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While the development of different vaccines has slowed the dissemination of SARS-CoV-2, the occurrence of breakthrough infections continues to fuel the pandemic. As a strategy to secure at least partial protection, with a single dose of a given COVID-19 vaccine to maximum possible fraction of the population,delayedadministration of subsequent doses (or boosters) has been implemented in many countries. However, waning immunity and emergence of new variants of SARS-CoV-2 suggest that such measures may jeopardize the attainment of herd immunity due to intermittent lapses in protection. Optimizing vaccine dosing schedules could thus make the difference between periodic occurrence of breakthrough infections or effective control of the pandemic. To this end, we have developed a mechanistic mathematical model of adaptive immune response to vaccines and demonstrated its applicability to COVID-19 mRNA vaccines as a proof-of-concept for future outbreaks. The model was thoroughly calibrated against multiple clinical datasets involving immune response to SARS-CoV-2 infection and mRNA vaccines in healthy and immunocompromised subjects (cancer patients undergoing therapy); the model showed robust clinical validation by accurately predicting neutralizing antibody kinetics, a correlate of vaccine-induced protection, in response to multiple doses of mRNA vaccines. Importantly, we estimated population vulnerability to breakthrough infections and predicted tailored vaccination dosing schedules to maximize protection and thus minimize breakthrough infections, based on the immune status of a sub-population. We have identified a critical waiting window for cancer patients (or, immunocompromised subjects) to allow recovery of the immune system (particularly CD4+ T-cells) for effective differentiation of B-cells to produce neutralizing antibodies and thus achieve optimal vaccine efficacy against variants of concern, especially between the first and second doses. Also, we have obtained optimized dosing schedules for subsequent doses in healthy and immunocompromised subjects, which vary from the CDC-recommended schedules, to minimize breakthrough infections. The developed modeling tool is based on generalized adaptive immune response to antigens and can thus be leveraged to guide vaccine dosing schedules during future outbreaks.

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time course of tumour responses to immune checkpoint inhibitors. The model takes into account intrinsic tumour growth rates, the rates of immune activation and of tumour-immune cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug-cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug-cancer sensitivities in individual patients.

Pancreatic Ductal Adenocarcinoma (PDAC) is regarded as one of the most lethal cancer types for its challenges associated with early diagnosis and resistance to standard chemotherapeutic agents, thereby leading to a poor five-year survival rate. The complexity of the disease calls for a multidisciplinary approach to better manage the disease and improve the status quo in PDAC diagnosis, prognosis, and treatment. To this end, the application of quantitative tools can help improve the understanding of disease mechanisms, develop biomarkers for early diagnosis, and design patient-specific treatment strategies to improve therapeutic outcomes. However, such approaches have only been minimally applied towards the investigation of PDAC, and we review the current status of mathematical modeling works in this field.

Graphical abstract, Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomaterials. Comprehensive investigation of these parameters using traditional experimental approaches is impractical due to the vast parameter space; mathematical models provide a more tractable approach to navigate through such a multidimensional space. To this end, we have developed a predictive mathematical model of whole-body NP pharmacokinetics and their tumor delivery in vivo, and have conducted local and global sensitivity analyses to identify the factors that result in low tumor delivery efficiency and high off-target accumulation of NPs. Our analyses reveal that NP degradation rate, tumor blood viscosity, NP size, tumor vascular fraction, and tumor vascular porosity are the key parameters in governing NP kinetics in the tumor interstitium. The impact of these parameters on tumor delivery efficiency of NPs is discussed, and optimal values for maximizing NP delivery are presented.

The photovoltaic evaporative chimney is a novel solar-cooling system that serves a double purpose: it increases the efficiency of the photovoltaic (PV) panels and it cools down a water stream which can be used to dissipate the heat from a refrigeration cycle. One of the major issues arising from the operation of the chimney is the temperature stratification in the panel due to the movement of the air in the chimney. This effect can trigger the activation of the bypass diodes of the module, creating local maximum power points (MPP) that can compromise the grid-tied inverter tracking. To fill this gap, this paper deals with the design and implementation of an I–V curve measurement system to be used in the performance analysis of the system. The I–V curve tracer consists of a capacitive load controlled by a single board computer. The final design includes protections, capacitor charging/discharging power electronics, remote commands inputs, and current, voltage, irradiance, and temperature sensors.The results show that the modules bypass diodes are not activated during the tests, and no local MPPs appear. Moreover, the curves measured show the benefits of the photovoltaic chimney: the cooling effect increases the power generated by the PV panels by around 10%.

We present a multiscale agent-based model of ductal carcinoma in situ (DCIS) to study how key phenotypic and signaling pathways are involved in the early stages of disease progression. The model includes a phenotypic hierarchy, and key endocrine and paracrine signaling pathways, and simulates cancer ductal growth in a 3D lattice-free domain. In particular, by considering stochastic cell dedifferentiation plasticity, the model allows for study of how dedifferentiation to a more stem-like phenotype plays key roles in the maintenance of cancer stem cell populations and disease progression. Through extensive parameter perturbation studies, we have quantified and ranked how DCIS is sensitive to perturbations in several key mechanisms that are instrumental to early disease development. Our studies reveal that long-term maintenance of multipotent stem-like cell niches within the tumor are dependent on cell dedifferentiation plasticity, and that disease progression will become arrested due to dilution of the multipotent stem-like population in the absence of dedifferentiation. We have identified dedifferentiation rates necessary to maintain biologically relevant multipotent cell populations, and also explored quantitative relationships between dedifferentiation rates and disease progression rates, which may potentially help to optimize the efficacy of emerging anti-cancer stem cell therapeutics.

The downregulation of miRNA-22 in triple negative breast cancer (TNBC) is associated with upregulation of eukaryotic elongation 2 factor kinase (eEF2K) protein, which regulates tumor growth, chemoresistance, and tumor immunosurveillance. Moreover, exogenous administration of miRNA-22, loaded in nanoparticles to prevent degradation and improve tumor delivery (termed miRNA-22 nanotherapy), to suppress eEF2K production has shown potential as an investigational therapeutic agent in vivo. To evaluate the translational potential of miRNA-22 nanotherapy, we developed a multiscale mechanistic model, calibrated to published in vivo data and extrapolated to the human scale, to describe and quantify the pharmacokinetics and pharmacodynamics of miRNA-22 in virtual patient populations. Our analysis revealed the dose-response relationship, suggested optimal treatment frequency for miRNA-22 nanotherapy, and highlighted key determinants of therapy response, from which combination with immune checkpoint inhibitors was identified as a candidate strategy for improving treatment outcomes. More importantly, drug synergy was identified between miRNA-22 and standard-of-care drugs for TNBC, providing a basis for rational therapeutic combinations for improved response.

Purpose Downregulation of miRNA-22 in triple-negative breast cancer (TNBC) is associated with upregulation of eukaryotic elongation 2 factor kinase (eEF2K) protein, which regulates tumor growth, chemoresistance, and tumor immunosurveillance. Moreover, exogenous administration of miRNA-22, loaded in nanoparticles to prevent degradation and improve tumor delivery (termed miRNA-22 nanotherapy), to suppress eEF2K production has shown potential as an investigational therapeutic agent in vivo. Methods To evaluate the translational potential of miRNA-22 nanotherapy, we developed a multiscale mechanistic model, calibrated to published in vivo data and extrapolated to the human scale, to describe and quantify the pharmacokinetics and pharmacodynamics of miRNA-22 in virtual patient populations. Results Our analysis revealed the dose-response relationship, suggested optimal treatment frequency for miRNA-22 nanotherapy, and highlighted key determinants of therapy response, from which combination with immune checkpoint inhibitors was identified as a candidate strategy for improving treatment outcomes. More importantly, drug synergy was identified between miRNA-22 and standard-of-care drugs against TNBC, providing a basis for rational therapeutic combinations for improved response Conclusions The present study highlights the translational potential of miRNA-22 nanotherapy for TNBC in combination with standard-of-care drugs.

Triple-negative breast cancer (TNBC) is an aggressive tumor with limited treatment options and poor prognosis. We applied the in vivo phage display technology to isolate peptides homing to the immunosuppressive cellular microenvironment of TNBC as a strategy for non-malignant target discovery. We identified a cyclic peptide (CSSTRESAC) that specifically binds to a vitamin D receptor, protein disulfide-isomerase A3 (PDIA3) expressed on the cell surface of tumor-associated macrophages (TAM), and targets breast cancer in syngeneic TNBC, non-TNBC xenograft, and transgenic mouse models. Systemic administration of CSSTRESAC to TNBC-bearing mice shifted the cytokine profile toward an antitumor immune response and delayed tumor growth. Moreover, CSSTRESAC enabled ligand-directed theranostic delivery to tumors and a mathematical model confirmed our experimental findings. Finally, in silico analysis showed PDIA3-expressing TAM in TNBC patients. This work uncovers a functional interplay between a cell surface vitamin D receptor in TAM and antitumor immune response that could be therapeutically exploited.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. To develop disease management strategies, a better understanding of SARS-CoV-2 pathogenesis and population susceptibility to infection are needed. To this end, physiologically-relevant mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency for infection) of the virus, and by incorporating cellular-scale viral dynamics and innate and adaptive immune responses, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body (respiratory tract, gut, liver, spleen, heart, kidneys, and brain). Following calibration with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, we conducted global sensitivity analysis of model parameters and ranked them for their significance in governing clearance of viral load to understand the effects of physiological factors and underlying conditions on viral load dynamics. Antiviral drug therapy, interferon therapy, and their combination was simulated to study the effects on viral load kinetics of SARS-CoV-2. The model revealed the dominant role of innate immunity (specifically interferons and resident macrophages) in controlling viral load, and the importance of timing when initiating therapy following infection., Graphical Abstract

Intratumoral drug delivery is a promising approach for the treatment of glioblastoma multiforme (GBM)., Intratumoral drug delivery is a promising approach for the treatment of glioblastoma multiforme (GBM). However, drug washout remains a major challenge in GBM therapy. Our strategy, aimed at reducing drug clearance and enhancing site-specific residence time, involves the local administration of a multi-component system comprised of nanoparticles (NPs) embedded within a thermosensitive hydrogel (HG). Herein, our objective was to examine the distribution of NPs and their cargo following intratumoral administration of this system in GBM. We hypothesized that the HG matrix, which undergoes rapid gelation upon increases in temperature, would contribute towards heightened site-specific retention and permanence of NPs in tumors. BODIPY-containing, infrared dye-labeled polymeric NPs embedded in a thermosensitive HG (HG–NPs) were fabricated and characterized. Retention and distribution dynamics were subsequently examined over time in orthotopic GBM-bearing mice. Results demonstrate that the HG–NPs system significantly improved site-specific, long-term retention of both NPs and BODIPY, with co-localization analyses showing that HG–NPs covered larger areas of the tumor and the peri-tumor region at later time points. Moreover, NPs released from the HG were shown to undergo uptake by surrounding GBM cells. Findings suggest that intratumoral delivery with HG–NPs has immense potential for GBM treatment, as well as other strategies where site-specific, long-term retention of therapeutic agents is warranted.

The application of nanomedicine for diagnosis and treatment of cancer has immense potential, but has witnessed only limited clinical success, in part due to insufficient understanding of the role of nanomaterial properties and physiological variables in governing nanoparticle (NP) pharmacology. Here, we present a multiscale mathematical model to examine the effects of physiological changes associated with patient age on the pharmacokinetics and tumor delivery efficiency of NPs. We show that physiological changes due to aging prolong the residence of NPs in the systemic circulation, thereby improving passive accumulation of NPs in tumors.Clinical Relevance — Understanding the effect of inter-individual variability on the pharmacological behavior of nanomaterials will improve their clinical translatability.

BackgroundPreviously, we characterized subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed-tomography (CT) scans, whereby conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we hypothesized that these imaging-based subtypes would exhibit different growth-rates and distinctive metabolic effects in the period prior to PDAC diagnosis.Materials and methodsRetrospectively, we evaluated 55 patients who developed PDAC as a second primary cancer and underwent serial pre-diagnostic (T0) and diagnostic (T1) CT-scans. We scored the PDAC tumors into high and low delta on T1 and, serially, obtained the biaxial measurements of the pancreatic lesions (T0-T1). We used the Gompertz-function to model the growth-kinetics and estimate the tumor growth-rate constant (α) which was used for tumor binary classification, followed by cross-validation of the classifier accuracy. We used maximum-likelihood estimation to estimate initiation-time from a single cell (10-6 mm3) to a 10 mm3 tumor mass. Finally, we serially quantified the subcutaneous-abdominal-fat (SAF), visceral-abdominal-fat (VAF), and muscles volumes (cm3) on CT-scans, and recorded the change in blood glucose (BG) levels. T-test, likelihood-ratio, Cox proportional-hazards, and Kaplan-Meier were used for statistical analysis and p-value ResultsCompared to high delta tumors, low delta tumors had significantly slower average growth-rate constants (0.024 month−1 vs. 0.088 month−1, p−1. Leave-one-out-cross-validation showed 80% accuracy in predicting the delta-class (AUC=0.84). High delta tumors exhibited accelerated SAF, VAF, and muscle wasting (p ConclusionImaging-based subtypes of PDAC exhibit distinct growth, metabolic, and clinical profiles during the pre-diagnostic period. Our results suggest that heterogeneous disease biology may be an important consideration in early detection strategies for PDAC.

While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules (drug‐loaded nanomaterials or monoclonal antibodies), which can experience challenges to effective delivery due to particle size‐dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non‐invasive in vivo imaging modalities. This allows for visualization and quantification of the whole‐body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non‐invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state‐of‐the‐art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities. This article is categorized under:Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic DiseaseDiagnostic Tools > in vivo Nanodiagnostics and ImagingNanotechnology Approaches to Biology > Nanoscale Systems in Biology, Pharmacological evaluation of nanoparticles and antibodies performed through quantitative imaging‐guided mathematical models.

In this work, we use a computational technique with multiple properties of consistency in order to approximate solutions of a bounded β-Fermi–Pasta–Ulam lattice in two space dimensions subject to harmonic driving in two adjacent boundaries. The processes of nonlinear supratransmission and infratransmission are employed in order to propagate binary signals in the medium by means of a suitable modulation of the driving amplitude.

An affine finite element scheme approximation of a time dependent linear convection-diffusion-reaction problem in 2D and 3D is presented. For these equations which do not satisfy an underlying maximum principle, sufficient conditions are given in terms of the coefficient functions, the computational grid and the discretization parameters to ensure that the nonnegativity property of the true solution is also satisfied by its approximation. Numerical examples are given which confirm the necessity and sufficiency of the discretization conditions to guarantee the nonnegativity of the approximation. We present a monotone FEM scheme for a convection-diffusion-reaction problem in 2, 3D.The considered equation does not possess an underlying maximum principle.Sufficient conditions are given to ensure the nonnegativity of the approximations.Numerical examples confirm the necessity and sufficiency of the conditions.

Adiabatic cooling pads are mostly used as a previous step for cooling systems, they cause the raise of the cooling system global efficiency. In this study, several types of pads have been analysed regarding on its compactness and thickness. The problem is addressed from an experimental, analytical and numerical point of view.vThe validation of the temperature drop and cooling efficiency of the cooling pad numerical model is the main objective of this paper, and, in order to get this goal, Discrete Phase Model (DPM) of ANSYS Fluent software is used to calculate how water droplets, injected over the pad to cool the air, evaporate and how the continuous phase affect them. The results of this paper, focused to be a part of a complete cooling system analysis carried out by the research group, show the performance of an adiabatic cooling pad varying its width and compactness. The authors acknowledge the financial support received from the Spanish Government, through Projects ENE2013-48696-C2-1-R and C2-2-R as well as by the FEDER (Fondo Europeo de Desarrollo Regional).

espanolLas emisiones de gotas ocasionadas por el principio de funcionamiento de torres de refrigeracion son indeseables por diferentes motivos, pero principalmente porque pueden suponer un deterioro de la salud humana (por ejemplo por contagio por legionella). Pese a su mayor eficiencia energetica, derivada del menor nivel de presion introducido en el condensador al emplear agua como medio de condensacion, muchas administraciones estan limitando o prohibiendo el empleo de este tipo de sistemas al ser catalogados como fuentes potenciales de contaminacion. El nivel de emisiones del dispositivo asi como su eficiencia energetica, dependen en mayor medida de las condiciones de operacion del sistema y de los elementos constructivos del mismo (binomio sistema de distribucion-separador de gotas y relleno). La presente Tesis Doctoral muestra un estudio detallado de la influencia del binomio sistema de distribucion-separador de gotas asi como de las condiciones de operacion en el comportamiento termico y en las emisiones de torres de refrigeracion con objeto de optimizar el funcionamiento de la misma. Asimismo se estudia la dispersion de las emisiones para evaluar el impacto de la instalacion. La metodologia de trabajo ha sido principalmente experimental, donde los resultados relativos a la influencia de estos elementos sobre el comportamiento termico, las emisiones y la dispersion de las mismas ha sido determinada en la instalacion experimental de torre de refrigeracion dispuesta para tal efecto. Se ha empleado una torre meteorologica para la determinacion de las variables atmosfericas. Se ha llevado a cabo un modelo numerico para obtener un mayor conocimiento del campo fluido en el interior de los componentes de la torre, cuyos resultados se han comparado con los obtenidos experimentalmente en el tunel de medida de presion experimental (construido ex-profeso para ello). El estudio del comportamiento termico de la torre en funcion del binomio y de las condiciones de operacion ha dejado como resultados significativos que la eficiencia de la torre puede verse modificada en un 20% de media cambiando el sistema de distribucion para los separadores ensayados. Se han propuesto correlaciones adimensionales para cada geometria ensayada validadas con datos experimentales con un 1% de diferencia y se han valorado las implicaciones energeticas. El impacto energetico que puede ocasionar el cambio del elementos-condiciones de operacion para un sistema se ha evaluado a traves de la temperatura de salida del agua, la cual puede ser de hasta 1oC inferior de media. El estudio de la influencia del binomio y las condiciones de funcionamiento sobre el nivel de emisiones de la torre se ha realizado empleando en metodo del papel hidrosensible. La mayor contribucion realizada a la metodologia es el desarrollo de una aplicacion informatica con un clasificador automatico que permite determinar si los cambios de tonalidad detectados en el papel tienen su origen en una gota o no. Se ha determinado la cantidad y forma de las gotas a la salida para un amplio rango de casos y condiciones de operacion. La combinacion de minimo arrastre, 0,00009%, se ha obtenido para la combinacion separador de gotas de estructura de panal de abeja y sistema de distribucion por gravedad. Se han comparado los resultados con las normativas internacionales vigentes observando una posible revision de las mismas debido a las bajos niveles de emision alcanzados por las tecnologias actuales de componentes, muy por debajo de los valores establecidos en las normativas. Un resultado relevante es la determinacion de las curvas experimentales de eficiencia captura de los separadores ensayados. El estudio de emisiones se ha completado con la determinacion de la dispersion de las mismas en entornos urbanos mediante la tecnica del papel hidrosensible para ocho experimentos. Se ha analizado la influencia de las condiciones ambientales en la deposicion obteniendo tendencias decrecientes con la velocidad de viento y la distancia con respecto a la torre. Se ha observado que la zona de ensayo tiene influencia sobre los resultados (hasta un 70% en funcion del nivel de velocidad de viento). Para completar el trabajo experimental se ha generado un modelo numerico para los separadores de gotas de la tipologia de lamas ensayados, comparado con datos experimentales propios y validado a traves de resultados bibliograficos. Se ha determinado la influencia de cerrar el conjunto de ecuaciones que gobiernan el problema con modelos RANS y LES. La discretizacion de las ecuaciones con este ultimo no supone una mejora sustancial en la precision de los resultados obtenidos con respecto a los modelos RANS. Sin embargo si se ha encontrado la necesidad de modelar la capa liquida de agua formada en el separador. Mediante el analisis de esta informacion se ha obtenido un amplio conocimiento de la influencia del binomio sistema de distribucion-separador de gotas en el comportamiento de una torre de refrigeracion. La metodologia aplicada permitira mejorar los futuros disenos de estos componentes asi como optimizar las condiciones de operacion, siempre teniendo en cuenta que se debe alcanzar un compromiso entre el impacto energetico (comportamiento termico, perdida de presion) y las emisiones (arrastre, PM10) de la torre de refrigeracion. http://repositorio.bib.upct.es/dspace/ EnglishCooling tower emissions are harmful for several reasons, but mainly due to human health hazards (i.e. Legionella outbreaks). Despite the higher performance of this kind of devices, because of the lower condensating pressure level originated by water-cooled systems, many local governments are limiting or banning these systems as they have been listed as potential sources of contamination. The cooling tower level of emissions as well as its thermal performance depend mostly on the operating conditions and its elements (the couple of elements water distribution system and drift eliminator, also known as binomial, and the fill). The present Doctoral Thesis presents a detailed study on the influence of the binomial water distribution system-drift eliminator and the operating conditions on cooling tower thermal performance and emissions. The dispersion of the emissions is also studied. A broad experimental study has been undertaken. Experiments related to thermal performance, emissions and dispersion in an urban areas have been carried out in the cooling tower experimental facility. A weather mast has been used to characterize ambient conditions. To achieve a higher knowledge of the flow inside the tower, a numerical model of the drift eliminators has been developed. Numerical results have been compared to those observed in the experiments carried out in the experimental drop-pressure tunnel. Cooling tower thermal behavior as a function of the binomial and the operating conditions has led to differences about 20% between distribution systems for the eliminators tested. Dimensionless correlations for all the tested geometries have been proposed. These correlations have been validated through experimental results with about 1% differences. The energy consumption of the system has been evaluated through the calculation of the outlet water temperature, which can be 1oC lower on average depending on the distribution system. The influence of the binomial and the operating conditions on cooling tower emission has been carried out using the sensitive paper method. One of the most relevant contributions to the methodology is the developed automatic classifier which allows to discern between the stains coming from real drops. The number and shape of exiting droplets have been calculated for each combination tested. The lowest level of emissions, 0, 00009%, has been observed for the combination honeycomb-type drift eliminator and the gravity distribution system. Results are discussed according to international standars. According to the limits, a review of these standars is proposed because today technologies can guarantee lower drift rates. The experimental collection efficiency for the tested eliminators has found to be an important result. Cooling tower emission study is completed with the experimental determination of the downwind deposition. The sensitive paper method is also used for experimentally investigating drift deposition in urban areas for eight tests. The influence of ambient conditions on cooling tower drift deposition has been investigated. Decreasing patterns of deposition have been found when increasing the distance from the tower and the wind velocity. The test zone also affects the results (70% differences depending on the wind velocity). To complete experimental results, a numerical model for the lath-type eliminators has been developed. This model has been compared to the experimental results derived in this document and those available in the literature (numerical). It is has been investigated the difference between closing the systems of fundamental equations using RANS and LES approaches. The LES model does not improve results comparing them with the results obtained with RANS models. However, the need of modeling the water film formed in the eliminators has been highlighted. The accomplishment of this information provides a deep knowledge on the influence of the binomial water distributions system-eliminator and the operating conditions on cooling tower performance. This methodology provides with the necessary knowledge to improve future designs and to ensure better operating conditions, always reaching a compromise between the energy consumption (thermal behavior, pressure losses) and emissions (drift and PM10).

The energy consumption increase in the last few years has contributed to developing energy efficiency policies in many countries, the main goal of which is decreasing CO 2 emissions. One of the reasons for this increment has been caused by the use of air conditioning systems due to new comfort standards. In that regard, cooling towers and evaporative condensers are presented as efficient devices that operate with low-level water temperature. Moreover, the energy consumption and the cost of the equipment are lower than other systems like air condensers at the same operation conditions. This work models an air conditioning system in TRNSYS software, the main elements if which are a cooling tower, a water-water chiller and a reference building. The cooling tower model is validated using experimental data in a pilot plant. The main objective is to implement an optimizing control strategy in order to reduce both energy and water consumption. Furthermore a comparison between three typical methods of capacity control is carried out. Additionally, different cooling tower configurations are assessed, involving six drift eliminators and two water distribution systems. Results show the influence of optimizing the control strategy and cooling tower configuration, with a maximum energy savings of 10.8% per story and a reduction of 4.8% in water consumption.

Water drift emitted from cooling towers is objectionable for several reasons, mainly due to human health hazards. Generation and control of drift depends mostly on the drift eliminator, a device installed in mechanical cooling towers to prevent the escape of droplets (drift). These eliminators induce a rapid alternation of direction changes, and then the droplets cannot follow the path lines of the airflow within the channels of the eliminator and impact on the plates of it, falling back to the cooling tower ground. This paper focuses on the numerical study of a type of drift eliminator, validated by experimental tests. Three main aspects are considered: the water film formed on the plates of drift eliminators, the size of water droplets detached from this film and the condition of the detachment of these droplets. Good agreement is obtained between numerical and experimental results. The study shows that the behavior of water droplets is very influenced by the air velocity inside the cooling tower. This research is sponsored by the Spanish Government (Projects ENE2010-21679-C02-01 and -02), as well as by the Seneca-Agency for Science and Technology of the Region of Murcia, Spain (Project 15184/PI/10).

The saturated magnetization curves of a sintered Bi2Sr2CaCu2O8+δ superconductor are measured at different temperatures below Tc. The data are fitted by an extended critical‐state model, so that the lower critical field, Hc1, and the first field for vortex entry, H1, are obtained. With decreasing temperature, Hc1 increases almost linearly whereas H1≳Hc1 below 50 K. Above 50 K, Bean–Livingston surface barriers disappear and the M(H) curves show anomalies that suggest that the critical‐state model is not valid.

The onset of ferromagnetism has been experimentally observed in small Pd particles of average diameter 2.4 nm. High-resolution studies reveal that a high percentage of the fcc particle exhibits single and multiple twinning boundaries. The spontaneous magnetization close to 0.02 emu/g seems to indicate that only a small fraction of atoms holds a permanent magnetic moment and contributes to ferromagnetism. The possible origin of ferromagnetism is briefly discussed according to different models recently reported.