Smart Building: Decision Making Architecture for Thermal Energy Management

Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction

Protein Translation Inhibition is Involved in the Activity of the Pan-PIM Kinase Inhibitor PIM447 in Combination with Pomalidomide-Dexamethasone in Multiple Myeloma

Background: Proviral Insertion site for Moloney murine leukemia virus (PIM) kinases are overexpressed in hematologic malignancies, including multiple myeloma. Previous preclinical data from our group demonstrated the anti-myeloma effect of the pan-PIM kinase inhibitor PIM447. Methods: Based on those data, we evaluate here, by in vitro and in vivo studies, the activity of the triple combination of PIM447 + pomalidomide + dexamethasone (PIM-Pd) in multiple myeloma. Results: Our results show that the PIM-Pd combination exerts a potent anti-myeloma effect in vitro and in vivo, where it markedly delays tumor growth and prolongs survival of treated mice. Mechanism of action studies performed in vitro and on mice tumor samples suggest that the combination PIM-Pd inhibits protein translation processes through the convergent inhibition of c-Myc and mTORC1, which subsequently disrupts the function of eIF4E. Interestingly the MM pro-survival factor IRF4 is also downregulated after PIM-Pd treatment. As a whole, all these molecular changes would promote cell cycle arrest and deregulation of metabolic pathways, including glycolysis and lipid biosynthesis, leading to inhibition of myeloma cell proliferation. Conclusions: Altogether, our data support the clinical evaluation of the triple combination PIM-Pd for the treatment of patients with multiple myeloma.This work was supported by funding from Spanish FIS (PI15/00067, PI15/02156 and PI18/01600) and FEDER, AECC (GCB120981SAN), Junta de Castilla y León, Consejería de Sanidad (GRS 862/A/13 and BIO/SA05/14), Fundación Memoria de D. Samuel Solórzano Barruso of the University of Salamanca (FS/22-2015), Fundación Ramón Areces (FRA16/003), Sociedad Española de Hematología y Hemoterapia and Centro en Red de Medicina Regenerativa y Terapia Celular de Castilla y León. E.M.O. was supported by an Inplant grant from IDIVAL. T.P. is supported by a grant from AECC (INVES18043PAÍN)

Preclinical evaluation of the simultaneous inhibition of MCL-1 and BCL-2 with the combination of S63845 and venetoclax in multiple myeloma

This work was supported by the Spanish ISCIII-FIS and FEDER Funds (PI 15/00067 and PI 15/02156) and the Regional Health Council of Castilla y León (GRS 1604/A/17). EMA was supported by a grant from the Regional Education Council of Castilla y León co-financed by the European Social Fund

Predicting long-term disease control in transplant-ineligible patients with multiple myeloma: impact of an MGUS-like signature

Disease control at 5 years would be a desirable endpoint for elderly multiple myeloma (MM) patients, but biomarkers predicting this are not defined. Therefore, to gain further insights in this endpoint, a population of 498 newly diagnosed transplant-ineligible patients enrolled in two Spanish trials (GEM2005MAS65 and GEM2010MAS65), has been analyzed. Among the 435 patients included in this post-hoc study, 18.6% remained alive and progression free after 5 years of treatment initiation. In these patients, overall survival (OS) rate at 10 years was 60.8% as compared with 11.8% for those progressing within the first 5 years. Hemoglobin (Hb) = 12 g/dl (OR 2.74, p = 0.001) and MGUS-like profile (OR 4.18, p = 0.005) were the two baseline variables associated with long-term disease-free survival. Upon including depth of response (and MRD), Hb = 12 g/dl (OR 2.27) and MGUS-like signature (OR 7.48) retained their predictive value along with MRD negativity (OR 5.18). This study shows that despite the use of novel agents, the probability of disease control at 5 years is still restricted to a small fraction (18.6%) of elderly MM patients. Since this endpoint is associated with higher rates of OS, this study provides important information about diagnostic and post-treatment biomarkers helpful in predicting the likelihood of disease control at 5 years

She\u27s So Bubbly

We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self-consistent classification of large etendue telescope alert streams, such as that provided by the Zwicky Transient Facility (ZTF) and, in the future, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). ALeRCE is a Chilean-led broker run by an interdisciplinary team of astronomers and engineers working to become intermediaries between survey and follow-up facilities. ALeRCE uses a pipeline that includes the real-time ingestion, aggregation, cross-matching, machine-learning (ML) classification, and visualization of the ZTF alert stream. We use two classifiers: a stamp-based classifier, designed for rapid classification, and a light curve–based classifier, which uses the multiband flux evolution to achieve a more refined classification. We describe in detail our pipeline, data products, tools, and services, which are made public for the community (see https://alerce.science). Since we began operating our real-time ML classification of the ZTF alert stream in early 2019, we have grown a large community of active users around the globe. We describe our results to date, including the real-time processing of 1.5 × 10⁸ alerts, the stamp classification of 3.4 × 10⁷ objects, the light-curve classification of 1.1 × 10⁶ objects, the report of 6162 supernova candidates, and different experiments using LSST-like alert streams. Finally, we discuss the challenges ahead in going from a single stream of alerts such as ZTF to a multistream ecosystem dominated by LSST

Honey bee colony winter loss rates for 35 countries participating in the COLOSS survey for winter 2018–2019, and the effects of a new queen on the risk of colony winter loss

peer-reviewedThis article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered 738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.0–4.1%) colonies with unsolvable queen problems 79,146 (10.7%, 95% CI 10.5–10.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.8–2.0%) lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.4–16.9%), varying greatly between countries, from 5.8% to 32. 0%. We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems and found that, overall, larger beekeeping operations with more than 150 colonies experienced significantly lower losses (p<0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p<0.001). The percentage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unresolvable queen problems, and lower losses from winter mortality (p<0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at regional level

Peabody Picture Vocabulary Test-III: Normative data for Spanish-speaking pediatric population

OBJECTIVE: To generate normative data for the Peabody Picture Vocabulary Test-III (PPVT-III) in Spanish-speaking pediatric populations. METHOD: The sample consisted of 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Honduras, Guatemala, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Each participant was administered the PPVT-III as part of a larger neuropsychological battery. PPVT-III scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the analyses. RESULTS: The final multiple linear regression models showed main effects for age in all countries, such that scores increased linearly as a function of age. In addition, age2 had a significant effect in all countries, except Guatemala and Paraguay. Models showed that children whose parent(s) had a MLPE >12 years obtained higher scores compared to children whose parent(s) had a MLPE ≤12 years in all countries, except for Cuba, Peru, and Puerto Rico. Sex affected scores for Chile, Ecuador, Guatemala, Mexico, and Spain. CONCLUSIONS: This is the largest Spanish-speaking pediatric normative study in the world, and it will allow neuropsychologists from these countries to have a more accurate interpretation of the PPVT-III when used in pediatric populations

Cut-offs and response criteria for the Hospital Universitario la Princesa Index (HUPI) and their comparison to widely-used indices of disease activity in rheumatoid arthritis

Objective To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Methods Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. Results The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if =2, low disease activity if >2 and =5), moderate if >5 and <9 and high if =9. HUPI''s AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28''s AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. Conclusions The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis

J-PLUS: The javalambre photometric local universe survey

ABSTRACT: TheJavalambrePhotometric Local UniverseSurvey (J-PLUS )isanongoing 12-band photometricopticalsurvey, observingthousands of squaredegrees of theNorthernHemispherefromthededicated JAST/T80 telescope at the Observatorio Astrofísico de Javalambre (OAJ). The T80Cam is a camera with a field of view of 2 deg2 mountedon a telescopewith a diameter of 83 cm, and isequippedwith a uniquesystem of filtersspanningtheentireopticalrange (3500–10 000 Å). Thisfiltersystemis a combination of broad-, medium-, and narrow-band filters, optimallydesigned to extracttherest-framespectralfeatures (the 3700–4000 Å Balmer break region, Hδ, Ca H+K, the G band, and the Mg b and Ca triplets) that are key to characterizingstellartypes and delivering a low-resolutionphotospectrumforeach pixel of theobservedsky. With a typicaldepth of AB ∼21.25 mag per band, thisfilter set thusallowsforanunbiased and accuratecharacterization of thestellarpopulation in our Galaxy, itprovidesanunprecedented 2D photospectralinformationforall resolved galaxies in the local Universe, as well as accuratephoto-z estimates (at the δ z/(1 + z)∼0.005–0.03 precisionlevel) formoderatelybright (up to r ∼ 20 mag) extragalacticsources. Whilesomenarrow-band filters are designedforthestudy of particular emissionfeatures ([O II]/λ3727, Hα/λ6563) up to z < 0.017, theyalsoprovidewell-definedwindowsfortheanalysis of otheremissionlines at higherredshifts. As a result, J-PLUS has thepotential to contribute to a widerange of fields in Astrophysics, both in thenearbyUniverse (MilkyWaystructure, globular clusters, 2D IFU-likestudies, stellarpopulations of nearby and moderate-redshiftgalaxies, clusters of galaxies) and at highredshifts (emission-line galaxies at z ≈ 0.77, 2.2, and 4.4, quasi-stellarobjects, etc.). Withthispaper, wereleasethefirst∼1000 deg2 of J-PLUS data, containingabout 4.3 millionstars and 3.0 milliongalaxies at r <  21mag. With a goal of 8500 deg2 forthe total J-PLUS footprint, thesenumbers are expected to rise to about 35 millionstars and 24 milliongalaxiesbytheend of thesurvey.Funding for the J-PLUS Project has been provided by the Governments of Spain and Aragón through the Fondo de Inversiones de Teruel, the Spanish Ministry of Economy and Competitiveness (MINECO; under grants AYA2017-86274-P, AYA2016-77846-P, AYA2016-77237-C3-1-P, AYA2015-66211-C2-1-P, AYA2015-66211-C2-2, AYA2012-30789, AGAUR grant SGR-661/2017, and ICTS-2009-14), and European FEDER funding (FCDD10-4E-867, FCDD13-4E-2685