Miracle-dz/UniFAR-FTUs huggingface dataset:
High Diversity and Abundance of Foraminifera Associated with Mediterranean Benthic Red Algae Mats

The Mediterranean Sea comprises habitats such as Posidonia oceanica seagrass meadows that exhibit high associated biodiversity of sessile organisms. Recent pilot research indicates that benthic mats formed by the scarcely investigated fleshy red alga Phyllophora crispa also host a high diversity of benthic fauna. Among the key taxa found in these mats in the recent pilot studies are benthic foraminifera that live as epiphytes on the red algae thalli. Knowledge about their abundance and species richness associated with this habitat in relation to reference habitats is missing. We thus carried out a comparative assessment focusing on foraminifera within samples from P. crispa mats and neighboring P. oceanica meadows on five different sampling sites around Giglio Island in the Tuscan Archipelago (Tyrrhenian Sea, Italy). A total of 104 different foraminiferal taxa were identified, of which a total of 85 taxa were found in P. crispa samples (46 exclusively in this habitat). This biodiversity was higher compared to other studies on phytal habitats in the Mediterranean Sea. The number of foraminiferal taxa associated with P. crispa was significantly higher (average 27.5 ± 8.1 taxa) compared to P. oceanica (leaves average 7.0 ± 3.6, shoots average 7.9 ± 3.4 taxa). The abundance of foraminifera (12,000 individuals m−2 surface area of P. crispa mat) was also higher than in the neighboring P. oceanica meadows (7792 individuals m−2 leaf and 8171 individuals m−2 shoot surface area). The most frequently found taxa across habitats were Miniacina miniacea, Lobatula lobatula, and Sejunctella sp. (24%, 20%, and 6% of the total population, respectively). Our results imply that P. crispa mats host an exceptional diversity of associated foraminifera that is even higher than those associated with seagrass meadows. Red algae mats built by P. crispa may thus be considered as potential refuge habitats and biodiversity reservoirs in management and conservation.
Intelligent inverse treatment planning via deep reinforcement learning, a proof-of-principle study in high dose-rate brachytherapy for cervical cancer

Inverse treatment planning in radiation therapy is formulated as solving optimization problems. The objective function and constraints consist of multiple terms designed for different clinical and practical considerations. Weighting factors of these terms are needed to define the optimization problem. While a treatment planning optimization engine can solve the optimization problem with given weights, adjusting the weights to yield a high-quality plan is typically performed by a human planner. Yet the weight-tuning task is labor intensive, time consuming, and it critically affects the final plan quality. An automatic weight-tuning approach is strongly desired. The procedure of weight adjustment to improve the plan quality is essentially a decision-making problem. Motivated by the tremendous success in deep learning for decision making with human-level intelligence, we propose a novel framework to adjust the weights in a human-like manner. This study used inverse treatment planning in high-dose-rate brachytherapy (HDRBT) for cervical cancer as an example. We developed a weight-tuning policy network (WTPN) that observes dose volume histograms of a plan and outputs an action to adjust organ weighting factors, similar to the behaviors of a human planner. We trained the WTPN via end-to-end deep reinforcement learning. Experience replay was performed with the epsilon greedy algorithm. After training was completed, we applied the trained WTPN to guide treatment planning of five testing patient cases. It was found that the trained WTPN successfully learnt the treatment planning goals and was able to guide the weight tuning process. On average, the quality score of plans generated under the WTPN’s guidance was improved by ~8.5% compared to the initial plan with arbitrarily set weights, and by 10.7% compared to the plans generated by human planners. To our knowledge, this was the first time that a tool was developed to adjust organ weights for the treatment planning optimization problem in a human-like fashion based on intelligence learnt from a training process, which was different from existing strategies based on pre-defined rules. The study demonstrated potential feasibility to develop intelligent treatment planning approaches via deep reinforcement learning.
Energy Transfer as A Driving Force in Nucleic Acid–Protein Interactions

Many nucleic acid–protein structures have been resolved, though quantitative structure-activity relationship remains unclear in many cases. Thrombin complexes with G-quadruplex aptamers are striking examples of a lack of any correlation between affinity, interface organization, and other common parameters. Here, we tested the hypothesis that affinity of the aptamer–protein complex is determined with the capacity of the interface to dissipate energy of binding. Description and detailed analysis of 63 nucleic acid–protein structures discriminated peculiarities of high-affinity nucleic acid–protein complexes. The size of the amino acid sidechain in the interface was demonstrated to be the most significant parameter that correlates with affinity of aptamers. This observation could be explained in terms of need of efficient energy transfer from interacting residues. Application of energy dissipation theory provided an illustrative tool for estimation of efficiency of aptamer–protein complexes. These results are of great importance for a design of efficient aptamers.
The role of cell adhesion in hematopoiesis and leukemogenesis

The cells of the bone marrow microenvironment are emerging as important contributors and regulators of normal hematopoiesis. This microenvironment is perturbed during leukemogenesis, and evidence points toward a bidirectional communication between leukemia cells and the normal cells of the bone marrow, mediated by direct cell–cell contact as well as soluble factors. These interactions are increasingly appreciated to play a role in leukemogenesis and possibly in resistance to chemotherapy. In fact, several compounds that specifically target the bone marrow microenvironment, including inhibitors of cell adhesion, are being tested as adjuncts to leukemia therapy.
Regulation of inflammation during gestation and birth outcomes: Inflammatory cytokine balance predicts birth weight and length

The maternal environment during gestation influences offspring health at birth and throughout the life course. Recent research has demonstrated that endogenous immune processes such as dysregulated inflammation adversely impact birth outcomes, increasing the risk for preterm birth and restricted fetal growth. Prior analyses examining this association suggest a relationship between maternal C‐reactive protein (CRP), a summary measure of inflammation, and offspring anthropometric outcomes. This study investigates pro‐ and anti‐inflammatory cytokines, and their ratio, to gain deeper insight into the regulation of inflammation during pregnancy.
Secretion of secretory phospholipase A2 into Spodoptera exigua larval midgut lumen and its role in lipid digestion

In insects, lipid digestion is controversial because insects have no bile salts to solubilize dietary lipids. One hypothesis is that a secretory type of phospholipase A2 (sPLA2) provides lysophospholipid (LPL) from dietary phospholipids (PLs). We identified a sPLA2, Se‐sPLA2, in beet armyworm, Spodoptera exigua, that hydrolyses PLs at sn‐2. Our goal was to investigate its role in lipid digestion. Se‐sPLA2 was expressed in the entire alimentary canal. Incubating the isolated midgut in a cell culture medium led to secretion of Se‐sPLA2 and other proteins. Ex vivo RNA interference (RNAi) of Se‐sPLA2 expression in isolated midgut culture led to significantly decreased Se‐sPLA2 secretion into the medium. Feeding double‐stranded RNA specific to Se‐sPLA2 to larvae suppressed sPLA2 activity in gut contents. A recombinant Se‐sPLA2 was susceptible to benzylideneacetone (BZA), a specific PLA2 inhibitor. After feeding BZA to larvae, we recorded significant decreases in gut content sPLA2 activity, body growth and total haemolymph lipid contents. RNAi against Se‐sPLA2 resulted in reduced digestibility. Addition of a specific LPL, 1‐palmitoyl‐sn‐glycero‐3‐phosphocholine, to BZA‐treated larvae rescued digestibility and larval growth. These results strongly bolster our hypothesis that Se‐sPLA2 secreted from the midgut acts in lipid digestion by providing necessary LPL to solubilize dietary neutral lipids.
Effectiveness of Interventions and Behaviour Change Techniques for Improving Dietary Intake in Young Adults: A Systematic Review and Meta-Analysis of RCTs

Poor eating habits are common during young adulthood and influence chronic disease morbidity. This systematic review evaluates the effectiveness of interventions aiming to improve dietary intake among young adults and, identifies which behaviour change techniques (BCTs) are most effective. Six electronic databases were searched for RCTs published until October 2018, and evaluating behavioural interventions assessing change in dietary intake in young adults (17–35 years). Of the 18,779 articles identified, 54 were included. Forty studies focused on fruit and/or vegetable intake, of which 63% showed a significant between-group difference in favour of the intervention group. Meta-analysis (n = 17) demonstrated a significant increase in fruit and vegetable intake of +68.6 g/day after three months of intervention and +65.8 g/day for interventions >3 months when compared to control. A meta-analysis (n = 5) on total energy intake found no significant differences between groups. The BCTs with the highest effectiveness ratio were habit formation (100%), salience of consequences (83%) and adding objects to the environment (70%). The review highlights the potential of behavioural interventions to improve young adults’ fruit and vegetable intake but was less convincing for other dietary outcomes. Due to the lack of studies including each BCT, the BCTs imperative to success could not be identified.
Metal Oxide Nanoparticles and their Nanocomposite-based Materials as Photocatalysts in the Degradation of Dyes

The introduction of inorganic and organic pollutants into water bodies has become a serious issue globally. The waste streams released from the textile, plastic, leather, paper, pharmaceutical, and food industries introduce different natural and synthetic dyes into the aquatic system. Nanomaterials play a significant role in the photocatalytic degradation of dyes present in wastewater. Inorganic metal oxide nanoparticles have many improved physical and chemical properties and attracted much attention in photocatalytic activities. Dyes have been released in our aquatic bodies due to many anthropogenic activities and caused life-threatening problems. Various conventional methods were reported to remove dyes from water and wastewater; the photocatalytic method is one of the efficient and cost-effective. The present review article includes detailed information on photocatalysis, the potential of metal oxide and their composite materials as photocatalysts in the degradation of toxic dyes, and some common synthetic and characterization methods used for metal oxide-based nanoparticles.
Foresight for income and employment: What can we learn for agricultural research for development

Challenges related to poverty, hunger, nutrition, health, and the environment are widespread and urgent. One way to stress the urgency of making the right decisions about the future of the global food systems now is to better understand and more clearly articulate the alternative scenarios that food systems face. Developing, synthesizing, and presenting such alternatives to decision makers in a clear way is the ultimate goal of e CGIAR Foresight team.No single source of information focuses regularly and systematically on the future of food and agriculture, and challenges facing developing countries. Our work aims to fill that gap with a focus on agricultural income and employment.group systematically collects information about past, on-going and planned foresight activities across CGIAR centers and their partners, spanning the global agricultural research for development arenaWe present a comprehensive overview and synthesis of the results of relevant foresight research, which through the tagging with metadata allows for customized investigations in greater detail. The cross-cutting nature of this work allows for a more comprehensive picture and assessments of possible complementarities/trade-offs.Potential users of this report and associated activities include CGIAR science leaders and scientists as well as the broader research community, national and international development partners, national governments and research organizations, funders, and the private sector.The approach developed by the CGIAR foresight group is used to make foresight study results accessible across organizations and domains in order to aid policy and decision makers for strategic planning. The approach allows visualization of both the available information across multiple entry points as well as the identification of critical knowledge gaps.
Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education

This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, coding, and data analysis strategy of 141 items included in the corpus. Key findings extracted from the review incorporate a taxonomy of artificial intelligence applications with associated teaching and learning practice and a framework for helping teachers to develop and self-reflect on the skills and capabilities envisioned for employing artificial intelligence in education. Implications for ethical use and a set of propositions for enacting teaching and learning using artificial intelligence are demarcated. The findings of this review contribute to developing a better understanding of how artificial intelligence may enhance teachers’ roles as catalysts in designing, visualising, and orchestrating AI-enabled teaching and learning, and this will, in turn, help to proliferate AI-systems that render computational representations based on meaningful data-driven inferences of the pedagogy, domain, and learner models.
Challenges of e-Mentoring Medical Students During the COVID-19 Pandemic

In the current pandemic scenario, the School of Medical Sciences, Universiti Sains Malaysia had adopted an e-mentoring system to help undergraduate medical students acclimatise to new subjects, improve academic performance and decrease attrition. The authors highlight the challenges of e-mentoring, including aspects of interpersonal dynamics, slow development of relationships in e-mentoring and the requirement of specific skills in technology for useful online mentoring, are the few challenges discussed. Some possible solutions were also shared. This article is beneficial to institutions implementing or planning to implement an e-mentoring system.
Health Equity and a Paradigm Shift in Occupational Safety and Health

Despite significant improvements in occupational safety and health (OSH) over the past 50 years, there remain persistent inequities in the burden of injuries and illnesses. In this commentary, the authors assert that addressing these inequities, along with challenges associated with the fundamental reorganization of work, will require a more holistic approach that accounts for the social contexts within which occupational injuries and illnesses occur. A biopsychosocial approach explores the dynamic, multidirectional interactions between biological phenomena, psychological factors, and social contexts, and can be a tool for both deeper understanding of the social determinants of health and advancing health equity. This commentary suggests that reducing inequities will require OSH to adopt the biopsychosocial paradigm. Practices in at least three key areas will need to adopt this shift. Research that explicitly examines occupational health inequities should do more to elucidate the effects of social arrangements and the interaction of work with other social determinants on work-related risks, exposures, and outcomes. OSH studies regardless of focus should incorporate inclusive methods for recruitment, data collection, and analysis to reflect societal diversity and account for differing experiences of social conditions. OSH researchers should work across disciplines to integrate work into the broader health equity research agenda.
CENPF Upregulation is Associated with Immunosuppressive Status and Predicts Poor Clinical Outcomes in Lung Adenocarcinoma Validated by Qrt- PCR

Background: CENPF was differentially expressed in various cancers. However, the relationship between CENPF and immune infiltrates in lung adenocarcinoma was previously unknown.Methods: We implemented a comprehensive analysis of expression of CENPF in the GEO and TCGA databases. CENPF was evaluated for its prognostic value combining clinical samples from the GEPIA2 and TCGA databases. The Metascape together with WebGestalt databases were used for enrichment analysis of genesets that were most postively associated with CENPF. We retrieved the score for immune cell infiltration in TCGA data and examined the correlation between CENPF expression and the infiltration of immune cell by R software.Results: The outcomes exhibited that up-regulated CENPF mRNA expression was evidently related to poor PFS, DSS and OS in patients with lung adenocarcinoma. Moreover, high expression of CENPF was markedly related to genes associated with immune checkpoint. Further analysis showed that T cell CD4+ Th2 infiltration increased in lung adenocarcinoma samples with high CENPF expression.Conclusions: Our study indicated that CENPF led to T cell CD4+ Th2 infiltration through oncogenic activity and may be employed as a biomarker for the prediction of prognosis in lung adenocarcinoma.
The Divergent Dynamics of Economic Growth

This book explains how changing technology and economizing behaviour induce vast changes in productivity, resource allocation, labour utilization, and patterns of living. Economic growth is seen as a process by which businesses, regimes, countries, and the whole world pass through distinct epochs, each one emerging from its predecessor, each one creating the conditions for its successor. Viewed from a long-run perspective, growth must be characterized as an explosive process, marked by turbulent transitions in social and political life as societies adapt to new opportunities, the demise of old ways of living, and to the vast increase and redistribution of human populations. The book is based on a synthesis of classical economics and contemporary concepts of adaptation and economic evolution. Although it is based on analytical methods, the text has been stripped of all equations and with few exceptions is devoid of technical jargon.
Design of a high intensity turbulent combustion system

DESIGN OF A HIGH INTENSITY TURBULENT COMBUSTION SYSTEM Report Title The work is focused on the design and development of a high intensity turbulent combustion system which can be operated at compressible (0.3 < M < 0.5), preheated (T0=500K) and premixed conditions in order to investigate the 'Thickened Flame' regime. An air-methane mixture has been used as the fuel for this study. An optically accessible backward-facing step stabilized combustor has been designed for a maximum operating pressure of 6 bar. A grid has been introduced with different blockage ratios (BR = 54%, 61% & 67%) in order to generate turbulence inside the combustor for the experiment. Optical access is provided via quartz windows on three sides of the combustion chamber. Finite Element Analysis (FEA) is done in order to verify the structural integrity of the combustor at rated conditions. In order to increase the inlet temperature of the air, a heating section was designed to use commercially available in-line heaters. Separate cooling subsystems have been designed for chamber cooling and exhaust cooling. The LabVIEW software interface has been selected as the control mechanism for the experimental setup. A 10 kHz Time Resolved Particle Image Velocimetry (TR-PIV) system and a 3 kHz Planer Laser Induced Fluorescence (PLIF) system have been integrated with the system in order to diagnose the flow field and the flame respectively. DESIGN OF A HIGH INTENSITY TURBULENT COMBUSTION SYSTEM MOHAMMAD ARIF HOSSAIN Department of Mechanical Engineering
A Third-Order Constrained Approximate Time-Optimal Feedrate Planning Algorithm

Robot end-effector tracking of a specific spatial path to fulfill certain requirements is a topic of great interest. First, considering both dynamic constraints and kinematic constraints, the planned velocity has characteristics of bounded high-order derivatives to ensure smooth motion. Second, to meet high-efficiency requirements, the feedrate of the end-effector should be planned within the best possible time. Although some studies have shown that they obtained the time-optimal solution by considering the second-order constraints, this is still an open problem for third-order constraints. Therefore, this article proposes an approximate time-optimal feedrate (ATOF) planning algorithm that considers third-order constraints. This algorithm is primarily based on the bidirectional scanning method, which includes two steps. First, we calculate the second-order time-optimal velocity (TOV2) curve under the third-order maximum velocity curve. Then, considering TOV2, we propose an ATOF algorithm that includes single-direction speed planning and speed curve smoothing. It is more practical for not only considering the Coulomb viscous friction and torque rate but also avoiding difficult calculations at the singular point and solves discontinuous joint-acceleration under second-order constraints. Finally, we design two sets of experiments to verify the higher calculation efficiency and effectiveness of the proposed ATOF algorithm.
Conceptual Design of a Creative Artificial Intelligence System Based on the Neurocognitive Bases of Human Creativity in the Brain

ABSTRACT The main objective of this paper is the conceptual design of a computational AI system that emulates human creativity. To do this, extensive research has been done on recent discoveries about the neural bases of human creativity. As a result, eleven neurocognitive factors have been identified on which the tremendous creative capacity of the human brain is based. The integration of these factors has made it possible to create a neurocognitive model of human creativity. The analysis of each of creative neurocognitive structures separately suggests certain characteristics that must be present in the structure of a creative computational system to emulate brain creativity. Properly integrating these characteristics, a general architecture for a creative multi-agent system has been proposed, as well as the guidelines for the correct representation of knowledge. Based on this general architecture a creative computational system can be implemented for a specific field of knowledge, or general purpose.