Design of an electroflotation system for the concentration and harvesting of freshwater microalgae

Microalgae are considered as one of the most promising alternatives for the integrated use of agro-industrial water residues and the production of metabolites of high industrial interest. This is due to algae can grow on wastewater which in turn can reduce the emission of nutrients to rivers and lakes. However, the greatest scientific-technological barrier is the concentration and separation of the biomass produced. There are several processes used at different levels (from laboratory to industrial scale) such as flocculation, centrifugation, flotation, etc. These can be very expensive or can (possibly) contaminate the biomass. Unlike the previous ones, electroflotation has been proposed as a cost-efficient method, nevertheless its final efficiency will depend heavily on the type of alga and culture medium. Taking into account the above, the present project aims to design an electroflotation system for the concentration and harvest of microalgae biomass. The effect of several factors (pH, time, voltage and distance between the electrodes) and for types of materials (Copper, Aluminium, Iron and Steel) on biomass recovery efficiency from a culture of Chlorella vulgaris UTEX 1803 was evaluated by the implementation of a Design of experiments (43 non-factorial design) using STATISTICA 7.0. Results show that, the materials with higher concentration efficiency were cooper and aluminium with 40 and 80% respectively, and the most relevant factors were distance between electrodes (1-2 cm), time (>20 min) and Voltage (>15V). In order to increase the efficiency of the overall process a new 43 experimental factorial design was proposed using as factors distance between electrodes, time, voltage and agitation. Results show that agitation positively affects the total efficiency until reaching a total concentration of the biomass (100%). It was found that a voltage close to 50V and a time greater than 25 min positively affect the final efficiency of the copper and aluminium electrodes, however aluminium has the highest efficiency (> 95%) compared to copper (<85%)

Cranio-spinal migration of a metallic clip placed during arteriovenous malformation resection - A case report, review of the literature, and management strategies

<p>Abstract</p> <p>Background</p> <p>Microclip placement during AVM resection is generally accepted to be a safe practice in neurosurgery. Here, we describe an unusual complication involving cranio-spinal clip migration discovered five years after the initial AVM surgery.</p> <p>Case Presentation</p> <p>A 53-year-old man underwent resection of a superior vermian AVM that required the placement of two microclips during the procedure. Five years after surgery, the patient suffered from descending sensory radiculopathy that resolved spontaneously. The workup revealed cranio-spinal migration of one of the previously placed microclips.</p> <p>Conclusions</p> <p>AVM clip migration is a rare phenomenon; however, the diagnosis should be entertained in patients with posterior fossa instrumentation who suffer from unusual neurologic symptoms.</p

Earth system data cubes unravel global multivariate dynamics

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model-data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

Earth system data cubes unravel global multivariate dynamics

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model-data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

A scalable monitoring for the CMS Filter Farm based on elasticsearch

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured information can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central" es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2

Three Adult Cases of STAT1 Gain-of-Function with Chronic Mucocutaneous Candidiasis Treated with JAK Inhibitors

Purpose; The aim of this study was to characterize clinical effects and biomarkers in three patients with chronic mucocutaneous candidiasis (CMC) caused by gain-of-function (GOF) mutations in the STAT1 gene during treatment with Janus kinase (JAK) inhibitors. Methods: Mass cytometry (CyTOF) was used to characterize mononuclear leukocyte populations and Olink assay to quantify 265 plasma proteins. Flow-cytometric Assay for Specific Cell-mediated Immune-response in Activated whole blood (FASCIA) was used to quantify the reactivity against Candida albicans. Results: Overall, JAK inhibitors improved clinical symptoms of CMC, but caused side effects in two patients. Absolute numbers of neutrophils, T cells, B cells, and NK cells were sustained during baricitinib treatment. Detailed analysis of cellular subsets, using CyTOF, revealed increased expression of CD45, CD52, and CD99 in NK cells, reflecting a more functional phenotype. Conversely, monocytes and eosinophils downregulated CD16, consistent with reduced inflammation. Moreover, T and B cells showed increased expression of activation markers during treatment. In one patient with a remarkable clinical effect of baricitinib treatment, the immune response to C. albicans increased after 7 weeks of treatment. Alterations in plasma biomarkers involved downregulation of cellular markers CXCL10, annexin A1, granzyme B, granzyme H, and oncostatin M, whereas FGF21 was the only upregulated marker after 7 weeks. After 3 months, IFN-gamma and CXCL10 were downregulated. Conclusions: The clinical effect of JAK inhibitor treatment of CMC is promising. Several biological variables were altered during baricitinib treatment demonstrating that lymphocytes, NK cells, monocytes, and eosinophils were affected. In parallel, cellular reactivity against C. albicans was enhanced

Balancing financial incentives during COVID-19: A comparison of provider payment adjustments across 20 countries

Provider payment mechanisms were adjusted in many countries in response to the COVID-19 pandemic in 2020. Our objective was to review adjustments for hospitals and healthcare professionals across 20 countries. We developed an analytical framework distinguishing between payment adjustments compensating income loss and those covering extra costs related to COVID-19. Information was extracted from the Covid-19 Health System Response Monitor (HSRM) and classified according to the framework. We found that income loss was not a problem in countries where professionals were paid by salary or capitation and hospitals received global budgets. In countries where payment was based on activity, income loss was compensated through budgets and higher fees. New FFS payments were introduced to incentivize remote services. Payments for COVID-19 related costs included new fees for out- and inpatient services but also new PD and DRG tariffs for hospitals. Budgets covered the costs of adjusting wards, creating new (ICU) beds, and hiring staff. We conclude that public payers assumed most of the COVID-19-related financial risk. In view of future pandemics policymakers should work to increase resilience of payment systems by: (1) having systems in place to rapidly adjust payment systems; (2) being aware of the economic incentives created by these adjustments such as cost-containment or increasing the number of patients or services, that can result in unintended consequences such as risk selection or overprovision of care; and (3) periodically evaluating the effects of payment adjustments on access and quality of care