Heat capacities of polyethylene and linear fluoropolymers

Heat capacities at constant pressure, C_p, and at constant volume C_v, were calculated with the help of normal mode frequency spectra and compared to experimental data for crystalline or semicrystalline polyethylene, poly(vinyl fluoride), poly(vinylidene fluoride), polytrifluooroethylene and poly(tetrafluoroethylene). A calculation scheme using a Tarasov function for 2N skeletal vibrational modes and an approximation of the residual 7N normal modes from known data on polyethylene and polytetrafluoroethylene is developed for all homologous, linear fluoropolymers. N is the number of carbon backbone atoms of the repeating unit. Calculations can be carried out over the whole temperature range 0 K to melting. For the two theta temperatures and the constant A₀ used for C_v to C_p conversion, fluorine-concentration dependent curves are given. The relations are expected to hold also for copolymers and blends of intermediate fluorine contents. Recommended experimental (data bank) heat capacities agree to ±2.5% with the calculations.     

Data-enabled extremum seeking: A cooperative concurrent learning-based approach

This paper introduces a new class of feedback-based data-driven extremum seeking algorithms for the solution of model-free optimization problems in smooth continuous-time dynamical systems. The novelty of the algorithms lies on the incorporation of memory to store recorded data that enables the use of information-rich datasets during the optimization process, and allows to dispense with the time-varying dither excitation signal needed by standard extremum seeking algorithms that rely on a persistence of excitation (PE) condition. The model-free optimization dynamics are developed for single-agent systems, as well as for multi-agent systems with communication graphs that allow agents to share their state information while preserving the privacy of their individual data. In both cases, sufficient richness conditions on the recorded data, as well as suitable optimization dynamics modeled by ordinary differential equations are characterized in order to guarantee convergence to a neighborhood of the solution of the extremum seeking problems. The performance of the algorithms is illustrated via different numerical examples in the context of source-seeking problems in multivehicle systems.     

Failure Analysis of a Cast Mn-Bronze Propeller

The investigation of a failure of a cast manganese bronze propeller, fractured after a short service period (~4–5 months), was conducted. Chemical analysis, visual inspection, optical microscopy, fractographic evaluation, SEM/EDS analysis, and hardness testing were used as the principal analytical tools for the failure investigation. The findings suggest that the failure occurred due to fatigue mechanism under low stress conditions. The non-conformities detected in material chemical composition, as well as the presence of internal and surface flaws could be considered as the main contributors of the premature failure of the propeller.     

Satellite-derived conditions and advection patterns off Iberia and NW Africa: Potential implications to sardine recruitment dynamics and population structuring

Surface velocity estimates from wind and altimeter data, together with satellite-derived sea surface temperature and chlorophyll, were used to explore the advection patterns and environmental conditions using a simple Lagrangian model. Although the model is generic (only considering the physical transport), the results are of particular interest for sardine (Sardina pilchardus) early life stages, due to the spawning dynamics of the species off Iberia and NW Africa. Particles were released on the shelf of the Iberian and northern African Atlantic coasts every five days from 1998 to 2004 and advected for 27-days. Trajectories were computed using combinations of three surface velocity constituents: Ekman velocity, geostrophic velocity derived from sea level anomaly maps and mean geostrophic velocity derived from two mean dynamic topographies. Daily time series of sea surface temperature, chlorophyll-a concentration and water depth where constructed for each particle trajectory. The results showed strong regional and seasonal dependence of the transport due to wind, with average seasonal cycles of the percentage of particles found in the shelf reflecting the anticipated effect of the seasonal north–south migration of the trade wind belt. The addition of the geostrophic transport led to the attenuation of seasonal cycles and higher mean/maximum values in the probability of retention within the shelf. This increased capacity for retention even during strong upwelling conditions seems to have been overlooked by theories aiming to describe the reproductive strategies of pelagic fish and understand recruitment dynamics based primarily on wind variability. On the other hand, the average surface chlorophyll values indicated a distribution area with higher primary production for particles that never leave the shelf, in comparison to those that return to it or are found in the open sea a month after release, which is in agreement with existing hypotheses that offshore advection is detrimental to larval survival mainly due to the higher risk of starvation. Finally, the exchange between adjacent shelf areas was generally small (less than 5%) within the study period, with the exception of the Gulf of Cadiz. In the latter area, up to 50% of particles released in the southern Iberian shelf reached the Moroccan shelf in several events, contradicting previous suggestions that the Strait of Gibraltar acts as a physical barrier that promotes genetic differentiation among neighbouring sardine populations in the Atlantic. Overall, these results provide useful insights for the study of sardine dynamics in the northeast Atlantic but the unexpectedly high sensitivity of summary metrics (namely retention probability) to the choice of surface velocity field preclude firm conclusions and indicate alternative routes for future studies.     

Continuous spatial assignment of moving users

Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), there is currently no method for dynamic settings. In this paper, we consider the continuous assignment problem (CAP), where an optimal assignment must be constantly maintained between mobile users and a set of servers. The fact that the users are mobile necessitates real-time reassignment so that the quality of service remains high (i.e., their distance from their assigned servers is minimized). The large scale and the time-critical nature of targeted applications require fast CAP solutions. We propose an algorithm that utilizes the geometric characteristics of the problem and significantly accelerates the initial assignment computation and its subsequent maintenance. Our method applies to different cost functions (e.g., average squared distance) and to any Minkowski distance metric (e.g., Euclidean, L ₁ norm, etc.).     

Data mining for agent reasoning: A synergy for training intelligent agents

The task-oriented nature of data mining (DM) has already been dealt successfully with the employment of intelligent agent systems that distribute tasks, collaborate and synchronize in order to reach their ultimate goal, the extraction of knowledge. A number of sophisticated multi-agent systems (MAS) that perform DM have been developed, proving that agent technology can indeed be used in order to solve DM problems. Looking into the opposite direction though, knowledge extracted through DM has not yet been exploited on MASs. The inductive nature of DM imposes logic limitations and hinders the application of the extracted knowledge on such kind of deductive systems. This problem can be overcome, however, when certain conditions are satisfied a priori. In this paper, we present an approach that takes the relevant limitations and considerations into account and provides a gateway on the way DM techniques can be employed in order to augment agent intelligence. This work demonstrates how the extracted knowledge can be used for the formulation initially, and the improvement, in the long run, of agent reasoning.     

Decatungstate catalyst supported on silica and γ-alumina: Efficient photocatalytic oxidation of benzyl alcohols

Four supported catalysts with the same tungsten loading were prepared by depositing decatungstate species W₁₀O⁴⁻₃₂, through wet impregnation, on the surface of γ-alumina and silica at different pH values. The prepared samples were characterized using BET measurements as well as XRD, UV–vis DR, and XP spectroscopies. Higher dispersion of W(VI) oxo-species was obtained in the silica-supported catalysts compared with the corresponding alumina-supported ones. Within the same support, the dispersion was higher when the impregnation pH is lower than the point of zero charge (pzc) of the support. The decatungstate anions were present mainly on the silica surface without any modification, whereas these underwent a partial depolymerization on their deposition on the γ-alumina surface. The extent of depolymerization was less in the sample prepared at pH above pzc. These findings were explained in terms of the mode of deposition of the W(VI) species from the solution onto the support surface. The photocatalytic activity of the aforementioned catalysts, concerning the photooxidation of 1-phenylethanol, depends on the fraction of the W₁₀O⁴⁻₃₂ supported species rather than on the W(VI) dispersion. Thus, extremely high conversions have been obtained over the silica-based catalysts and also over the γ-alumina-based catalyst prepared at relatively high pH. These catalysts also are very effective in the photooxidation of a series of secondary and primary benzyl alcohols, in which benzyl ketones and benzoic acids were formed as the only or major products, respectively. The easy separation of the solid catalyst from the reaction mixture, the high activity, selectivity, and stability as well as the retained activity in subsequent catalytic cycles, make these supported catalysts suitable for a small-scale synthesis. Based on product analysis and kinetic data on the heterogeneous oxidation of benzyl alcohols, we suggest that a hydrogen abstraction transfer (HAT) mechanism predominates with respect to an electron transfer (ET) one in these reactions.     

Model-based control of temperature and energy requirements in a fluidised furnace reactor

The main objective is to improve the control performance during catalyst processing experiments in a furnace heated fluidised bed reactor. A model-based predictive control strategy is implemented for the tight control of the reactor temperature and the overall energy requirements. A detailed dynamic model is developed for the furnace reactor and validated using open-loop experimental data. Dynamic programming techniques are used for the calculation of the optimal sequence of manipulated variables that minimise the difference between the desired and the predicted reactor temperature trajectories. The model predictive control strategy leads to superior performance than the previously installed system that consisted of conventional PID controllers.     

ApoA1 Deficiency Reshapes the Phenotypic and Molecular Characteristics of Bone Marrow Adipocytes in Mice

In the present study, we studied the effect of apolipoprotein A-1 (APOA1) on the spatial and molecular characteristics of bone marrow adipocytes, using well-characterized ApoA1 knockout mice. APOA1 is a central regulator of high-density lipoprotein cholesterol (HDL-C) metabolism, and thus HDL; our recent work showed that deficiency of APOA1 increases bone marrow adiposity in mice. We found that ApoA1 deficient mice have greatly elevated adipocytes within their bone marrow compared to wild type counterparts. Morphologically, the increased adipocytes were similar to white adipocytes, and displayed proximal tibial-end localization. Marrow adipocytes from wild type mice were significantly fewer and did not display a bone-end distribution pattern. The mRNA levels of the brown/beige adipocyte-specific markers Ucp1, Dio2, Pat2, and Pgc1a; and the expression of leptin were greatly reduced in the ApoA1 knock-out in comparison to the wild-type mice. In the knock-out mice, adiponectin was remarkably elevated. In keeping with the close ties of hematopoietic stem cells and marrow adipocytes, using flow cytometry we found that the elevated adiposity in the ApoA1 knockout mice is associated with a significant reduction in the compartments of hematopoietic stem cells and common myeloid, but not of the common lymphoid, progenitors. Moreover, the ‘beiging’-related marker osteopontin and the angiogenic factor VEGF were also reduced in the ApoA1 knock-out mice, further supporting the notion that APOA1—and most probably HDL-C—regulate bone marrow microenvironment, favoring beige/brown adipocyte characteristics.