Thermo-statistical description of gas mixtures from space partitions

The new mathematical framework based on the free energy of pure classical fluids presented in [R. D. Rohrmann, Physica A 347, 221 (2005)] is extended to multi-component systems to determine thermodynamic and structural properties of chemically complex fluids. Presently, the theory focuses on $D$-dimensional mixtures in the low-density limit (packing factor $\eta < 0.01$). The formalism combines the free-energy minimization technique with space partitions that assign an available volume $v$ to each particle. $v$ is related to the closeness of the nearest neighbor and provides an useful tool to evaluate the perturbations experimented by particles in a fluid. The theory shows a close relationship between statistical geometry and statistical mechanics. New, unconventional thermodynamic variables and mathematical identities are derived as a result of the space division. Thermodynamic potentials $\mu_{il}$, conjugate variable of the populations $N_{il}$ of particles class $i$ with the nearest neighbors of class $l$ are defined and their relationships with the usual chemical potentials $\mu_i$ are established. Systems of hard spheres are treated as illustrative examples and their thermodynamics functions are derived analytically. The low-density expressions obtained agree nicely with those of scaled-particle theory and Percus-Yevick approximation. Several pair distribution functions are introduced and evaluated. Analytical expressions are also presented for hard spheres with attractive forces due to K\^ac-tails and square-well potentials. Finally, we derive general chemical equilibrium conditions.Comment: 14 pages, 8 figures. Accepted for publication in Physical Review

Use of a stimulated echo sequence in the MRI study of the brain and spine

We describe in this paper how the STEAM sequence can be an efficient tool to obtain images free of flow artifacts in anatomical situation where the spin echo failed. The simplest way to eliminate flow artifacts is to exploit the dephasing induced by motion in magnetic field gradients and to reduce to zero the signal from moving tissues. This can be achieve by increasing the time elapsed between the spin excitation and the signal observed. Because of T2 relaxation, such an increase results in a signal decrease when the spin echo sequence is used. The STEAM sequence has the unique property that the time elapsed between observation and excitation can be increased without change in T2 value and so allows a good suppression of signals from the moving spins with short TE. Our results demonstrate that, although the stimulated echo intensity is only half that of a spin echo taken at the same read out time, the advantages of STEAM imaging can compensate for this partial loss in signal to noise in some particular clinical situations. The influence of mixing time on contrast has been evaluated using thoracic spine imaging and it has been shown that contrast between spine and CSF can be significantly improved (+ 60%) when TM is increased (from 17 ms to 50 ms). In the same time, the contrast between spine and fat issue decreases (40%). This last effect facilitates the adjustment of contrast window. Suppression of motion artifacts has first been evaluated with thoracic spine imaging, using a whole body coil. Suppression of artifacts was better than that obtained with a flow compensated spin echo sequence, especially in the case of kyphotic patients when a presaturation band was inefficient. In a second step suppression of motion artifacts has been evaluated from posterior fossa examination after injection of a paramagnetic contrast agent. The images obtained with the stimulated echo sequence show a dramatic reduction of signal from blood in the lateral sinus, and therefore an increase of quality by elimination of motion artifacts

A stereotaxic method for sectioning the corpus callosum in cat

We have described a method by which the corpus callosum of the cat may be sectioned. Two needles are held in the electrode carriers of a standard Horsley-Clarke instrument and are positioned in front of and behind the corpus callosum. A thread running between them is brought under tension, pressing down on the callosal fibers and dividing them. Interference with cerebral circulation, operative trauma, and demands upon the operator's skill are minimized. The procedure has been carried out successfully on fifteen cats and appears to be readily adaptable to other laboratory animals.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32418/1/0000497.pd

Sensor monitoring strategy

In its overall strategy, COMMON SENSE work packages (11) can be grouped into 3 key phases: (1) RD basis for cost-effective sensor development, (2) Sensor development, sensor web platform and integration, and (3) Field testing. In the Phase 1, within WP1 and WP2, partners have provided a general understanding and integrated basis for a cost effective sensors development. In Phase 2, within the WP3 and WPs 4 to 8, the new sensors have been created and planned to be integrated into instruments for the different identified platforms and how data produced will be processed, organised and saved. During the phase 3, within WP9, partners are deploying precompetitive prototypes at chosen platforms (e.g. research vessels, oil platforms, buoys and submerged moorings, ocean racing yachts, drifting buoys). Starting from August 2015 (month 22; Task 9.2), these platforms are permitting the partnership to test the adaptability and performance of the in-situ sensors and verify if the transmission of data is properly made and correct observed deviations. Sensor monitoring strategy (Deliverable 2.4 for Task 2.5) is the last task within Phase 1. As the other tasks in Phase 1 it has to provide a basis for designing field testing activities to be useful. That is how to validate the performance of sensors, integration, data acquisition, transmission, under real conditions in different platforms. Since there is a wide sensor variety, each one with its own characteristics, and several platforms, to prepare a general methodological review and give the corresponding directions as it was initially planned, would be a huge and useless effort. Given the initially fixed calendar a first version of the present deliverable was presented when most of the sensors were still not developed. The document addressed how projected sensors should be tested, their limitations and conditions for their monitoring and final certification. Now, when D2.2 (Procedures of sensors deployment methodology on physical supports/platforms) has been rewritten (May 2016), all sensors are fully developed and most of them have started their tests at sea, the present new updated version of the deliverable becomes more precise, with much better knowledge on the real sensors and their performance. In addition, a complete new chapter on data transmission –initially proposed but not developed in the previous version– is included. The information from the six sensor developers in COMMON SENSE on which the initial plan on where and how to test each sensor that was presented in D9.1 (April 2015) has been updated (May 2016). The update includes the final properties of sensors after the respective full laboratory tests and even some of the results from field tests that had been carried out starting August 2015. This task assesses field testing procedures and deployment specificities. Two tables are presented based on the information of the report for D9.1 delivered in April 2015. One table was created for sensor developers and one for those who will test the sensors at sea. In this report some information from the testers’ table is shown and updated according to the new version of D2.2 (May 2016) for platforms. Objectives and rationale The objective of Task 2.5 within the WP2 is the definition of sensor monitoring strategy based on the premises for water monitoring, sensor performances and data storage and transmission. For any new sensor, available instruments currently used in the oceanographic studies will be identified to perform comparisons. Suitable transmission technology will be selected according to the test conditions: open sea, coastal areas, remote locations, etc. Sensitivity and stress tests will be designed in order to establish confidence limits under different environmental situations, so that the results obtained in the testing exercises (WP9) will enable to certify the performance of the new instruments

Theoretical Examination of the Lithium Depletion Boundary

We explore the sensitivity in open cluster ages obtained by the lithium depletion boundary (LDB) technique to the stellar model input physics. The LDB age technique is limited to open clusters with ages ranging from 20 to 200 Myr. Effective 1-sig errors in the LDB technique due to uncertain input physics are roughly 3% at the oldest age increasing to 8% at the youngest age. Bolometric correction uncertainties add an additional 10 to 6% error to the LDB age technique for old and young clusters, respectively. Rotation rates matching the observed fastest rotators in the Pleiades affect LDB ages by less than 2%. The range of rotation rates in an open cluster are expected to ``smear'' the LDB location by only 0.02 mag for a Pleiades age cluster increasing to 0.06 mag for a 20 Myr cluster. Thus, the observational error of locating the LDB (~7-10%) and the bolometric correction uncertainty currently dominate the error in LDB ages. For our base case, we formally derive a LDB age of 148 +- 19 Myr for the Pleiades, where the error includes 8, 3, and 9% contributions from observational, theoretical, and bolometric correction sources, respectively. A maximally plausible 0.3 magnitude shift in the I-band bolometric correction to reconcile main sequence isochrone fits with the observed (V-I) color for the low mass Pleiades members results in an age of 126 +- 11 Myr, where the error includes observational and theoretical errors only. Upper main-sequence-fitting ages that do not include convective core overshoot for the Pleiades (~75 Myr) are ruled out by the LDB age technique.Comment: 35 pages, 9 figures, accepted Ap

Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks.

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model

Influence of dietary conjugated linoleic acid on growth, meat quality, lipogenesis, plasma leptin and physiological variables of lipid metabolism in rabbits

We investigated the effects of conjugated linoleic acid (CLA) supplementation on growth, feed efficiency, carcass characteristics, meat quality, lipogenesis, and lipid metabolism in rabbits. One hundred forty-four New Zealand White rabbits, half males, half females, age 55 d, mean 1.8 kg BW, were randomly assigned to three weight- and sex-balanced feeding groups in which conventional pelleted diets were supplemented with 0, 0.25, or 0.5% of a CLA preparation. The CLA preparation contained 65% CLA isomers. Twelve rabbits (six males and six females from each group) were slaughtered at each of three slaughtering trials (2.5, 2.8, and 3.1 kg BW, or 76, 90, and 104 d of age). Conjugated linoleic acid supplementation did not influence growth performance (P > or = 0.05) or carcass characteristics but reduced perirenal fat at heavier slaughtering weights (P = 0.09 at 2.8 kg BW; P < 0.01 at 3.1 kg BW). Conjugated linoleic acid reduced acetyl-CoA-carboxylase (CBX) activity in liver (P < 0.05) and adipose tissues (P < 0.01) but did not influence malic enzyme (ME) or glucose-6-phosphate dehydrogenase activity. Significant differences were found between sex in interscapular fat (P < 0.05) for CBX, in perirenal (P < 0.01) and interscapular (P < 0.05) fat for ME, and a tendency (P = 0.070) in liver for glucose-6-phosphate dehydrogenase. The oxidative stability of longissimus lumborum muscle was increased at the higher level of supplementation (P < 0.05). Conjugated linoleic acid reduced (P < 0.05) triglycerides and total cholesterol in plasma with a trend to increased serum leptin (P = 0.06). Plasma triglycerides were higher in males than females (P < 0.01) and plasma leptin tended to be higher in females (2.57 vs. 2.13 ng/ml, P = 0.06). It is concluded that dietary CLA reduced carcass fat in rabbits slaughtered at 2.8 kg or above and altered lipid metabolism to produce lower concentrations of serum triglycerides and total cholesterol and higher concentrations of leptin

Fault tolerant LPV control of the GTM UAV with dynamic control allocation

The aim of the paper is to present a dynamic control allocation architecture for the design and development of reconfigurable and fault-tolerant control systems in aerial vehicles. The baseline control system is designed for the nominal dynamics of the aircraft, while faults and actuator saturation limits are handled by the dynamic control allocation scheme. Coordination of these components is provided by a supervisor which re-allocates control authority based on health information, flight envelope limits and cross coupling between lateral and longitudinal motion. The monitoring components and FDI filters provide the supervisor with information about different fault operations, based on that it is able to make decisions about necessary interventions into the vehicle motions and guarantee fault-tolerant operation of the aircraft. The design of the proposed reconfigurable control algorithm is based on Linear Parameter-varying (LPV) control methods that uses a parameter dependent dynamic control allocation scheme. The design is demonstrated on the lateral axis motion of the NASA AirSTAR Flight Test Vehicle simulation model

Procedures of sensors deployment methodology on physical supports/platforms

The aim of task 2.3 is to define specific platform characteristics and identify deployment difficulties in order to determine the adequacy of sensors within specific platforms. In order to obtain the necessary information, two online questionnaires were realized. One questionnaire was created for sensor developers and one for those partners that will test the sensors at sea. The seven developers in COMMON SENSE have provided information on seven sensors: two for underwater noise – CEFAS and IOPAN; two for microplastics – IDRONAUT and LEITAT; one for an innovative piro and piezo resistive polymeric temperature and pressure – CSIC; one for heavy metal – CSIC; one for eutrophication sensor – DCU. Outside the scope of the questionnaire, FTM has proposed three sensors of which two for oil spill and one for heavy metals, realized in the framework of a previous EU project but that can be improved and tested with several platforms. This information is anyway incomplete because in most cases for the novel sensors which will be developed over the course of COMMON SENSE, the sensors cannot be clearly designed yet as the project only started a few months ago - and, consequently, technical characteristics cannot actually be perfectly defined. This produces some lag in the acquired information that will be solved in the near future. In the other questionnaire, partners-testers have provided information on eleven platforms. Outside the questionnaire, IOPAN has described two more platforms, one of which is a motorboat not previously listed in the DoW, and they have informed us that the oceanographic buoy in Gdansk Bay is not actually available. This is valid also for platforms from other partners where there were only preliminary contacts like for example for Aqualog and OBSEA Underwater observatory. In the following months, new information will be provided and questionnaires information updated. Then important characteristics have to be considered such as maintenance, energy autonomy, data transfer/storage and dimension of the sensors that are actually missing. Further updates of this report are therefore necessary in order to individuate the most suitable platforms to test each kind of sensor and then used at the end of 2014 when WP9 (Testing activities) will start. Objectives and rationale The objective of deliverable 2.2 is the definition of the characteristics and procedures of sensors deployment methodology on physical supports/platforms, possible needs and characteristics of the available platform. This is preparatory for the activities in other WPs and tasks: - for task 2.2 (New generation technologies), that will provide cost-effective sensors for large scale production through Deliverable 2.1 [month 10]; - for task 2.5 (Monitoring strategy) where sensitivity and stress tests of new sensors will be designed in order to establish confidence limits under different situations and certify the performance of the new instruments [Deliverable 2.5 at month 16]. - for WP9 (Field testing) starting at month 12 (October 2014) when the deployment of new sensors will be drawn and then realized