Wayfinding across ocean and tundra: what traditional cultures teach us about navigation

Research on human navigation by psychologists and neuroscientists has come mainly from a limited range of environments and participants inhabiting western countries. By contrast, numerous anthropological accounts illustrate the diverse ways in which cultures adapt to their surrounding environment to navigate. Here, we provide an overview of these studies and relate them to cognitive science research. The diversity of cues in traditional navigation is much higher and multimodal compared with navigation experiments in the laboratory. It typically involves an integrated system of methods, drawing on a detailed understanding of the environmental cues, specific tools, and forms part of a broader cultural system. We highlight recent methodological developments for measuring navigation skill and modelling behaviour that will aid future research into how culture and environment shape human navigation

Architectural experience: Clarifying its central components and their relation to core affect with a set of first-person-view videos

When studying architectural experience in the lab, it is of paramount importance to use a proxy as close to real-world experience as possible. Whilst still images visually describe real spaces, and virtual reality allows for dynamic movement, each medium lacks the alternative attribute. To merge these benefits, we created and validated a novel dataset of valenced videos of first-person-view travel through built environments. This dataset was then used to clarify the relationship of core affect (valence and arousal) and architectural experience. Specifically, we verified the relationship between valence and fascination, coherence, and hominess - three key psychological dimensions of architectural experience which have previously been shown to explain aesthetic ratings of built environments. We also found that arousal is only significantly correlated with fascination, and that both are embedded in a relationship with spatial complexity and unusualness. These results help to clarify the nature of fascination, and to distinguish it from coherence and hominess when it comes to core affect. Moreover, these results demonstrate the utility of a video dataset of affect-laden spaces for understanding architectural experience

Microarrays as Platform for Multiplex Assays in Biomarker and Drug Discovery

Despite the tremendous advances in the understanding of the molecular mechanisms and the complexity of the diseases is one of the present challenges for the scientific community; then, novel strategies are required to be designed and developed for effective strategies for early diagnosis and treatment. As many cellular alterations are observed at protein level, high-throughput assays are dramatically needed for biomarker discovery. Herein, we describe advantages and limitations of protein microarrays, as proteomics strategy useful for multiplex and high-throughput protein characterization in clinical samples. Finally, a few examples are discussed; mostly of them related to currently disease biomarkers already identified in proximal fluids by protein arrays are discussed

Technological advances in fibrin for tissue engineering

Fibrin is a promising natural polymer that is widely used for diverse applications, such as hemostatic glue, carrier for drug and cell delivery, and matrix for tissue engineering. Despite the significant advances in the use of fibrin for bioengineering and biomedical applications, some of its characteristics must be improved for suitability for general use. For example, fibrin hydrogels tend to shrink and degrade quickly after polymerization, particularly when they contain embedded cells. In addition, their poor mechanical properties and batch-to-batch variability affect their handling, long-term stability, standardization, and reliability. One of the most widely used approaches to improve their properties has been modification of the structure and composition of fibrin hydrogels. In this review, recent advances in composite fibrin scaffolds, chemically modified fibrin hydrogels, interpenetrated polymer network (IPN) hydrogels composed of fibrin and other synthetic or natural polymers are critically reviewed, focusing on their use for tissue engineering.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Programa de Actividades de I + D entre Grupos de Investigación de la Comunidad de Madrid, S2018/BAA-4480, Biopieltec-CM, Programa Estatal de I + D + i Orientada a los Retos de la Sociedad, RTI2018-101627-B-I00, Proyectos de Generación de Conocimiento 2021, PID2021-126523OB-I00, Proyectos en colaboración público-privada 2021, CPP2021-008396, LOLICOMB Project, PID2020-116439GB-I00 and Cátedra Fundación Ramón Areces. Grant PID2021-126523OB-I00 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe.” Grant CPP2021-008396 funded by MCIN/AEI/ 10.13039/501100011033 and by the European Union “NextGenerationEU/PRTR.”Publicad

Machine learning applied to transcriptomic data to identify genes associated with feed efficiency in pigs

Background: To date, the molecular mechanisms that underlie residual feed intake (RFI) in pigs are unknown. Results from diferent genome‑wide association studies and gene expression analyses are not always consistent. The aim of this research was to use machine learning to identify genes associated with feed efciency (FE) using transcriptomic (RNA‑Seq) data from pigs that are phenotypically extreme for RFI. Methods: RFI was computed by considering within‑sex regression on mean metabolic body weight, average daily gain, and average backfat gain. RNA‑Seq analyses were performed on liver and duodenum tissue from 32 high and 33 low RFI pigs collected at 153 d of age. Machine‑learning algorithms were used to predict RFI class based on gene expression levels in liver and duodenum after adjusting for batch efects. Genes were ranked according to their contribution to the classifcation using the permutation accuracy importance score in an unbiased random forest (RF) algorithm based on conditional inference. Support vector machine, RF, elastic net (ENET) and nearest shrunken centroid algorithms were tested using diferent subsets of the top rank genes. Nested resampling for hyperparameter tuning was implemented with tenfold cross‑validation in the outer and inner loops. Results: The best classifcation was obtained with ENET using the expression of 200 genes in liver [area under the receiver operating characteristic curve (AUROC): 0.85; accuracy: 0.78] and 100 genes in duodenum (AUROC: 0.76; accuracy: 0.69). Canonical pathways and candidate genes that were previously reported as associated with FE in several species were identifed. The most remarkable pathways and genes identifed were NRF2‑mediated oxidative stress response and aldosterone signalling in epithelial cells, the DNAJC6, DNAJC1, MAPK8, PRKD3 genes in duodenum, and melatonin degradation II, PPARα/RXRα activation, and GPCR‑mediated nutrient sensing in enteroendocrine cells and SMOX, IL4I1, PRKAR2B, CLOCK and CCK genes in liver. Conclusions: ML algorithms and RNA‑Seq expression data were found to provide good performance for classifying pigs into high or low RFI groups. Classifcation was better with gene expression data from liver than from duodenum. Genes associated with FE in liver and duodenum tissue that can be used as predictive biomarkers for this trait were identifed.info:eu-repo/semantics/publishedVersio

Psychological impact on care professionals due to the SARS-Cov-2 virus in Spain

Objective:To analyze the psychological impact of the SARS-Cov-2 pandemic on nursesin Spain in three different dimensions: exposure to stressors, perceived emotions, andstress coping. Background: On March 11, 2019, the World Health Organization recognized a globalpandemic caused by a SARS-Cov-2 virus, COVID-19, which rapidly spread across theplanet, involving a community health emergency of international scope.Introduction:The pandemic situation in health centers has led to significant changesin the work environment, compromising care professionals’ physical and psychologicalhealth and resulting in strong physical and mental exhaustion.Methods: An observational, descriptive, cross-sectional study was carried out, betweenFebruary and April 2021, in a large sample of 1360 participants. The researchers con-ducted the dissemination of a validated questionnaire to working nurses in Spain.Results:The sex variable in relation to the study dimensions (stressors, perceived emo-tions, and coping strategies) showed a mean for stressors of 62.2±10.5 in women and59.8±12.5 in men (p=0.010), showing statistically significant differences. Age was aprotective factor for all dimensions (p<0.001). Time of experience showed statisticallysignificant differences for stressors and coping strategies in professionals with more than15 years of experience. Discussion: Female nurses who are younger, have less work experience, have not builta family of their own, and live in smaller or indoor flats may be more vulnerable to theeffects of the COVID-19 pandemic on their mental health. Other national and inter-national studies, in this line, have shown an important psychological impact on theseprofessionals.Conclusion:It is necessary to design and adopt effective strategies and measures for theprotection of nurses’ mental health, as well as for the prevention and early diagnosis ofpossible mental health problems

Obstetric outcomes of sars-cov-2 infection in asymptomatic pregnant women

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER)Around two percent of asymptomatic women in labor test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Spain. Families and care providers face childbirth with uncertainty. We determined if SARS-CoV-2 infection at delivery among asymptomatic mothers had different obstetric outcomes compared to negative patients. This was a multicenter prospective study based on universal antenatal screening for SARS-CoV-2 infection. A total of 42 hospitals tested women admitted for delivery using polymerase chain reaction, from March to May 2020. We included positive mothers and a sample of negative mothers asymptomatic throughout the antenatal period, with 6-week postpartum follow-up. Association between SARS-CoV-2 and obstetric outcomes was evaluated by multivariate logistic regression analyses. In total, 174 asymptomatic SARS-CoV-2 positive pregnancies were compared with 430 asymptomatic negative pregnancies. No differences were observed between both groups in key maternal and neonatal outcomes at delivery and follow-up, with the exception of prelabor rupture of membranes at term (adjusted odds ratio 1.88, 95% confidence interval 1.13-3.11; p = 0.015). Asymptomatic SARS-CoV-2 positive mothers have higher odds of prelabor rupture of membranes at term, without an increase in perinatal complications, compared to negative mothers. Pregnant women testing positive for SARS-CoV-2 at admission for delivery should be reassured by their healthcare workers in the absence of symptoms

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good