Miracle-dz/UniFAR-FTUs huggingface dataset:
Pressure Dependence of the Low Temperature Carbonation Kinetics of Calcium Oxide for Potential Thermochemical Energy Storage Purposes and Sustainable CO2 Fixation

The pressure effect on the carbonation behavior of CaO as model compound is studied under mild hydrothermal conditions, as relevant to sustainable geological CO2 sequestration and for potential utilization in thermochemical energy storage. Reaction yields are determined experimentally by means of in situ powder X‐ray diffraction using CaO powder samples in a controlled reaction with CO2 under gas pressures between 1.0 and 5.0 MPa and at temperatures between 298 and 373 K. The results show a two‐step conversion of CaO to CaCO3, involving Ca(OH)2 as a reactive intermediate, with differing influences of the microstructures on the individual reaction sub‐steps. A kinetic evaluation of the experimental data delivers a high rate‐enhancing effect of temperature on the hydration reaction, whereas the CaCO3 formation is strongly dependent on the available CO2 gas pressure. With this systematic investigation the optimal pressure and temperature conditions for this reaction system can be determined delivering a contribution to a sustainable climate and energy management.
Morphology Matters

Supplemental Digital Content is available in the text. The 2019 World Health Organization (WHO) classification of colorectal carcinoma (CRC) profoundly reclassified CRC subtypes and introduces tumor budding as a second major grading criterion, while condensing conventional grade into a 2-tiered system. So far it remains largely unexplored how these parameters interact with each other and whether they truly have an independent impact on patient prognosis. We reclassified a large single-center cohort of 1004 CRCs spanning 2 decades for adjusted WHO grade (low vs. high), tumor budding (Bd1/Bd2/Bd3), and CRC subtype (adenocarcinoma not otherwise specified, micropapillary, mucinous, serrated, medullary, adenoma-like, signet-ring cell, mixed adenoneuroendocrine carcinoma/neuroendocrine carcinoma, undifferentiated) according to the criteria of the 2019 WHO classification. We investigated the interaction of these parameters, their connection to stage/microsatellite status, and their significance for patient survival in the different subgroups. Specific subtypes other than adenocarcinoma not otherwise specified represented one third of all CRCs and were unevenly distributed throughout stage and microsatellite subgroups. Subtypes, WHO grade and tumor budding profoundly impacted all survival parameters (P<0.001 for all analyses), with CRC subtypes and tumor budding—but not WHO grade—being stage-independent prognosticators for all survival comparisons. WHO grade had very limited prognostic value in CRC subtypes, while tumor budding retained its strong prognostic impact in most scenarios. Accurate delineation of CRC subtypes introduced in the 2019 WHO classification provides strong stage-independent prognostic information, arguing that they should be considered in pathology reports and in clinical trials. Of the morphology-based grading schemes included in the 2019 WHO, tumor budding outperforms WHO grade.
Exploiting the DepMap cancer dependency data using the depmap R package

The `depmap` package facilitates access in the R environment to the data from the DepMap project, a multi-year collaborative effort by the Broad Institute and Wellcome Sanger Institute, mapping genetic and chemical dependencies and other molecular biological measurements of over 1700 cancer cell lines. The 'depmap' package formats this data to simply the use of popular R data analysis and visualizing tools such as 'dplyr' and 'ggplot2'. In addition, the 'depmap' package utilizes 'ExperimentHub', storing versions of the DepMap data accessible from the Cloud, which may be selectively downloaded, providing a reproducible research framework to support exploiting this data. This paper describes a workflow demonstrating how to access and visualize the DepMap data in R using this package.
Deep Stock Trading: A Hierarchical Reinforcement Learning Framework for Portfolio Optimization and Order Execution *

Portfolio management via reinforcement learning is at the forefront of ﬁntech research, which explores how to optimally reallocate a fund into different ﬁnancial assets over the long term by trial-and-error. Existing methods are impractical since they usually assume each reallocation can be ﬁnished immediately and thus ignoring the price slippage as part of the trading cost. To address these issues, we propose a hierarchical reinforced stock trading system for portfolio management ( HRPM ). Concretely, we decompose the trading process into a hierarchy of portfolio management over trade execution and train the corresponding policies. The high-level policy gives portfolio weights at a lower frequency to maximize the long term proﬁt and invokes the low-level policy to sell or buy the corresponding shares within a short time window at a higher frequency to minimize the trading cost. We train two levels of policies via pre-training scheme and iterative training scheme for data efﬁciency. Extensive experimental results in the U.S. market and the China market demonstrate that HRPM achieves signiﬁcant improvement against many state-of-the-art approaches.
A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting

Generative probabilistic modeling of biological sequences has widespread existing and potential application across biology and biomedicine, from evolutionary biology to epidemiology to protein design. Many standard sequence analysis meth-ods preprocess data using a multiple sequence alignment (MSA) algorithm, one of the most widely used computational methods in all of science(Van Noorden et al., 2014). However, as we show in this article, training generative probabilistic models with MSA preprocessing leads to statistical pathologies in the context of sequence prediction and forecasting. To address these problems, we propose a principled drop-in alternative to MSA preprocessing in the form of a structured observation distribution (the “MuE” distribution). The MuE is a latent alignment model in which not only the alignment variable but also the regressor sequence can be latent. We prove theoretically that the MuE distribution comprehensively generalizes popular methods for inferring biological sequence alignments, and provide a precise characterization of how such biological models have differed from natural language latent alignment models. We show empirically that models that use the MuE as an observation distribution out-perform comparable methods across a variety of datasets, and apply MuE models to a novel problem for generative probabilistic sequence models:
Evaluation of influence of selected metal cations on antioxidant activity of extracts from savory (Satureja hortensis)

The analysis of the antioxidant activity of ethanol, methanol, acetone and aqueous extracts from the dried leaves and stems of savory is presented. The culinary herb used to study was procured from ecological agriculture in the Podlasie region of Poland. The antioxidant properties of extracts were calculated using the 1,1-diphenyl-2-picryl-hydrazyl radical (DPPH) and ferric-reducing antioxidant power (FRAP) (expressed as mg Trolox per g of dry mass) methods. In addition, the total phenolics contents of the herbal extracts were determined using the Folin-Ciocalteu reagent. The antioxidative activity of extracts as dependent on the type of solvent used for the extraction and concentration of savory in extracts is discussed. The influence of the concentration of different metal ion solutions on the anti-radicals’ properties of savory extracts was evaluated.
Phenylamino pyrimidine-1,2,3-triazole derivatives as analogs of imatinib: searching for novel compounds against chronic myeloid leukemia

The enzyme tyrosine kinase Bcr-Abl-1 is the main molecular target in the treatment of chronic myeloid leukemia and can be competitively inhibited by tyrosine kinase inhibitors such as imatinib. New potential competitive inhibitors were synthesized using the phenylamino pyrimidine pyridine (PAPP) group as a pharmacophoric fragment, and these compounds were biologically evaluated. The synthesis of the twelve new compounds was performed in three steps and assisted by microwave irradiation in a 1,3-dipolar cycloaddition to obtain 1,2,3-triazole derivatives substituted on carbon C-4 of the triazole nucleus. All of them had their inhibitory activities evaluated against a chronic myeloid leukemia cell line (K562) that expresses the enzyme tyrosine kinase Bcr-Abl-1 and against healthy cells (WSS-1) to observe their selectivity. Three compounds had promising results, showing an IC50 between 1.0 and 7.3 mM, and were subjected to molecular docking studies. This result suggests that such compounds can interact at the same binding site as imatinib, probably sharing a competitive inhibition mechanism. One of them showed the greatest interaction affinity for Bcr-Abl-1 in the docking studies.
COPD_A_293577 1183..1192

1Centre for Chronic Conditions and Injuries (CCCI), Public Health Foundation of India, Gurgaon, India; 2Institute of Health Transformation, Faculty of Health, Deakin University, Burwood, Melbourne, Australia; 3Centre for Chronic Disease Control (CCDC), Delhi, India; 4Department of Epidemiology, London School of Hygiene and Tropical Medicine, London, UK Purpose: Undiagnosed Chronic Obstructive Pulmonary Disease (COPD) results in high morbidity, disability and mortality in India. Effective strategies for active COPD screening in community settings are needed to increase early identification, risk reduction and timely management. The objective of this study was to test the diagnostic accuracy of a sequential two-step screening strategy to detect COPD, implemented by community health workers (CHWs), among adults aged ≥40 years in a rural area of North India. Patients and Methods: Trained CHWs screened all consenting (n=3256) eligible adults in two villages using the Lung Function Questionnaire (LFQ) to assess their COPD risk and conducted pocket spirometry on 268 randomly selected (132 with high risk ie LFQ score ≤18 and 136 with low risk ie LFQ score >18) individuals. Subsequently, trained researchers conducted post-bronchodilator spirometry on these randomly selected individuals using a diagnostic quality spirometer and confirmed the COPD diagnosis according to the Global Initiative for Obstructive Lung Disease (GOLD) criteria (FEV1/FVC ratio <0.7). Results: This strategy of using LFQ followed by pocket spirometry was sensitive (78.6%) and specific (78.8%), with a positive predictive value of 66% and negative predictive value of 88%. It could accurately detect 67% of GOLD Stage 1, 78% of GOLD Stage 2, 82% of GOLD Stage 3 and 100% of GOLD Stage 4 individuals with airflow limitation. Conclusion: COPD can be accurately detected by trained CHWs using a simple sequential screening strategy. This can potentially contribute to accurate assessment of COPD and thus its effective management in low-resource settings.
Drought in Temperate Mesic Regions Leads to Micro-density Anomalies in White Pine

Wood density and wood volume determine the amount of carbon fixed by trees; however, while we are beginning to understand normal seasonal variation in wood density, anomalies are common, and their drivers are poorly understood. In conifers, wood density normally increases continuously throughout the season, but intra-annual fluctuations in wood density can occur and have been linked to climatic events. The causes of these fluctuations in density at the micro-scale (hereafter micro-density anomalies) are still debated. Mesic regions are experiencing more droughts, but micro-density anomalies are rarely studied in these ecosystems. This study examined micro-density anomaly distribution within the boles of white pines (Pinus strobus) in central Massachusetts and its relationship with climate. We cored 41 white pines at (i) breast height (1.5m), (ii) near branches, (iii) and from the 2010 growth section. To determine if the timing of climatic variables impacted anomaly formation, we broke the growing season apart into early, mid, and late growing season. All of the trees had at least two micro-density anomalies. There was not a higher occurrence of micro-density anomalies near branches or in the 2010 growth section. Even in this temperate mesic ecosystem, anomaly formation was related to particular drought events. Micro-density anomalies coincided with low soil moisture in the early, mid, and late growing season as well as higher mid-season air temperature. It is unclear why the anomalies are uniformly distributed throughout the bole. Micro-density anomalies may be a physiological response to drought and may prevent embolisms from forming. Thus, with a better understanding of micro-density anomaly drivers we can anticipate how trees in mesic areas may react to drought.
Psychological Resilience in the Face

This chapter draws on stress and coping perspectives to document the contextual, relational, and personal characteristics associated with psychological resilience following late-life spousal loss. It highlights how social/structural and developmental factors are linked with older bereaved spouses’ high levels of resilience relative to their younger counterparts. The chapter synthesizes research on psychological adaptation to late-life spousal loss, highlighting factors that distinguish those who withstand or bounce back emotionally, relative to those who suffer from intense or sustained distress. Potentially modifiable aspects of the death and structural factors linked to resilience are highlighted in an effort to challenge notions that resilience is a trait-like feature of the individual alone. The chapter concludes by identifying avenues for future research.
Multilingual and Multimodal Hate Speech Detection in Social Media Detección Multilingüe y Multimodal de Mensajes de Odio en Redes Sociales

En esta tesis doctoral proponemos el diseño y desarrollo de tecnoloǵıas para el tratamiento automático de mensajes de odio. La hipótesis en la que se sustenta el proyecto es que la detección de odio puede mejorar al incorporar, en el procesamiento de textos, otras fuentes de información como las imágenes, que en varias ocasiones son compartidas junto a dichos mensajes. De esta forma, pretendemos desarrollar estrategias para la detección automática de odio desde un enfoque multimodal. Por otra parte, en el marco del proyecto tendremos en cuenta el análisis multilingüe de mensajes de odio, haciendo uso de estrategias de transferencia de aprendizaje para el tratamiento en idiomas con poca información. Para el desarrollo de la investigación, nos planteamos construir un conjuno de datos que permita el procesamiento multilingüe y multimodal. En general, el trabajo estará enfocado en técnicas de aprendizaje profundo en la propuesta de aproximaciones para la detección de odio.
MMP-2 and MMP-9 Polymorphisms and Preeclampsia Risk in Tunisian Arabs: A Case-Control Study

The abnormal production of matrix metalloproteinases (MMPs), especially MMP-9 and MMP-2, plays a pivotal role in hypertensive disorders of pregnancy, and as such, can influence the development of preeclampsia. These alterations may result from functional genetic polymorphisms in the promoter region of MMP-9 and MMP-2 genes, which modify MMP-9 and MMP-2 expression. We investigated the association of MMP-9 polymorphism rs3918242 (-1562 C>T) and MMP-2 polymorphism rs2285053 (-735 C>T) with the risk of preeclampsia. This case–control study was conducted on 345 women with preeclampsia and 281 age-matched women with normal pregnancies from Tunisian hospitals. Genomic DNA was extracted from whole blood collected at delivery. Genotypes for -1562 C>T and -735 C>T polymorphisms were performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). An increased frequency of heterozygous MMP-9 -1562 C/T genotype carriers was observed in women with preeclampsia compared to healthy controls (p = 0.03). In contrast, the MMP-2 -735 C>T polymorphism was not significantly different regarding frequency distribution of the allele and genotype between healthy pregnant women and women with preeclampsia. Our study suggests that the MMP-9 -1562 C/T variant, associated with high MMP-9 production, could be a genetic risk factor for preeclampsia in Tunisian women.
Automatic Policy Generation for Inter-Service Access Control of Microservices

Cloud applications today are often composed of many mi-croservices. To prevent a microservice from being abused by other (compromised) microservices, inter-service access con-trol is applied. However, the complexity of ﬁne-grained access control policies, along with the large-scale and dynamic nature of microservices, makes the current manual conﬁguration-based access control unsuitable. This paper presents A U - TO A RMOR , the ﬁrst attempt to automate inter-service access control policy generation for microservices, with two fundamental techniques: (1) a static analysis-based request extraction mechanism that automatically obtains the invocation logic among microservices, and (2) a graph-based policy management mechanism that generates corresponding access con-trol policies with on-demand policy update. Our evaluation on popular microservice applications shows that A UTO A RMOR is able to generate ﬁne-grained inter-service access control policies and update them timely based on changes in the application, with only a minor runtime overhead. By seamlessly integrating with the lifecycle of microservices, it does not require any changes to existing code and infrastructures.
Validating Safety in Human-Robot Collaboration: Standards and New Perspectives

Human–robot collaboration is currently one of the frontiers of industrial robot implementation. In parallel, the use of robots and robotic devices is increasing in several fields, substituting humans in “4D”—dull, dirty, dangerous, and delicate—tasks, and such a trend is boosted by the recent need for social distancing. New challenges in safety assessment and verification arise, due to both the closer and closer human–robot interaction, common for the different application domains, and the broadening of user audience, which is now very diverse. The present paper discusses a cross-domain approach towards the definition of step-by-step validation procedures for collaborative robotic applications. To outline the context, the standardization framework is analyzed, especially from the perspective of safety testing and assessment. Afterwards, some testing procedures based on safety skills, developed within the framework of the European project COVR, are discussed and exemplary presented.
N C ] 2 1 Ju l 2 01 6 A physical model for dementia

Aging associated brain decline often result in some kind of dementia. Even when this is a complex brain disorder a physical model can be used in order to describe its general behavior. This model is based in first principles. A probabilistic model for the development of dementia is obtained and fitted to some experimental data obtained from the Alzheimer’s Disease Neuroimaging Initiative. It is explained how dementia appears as a consequence of aging and why it is irreversible.
Interface electronic structure and valence band dispersion of bis(1,2,5-thiadiazolo)-p-quinobis(1,3-dithiole) on polycrystalline Au electrodes

Bis(1,2,5-thiadiazolo)-p-quinobis(1,3-dithiole) (BTQBT) is a promising material for application in vertical organic transistor devices because of considerable energy dispersion in its valence band (VB). In this study, the electronic structure at the interface of BTQBT on polycrystalline Au electrodes was elucidated by photoelectron spectroscopy (PES). The excitation photon energy-dependence of the PES corroborated a widely dispersing VB of the solid-state BTQBT on Au. An intermolecular transfer integral of 75 meV and the hole effective mass of 4.3m 0 were derived from the present results.
The Effect of Instruction Model Using Media and Motivation on Chemical Learning Results (Study of The Effect of Instruction Models Using Media and Motivation in Learning)

This study aims to determine the effect of instruction models using animation and motivation on student chemical learning results and the interaction between instruction models and motivation. The study was conducted on all students of class XI IPA SMA Negeri 10 Medan in 3 classes and samples were taken randomly. This research is an experimental research with 2x2 factorial anava design. The factors tested were PBL model factors with Macromedia Flash, PBL models with Power Point media, while motivational factors with high and low criteria. Based on the hypothesis test at a significant level a = 0.05, it was obtained that Fcount (A) was 5.530, Fcount (B) was 29.584, and Fcount (AB) was 4.556, while the price of Ftable (0.05) (1.56) = 4.01 then Fcount> Ftable which means there is influence and interaction of learning models using animation media and motivation on student learning results. The results of this study indicate that students who are taught with the PBL model using Macromedia Flash media on highly motivated students show the highest average of 85,667, and the average of low motivated students is 80.000. Furthermore, students who were taught with the PBL model using Power Point media on highly motivated students showed an average of 85.294, and an average of students with low motivation was 72.308. Thus it was concluded that in chemical learning the topic of buffer solutions is better to use PBL models with Macromedia Flash media.
Application of Analytical Hierarchy Process in Evaluating the Student Acceptance of E-Learning Implementation for Logic and System Modelling Learning

The logic and modeling of systems thinking are studied by students in various subjects, one of which is mathematics. An e-learning system can be used to learn these abilities. Survey was conducted using sample from student in Information system design courses. The data obtained was evaluated using the Analytical Hierarchy Process. The AHP method was chosen in order to obtain an effectiveness comparison between e-learning tools and face-to-face learning in the classroom.
Antagonism of Siderophore Producing Bacteria Against Blood Disease Bacteria

Siderophore is a chemical compound of Fe chelating. This compound is produced by several microorganisms that grow under iron-limiting conditions. Siderophore can facilitate the transfer of Fe from the environment to become available to plants. The siderophore ability to bind Fe as a competitor against other microorganisms, so that in the agricultural system it can be used as a plant disease controller. This study aims to determine the production of siderophore produced by several fluorescent pseudomonad isolates and its antagonistic tests against Blood Disease Bacteria (BDB). Siderohore detection is determined by the absorbance value obtained, and measured using a spectrophotometer at a wavelength of 410 nm. The antagonist test used a completely randomized designwith 7 treatments and 3 replications. The treatment is fluorescent pseudomonads isolates PfLAHP2, PfPb1, PfCas3, PfKd7, PfCas, PfPj1, and PfPj2. PfLAHP2 isolates produced the highest siderophore, which was 1.027, and the lowest isolate PfCas was 0.148. The antagonistic test of fluorescent pseudomonad against BDB showed that PfLAHP2 isolate produced the largest inhibitory zone, which was 1.042 cm.