into the copper concentrate increased: Cu by 1,9 %, Au by 3,2 %, and Ag by 1,8 %, while the sulfide concentrate yield decreased by 1,4 times. The increase in As content in the copper concentrate was 0,34 %.Изучены флотационные свойства образцов диалкилдитиофасфатов щелочных металлов БТФ-1552, ИМА-206, ИМА-И413. Оценены показатели обогащения с использованием реагента М-ТФ и его смеси с ИМА-И413 и ксантогенатом. На основе выполненных исследований установлено, что применение смеси собирателей ИМА-И413 и бутилового ксантогената в соотношении 5 : 1 при расходе 20 + 5 г/т позволяет повысить извлечение в медный концентрат: Cu на 0,79 %, Au на 4,1 % и Ag на 2,4 %, при снижении выхода сульфидного концентрата в 2 раза. Недостатком данной композиции реагентов является рост содержания As в медном концентрате на 0,67 %. Из испытанных образцов диалкилдитиофосфатов лучшие показатели по приросту извлечения меди и благородных металлов получены на собирателе БТФ-1552. Извлечение в медный концентрат увеличилось: Cu на 1,9 %, Au на 3,2 % и Ag на 1,8 %, при снижении выхода сульфидного концентрата в 1,4 раза. Рост содержания As в медном концентрате составил 0,34 %

Vibration Control Systems for Sensitive Equipment: Limiting Performance and Optimal Design

As vibration control requirements become increasingly stringent, designers and users of vibration control equipment turn to devices and systems combining various physical mechanisms. Subsystems based on different physical effects can be combined to achieve the optimal performance for the application. Building an optimal product line that would cover a wide field of applications by combining several products, as opposed to creating one optimal device for a particular application, presents an optimum vibration control problem. This paper reviews optimum vibration control problems based on the idea of limiting performance, and discusses recent development of vibration control devices

Scaling Big Data Mining Infrastructure: The Twitter Experience

The analytics platform at Twitter has experienced tremendous growth over the past few years in terms of size, complexity, number of users, and variety of use cases. In this paper, we discuss the evolution of our infrastructure and the development of capabilities for data mining on “big data”. One important lesson is that successful big data mining in practice is about much more than what most academics would consider data mining: life “in the trenches ” is occupied by much preparatory work that precedes the application of data mining algorithms and followed by substantial effort to turn preliminary models into robust solutions. In this context, we discuss two topics: First, schemas play an important role in helping data scientists understand petabyte-scale data stores, but they’re insufficient to provide an overall “big picture ” of the data available to generate insights. Second, we observe that a major challenge in building data analytics platforms stems from the heterogeneity of the various components that must be integrated together into production workflows—we refer to this as “plumbing”. This paper has two goals: For practitioners, we hope to share our experiences to flatten bumps in the road for those who come after us. For academic researchers, we hope to provide a broader context for data mining in production environments, pointing out opportunities for future work. 1

Full-Text Indexing for Optimizing Selection Operations in Large-Scale Data Analytics

MapReduce, especially the Hadoop open-source implementation, has recently emerged as a popular framework for large-scale data analytics. Given the explosion of unstructured data begotten by social media and other web-based applications, we take the position that any modern analytics platform must support operations on free-text fields as first-class citizens. Toward this end, this paper addresses one inefficient aspect of Hadoop-based processing: the need to perform a full scan of the entire dataset, even in cases where it is clearly not necessary to do so. We show that it is possible to leverage a full-text index to optimize selection operations on text fields within records. The idea is simple and intuitive: the full-text index informs the Hadoop execution engine which compressed data blocks contain query terms of interest, and only those data blocks are decompressed and scanned. Experiments with a proof of concept show moderate improvements in end-to-end query running times and substantial savings in terms of cumulative processing time at the worker nodes. We present an analytical model and discuss a number of interesting challenges: some operational, others research in nature