Investments into forest biorefineries under different price and policy structures

Increasing scarcity of oil reserves and the high CO₂ emissions from using oil have contributed to the development of renewable biofuels. Pulp and paper mill integrated forest biorefineries offer one important means to increase biofuel production. This study analyzes the effects of policies to support biofuel production in the pulp and paper sector. We study the relative effectiveness of three biofuel supporting policy instruments, namely production subsidy, input subsidy and investment subsidy. We present a partial equilibrium pulp and paper market model with a biorefinery investment option. A numerical model is used to evaluate the impacts of policy instruments on wood prices, as well as input choices and investment strategies of pulp and paper industries. The data represent the Finnish pulp and paper sector. We evaluate the values and direct costs of the policy instruments in a situation of exogenous biofuel production targets. The direct costs of input and investment subsidies are higher than those of a production subsidy. With all the policy instruments, Finnish pulp and paper mills would invest in wood-gasifying technology, instead of black liquor based one. The number of biorefinery units is dependent on the subsidy type — investment and input subsidies are likely to result in more numerous but smaller biofuel production units than a production subsidy. With all the policy instruments the demand for wood increases in Finland leading to higher wood prices. This, in turn, could reflect negatively on the profitability of the pulp and paper industries. To a significant degree, the model and the results can be generalized to other countries and markets where integrated pulp and paper mills are operating.     

Friction and a Tribochemical Reaction between Ice and Hexagonal Boron Nitride: A Theoretical Study

Friction between ice-Ih and hexagonal boron nitride (h-BN) has been determined by periodic ab initio calculations. Surfaces of ice-Ih and h-BN were brought into sliding contact, and the interaction energies were calculated as a function of interplanar distance and lateral displacement of the surfaces. The friction between the surfaces was calculated from the interaction energies, producing a friction coefficient of 0.140. Friction is further influenced at high loads by a tribochemical reaction between ice-Ih and h-BN.     

Correction to: Digitalization in knowledge work: the dream of enhanced performance

According to decision by the rector of University of Tampere, a version of the paper was submitted and published due to negligence.     

Spatial and temporal variations in water temperature in a high-altitude deep dimictic mountain lake (Nam Co), central Tibetan Plateau

Water temperature and the related thermal structure and stratification of a lake are very important to lake ecosystems because of their significant effects on the vertical exchanges of dissolved and particulate matter. In this study, we present high resolution, seasonal variations in water temperature at different depths of a large deep lake on the central Tibetan Plateau. The results show that Nam Co is a typical dimictic lake whose thermal stratification begins and ends in early June and early November, respectively. Increases in the water temperature during spring and the establishment of thermal stratification in the eastern small sub-basin occur approximately one month prior to the main basin which is likely caused by the different morphometry, different water transparency during spring, and the possible presence of a spring thermal bar. The Schmidt stability of the water column is directly controlled by surface water temperature. During the ice-covered period, the homogeneous water temperature exhibits a continuous increasing trend from approximately 0.5 °C to 3.5 °C. The daily mean surface water temperature of the main open lake area is highly correlated to the air temperature but shows a hysteresis effect of approximately 38 days, which shows the significant heat storage in such a large deep lake. Nam Co is a typical lake in this area in terms of its altitude, water depth and climatic conditions, so our results have broader significance for limnological and paleolimnological studies of similar lakes on the Tibetan Plateau.     

Robust estimation of bioaffinity assay fluorescence signals.

In this paper, the challenging problem of robust mean-signal estimation of a single-step microparticle bioaffinity assay is investigated. For this purpose, a density estimation-based robust algorithm (DER) was developed. The DER algorithm was comparatively evaluated with four other parameter estimation methods (mean value, median filtering, least square estimation, Welsch robust m-estimator). Two important questions were raised and investigated: 1) Which of the five methods can robustly estimate the mean bioaffinity signal? and 2) How many microparticles need to be measured in order to obtain an accurate estimate of the mean signal value? To answer the questions, bootstrap and coefficient of variation (CV) analyses were performed. In the CV analysis, the DER algorithm gave the best results: The CV ranged from 0.8% to 4.9% when the number of microparticles used for the mean signal estimation varied from 800 to 30. In the bootstrap analysis of the standard error, the DER algorithm had the smallest variance. As a conclusion, it can be underlined that: 1) of all methods tested, the DER algorithm gave the most consistent and reproducible results according to the bootstrap and CV analysis; 2) using the DER algorithm accurate estimates could be calculated based on 80-100 particles, corresponding to a typical assay measurement time of 1 min; and 3) the investigated bioaffinity signals contained a large number of outliers (observations that severely deviate from the majority of data) and therefore robust techniques were necessary for the mean signal estimation tasks.     

The Helsinki Office Environment Study: Air Change in Mechanically Ventilated Buildings

Abstract The objective of this study was to assess the magnitude and balance of mechanical ventilation in the rooms of Helsinki metropolitan office buildings with different types of ventilation systems. A random sample of 50 office buildings was selected from the Building Registry. Of these buildings, the 33 that have a mechanical ventilation system were included in this study. Most office buildings in the Helsinki metropolitan area have a ducted supply and exhaust system and hot water radiator heating. Air recirculation is used in about half of the buildings which have a mechanical supply and exhaust system. The average exhaust airflow was 1.2 L/s, m² (SD 0.73) or 17.2 L/s per person (SD 11.6). The variation of the airflows was found to be very high among the buildings, and among the rooms within the buildings. Therefore, even though the ventilation rates on average comply with the Finnish building code, it was found that many people were working in offices with airflows which were either too low or unnecessarily high.     

REPLICA MBTAC: multithreaded dual-mode processor

Prevailing trend in design of chip multiprocessors (CMP) has been that single-core processors are replicated. Therefore, they typically define asynchronous computational model, require heavily locality-aware memory allocation, and present high overheads in intercommunication. This kind of properties make parallel programming very challenging and prone to errors. We introduce our new dual-mode MultiBunched/Threaded Architecture with Chaining (MBTAC) processor core, the main building block of the REPLICA CMP. It provides a modern, sophisticated way for writing general purpose parallel programs backed up by native execution capabilities/realization of key concepts. These include support for cost-efficient machine instruction-level synchronization and uniform shared global memory for enabling easy-to-program memory allocation of data structures and data movement. MBTAC makes use of low-overhead thread-context switching solution; it has parallel computing savvy functional unit organization to exploit inter-thread instruction-level parallelism and highly efficient multioperations. To evaluate the goodness of our proposal, we implemented three MBTAC constellations featuring up to 2048 parallel threads on FPGA, compared it with respect to DLX and Intel’s Core i7 processors. The results point toward high performance in communication-intensive problems, simplified parallel programmability, and regular, implementation-friendly structure.     

Performance and programmability comparison of the thick control flow architecture and current multicore processors

The Journal of Supercomputing - Commercial multicore central processing units (CPU) integrate a number of processor cores on a single chip to support parallel execution of computational tasks....     

On the cosimulation of multibody systems and hydraulic dynamics

Multibody System Dynamics - The simulation of mechanical devices using multibody system dynamics (MBS) algorithms frequently requires the consideration of their interaction with components of a...     

Using regression makes extraction of shared variation in multiple datasets easy

In many data analysis tasks it is important to understand the relationships between different datasets. Several methods exist for this task but many of them are limited to two datasets and linear relationships. In this paper, we propose a new efficient algorithm, termed cocoreg, for the extraction of variation common to all datasets in a given collection of arbitrary size. cocoreg extends redundancy analysis to more than two datasets, utilizing chains of regression functions to extract the shared variation in the original data space. The algorithm can be used with any linear or non-linear regression function, which makes it robust, straightforward, fast, and easy to implement and use. We empirically demonstrate the efficacy of shared variation extraction using the cocoreg algorithm on five artificial and three real datasets.