Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct physiological responses of Coccolithus braarudii life cycle phases to light intensity and nutrient availability

Coccolithophores feature a haplo-diplontic life cycle comprised of diploid cells producing heterococcoliths and haploid cells producing morphologically different holococcoliths. These life cycle phases of each species appear to have distinct spatial and temporal distributions in the oceans, with the heavily-calcified heterococcolithophores (HET) often more prevalent in winter and at greater depths, whilst the lightly-calcified holococcolithophores (HOL) are more abundant in summer and in shallower waters. The haplo-diplontic life cycle may therefore allow coccolithophores to expand their ecological niche, switching between life cycle phases to exploit conditions that are more favourable. However, coccolithophore life cycles remain poorly understood and fundamental information on the physiological differences between life cycle phases is required if we are to better understand the ecophysiology of coccolithophores. In this study, we have examined the physiology of HET and HOL phases of the coccolithophore Coccolithus braarudii in response to changes in light and nutrient availability. We found that the HOL phase was more tolerant to high light than the HET phase, which exhibited defects in calcification at high irradiances. The HET phase exhibited defects in coccolith formation under both nitrate (N) and phosphate (P) limitation, whilst no defects in calcification were detected in the HOL phase. The HOL phase grew to a higher cell density under P-limitation than N-limitation, whereas no difference was observed in the maximum cell density reached by the HET phase at these nutrient concentrations. HET cells grown under a light:dark cycle divided primarily in the dark and early part of the light phase, whereas HOL cells continued to divide throughout the 24 h period. The physiological differences may contribute to the distinct biogeographical distributions observed between life cycle phases, with the HOL phase potentially better adapted to high light, low nutrient regimes, such as those found in seasonally stratified surface waters. Highlights Coccolithus braarudii life cycle phases exhibit different physiological responses. The heavily-calcified heterococcolithophores (HET) life cycle phase is more sensitive to high light. The lightly-calcified holococcolithophores (HOL) life cycle phase may be better suited to growth under low phosphate availability.
Leukemia-intrinsic determinants of CAR-T response revealed by iterative in vivo genome-wide CRISPR screening

CAR-T therapy is a promising new treatment modality for B-cell malignancies. However, the majority of patients inevitably go on to experience disease relapse through largely unknown means. To investigate leukemia-intrinsic CAR-T resistance mechanisms, we performed genome-wide CRISPR-Cas9 loss-of-function screens in an immunocompetent murine model of B-cell acute lymphoblastic leukemia (B-ALL) utilizing a novel, modular guide RNA library. We identified IFNγ/JAK/STAT signaling and components of antigen processing and presentation pathway as key mediators of resistance to CAR-T therapy in vivo, but not in vitro. Transcriptional characterization of this model demonstrated an upregulation of these pathways in CAR-T treated relapsed tumors, and examination of data from CAR-T treated patients with B-ALL revealed an association between poor outcomes and increased expression of JAK/STAT/MHC-I in leukemia cells. Overall, our data identify an unexpected mechanism of resistance to CAR-T therapy in which tumor cell interaction with CAR-T cells in vivo induces expression of an adaptive T-cell resistance program in tumor cells.
Technical and Sentiment Analysis in Financial Forecasting with Genetic Programming

Financial Forecasting is a popular and thriving research area that relies on indicators derived from technical and sentiment analysis. In this paper, we investigate the advantages that sentiment analysis indicators provide, by comparing their performance to that of technical indicators, when both are used individually as features into a genetic programming algorithm focusing on the maximization of the Sharpe ratio. Moreover, while previous sentiment analysis research has focused mostly on the titles of articles, in this paper we use the text of the articles and their summaries. Our goal is to explore further on all possible sentiment features and identify which features contribute the most. We perform experiments on 26 different datasets and show that sentiment analysis produces better, and statistically significant, average results than technical analysis in terms of Sharpe ratio and risk.
Lactobacillus Rhamnosus GG (ATCC 53103) in the Management of Acute Diarrhea in Children

Probiotics have a role as adjuvant therapy in the management of childhood diarrhea along with oral zinc and oral rehydration salts (WHO). Increasing scientific evidence in the past decade has shown the role of probiotics in reducing the duration of diarrhea by a minimum of 24 hours. There are multiple probiotics that exist in the market as food supplements and some as pharmaceuticals, but strong scientific evidence and recommendations exist only for a few.
Transferrable Framework Based on Knowledge Graphs for Generating Explainable Results in Domain-Specific, Intelligent Information Retrieval

In modern industrial systems, collected textual data accumulates over time, offering an important source of information for enhancing present and future industrial practices. Although many AI-based solutions have been developed in the literature for a domain-specific information retrieval (IR) from this data, the explainability of these systems was rarely investigated in such domain-specific environments. In addition to considering the domain requirements within an explainable intelligent IR, transferring the explainable IR algorithm to other domains remains an open-ended challenge. This is due to the high costs, which are associated with intensive customization and required knowledge modelling, when developing new explainable solutions for each industrial domain. In this article, we present a transferable framework for generating domain-specific explanations for intelligent IR systems. The aim of our work is to provide a comprehensive approach for constructing explainable IR and recommendation algorithms, which are capable of adopting to domain requirements and are usable in multiple domains at the same time. Our method utilizes knowledge graphs (KG) for modeling the domain knowledge. The KG provides a solid foundation for developing intelligent IR solutions. Utilizing the same KG, we develop graph-based components for generating textual and visual explanations of the retrieved information, taking into account the domain requirements and supporting the transferability to other domain-specific environments, through the structured approach. The use of the KG resulted in minimum-to-zero adjustments when creating explanations for multiple intelligent IR algorithms in multiple domains. We test our method within two different use cases, a semiconductor manufacturing centered use case and a job-to-applicant matching one. Our quantitative results show a high capability of our approach to generate high-level explanations for the end users. In addition, the developed explanation components were highly adaptable to both industrial domains without sacrificing the overall accuracy of the intelligent IR algorithm. Furthermore, a qualitative user-study was conducted. We recorded a high level of acceptance from the users, who reported an enhanced overall experience with the explainable IR system.
Tracking the rise of robots: A survey of the IFR database and its applications

Robots are continuously transforming industrial production worldwide and thereby also inducing changes in a variety of production-related economic and social relations. While some observers call this transformation an unprecedented "revolution", others regard it as a common pattern of capitalist development. This paper contributes to the literature on effects of the rise of industrial robots in three ways. Firstly, we describe the historic evolution and organizational structure of the International Federation of Robotics (IFR), which collects data on the international distribution of industrial robots by country, industry, and application from industrial robot suppliers worldwide since 1993. Secondly, we extensively analyze this IFR dataset on industrial robots and point out its specificities and limitations. We develop a correspondence table between the IFR industry classification and the International Standard Industrial Classification (ISIC) Revision 4 and shed some light on the price development of industrial robots by compiling data on robot prices. We further compute implicit depreciation rates inherent to the operational stocks of robots in the IFR dataset and find an average depreciation rate of aggregate robot stocks between 4% and 7% per year between 1993 and 2019. Moreover, tracking the share of industrial robots not classified to any industry or application, we find that their share in total robot stocks has sharply declined since 2005. We also compare the IFR data with other data sources such as UN Comtrade data on net imports of industrial robots or data on robot adoption from firm-level surveys in selected countries. Thirdly, we provide a comprehensive overview of the empirical research on industrial robots that is based on the IFR dataset. We identify four important strands of research on the rise of robots: (i) patterns of robot adoption and industrial organization, (ii) productivity and growth effects, (iii) impacts on employment and wages, and (iv) links with demographics, health, and politics.
VIVA: An End-to-End System for Interactive Video Analytics

The growth of video volumes and increased DNN capabilities has led to a growing desire for video analytics. In response, the data analytics community has proposed multiple systems that optimize specific query types (e.g., selection queries) or a particular step in query execution (e.g., video retrieval from storage). However, none of these systems provide end-to-end, practical video analytics for users to iteratively and interactively engage with queries, as is the case with analytics systems for structured data. In response, we are building VIVA: an end-to-end system for interactive video analytics. VIVA contains five novel components. First, VIVA uses relational hints , which allow users to express relationships between columns that are difficult to automatically infer (e.g., mentions of a person in a transcript can be used as a proxy for the person appearing in the video). Second, VIVA introduces a mixed-data query optimizer that optimizes queries across both structured and unstructured data. Third, VIVA features an embedding cache that decides which results/embeddings to store for future queries. Finally, VIVA co-optimizes storage and query execution with its video file manager and accelerator-based execution engine . The former decides how to pre-fetch/manage video, while the latter selects and manages heterogeneous hardware backends spanning the growing number of DNN accelerators. We describe the challenges and design requirements for VIVA’s development and outline ongoing and future work for realizing VIVA.
Spatio‐Temporal Changes in Extreme Rainfall Events Over Different Indian River Basins

During recent decades, India experienced more frequent and severe floods due to increasing extreme rainfall events over different Indian River Basins (IRBs). The present study uses Generalized Extreme Value distribution, Expert Team on Climate Change and Detection Indices, and Standardized Precipitation Index to examine the trend in extreme rainfall events over the IRBs using long‐term observed high‐resolution gridded rainfall data (1901‐2019) obtained from India Meteorological Department. The analysis depicts a marked shifting trend in extreme rainfall events from northeastern Indian river basins toward the western Indian river basins during the recent decades of 1981‐2019. The spatial variations in the annual maximum rainfall for the 10‐, 30‐, and 100‐year return levels show statistically significant increasing trends over the IRBs. The observed decadal changes of rainfall during wet and dry conditions showed the shifting and increasing (15%–58.74%) pattern in extreme rainfall events during the last decades of the 20th and current twenty first century over the west‐flowing river basins. This research highlights the significant increasing trend in extreme rainfall events, which may pose a grave risk to agriculture, human life, and infrastructure, predominantly on the vulnerable sections of the society.
THE MECHANICS OF SOILS, AN INTRODUCTION TO CRITICAL STATE SOIL MECHANICS

The book describes the mechanical behaviour of soil when it is compressed, sheared or is saturated with water. The subject is approached through the theory of critical state soil mechanics and attempts to convey a fundamental understanding of the mechanical stress-strain behaviour of soils. The subject is discussed in the following chapters: (1) an introduction to engineering soils, (2) stresses and strains in soils, (3) states of stress and strain in soils, (4) stress and strain paths and invariants, (5) laboratory testing of soils, (6) flow of water in soils, (7) compression, (8) one-dimensional consolidation, (9) shear testing, (10) the critical state line and the Roscoe surface, (11) the behaviour of overconsolidated samples: the Hvorslev surface, (12) the behaviour of sands, (13) behaviour of soils before failure, (14) routine soil tests and the critical state model, and, (15) soil parameters for design. /TRRL/
Hydrogel Containing Borassus flabellifer L. Male Flower Extract for Antioxidant, Antimicrobial, and Anti-Inflammatory Activity

Borassus flabellifer L. is a plant in Arecaceae family, widely distributed and cultivated in tropical Asian countries. The purpose of this study was to identify the bioactive compounds of B. flabellifer L. male flower ethanolic extract and investigate the antioxidant, anti-inflammatory, and antibacterial activities against Cutibacterium acnes. Total phenolic compounds and total flavonoids in B. flabellifer L. male flower ethanolic extract were determined by the Folin–Ciocalteu method and aluminum chloride colorimetric assay, respectively. Active substances in the extract and their quantities were analyzed by liquid chromatography and mass spectrometry (LC–MS/MS). The antioxidant evaluation was carried out using DPPH, ABTS free radical scavenging assays, and FRAP assay. C. acnes inhibitory activity was performed by the broth microdilution method. Anti-inflammatory activity was determined by the protein denaturation assay. In addition, gel containing different amounts of B. flabellifer L. male flower extract was formulated. The physical stability of the gel was observed by measuring viscosity and pH after six heating and cooling cycles, as well as 1-month storage at 4, 30, and 45 °C. The total phenolic content in the extract was 268.30 ± 12.84 mg gallic acid equivalent/g crude dry extract. The total flavonoid contents in the extract were 1886.38 ± 55.86 mg quercetin equivalent/g extract and 2884.88 ± 128.98 mg EGCG equivalent/g extract, respectively. The LC–MS/MS analysis revealed the presence of gallic acid, coumarin, and quercetin and the concentrations of quercetin, coumarin, and gallic acid in B. flabellifer male flower ethanolic extract were 0.912, 0.021, and 1.610 µg/mL, respectively. DPPH and ABTS antioxidant assays indicated that the B. flabellifer L. male flower extract had IC50 values of 31.54 ± 0.43 and 164.5 ± 14.3 µg/mL, respectively. FRAP assay revealed that the B. flabellifer male flower extract had high ferric ion reducing power. The extract was able to inhibit C. acnes bacteria with a minimum inhibitory concentration (MIC) of 250 mg/mL. At 250 and 500 µg/mL, the extract demonstrated the highest anti-inflammatory activity. The gel containing 31.25% w/w and 62.5% w/w showed good physical stability after six heating and cooling cycles, as well as 1-month storage.
Nucleotide Excision Repair Pathway Activity Is Inhibited by Airborne Particulate Matter (PM10) through XPA Deregulation in Lung Epithelial Cells

Airborne particulate matter with a diameter size of ≤10 µm (PM10) is a carcinogen that contains polycyclic aromatic hydrocarbons (PAH), which form PAH–DNA adducts. However, the way in which these adducts are managed by DNA repair pathways in cells exposed to PM10 has been partially described. We evaluated the effect of PM10 on nucleotide excision repair (NER) activity and on the levels of different proteins of this pathway that eliminate bulky DNA adducts. Our results showed that human lung epithelial cells (A549) exposed to 10 µg/cm2 of PM10 exhibited PAH–DNA adducts as well as an increase in RAD23 and XPD protein levels (first responders in NER). In addition, PM10 increased the levels of H4K20me2, a recruitment signal for XPA. However, we observed a decrease in total and phosphorylated XPA (Ser196) and an increase in phosphatase WIP1, aside from the absence of XPA–RPA complex, which participates in DNA-damage removal. Additionally, an NER activity assay demonstrated inhibition of the NER functionality in cells exposed to PM10, indicating that XPA alterations led to deficiencies in DNA repair. These results demonstrate that PM10 exposure induces an accumulation of DNA damage that is associated with NER inhibition, highlighting the role of PM10 as an important contributor to lung cancer.
A Chip Off the Old Block? The Relationship of Family Factors and Young Adults’ Views on Aging

Views on aging (VoA), such as self-perceptions of aging or age stereotypes are generated in early childhood and continue to develop throughout the entire lifespan. The ideas a person has about their own aging and aging in general influence their behavior toward older persons as well as their own actual aging, which is why VoA are already important in adolescence and young adulthood. The current study investigates VoA of young adults in different domains (continued growth, physical decline, social loss) and how different family aspects are related to VoA. From February to March 2021, N = 305 young adults [aged 18–30 years, Mage(SD) = 22.20 (2.60)] participated in an online survey, in which, in addition to sociodemographic variables and family aspects (contact with grandparents, family age climate, i.e., the frequency and valence of talking about age in the family), self-perceptions of aging, age stereotypes, and the young adults’ ratings of their parents’ VoA were assessed. The results of stepwise regression analyses predicting the young adults’ VoA, revealed significant associations between the quality of contact with grandparents and the self-perceptions of aging of young adults. However, the frequency of contact was neither related to young adults’ self-perceptions of aging nor age stereotypes. Grandparents’ health status emerged as a significant moderator between the relationship of contact quality and the young adults’ self-perceptions of aging as continued growth and physical decline. Family climate was also found to be significantly related to young adults’ self-perceptions of aging. Similarities regarding VoA within the family were demonstrated, based on proxy report from the respondents. The results underline the importance of family aspects for the development of VoA in young adulthood, and the significance of interventions targeting these factors to combat ageism.
Chronic Critical Illness in Patients with COVID-19: Characteristics and Outcome of Prolonged Intensive Care Therapy

The spread of SARS-CoV-2 caused a worldwide healthcare threat. High critical care admission rates related to Coronavirus Disease 2019 (COVID-19) respiratory failure were observed. Medical advances helped increase the number of patients surviving the acute critical illness. However, some patients require prolonged critical care. Data on the outcome of patients with a chronic critical illness (CCI) are scarce. Single-center retrospective study including all adult critically ill patients with confirmed COVID-19 treated at the Department of Intensive Care Medicine at the University Medical Center Hamburg-Eppendorf, Germany, between 1 March 2020 and 8 August 2021. We identified 304 critically ill patients with COVID-19 during the study period. Of those, 55% (n = 167) had an ICU stay ≥21 days and were defined as chronic critical illness, and 45% (n = 137) had an ICU stay <21 days. Age, sex and BMI were distributed equally between both groups. Patients with CCI had a higher median SAPS II (CCI: 39.5 vs. no-CCI: 38 points, p = 0.140) and SOFA score (10 vs. 6, p < 0.001) on admission. Seventy-three per cent (n = 223) of patients required invasive mechanical ventilation (MV) (86% vs. 58%; p < 0.001). The median duration of MV was 30 (17–49) days and 7 (4–12) days in patients with and without CCI, respectively (p < 0.001). The regression analysis identified ARDS (OR 3.238, 95% CI 1.827–5.740, p < 0.001) and referral from another ICU (OR 2.097, 95% CI 1.203–3.654, p = 0.009) as factors significantly associated with new-onset of CCI. Overall, we observed an ICU mortality of 38% (n = 115) in the study cohort. In patients with CCI we observed an ICU mortality of 28% (n = 46) compared to 50% (n = 69) in patients without CCI (p < 0.001). The 90-day mortality was 28% (n = 46) compared to 50% (n = 70), respectively (p < 0.001). More than half of critically ill patients with COVID-19 suffer from CCI. Short and long-term survival rates in patients with CCI were high compared to patients without CCI, and prolonged therapy should not be withheld when resources permit prolonged therapy.
Factors Associated With Adverse Outcomes Following Duodenal Atresia Surgery in Neonates: A Retrospective Study

Objectives There is limited evidence on the infants' postoperative complications who have undergone surgical repair of duodenal atresia and stenosis. This study aimed to identify the factors associated with poor surgical outcomes after the initial repair. Methods We retrospectively reviewed the data of 82 patients who underwent surgery for duodenal atresia and stenosis between January 1994 and December 2013 at our institution. Gestational age, birth weight, fetal growth, and other associated anomalies were recorded. Multivariate regression analyses were used to identify the factors associated with surgical outcomes, including postoperative complications and time to full oral intake. Results The median gestational age was 37.6 weeks, with 30 (37%) preterm (<37 weeks) and 11 (13%) early preterm (<34 weeks) infants. The median birth weight was 2531 g, with 27 (33%) patients < 2000 g and 10 (12%) patients < 1500 g. Postoperative surgical complications were identified in 18 (22%) cases, of which 12 (15%) required additional operations. Multivariate regression analysis revealed that a combination of very low birth weight (<1500 g) and early preterm was significantly associated with both surgical and non-surgical postoperative complications (p = 0.0028 and 0.021, respectively) and a prolonged time to full oral intake postoperatively (p = 0.013). Conclusion Very low birth weight and early preterm were significantly associated with postoperative complications and a prolonged time to full oral intake.