Particle size segregation in granular flow in silos

Segregation and layering of alumina in storage silos are investigated, with a view to predicting output quality versus time, given known variations in input quality on emplacement. A variety of experiments were conducted, existing relevant publications were reviewed, and the basis for an algorithm for predicting the effect of withdrawing from a central flowing region, in combination with variations in quality due to geometric, layering and segregation effects, is described in this report

Faster tuple lattice sieving using spherical locality-sensitive filters

To overcome the large memory requirement of classical lattice sieving algorithms for solving hard lattice problems, Bai-Laarhoven-Stehl\'{e} [ANTS 2016] studied tuple lattice sieving, where tuples instead of pairs of lattice vectors are combined to form shorter vectors. Herold-Kirshanova [PKC 2017] recently improved upon their results for arbitrary tuple sizes, for example showing that a triple sieve can solve the shortest vector problem (SVP) in dimension $d$ in time $2^{0.3717d + o(d)}$, using a technique similar to locality-sensitive hashing for finding nearest neighbors. In this work, we generalize the spherical locality-sensitive filters of Becker-Ducas-Gama-Laarhoven [SODA 2016] to obtain space-time tradeoffs for near neighbor searching on dense data sets, and we apply these techniques to tuple lattice sieving to obtain even better time complexities. For instance, our triple sieve heuristically solves SVP in time $2^{0.3588d + o(d)}$. For practical sieves based on Micciancio-Voulgaris' GaussSieve [SODA 2010], this shows that a triple sieve uses less space and less time than the current best near-linear space double sieve.Comment: 12 pages + references, 2 figures. Subsumed/merged into Cryptology ePrint Archive 2017/228, available at https://ia.cr/2017/122

Development of laboratory instrumentation for the study of soil erodibility

In order to carry out a study of the relative efficiency of various erodibility indices, and of the relative erodibility of soils developed in the Peak District of Derbyshire (England), three instruments were developed. These instruments were: a wet-sieve aggregate analyser of the Yoder pattern, a compact laboratory rainfall simulator using spray nozzles, a radiant drying unit using infra-red lamps. The efficiency of the instruments and the validity of the operating -techniques are critically evaluated and suggestions for improvement are advanced

Root optimization of polynomials in the number field sieve

The general number field sieve (GNFS) is the most efficient algorithm known for factoring large integers. It consists of several stages, the first one being polynomial selection. The quality of the chosen polynomials in polynomial selection can be modelled in terms of size and root properties. In this paper, we describe some algorithms for selecting polynomials with very good root properties.Comment: 16 pages, 18 reference

The Significance of Powder Breakdown During Conveying Within Industrial Milk Powder Plants

Instant whole milk powder (IWMP) is designed to rapidly dissolve in water, which depends on the particle size distribution (PSD). The fragile milk powder exiting the dryer has to be conveyed for packing, which can break down the particles, worsening the dissolution properties. This work investigated the importance of in-plant conveying in determining the nal functional properties at the industrial scale. IWMP breakdown was compared between two plants with di erent transport systems; a pneumatic system and bucket elevator. It was expected that the plant with the bucket elevator consistently produced powder with superior dissolution due to lower breakdown during transport. This was evaluated using the change in PSD. It was found that both plants had a similar decrease in the median particle size, and powder with an initially larger particle size showed more breakdown. However, it was not enough to compensate for the initially larger size. Thus powder that started out larger still had a larger particle size after transport. When quanti ed using the change in bulk density, a low initial bulk density compensated for large breakdown during conveying and ameliorated the impact on the functional properties. Thus in order to produce IWMP with the desired functionalities the focus should be on improving the initial agglomeration, as oppose to reducing transport breakdown.

Simple bucket flotation and wet-sieving in the wet tropics

Flotation and wet-sieving are simple techniques for recovering plant remains, animal bones, shells, small artefacts etc from archaeological deposits. Many different methods and machines have been designed to facilitate flotation and wet-sieving (see Pearsall 2000 for the best review of the subject). The author has successfully used the following method in numerous archaeological projects across the world, including Papua New Guinea. I do not claim to have invented this method. It is an amalgam of ideas and techniques derived both from methods taught to me by a variety of people, such as Gordon Hillman, John Giorgi and Mark Nesbitt, and my own experimentation. The method is simple, requiring either equipment available in even the most remote locations or that which is light and easy to carry, but is very effective, even in the, sometimes difficult, conditions seen in the tropical regions. In fact, the close control over the flotation process that this method affords is perfectly suited to the many archaeological deposits found in the area containing plant remains that do not float! The example used to illustrate the method is that of excavations at Lachitu Cave and Taora Rockshelter, Fichin Village, Sandaun Province, Papua New Guinea, undertaken in May and June 2004. I end this introduction with a cautionary note: no single method is suitable for every site and soil the archaeologist encounters; experimentation, practice and persistence, with reference to key principles, are the keys to success. Bearing this in mind, this guide should be seen as a starting point for experimenting with suitable techniques for your site

Tamarind (Tamarindus indica L.) parkland mycorrhizal potential within three agro-ecological zones of Senegal

Introduction. Tamarind (Tamarindus indica L.) belongs to the Fabaceae family; it is a multipurpose tree with slow growth. In order to help improve its growth and development, we assessed mycorrhizal diversity of tamarind parklands in Senegal. Materials and methods. Three sites of tamarind populations were sampled for each agro-ecological zone in Senegal: the Sahelian zone (i), Sahelo-Sudan zone (ii) and Sudan zone (iii). Soil and root samples were collected in each site and used for arbuscular mycorrhizal (AM) spore isolation and root colonization assessment. We identified the mycorrhizal fungi from spore collections and evaluated the root mycorrhization rate, defined as percentage of roots colonized according to agro-ecological zones. Results and discussion. The results did not reveal a specific AM fungal strain associated with tamarind plants. Three arbuscular mycorrhizal fungi (AMF) were identified from spores on the genus level: Glomus, Scutellospora and Acaulospora. Tamarind sites with sandy soil texture (70-90%) and located in dry areas (Sahel and Sudano-Sahel zones) were shown to be rich in mycorrhizal propagules. High densities of soil AM propagules evaluated with the Most Probable Number method (MPN) were found in Niokhoul (1100 propagules per 50 g of soil), Sakal (790 propagules per 50 g of soil) and Mbassis (780 propagules per 50 g of soil). However, higher mycorrhizal colonization (11%) was observed in the Sahel agro-ecological zone compared with the Sudano-Sahelian and Sahelian zones (3%) of Senegal. Conclusion. Our study explored natural AMF diversity as a starting point to develop inocula to be used in commercial nursery production of tamarinds

Robotic agricultural instrument for automated extraction of nematode cysts and eggs from soil to improve integrated pest management

Soybeans are an important crop for global food security. Every year, soybean yields are reduced by numerous soybean diseases, particularly the soybean cyst nematode (SCN). It is difficult to visually identify the presence of SCN in the field, let alone its population densities or numbers, as there are no obvious aboveground disease symptoms. The only definitive way to assess SCN population densities is to directly extract the SCN cysts from soil and then extract the eggs from cysts and count them. Extraction is typically conducted in commercial soil analysis laboratories and university plant diagnostic clinics and involves repeated steps of sieving, washing, collecting, grinding, and cleaning. Here we present a robotic instrument to reproduce and automate the functions of the conventional methods to extract nematode cysts from soil and subsequently extract eggs from the recovered nematode cysts. We incorporated mechanisms to actuate the stage system, manipulate positions of individual sieves using the gripper, recover cysts and cyst-sized objects from soil suspended in water, and grind the cysts to release their eggs. All system functions are controlled and operated by a touchscreen interface software. The performance of the robotic instrument is evaluated using soil samples infested with SCN from two farms at different locations and results were comparable to the conventional technique. Our new technology brings the benefits of automation to SCN soil diagnostics, a step towards long-term integrated pest management of this serious soybean pest