Pre-treatment methods of Edam cheese milk. Effect on the whey composition

Edam cheese milk was subjected to high-heat treatment (HH), ultrafiltration (UF) and microfiltration (MF). The effect on the recovery yield and the composition of whey was studied. Traditional Edam process was used as a reference. HH reduced the whey protein concentration of milk and whey, but the recovery from milk to whey was not affected. Reduction of whey proteins was the highest (28%) with MF treatment, during which 15% was lost in the MF permeate and 13% was co-precipitated with the cheese curd. Co-precipitation of the whey proteins was the highest (84%) with ultrafiltered milk. MF and UF treatments produced 22% less whey with increased whey protein concentration. Elevation of the cheese milk protein concentration by microfiltration or ultrafiltration decreased the recovery of fat in whey. None of the treatments decreased the residual casein concentration in whey. The protein composition was altered by UF and MF treatments, which significantly increased the caseinomacropeptide content of total protein in whey. The whey was processed into whey protein concentrate powders. The amino acid composition of the whey protein concentrate produced from microfiltration process was significantly different from the others.     

Subsurface public assembly spaces in Finland

One of the most famous public spaces in Finland built underground in rock is the Retretti art centre and concert hall. This paper describes the Retretti caverns, as well as the Kannussillanmaki Theatre, near Espoo. In addition, the authors provide information about two underground projects now in the planning stages: a cultural and sports centre on an island near Helsink; and a space for public meetings and exhibitions, underneath Sibelius Park.     

The Evaluation of a Personalised Health Information System for Patients with Cancer

In this paper we describe the evaluation of a personalised information system for patients with cancer. Our system dynamically generates hypertext pages that explain treatments, diseases, measurements etc related to the patient's condition, using information in the patient's medical record as the basis for the tailoring. We describe results of a controlled trial comparing this system with a nonpersonalised one. The results of the trial slow significant results concerning the patients' preferences for personalised information. We discuss the implications of our evaluation and results for the development and evaluation of future personalised systems, and adaptive hypertext systems in particular.     

Modelling lidar-derived boreal forest canopy cover with SPOT 4 HRVIR data

Forest canopy cover (C) is needed in forest area monitoring and for many ecological models. Airborne scanning lidar sensors can produce fairly accurate C estimates even without field training data. However, optical satellite images are more cost-efficient for large area inventories. Our objective was to use airborne lidar data to obtain accurate estimates of C for a set of sample plots in a boreal forest and to generalize C for a large area using a satellite image. The normalized difference vegetation index (NDVI) and reduced simple ratio (RSR) were calculated from the satellite image and used as predictors in the regressions. RSR, which combines information from the red, near-infrared, and shortwave infrared bands, provided the best performance in terms of absolute root mean square error (RMSE) (7.3%) in the training data. NDVI produced a markedly larger RMSE (10.0%). However, in an independent validation data set, RMSE increased (13.0–17.1%) because the systematic sample of validation plots contained more variation than the training plots. Our results are better than those reported earlier, which is probably explained by more consistent C estimates derived from the lidar. Our approach provides an efficient method for creating C maps for large areas.     

An inexact interior-point method for system analysis

In this article, a primal-dual interior-point algorithm for semidefinite programming that can be used for analysing e.g. polytopic linear differential inclusions is tailored in order to be more computationally efficient. The key to the speedup is to allow for inexact search directions in the interior-point algorithm. These are obtained by aborting an iterative solver for computing the search directions prior to convergence. A convergence proof for the algorithm is given. Two different preconditioners for the iterative solver are proposed. The speedup is in many cases more than an order of magnitude. Moreover, the proposed algorithm can be used to analyse much larger problems as compared to what is possible with off-the-shelf interior-point solvers.     

Variable Length Instruction Compression on Transport Triggered Architectures

The memories used for embedded microprocessor devices consume a large portion of the system’s power. The power dissipation of the instruction memory can be reduced by using code compression methods, which may require the use of variable length instruction formats in the processor. The power-efficient design of variable length instruction fetch and decode is challenging for static multiple-issue processors, which aim for low power consumption on embedded platforms. The memory-side power savings using compression are easily lost on inefficient fetch unit design. We propose an implementation for instruction template-based compression and two instruction fetch alternatives for variable length instruction encoding on transport triggered architecture, a static multiple-issue exposed data path architecture. With applications from the CHStone benchmark suite, the compression approach reaches an average compression ratio of 44% at best. We show that the variable length fetch designs reduce the number of memory accesses and often allow the use of a smaller memory component. The proposed compression scheme reduced the energy consumption of synthesized benchmark processors by 15% and area by 33% on average.     

Corpus-based vocabulary lists for language learners for nine languages

We present the KELLY project and its work on developing monolingual and bilingual word lists for language learning, using corpus methods, for nine languages and thirty-six language pairs. We describe the method and discuss the many challenges encountered. We have loaded the data into an online database to make it accessible for anyone to explore and we present our own first explorations of it. The focus of the paper is thus twofold, covering pedagogical and methodological aspects of the lists’ construction, and linguistic aspects of the by-product of the project, the KELLY database.     

Parallax correction via disparity estimation in a multi-aperture camera

In this paper, an image fusion algorithm is proposed for a multi-aperture camera. Such camera is a feasible alternative to traditional Bayer filter camera in terms of image quality, camera size and camera features. The camera consists of several camera units, each having dedicated optics and color filter. The main challenge of a multi-aperture camera arises from the fact that each camera unit has a slightly different viewpoint. Our image fusion algorithm corrects the parallax error between the sub-images using a disparity map, which is estimated from the single-spectral images. We improve the disparity estimation by combining matching costs over multiple views using trifocal tensors. Images are matched using two alternative matching costs, mutual information and Census transform. We also compare two different disparity estimation methods, graph cuts and semi-global matching. The results show that the overall quality of the fused images is near the reference images.     

Derived types in semantic association discovery

Semantic associations are direct or indirect linkages between two entities that are construed from existing associations among entities. In this paper we extend our previous query language approach for discovering semantic associations with an ability to retrieve semantic associations that, besides explicitly stated (base) associations, may contain associations derived using logic-based derivation rules. As will be shown, this makes it possible to find semantic associations that are both compact and intuitive. To implement this new feature, we introduce a rewriting principle that utilizes derived associations to reduce resulting semantic associations if possible. Other proposed means to assist the interpretation of query results include answer expansion and the ordering of answers. The incorporated answer expansion feature lets the user investigate rewritten semantic associations in a query result at the desired level of detail. The ordering of answers is based on the lengths of the resulting semantic associations, whereby priority is given to shorter semantic associations which often express close and relevant relationships.     

A fracture model for surface flaws and certain types of weld defects in ductile materials

A model is proposed for prediction of fracture initiation from surface flaws, bands of slag inclusions and zones with low yield strength in thin-walled structures. The model applies to cases where the whole ligament or defect zone is plasticized. Application of the model to design cases requires information from stress and elongation measurements on tensile specimens cut perpendicular to defect regions of the actual type. Predictions by the model of critical stresses are compared to results from burst tests on pipes with surface flaws. The correlation is found to be good and existing deviations between experiment and theory can be given a rational explanation within the framework of the model. This suggests that bulging and out of plane loading effects which are not taken into account in the model are not significant in these problems. The model thus makes a “limit” analysis possible for “two-dimensional” structures containing defects of the types mentioned above.