Chemo-enzymatic saccharification strategy of microalgae chlorella sorokiniana

Biofuel production using microalgae attracted much attention because it can be cultured using CO2 and sunlight. With high carbohydrate content, microalgae have the potential to be used as a fermentation feedstock for bioethanol production. In present work, chemo-enzymatic saccharification of Chlorella sorokiniana microalgae were investigated. Chemical hydrolysis of the biomass followed by enzymatic hydrolysis and was also evaluated the effect of combining the two enzymes and the sequential addition. The effect of α-amylase concentrations was analyzed in ranged between 50 and 8000 U/g of biomass and for amyloglucosidase between 90 and 600 U/g of biomass. The higher concentrations showed the highest conversion of reducing sugars. The α-amylase concentration 8000 U/g of biomass presented a conversion of 43.06 ± 2.92% (w/w), while amyloglucosidase with 600 U/g of biomass obtained 76.57 ± 6.42% (w/w). The combination of two enzymes simultaneously was more efficient than the sequential addition for low enzyme concentrations (α-amylase 50 U/g and amyloglucosidase 90 U/g) with a total reducing sugar of 22.78 ± 3.06 and 16.92 ± 2.06% (w/w), respectively. On the other hand, using the higher enzymes concentrations, no difference was observed between the two addition strategies, 58.9 ± 3.55 and 57.05 ± 2.33% (w/w) for the sequential and simultaneous, respectively. Both strategies didn’t present advantage, since the amyloglucosidase enzyme alone produced slightly higher results. Even thought, the obtained results showed successfully performed saccharification of microalgal biomass and clearly point to microalgae use for saccharification and subsequent bioethanol production.Part of this work has been supported by European governments (INTERREG VA-POCTEP- 2014-2020; 0055_ALGARED_PLUS_5_E) and the Portuguese Science Foundation (FCT) through the grant UID/MAR/00350/2013 to the CIMA of the University of Algarve.info:eu-repo/semantics/publishedVersio

Beyond classical sulfone chemistry: metal- and photocatalytic approaches for C-S bond functionalization of sulfones

The exceptional versatility of sulfones has been extensively exploited in organic synthesis across several decades. Since the first demonstration in 2005 that sulfones can participate in Pd-catalysed Suzuki-Miyaura type reactions, tremendous advances in catalytic desulfitative functionalizations have opened a new area of research with burgeoning activity in recent years. This emerging field is displaying sulfone derivatives as a new class of substrates enabling catalytic C-C and C-X bond construction. In this review, we will discuss new facets of sulfone reactivity toward further expanding the flexibility of C-S bonds, with an emphasis on key mechanistic features. The inherent challenges confronting the development of these strategies will be presented, along with the potential application of this chemistry for the synthesis of natural products. Taken together, this knowledge should stimulate impactful improvements on the use of sulfones in catalytic desulfitative C-C and C-X bond formation. A main goal of this article is to bring this technology to the mainstream catalysis practice and to serve as inspiration for new perspectives in catalytic transformation

Investigation of thin gate-stack Z2-FET devices as capacitor-less memory cells

Thin-oxide Z2-FET cells operating as capacitor-less DRAM devices are experimentally demonstrated. Both the retention time and memory window demonstrate the feasibility of implementing this cell in advanced 28 nm node FD SOI technology. Nevertheless a performance drop and higher variability with respect to thicker oxide Z2-FET cells are observed.H2020 REMINDER European project (grant agreementNo 687931) and TEC2014-59730 are thanked for financialsupport

A novel mobile application to determine mandibular and tongue laterality discrimination in women with chronic temporomandibular disorder

Chronic pain from temporomandibular disorders (TMDs) is caused by a somatosensory disturbance due to sustained activation of central nervous system nociceptive pathways, which can induce changes in neuroplasticity in the thalamus, basal ganglia and limbic system, as well as disturbances in the somatosensory, prefrontal and orbitofrontal cortex and cognitive impairment. The main objective of this study was to determine the discrimination capacity of mandibular and tongue laterality between women with chronic TMDs and asymptomatic women. This descriptive-comparative study examined 2 groups with a total of 30 women. All participants were between the ages of 23 and 66 years and were assigned to the chronic TMD group or the asymptomatic group according to the inclusion criteria. We employed a mobile application developed specifically for this study to measure the accuracy and reaction time (RT) of mandibular and tongue laterality discrimination. The chronic TMD group had a lower success rate in laterality discrimination (mean mandibular accuracy of 40% and mean tongue accuracy of 67%) than the asymptomatic group (mean mandibular accuracy of 61% and mean tongue accuracy of 90%). These results showed statistically significant differences between the groups for mandibular laterality discrimination (d, 1.14; p<0.01) and tongue laterality discrimination (d, 0.79; p=0.03). The asymptomatic group had faster RTs than the chronic TMD group. The data revealed statistically significant differences for the right mandibular RT (d, 0.89; p=0.02) and right tongue RT (d, 0.83; p=0.03). However, there were no significant differences for left mandibular and left tongue RT. We found that the women with chronic TMDs had a lower success rate and slower RTs in the discrimination of mandibular laterality when compared with the asymptomatic women

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained

Design of New Dispersants Using Machine Learning and Visual Analytics

Artificial intelligence (AI) is an emerging technology that is revolutionizing the discovery of new materials. One key application of AI is virtual screening of chemical libraries, which enables the accelerated discovery of materials with desired properties. In this study, we developed computational models to predict the dispersancy efficiency of oil and lubricant additives, a critical property in their design that can be estimated through a quantity named blotter spot. We propose a comprehensive approach that combines machine learning techniques with visual analytics strategies in an interactive tool that supports domain experts’ decision-making. We evaluated the proposed models quantitatively and illustrated their benefits through a case study. Specifically, we analyzed a series of virtual polyisobutylene succinimide (PIBSI) molecules derived from a known reference substrate. Our best-performing probabilistic model was Bayesian Additive Regression Trees (BART), which achieved a mean absolute error of (Formula presented.) and a root mean square error of (Formula presented.), as estimated through 5-fold cross-validation. To facilitate future research, we have made the dataset, including the potential dispersants used for modeling, publicly available. Our approach can help accelerate the discovery of new oil and lubricant additives, and our interactive tool can aid domain experts in making informed decisions based on blotter spot and other key propertie

The Low-mass Stellar Population in L1641: Evidence for Environmental Dependence of the Stellar Initial Mass Function

We present results from an optical photometric and spectroscopic survey of the young stellar population in L1641, the low-density star-forming region of the Orion A cloud south of the Orion Nebula Cluster (ONC). Our goal is to determine whether L1641 has a large enough low-mass population to make the known lack of high-mass stars a statistically-significant demonstration of environmental dependence of the upper mass stellar initial mass function (IMF). Our spectroscopic sample consists of IR-excess objects selected from the Spitzer/IRAC survey and non-excess objects selected from optical photometry. We have spectral confirmation of 864 members, with another 98 probable members; of the confirmed members, 406 have infrared excesses and 458 do not. Assuming the same ratio of stars with and without IR excesses in the highly-extincted regions, L1641 may contain as many as ~1600 stars down to ~0.1 solar mass, comparable within a factor of two to the the ONC. Compared to the standard models of the IMF, L1641 is deficient in O and early B stars to a 3-4 sigma significance level, assuming that we know of all the massive stars in L1641. With a forthcoming survey of the intermediate-mass stars, we will be in a better position to make a direct comparison with the neighboring, dense ONC, which should yield a stronger test of the dependence of the high-mass end of the stellar initial mass function upon environment.Comment: 19 pages, 21 figures. Accepted by Ap

NeBula: Team CoSTAR's robotic autonomy solution that won phase II of DARPA Subterranean Challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR¿s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.The work is partially supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004), and Defense Advanced Research Projects Agency (DARPA)

The impact of polyphenols on chondrocyte growth and survival: a preliminary report

Background: Imbalances in the functional binding of fibroblast growth factors (FGFs) to their receptors (FGFRs) have consequences for cell proliferation and differentiation that in chondrocytes may lead to degraded cartilage. The toxic, proinflammatory, and oxidative response of cytokines and FGFs can be mitigated by dietary polyphenols. Objective: We explored the possible effects of polyphenols in the management of osteoarticular diseases using a model based on the transduction of a mutated human FGFR3 (G380R) in murine chondrocytes. This mutation is present in most cases of skeletal dysplasia and is responsible for the overexpression of FGFR3 that, in the presence of its ligand, FGF9, results in toxic effects leading to altered cellular growth. Design: Different combinations of dietary polyphenols derived from plant extracts were assayed in FGFR3 (G380R) mutated murine chondrocytes, exploring cell survival, chloride efflux, extracellular matrix (ECM) generation, and grade of activation of mitogen-activated protein kinases. Results: Bioactive compounds from Hibiscus sabdariffa reversed the toxic effects of FGF9 and restored normal growth, suggesting a probable translation to clinical requests in humans. Indeed, these compounds activated the intracellular chloride efflux, increased ECM generation, and stimulated cell proliferation. The inhibition of mitogen-activated protein kinase phosphorylation was interpreted as the main mechanism governing these beneficial effects. Conclusions: These findings support the rationale behind the encouragement of the development of drugs that repress the overexpression of FGFRs and suggest the dietary incorporation of supplementary nutrients in the management of degraded cartilage.The authors are grateful for the constant support provided by the Hospital Universitari de Sant Joan and the Universitat Rovira i Virgili. Salvador Fernández-Arroyo is the recipient of a Sara Borrell grant (CD12/00672) from the Instituto de Salud Carlos III, Madrid, Spain. The authors also thank the Andalusian Regional Government Council of Innovation and Science for the Excellence Project P11-CTS-7625 and Generalitat Valenciana for the project PROMETEO/2012/007. This work was also supported by projects of the Fundación Areces and the Fundación MAGAR

The long-run behaviour of the terms of trade between primary commodities and manufactures : a panel data approach

This paper examines the Prebisch and Singer hypothesis using a panel of twenty-four commodity prices from 1900 to 2010. The modelling approach stems from the need to meet two key concerns: (i) the presence of cross-sectional dependence among commodity prices; and (ii) the identification of potential structural breaks. To address these concerns, the Hadri and Rao (Oxf Bull Econ Stat 70:245–269, 2008) test is employed. The findings suggest that all commodity prices exhibit a structural break whose location differs across series, and that support for the Prebisch and Singer hypothesis is mixed. Once the breaks are removed from the underlying series, the persistence of commodity price shocks is shorter than that obtained in other studies using alternative methodologies.info:eu-repo/semantics/publishedVersio