Properties and Stability of Mining-Induced Meromixis in Two Small Boreal Lakes in Eastern Finland

Mine waters are a significant point source stressor for aquatic environments, not only due to their acidity and high metal concentrations, but also because of their high electrolyte concentrations. Ion-rich mine waters can disturb the seasonal mixing of lake waters, even leading to permanent stratification, i.e. meromixis. In this study, we investigated two small natural lakes receiving waters from closed Ni-Cu mines. To characterize the present chemical and physical conditions of these two boreal lakes, we collected water samples and in-situ water column measurements seasonally in 2017 and 2018. We modelled the stability of meromixis in the lakes under varying physico-chemical and meteorological conditions with the MATLAB-based open-source model code, MyLake. Chemical analyses and water column measurements show that both lakes are currently meromictic with a chemocline separating the circulating, well-oxygenated upper water from the non-circulating, hypoxic bottom water. The main anion was SO₄ in both lakes, while the main cations were Ca, Mg, Na, and K. Elevated concentrations of conservative elements flowing from the mine areas are crucial in maintaining the meromixis. Modelling scenarios suggest that the meromixis would be sustained for several decades even if the external load ceased completely. Lake morphology and sheltered surroundings also seem to contribute to maintaining the meromixis in these lakes. Consequently, our results indicate that small headwaters are sensitive to persistent meromixis even when external loading is mild.

     

Fatty Acid Fingerprints and Hyaluronic Acid in Extracellular Vesicles from Proliferating Human Fibroblast-like Synoviocytes

Extracellular vesicles (EVs) function as conveyors of fatty acids (FAs) and other bioactive lipids and can modulate the gene expression and behavior of target cells. EV lipid composition influences the fluidity and stability of EV membranes and reflects the availability of lipid mediator precursors. Fibroblast-like synoviocytes (FLSs) secrete EVs that transport hyaluronic acid (HA). FLSs play a central role in inflammation, pannus formation, and cartilage degradation in joint diseases, and EVs have recently emerged as potential mediators of these effects. The aim of the present study was to follow temporal changes in HA and EV secretion by normal FLSs, and to characterize the FA profiles of FLSs and EVs during proliferation. The methods used included nanoparticle tracking analysis, confocal laser scanning microscopy, sandwich-type enzyme-linked sorbent assay, quantitative PCR, and gas chromatography. The expression of hyaluronan synthases 1–3 in FLSs and HA concentrations in conditioned media decreased during cell proliferation. This was associated with elevated proportions of 20:4n-6 and total n-6 polyunsaturated FAs (PUFAs) in high-density cells, reductions in n-3/n-6 PUFA ratios, and up-regulation of cluster of differentiation 44, tumor necrosis factor α, peroxisome proliferator-activated receptor (PPAR)-α, and PPAR-γ. Compared to the parent FLSs, 16:0, 18:0, and 18:1n-9 were enriched in the EV fraction. EV counts decreased during cell growth, and 18:2n-6 in EVs correlated with the cell count. To conclude, FLS proliferation was featured by increased 20:4n-6 proportions and reduced n-3/n-6 PUFA ratios, and FAs with a low degree of unsaturation were selectively transferred from FLSs into EVs. These FA modifications have the potential to affect membrane fluidity, biosynthesis of lipid mediators, and inflammatory processes in joints, and could eventually provide tools for translational studies to counteract cartilage degradation in inflammatory joint diseases.     

Seasonal changes in pituitary function: amplification of midfollicular luteinizing hormone secretion during the dark season

OBJECTIVE: To analyze the effect of season on the pulsatility of gonadotropin secretion in women living in an area with a large annual variability in daylight length. DESIGN: A prospective study. Pulse studies were carried out in each subject during both the dark and light season. SETTING: The gynecologic endocrine research unit of the University Central Hospital of Oulu. PARTICIPANTS: Eleven ovulatory, healthy women volunteering for the study. INTERVENTIONS: Serum samples were collected at 10-minute intervals for 6 hours on days 7 to 9 of the cycle. MAIN OUTCOME MEASURES: Serum LH and FSH concentrations were measured and the data were analyzed with an algorithm computer-based program. RESULTS: The mean area of LH pulses analyzed was significantly higher during the dark season than the light season (49.1 +/- 3.1 versus 38.5 +/- 1.7 mIU/mL; conversion factor to SI unit, 1.00), while in the amplitude (1.9 +/- 0.1 versus 1.8 +/- 0.1 mIU/mL), number of pulses (5.2 +/- 0.3 versus 4.4 +/- 0.6), and the mean level (9.6 +/- 0.5 versus 9.4 +/- 0.9 mIU/mL) the difference did not reach statistical significance. The number (5.2 +/- 0.5 versus 5.2 +/- 0.4,), amplitude (1.0 +/- 0.05 versus 1.1 +/- 0.07 mIU/mL; conversion factor to SI unit, 1.00), area (29.9 +/- 2.4 versus 29.6 +/- 3.1 mIU/mL), and the mean level of FSH (5.4 +/- 0.6 versus 6.0 +/- 0.8 mIU/mL) during the dark and light seasons were identical, showing no seasonal variability. CONCLUSIONS: The results indicate increased pituitary LH secretion in the midfollicular phase during the dark season that may be related to increased melatonin secretion and decreased ovarian activity at this time of the year.     

From proprietary to open source—Growing an open source ecosystem

In today's business and software arena, Free/Libre/Open Source Software has emerged as a promising platform for software ecosystems. Following this trend, more and more companies are releasing their proprietary software as open source, forming a software ecosystem of related development projects complemented with a social ecosystem of community members. Since the trend is relatively recent, there are few guidelines on how to create and maintain a sustainable open source ecosystem for a proprietary software. This paper studies the problem of building open source communities for industrial software that was originally developed as closed source. Supporting processes, guidelines and best practices are discussed and illustrated through an industrial case study. The research is paving the road for new directions in growing a thriving open source ecosystem.     

Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms

An important application of reinforcement learning (RL) is to finite-state control problems and one of the most difficult problems in learning for control is balancing the exploration/exploitation tradeoff. Existing theoretical results for RL give very little guidance on reasonable ways to perform exploration. In this paper, we examine the convergence of single-step on-policy RL algorithms for control. On-policy algorithms cannot separate exploration from learning and therefore must confront the exploration problem directly. We prove convergence results for several related on-policy algorithms with both decaying exploration and persistent exploration. We also provide examples of exploration strategies that can be followed during learning that result in convergence to both optimal values and optimal policies.     

Quantitative release planning in extreme programming

Context

Extreme Programming (XP) is one of the most popular agile software development methodologies. XP is defined as a consistent set of values and practices designed to work well together, but lacks practices for project management and especially for supporting the customer role. The customer representative is constantly under pressure and may experience difficulties in foreseeing the adequacy of a release plan.

Objective

To assist release planning in XP by structuring the planning problem and providing an optimization model that suggests a suitable release plan.

Method

We develop an optimization model that generates a release plan taking into account story size, business value, possible precedence relations, themes, and uncertainty in velocity prediction. The running-time feasibility is established through computational tests. In addition, we provide a practical heuristic approach to velocity estimation.

Results

Computational tests show that problems with up to six themes and 50 stories can be solved exactly. An example provides insight into uncertainties affecting velocity, and indicates that the model can be applied in practice.

Conclusion

An optimization model can be used in practice to enable the customer representative to take more informed decisions faster. This can help adopting XP in projects where plan-driven approaches have traditionally been used.     

Effect of post-epitaxial-growth processing on the nonlinear response of saturable absorber

The nonlinear response of an ion-irradiated saturable Bragg reflector, further modified by thermal annealing, has been studied. We demonstrate that the absorption recovery time and the effective saturation fluence dependent on the pulse duration can be tailored over a wide range after epitaxial growth by the proper combination of ion irradiation and subsequent annealing. Thermal treatment is also an efficient means for the reduction of the unbleachable losses and the stabilization of the absorber parameters.     

JSMAA: open source software for SMAA computations

Most software for multi-criteria decision analysis (MCDA) implement a small set of compatible methods as a closed monolithic program. With such software tools, the decision models have to be input by hand. In some applications, however, the model can be generated using external information sources, and thus it would be beneficial if the MCDA software could integrate in the comprehensive information infrastructure. This article motivates for the need of model generation in the methodological context of stochastic multicriteria acceptability analysis (SMAA), and describes the JSMAA software that implements SMAA-2, SMAA-O and SMAA-TRI methods. JSMAA is an open source and divided in separate graphical user interface and library components, enabling its use in systems with a model generation subsystem.     

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.     

Grouping PCBs with Minimum Feeder Changes

In printed circuit board (PCB) assembly, the majority of electronic components are inserted by high-speed placement machines. Although the efficient utilization of the machinery is important for a manufacturer, it is hard to fully realize in high-mix low-volume production environments. On the machine level, the component setup strategy adopted by the manufacturer has a significant impact on the overall production efficiency. Usually, the setup strategy is formulated as a part type grouping problem or a minimum setup problem. In this article, we consider a hybridization of these two problems for the single machine case: The object function to be minimized includes a weighted sum of the number of part type groups (giving the number of setup occasions) and the number of feeder changeovers. We present algorithms for the problem and compare their efficiency.