Eggs, Larvae and Young of The Striped Bass, Roccus saxatilis

Detailed descriptions of the early development of the striped bass, Roccus saxitilis (Walbaum), with emphasis on variation in size and morphology, sequence of fin formation, changes in body form, and attainment of the full complement of maristic numbers, are presented and illustrated for the first time. The egg is spherical, transparent, non-adhesive and relatively large. It is pelagic and buoyant, although it sinks in quiet fresh water. When unfertilized, it averages 1.3 mm, in diameter, but is 3.4 mm. when fertilized and water-hardened. The granular yolk sac, green when alive and whitish-yellow when preserved, averages 1.2 mm., and the single amber-colored oil globule is about 0.6 mm. in diameter. Newly hatched striped bass prolarvae, which range from 2.9-3.7 mm. in total length, are relatively undeveloped and nearly transparent, with no mouth opening, unpigmented eyes, and a greatly enlarged yolk sac with the large oil globule projecting beyond the head. When 5-6 mm. long the yolk sac and oil globule are assimilated and the postlarvae I show advanced development of the internal anatomy. Although the fish is still transparent, scattered melanophores are found on the head and body and chromatophores in the eyes and the ventro-posterior edge of the body. Postlarvae transform to young between 7 and 10 mm. in length when the finfolds are lost except in the dorsal, anal and caudal regions. The largest fish in this group possess a well-formed skeleton with a full complement of 25 vertebrae. Between 10 and 20 mm. in length all fish are fully transformed, muscular tissue renders most of the internal structure obscure, and the myotomes, which generally correspond in number with the vertebrae, are no longer visible. At fish lengths of 20-30 mm. scales are found on all specimens, and with the exception of the pectoral fin-rays, a full complement of meristic structures is present in all other fins. At this stage the body is pigmented uniformly with small spots. Linear regressions between several dependent variables and the , independent variable of standard length indicate that the rate of development of head, eye. and snout to anus lengths is proportional to the length of the larvae and young. Body depth and standard length are non-linear among newly-hatched larvae. Hatchery-reared striped bass demonstrated a slow rate of growth, and were regarded as "stunted," when compared to growth rates observed in another study and field collections. Observations were also made on abnormal eggs and teratological larvae and young. Blue-sac disease is tentatively identified and described for the first time in larvae and pugnosed larvae and young are also described for the first time in striped bass.

Locally convex Riesz spaces and Archimedean quotient spaces

A Riesz space with a Hausdorff, locally convex topology determined by Riesz seminorms is called a locally convex Riesz space. A sequence {x_n} in a locally convex Riesz space L is said to converge locally to x ϵ L if for some topologically bounded set B and every real r ˃ 0 there exists N (r) and n ≥ N (r) implies x – x_n ϵ r^b. Local Cauchy sequences are defined analogously, and L is said to be locally complete if every local Cauchy sequence converges locally. Then L is locally complete if and only if every monotone local Cauchy sequence has a least upper bound. This is a somewhat more general form of the completeness criterion for Riesz – normed Riesz spaces given by Luxemburg and Zaanen. Locally complete, bound, locally convex Riesz spaces are barrelled. If the space is metrizable, local completeness and topological completeness are equivalent.

Two measures of the non-archimedean character of a non-archimedean Riesz space L are the smallest ideal A_o (L) such that quotient space is Archimedean and the ideal I (L) = { x ϵ L: for some 0 ≤ v ϵ L, n |x| ≤ v for n = 1, 2, …}. In general A_o (L) ᴝ I (L). If L is itself a quotient space, a necessary and sufficient condition that A_o (L) = I (L) is given. There is an example where A_o (L) ≠ I (L).

A necessary and sufficient condition that a Riesz space L have every quotient space Archimedean is that for every 0 ≤ u, v ϵ L there exist u₁ = sup (inf (n v, u): n = 1, 2, …), and real numbers m₁ and m₂ such that m₁ u₁ ≥ v₁ and m₂ v₁ ≥ u₁. If, in addition, L is Dedekind σ – complete, then L may be represented as the space of all functions which vanish off finite subsets of some non-empty set.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Is there a subgroup of long-term evolution among patients with advanced lung cancer?: Hints from the analysis of survival curves from cancer registry data

Background: Recently, with the access of low toxicity biological and targeted therapies, evidence of the existence of a long-term survival subpopulation of cancer patients is appearing. We have studied an unselected population with advanced lung cancer to look for evidence of multimodality in survival distribution, and estimate the proportion of long-term survivors. Methods: We used survival data of 4944 patients with non-small-cell lung cancer (NSCLC) stages IIIb-IV at diagnostic, registered in the National Cancer Registry of Cuba (NCRC) between January 1998 and December 2006. We fitted one-component survival model and two-component mixture models to identify short-and long-term survivors. Bayesian information criterion was used for model selection. Results: For all of the selected parametric distributions the two components model presented the best fit. The population with short-term survival (almost 4 months median survival) represented 64% of patients. The population of long-term survival included 35% of patients, and showed a median survival around 12 months. None of the patients of short-term survival was still alive at month 24, while 10% of the patients of long-term survival died afterwards. Conclusions: There is a subgroup showing long-term evolution among patients with advanced lung cancer. As survival rates continue to improve with the new generation of therapies, prognostic models considering short-and long-term survival subpopulations should be considered in clinical research.

Advanced Reaction Systems for Hydrogen Production

[EN] This PhD work started in March 2010 with the support of the University of the Basque Country (UPV/EHU) under the program named “Formación de Personal Investigador” at the Chemical and Environmental Engineering Department in the Faculty of Engineering of Bilbao. The major part of the Thesis work was carried out in the mentioned department, as a member of the Sustainable Process Engineering (SuPrEn) research group. In addition, this PhD Thesis includes the research work developed during a period of 6 months at the Institut für Mikrotechnik Mainz GmbH, IMM, in Germany. During the four years of the Thesis, conventional and microreactor systems were tested for several feedstocks renewable and non-renewable, gases and liquids through several reforming processes in order to produce hydrogen. For this purpose, new catalytic formulations which showed high activity, selectivity and stability were design. As a consequence, the PhD work performed allowed the publication of seven scientific articles in peer-reviewed journals. This PhD Thesis is divided into the following six chapters described below. The opportunity of this work is established on the basis of the transition period needed for moving from a petroleum based energy system to a renewable based new one. Consequently, the present global energy scenario was detailed in Chapter 1, and the role of hydrogen as a real alternative in the future energy system was justified based on several outlooks. Therefore, renewable and non-renewable hydrogen production routes were presented, explaining the corresponding benefits and drawbacks. Then, the raw materials used in this Thesis work were described and the most important issues regarding the processes and the characteristics of the catalytic formulations were explained. The introduction chapter finishes by introducing the concepts of decentralized production and process intensification with the use of microreactors. In addition, a small description of these innovative reaction systems and the benefits that entailed their use were also mentioned. In Chapter 2 the main objectives of this Thesis work are summarized. The development of advanced reaction systems for hydrogen rich mixtures production is the main objective. In addition, the use and comparison between two different reaction systems, (fixed bed reactor (FBR) and microreactor), the processing of renewable raw materials, the development of new, active, selective and stable catalytic formulations, and the optimization of the operating conditions were also established as additional partial objectives. Methane and natural gas (NG) steam reforming experimental results obtained when operated with microreactor and FBR systems are presented in Chapter 3. For these experiments nickel-based (Ni/Al2O3 and Ni/MgO) and noble metal-based (Pd/Al2O3 and Pt/Al2O3) catalysts were prepared by wet impregnation and their catalytic activity was measured at several temperatures, from 973 to 1073 K, different S/C ratios, from 1.0 to 2.0, and atmospheric pressure. The Weight Hourly Space Velocity (WHSV) was maintained constant in order to compare the catalytic activity in both reaction systems. The results obtained showed a better performance of the catalysts operating in microreactors. The Ni/MgO catalyst reached the highest hydrogen production yield at 1073 K and steam-to-carbon ratio (S/C) of 1.5 under Steam methane Reforming (SMR) conditions. In addition, this catalyst also showed good activity and stability under NG reforming at S/C=1.0 and 2.0. The Ni/Al2O3 catalyst also showed high activity and good stability and it was the catalyst reaching the highest methane conversion (72.9 %) and H2out/CH4in ratio (2.4) under SMR conditions at 1073 K and S/C=1.0. However, this catalyst suffered from deactivation when it was tested under NG reforming conditions. Regarding the activity measurements carried out with the noble metal-based catalysts in the microreactor systems, they suffered a very quick deactivation, probably because of the effects attributed to carbon deposition, which was detected by Scanning Electron Microscope (SEM). When the FBR was used no catalytic activity was measured with the catalysts under investigation, probably because they were operated at the same WHSV than the microreactors and these WHSVs were too high for FBR system. In Chapter 4 biogas reforming processes were studied. This chapter starts with an introduction explaining the properties of the biogas and the main production routes. Then, the experimental procedure carried out is detailed giving concrete information about the experimental set-up, defining the parameters measured, specifying the characteristics of the reactors used and describing the characterization techniques utilized. Each following section describes the results obtained from activity testing with the different catalysts prepared, which is subsequently summarized: Section 4.3: Biogas reforming processes using γ-Al2O3 based catalysts The activity results obtained by several Ni-based catalysts and a bimetallic Rh-Ni catalyst supported on magnesia or alumina modified with oxides like CeO2 and ZrO2 are presented in this section. In addition, an alumina-based commercial catalyst was tested in order to compare the activity results measured. Four different biogas reforming processes were studied using a FBR: dry reforming (DR), biogas steam reforming (BSR), biogas oxidative reforming (BOR) and tri-reforming (TR). For the BSR process different steam to carbon ratios (S/C) from 1.0 to 3.0, were tested. In the case of BOR process the oxygen-to-methane (O2/CH4) ratio was varied from 0.125 to 0.50. Finally, for TR processes different S/C ratios from 1.0 to 3.0, and O2/CH4 ratios of 0.25 and 0.50 were studied. Then, the catalysts which achieved high activity and stability were impregnated in a microreactor to explore the viability of process intensification. The operation with microreactors was carried out under the best experimental conditions measured in the FBR. In addition, the physicochemical characterization of the fresh and spent catalysts was carried out by Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), N2 physisorption, H2 chemisorption, Temperature Programmed Reduction (TPR), SEM, X-ray Photoelectron Spectroscopy (XPS) and X-ray powder Diffraction (XRD). Operating with the FBR, conversions close to the ones predicted by thermodynamic calculations were obtained by most of the catalysts tested. The Rh-Ni/Ce-Al2O3 catalyst obtained the highest hydrogen production yield in DR. In BSR process, the Ni/Ce-Al2O3 catalyst achieved the best activity results operating at S/C=1.0. In the case of BOR process, the Ni/Ce-Zr-Al2O3 catalyst showed the highest reactants conversion values operating at O2/CH4=0.25. Finally, in the TR process the Rh-Ni/Ce-Al2O3 catalyst obtained the best results operating at S/C=1.0 and O2/CH4=0.25. Therefore, these three catalysts were selected to be coated onto microchannels in order to test its performance under BOR and TR processes conditions. Although the operation using microreactors was carried out under considerably higher WHSV, similar conversions and yields as the ones measured in FBR were measured. Furthermore, attending to other measurements like Turnover Frequency (TOF) and Hydrogen Productivity (PROD), the values calculated for the catalysts tested in microreactors were one order of magnitude higher. Thus, due to the low dispersion degree measured by H2-chemisorption, the Ni/Ce-Al2O3 catalyst reached the highest TOF and PROD values. Section 4.4: Biogas reforming processes using Zeolites L based catalysts In this section three type of L zeolites, with different morphology and size, were synthesized and used as catalyst support. Then, for each type of L zeolite three nickel monometallic and their homologous Rh-Ni bimetallic catalysts were prepared by the wetness impregnation method. These catalysts were tested using the FBR under DR process and different conditions of BSR (S/C ratio of 1.0 and 2.0), BOR (O2/CH4 ratio of 0.25 and 0.50) and TR processes (at S/C=1.0 and O2/CH4=0.25). The characterization of these catalysts was also carried out by using the same techniques mentioned in the previous section. Very high methane and carbon dioxide conversion values were measured for almost all the catalysts under investigation. The experimental results evidenced the better catalytic behavior of the bimetallic catalysts as compared to the monometallic ones. Comparing the catalysts behavior with regards to their morphology, for the BSR process the Disc catalysts were the most active ones at the lowest S/C ratio tested. On the contrary, the Cylindrical (30–60 nm) catalysts were more active under BOR conditions at O2/CH4=0.25 and TR processes. By the contrary, the Cylindrical (1–3 µm) catalysts showed the worst activity results for both processes. Section 4.5: Biogas reforming processes using Na+ and Cs+ doped Zeolites LTL based catalysts A method for the synthesis of Linde Type L (LTL) zeolite under microwave-assisted hydrothermal conditions and its behavior as a support for heterogeneously catalyzed hydrogen production is described in this section. Then, rhodium and nickel-based bimetallic catalysts were prepared in order to be tested by DR process and BOR process at O2/CH4=0.25. Moreover, the characterization of the catalysts under investigation was also carried out. Higher activities were achieved by the catalysts prepared from the non-doped zeolites, Rh-Ni/D and Rh-Ni/N, as compared to the ones supported on Na+ and Cs+ exchanged supports. However, the differences between them were not very significant. In addition, the Na+ and Cs+ incorporation affected mainly to the Disc catalysts. Comparing the results obtained by these catalysts with the ones studied in the section 4.4, in general worst results were achieved under DR conditions and almost the same results when operated under BOR conditions. In Chapter 5 the ethylene glycol (EG) as feed for syngas production by steam reforming (SR) and oxidative steam reforming (OSR) was studied by using microchannel reactors. The product composition was determined at a S/C of 4.0, reaction temperatures between 625°C and 725°C, atmospheric pressure and Volume Hourly Space Velocities (VHSV) between 100 and 300 NL/(gcath). This work was divided in two sections. The first one corresponds to the introduction of the main and most promising EG production routes. Then, the new experimental procedure is detailed and the information about the experimental set-up and the measured parameters is described. The characterization was carried out using the same techniques as for the previous chapter. Then, the next sections correspond to the catalytic activity and catalysts characterization results. Section 5.3: xRh-cm and xRh-np catalysts for ethylene glycol reforming Initially, catalysts with different rhodium loading, from 1.0 to 5.0 wt. %, and supported on α-Al2O3 were prepared by two different preparation methods (conventional impregnation and separate nanoparticle synthesis). Then, the catalysts were compared regarding their measured activity and selectivity, as well as the characterization results obtained before and after the activity tests carried out. The samples prepared by a conventional impregnation method showed generally higher activity compared to catalysts prepared from Rh nanoparticles. By-product formation of species such as acetaldehyde, ethane and ethylene was detected, regardless if oxygen was added to the feed or not. Among the catalysts tested, the 2.5Rh-cm catalyst was considered the best one. Section 5.4: 2.5Rh-cm catalyst support modification with CeO2 and La2O3 In this part of the Chapter 5, the catalyst showing the best performance in the previous section, the 2.5Rh-Al2O3 catalyst, was selected in order to be improved. Therefore, new Rh based catalysts were designed using α-Al2O3 and being modified this support with different contents of CeO2 or La2O3 oxides. All the catalysts containing additives showed complete conversion and selectivities close to the equilibrium in both SR and OSR processes. In addition, for these catalysts the concentrations measured for the C2H4, CH4, CH3CHO and C2H6 by-products were very low. Finally, the 2.5Rh-20Ce catalyst was selected according to its catalytic activity and characterization results in order to run a stability test, which lasted more than 115 hours under stable operation. The last chapter, Chapter 6, summarizes the main conclusions achieved throughout this Thesis work. Although very high reactant conversions and rich hydrogen mixtures were obtained using a fixed bed reaction system, the use of microreactors improves the key issues, heat and mass transfer limitations, through which the reforming reactions are intensified. Therefore, they seem to be a very interesting and promising alternative for process intensification and decentralized production for remote application.

Advanced techniques for diagnostics and control applied to particle accelerators

201 p.