Miracle-dz/UniFAR-FTUs huggingface dataset:
Metal Oxide Polymer Nanocomposites in Water Treatments

Recently, several pollutants such as dyes, pharmaceuticals and phenolic compounds, which can cause toxic effects to human health, have identified in water resources. Water pollution has extensively studied and several conventional techniques, such as chemical treatment, adsorption, biological treatment, and membrane-based separation, have adopted for pollutants removal from wastewater/ water resources. However, these techniques had led to the production of soluble refractory organic compounds and health- threatening bacteria that are hard to be removed. Recently, photocatalysis has considered as one of the most viable technology for water treatment using sunlight to eliminate harm- ful bacteria and pollutants owing to its cost-effectiveness and high efficiency. Metal oxide and polymers have become promising materials for water treatment owing to their properties, such as surface mobility, large surface area and superb magnetic and optical properties. This book chapter discusses recent design and synthesis of visible light response polymer/metal oxide nanocomposite through several synthetic strategies for water treat- ment. The results show that the polymer-metal oxide nanocomposite possesses a superior photodegradation activity toward pollutants under simulated visible light. Major chal- lenges in polymer-metal oxide nanocomposite synthesis and future research perspectives for developing alternate synthesis methodologies are also discussed.
The Effect of Competence and Certification on Teacher Performance

The purpose of this study was to determine the effect of teacher competence and teacher certification on the performance of elementary school (SD) in Tungkal Jaya District. The sample of this research was all teachers in Tungkal Jaya District. The sampling technique was purposive sampling, namely, where the respondents who were taken were some of the teachers who were the study population as samples. The sample was 78 teachers. The data was collected by distributing questionnaires using a 5-point Likert scale to measure 69 statement items. The analysis technique used multiple linear regression analysis. The results showed that simultaneously teacher competence and teacher certification had a significant effect on teacher performance. Second, the teacher competence has a partial and significant effect on teacher performance. The three teacher certifications have a partial and significant effect on teacher performance.
Experience of students in cooperative education – A case study of Singapore’s work-study degree programme

The increase in the number of adults returning to complete their university education as ‘non-traditional students’ brings more attention to the challenges of a standard degree format. This paper examines the experiences of seven non-traditional students undergoing a cooperative education programme in Singapore, where students would alternate spending a few days in a week at a university while working full-time for the remaining days, in relation to the challenges and opportunities of the programme. Using qualitative thematic analysis, we discovered four themes greatly affected by the programme design – motivations for enrolling, transferability of knowledge, work–study balance and coping mechanisms. Overall, some obstacles hindering adults from continuing education were addressed by this cooperative education programme. The strong integration of work and study roles ensured that adults did not need to leave their job before starting university, reducing time and money-related pressures while increasing their commitment level to education. Additionally, rigid institutional practices were mitigated by the flexibility given by teaching faculty and work supervisors. We suggested several improvements to better suit the rising number of adults wanting to attain a degree. With the research results and recommendations proposed herein, this paper is useful to various universities willing to adopt cooperative education.
Establishment of an Artificial Neural Network Model Using Immune-Infiltration Related Factors for Endometrial Receptivity Assessment

Background: A comprehensive clinical strategy for infertility involves treatment and, more importantly, post-treatment evaluation. As a component of assessment, endometrial receptivity does not have a validated tool. This study was anchored on immune factors, which are critical factors affecting embryonic implantation. We aimed at establishing novel approaches for assessing endometrial receptivity to guide clinical practice. Methods: Immune-infiltration levels in the GSE58144 dataset (n = 115) from GEO were analysed by digital deconvolution and validated by immunofluorescence (n = 23). Then, modules that were most associated with M1/M2 macrophages and their hub genes were selected by weighted gene co-expression network as well as univariate analyses and validated using the GSE5099 macrophage dataset and qPCR analysis (n = 19). Finally, the artificial neural network model was established from hub genes and its predictive efficacy validated using the GSE165004 dataset (n = 72). Results: Dysregulation of M1 to M2 macrophage ratio is an important factor contributing to defective endometrial receptivity. M1/M2 related gene modules were enriched in three biological processes in macrophages: antigen presentation, interleukin-1-mediated signalling pathway, and phagosome acidification. Their hub genes were significantly altered in patients and associated with ribosomal, lysosomal, and proteasomal pathways. The established model exhibited an excellent predictive value in both datasets, with an accuracy of 98.3% and an AUC of 0.975 (95% CI 0.945–1). Conclusions: M1/M2 polarization influences endometrial receptivity by regulating three gene modules, while the established ANN model can be used to effectively assess endometrial receptivity to inform pregnancy and individualized clinical management strategies.
Atomistic Simulation Protocol for Improved Design of Si–O–C Hybrid Nanostructures as Li-Ion Battery Anodes: ReaxFF Reactive Force Field

Recently, silicon–oxygen–carbon hybrid nanostructures have received great attention as a promising anode material for Li-ion batteries, for which their diverse structures can be synthesized. Here, using molecular dynamics (MD) simulations with a reactive force field (ReaxFF), we studied the atomistic lithiation behaviors of sp2 carbon-coated Si and SiOx nanostructures, such as nanowires (NWs) and nanoparticles (NPs), in which various kinds and sizes of carbonaceous coating layers were explored. The introduction of an sp2 carbonaceous coating layer to Si-based anodes makes Li diffusion more facile, which leads to improved battery performances such as faster charge/discharge rates. Moreover, the carbonaceous coating layer can also provide a buffer effect to volume changes during lithiation along with the well-known functions of preventing the loss of electrical continuity and increasing electrical conductivity of Si-based anodes. However, a thick carbonaceous coating layer can strongly suppress the volume e.
Structural and Metabolic Profiling of Lycopersicon esculentum Rhizosphere Microbiota Artificially Exposed at Commonly Used Non-Steroidal Anti-Inflammatory Drugs

In this study, the effect of common non-steroidal anti-inflammatory drugs on Lycopersicon esculentum rhizosphere microbiota was monitored. The experiments were performed with artificially contaminated soil with ibuprofen (0.5 mg·kg−1), ketoprofen (0.2 mg·kg−1) and diclofenac (0.7 mg·kg−1). The results evidenced that the rhizosphere microbiota abundance decreased especially under exposure to diclofenac (187–201 nmol·g−1 dry weight soil) and ibuprofen (166–183 nmol·g−1 dry weight soil) if compared with control (185–240 nmol·g−1 dry weight soil), while the fungal/bacteria ratio changed significantly with exposure to diclofenac (<27%) and ketoprofen (<18%). Compared with control samples, the average amount of the ratio of Gram-negative/Gram-positive bacteria was higher in rhizosphere soil contaminated with ibuprofen (>25%) and lower in the case of diclofenac (<46%) contamination. Carbon source consumption increased with the time of assay in case of the control samples (23%) and those contaminated with diclofenac (8%). This suggests that rhizosphere microbiota under contamination with diclofenac consume a higher amount of carbon, but they do not consume a larger variety of its sources. In the case of contamination with ibuprofen and ketoprofen, the consumption of carbon source presents a decreasing tendency after day 30 of the assay. Rhizosphere microbiota emitting volatile organic compounds were also monitored. Volatile compounds belonging to alcohol, aromatic compounds, ketone, terpene, organic acids, aldehyde, sulphur compounds, esters, alkane, nitrogen compounds, alkene and furans were detected in rhizosphere soil samples. Among these, terpene, ketone, alcohol, aromatic compounds, organic acids and alkane were the most abundant compound classes (>75%), but their percentage changed with exposure to diclofenac, ketoprofen and ibuprofen. Such changes in abundance, structure and the metabolic activity of Lycopersicon esculentum rhizosphere microbiota under exposure to common non-steroidal anti-inflammatory drugs suggest that there is a probability to also change the ecosystem services provided by rhizosphere microbiota.
Telepresence Robots in the Classroom

This study used the concept of shared affordance space to explore students’ perceptions of the use of a telepresence robot in a face-to-face classroom. Results from this qualitative pilot study suggest the telepresence robot has the potential to provide enough autonomy and agency for both the remote user and the in-class students to perceive a shared affordance space. Robot users and classmates use human pronouns to describe the robot user and discuss a process of adjusting to its presence. The physical configuration of the classroom can either facilitate or hinder this process. The research provides greater understanding of the experiences of students in a face-to-face classroom that includes remote students attending class using a telepresence robot. It can help educators design and implement these experiences in a way that creates a beneficial classroom experience for both in-class and remote learners.
Commentary on the Special Issue on Emotions in Reading, Learning, and Communication: A Big Step Forward, More Giant Leaps to Come

ABSTRACT The articles in this special issue take an important step in beginning to test the PET framework. Together, these articles illustrate the importance of considering individual differences in attitudes and prior knowledge as well as differences in task demands when investigating the role of emotions in shaping cognitive processing while reading texts. This commentary begins with a focus on the type of emotion being studied (e.g., preexisting emotions/mood, achievement emotions, epistemic emotions, topic emotions). Next, the function of emotions in cognitive processing and self-regulation is discussed, including a consideration of key findings from the articles in this special issue and additional considerations about the ways in which emotions may shape discourse processing. Finally, practical methodological matters relating to the investigation of emotions during discourse processing are considered. Throughout, contributions of the articles in this special issue are featured as well as suggestions for potential avenues for future research.
Downscaling Snow Deposition Using Historic Snow Depth Patterns: Diagnosing Limitations From Snowfall Biases, Winter Snow Losses, and Interannual Snow Pattern Repeatability

Repeatable snow depth patterns have been identified in many regions between years with similar meteorological characteristics. This suggests that snow patterns from previous years could adjust snow deposition in space as a substitution for unmodeled snow processes. Here, we tested a pattern‐based snow deposition downscaling routine which assumes (a) a spatially consistent relationship between snow deposition and snow depth, (b) interannually repeatable snow patterns, and (c) unbiased mean snowfall. We investigated these assumptions, and future avenues for improvement, in water‐year 2014 over the California Tuolumne River Watershed. 6 km snowfall from an atmospheric model was downscaled to 25 m resolution using snow depth patterns from seven different years, and was compared to a more common terrain‐based downscaling method. Snow depth patterns were influenced not only by snow accumulation, but also snowmelt, snow sublimation, and snow density, resulting in pattern‐based snow deposition downscaling that was too spatially heterogeneous. However, snow depth simulated using terrain‐based downscaling was too spatially homogeneous, and less spatially correlated with observations (r = 0.27), than simulations with pattern‐based downscaling using snow depth patterns from the simulation season (r = 0.76), or from a different year (r = 0.52). Overall, modeled snow depth errors at peak‐snowpack timing were driven more by atmospheric model snowfall biases than different downscaling methods. In order of most‐ to least‐importance, future research should focus on bias‐correcting coarse‐scale snowfall estimates, correcting snow deposition patterns for winter snow losses and snow density spatial variability, and identifying the historic periods of most‐similar snow accumulation.
The Composition of the South Polar Cap of Mars Derived From Orbital Data

The flexure of the lithosphere under stresses imposed by the geologically young south polar cap is one of the few clues we have regarding the south polar cap composition and the present‐day thermal state of Mars. Here, we combine radar, gravity, and topography data with a flexural loading model to estimate the bulk density ( ρ ) and average real dielectric constant ( ε′ ) of the south polar cap, and the elastic thickness of the lithosphere ( Te ). Given the uncertainties of the data, our results constrain ρ to be 1,100–1,300 kg m−3 (best fit of 1,220 kg m−3 ), ε′ to be 2.5–3.4 (best fit of 3.3), and Te to be greater than 150 km (best fit of 360 km). Based on these results, the maximum lithospheric flexure is 770 m, and the polar cap volume could be up to 26% larger than previous estimates that did not account for lithospheric flexure. Our inferred compositions imply that the dust concentration would be at least 9 vol% if the CO2 ice content were negligible, and that the CO2 ice concentration would be more than the known 1 vol% CO2 if the dust concentration were less than 9 vol%. The 1‐ σ lower limit on Te implies a surface heat flow that is less than 23.5 mW m−2 . This lower limit is significantly less than the range of acceptable values at the north pole (330–450 km, heat flow of 11–16 mW m−2 ), and helps satisfy global thermal evolution simulations that predict hemispheric differences in surface heat flow.
Vector-GMA: A New Easy Method for Analyzing Morphometric Data

The new method of geometric morphometric analysis, called Vector-GMA is proposed. Unlike the classic TPS-based GMA, the new method allows considering missing and inapplicable landmarks and analyzing articulated structures. It also contains a set of tools for analyzing particular morphological features and searching for promising identification characters. The results of the analysis can be easily converted into phylogenetic matrix and analyzed with phylogenetic software. For the case study, the fore wings of all Cretaceous ichneumonids are analyzed.
Mediating the Low Verbal Intelligence–Early Adult Offending Relationship With Pro-Aggression Attitudes

This study was designed to explore a possible mechanism for the well-documented relationship between low verbal intelligence and early adult offending. It was hypothesized that low verbal intelligence, as measured by a brief vocabulary test, would predict higher pro-aggression thinking, which would then encourage future antisocial behavior. This hypothesis was tested in a longitudinal analysis of 411 male youths from the Cambridge Study of Delinquent Development (CSDD). After controlling for school performance, truancy, impulsivity, peer delinquency, and nonverbal intelligence, a path analysis revealed that low verbal intelligence at age 14 or 15 predicted violent offending (fighting) and property offending at age 21 or 22 by way of late adolescent pro-aggression attitudes. From these results, it was speculated that one mechanism linking low verbal intelligence to early adult offending is an attitude favorable to personal violation of the rights of others, in line with predictions from general personality and cognitive social learning (GPCSL) theory.
Modification of Cement Matrix with Complex Additive Based on Chrysotyl Nanofibers and Carbon Black

This paper presents the results of studying the properties of cement-based composites modified with a complex additive based on chrysotile nanofibers and carbon black. The optimal composition of complex additive was stated due to the particle size analysis of suspensions with different chrysotile to carbon black ratios and the mechanical properties study of the fine-grained concrete modified with the complex additive. It was found that the addition of chrysotile in the amount of 0.05% of cement mass together with carbon black in the amount of 0.01% of cement mass leads to a 31.9% compression strength increase of cement composite and a 26.7% flexural strength increase. In order to explain the change in the mechanical properties of the material, physical and chemical testing methods were used including IR-spectral analysis, differential thermal analysis, energy dispersive X-ray analysis as well as the study of the microstructure of the samples modified with the complex additive. They revealed the formation of durable hydration products including thaumasite and calcium silicate hydrates of lower basicity that form a dense structure of cement matrix, increasing the physical and mechanical characteristics of cement-based composites.
EU Climate Policy under the Paris Agreement

The European Union has long sought to play a leadership role in the international response to climate change. As part of the “European Green Deal”, it announced new wide-ranging plans to step up its ambition, and in December 2020 updated its mitigation target under the Paris Agreement to an at-least 55 per cent reduction by 2030 compared to the 1990 level. In this article, I provide a legal analysis of the new EU climate change policy as outlined in the European Commission’s Stepping Up Europe’s 2030 Climate Ambition (September 2020) in light of the Paris Agreement itself and other norms of international environmental law. I find that the European Union provides a degree of leadership in the implementation of the Paris Agreement, but that there are also areas of concern, in particular the missing notification of member states’ individual emission levels as part of a joint ndc under Article 4 of the Paris Agreement.
Determinants of the downward sloping segment of the EKC in high-income countries: The role of income inequality and institutional arrangement

Abstract Even among developed countries, each country has very different circumstances and political institutions regarding environmental issues. Moreover, the differences in individual attitudes about environmental issues within national borders and in the types of environmental behaviors affect the environmental policy of each country. Therefore, in contrast to the Environmental Kuznets curve (EKC) hypothesis, the effect of economic growth on environmental degradation differs between high-income countries. Evidences show that economic growth is not the only determinant of environmental change, particularly in high-income countries. In this respect, this paper examines the existence of the EKC as well as the effects of the level of political institution on the relationship between greenhouse gas (GHG) emission per capita and income inequality; it does this by using unbalanced data for 33 OECD countries from 1990 to 2014. The findings of this study show that the level of income inequality differentially affects the GHG emission depending on the level of institution. The EKC hypothesis holds only in countries with a high level of institution, and the threshold of the EKC is positioned at a lower income level in countries with stronger institutional arrangement, and such countries also show lower GHG emission per capita.
An integrated ASTER-based approach for mapping carbonatite and iron oxide-apatite deposits

Abstract Mapping of carbonatites and related mineral deposits has occupied prominent place in mineral resource exploration programs given their potential to host valuable concentrations of critical metals such as rare earth elements and niobium. Based on spectral characteristics of most indicative minerals for these rocks, a mapping approach was developed using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. The combination of band rationing outcomes with components from the principal component analysis and minimum noise fraction techniques highlighted the targeted rocks, with the excellent prospective zone representing ∼ 0.2% of the total investigated area. This approach was successfully applied to the Gleibat Lafhouda complex to rapidly delineate carbonatites and iron oxide-apatite ore outcrops. Results were validated through field observations and in-situ geochemical analysis using a portable X-ray fluorescence analyzer. Field data have also served as training data to perform a supervised classification, allowing further improvement of the mapping results.
Use of motion capture-coupled ultrasound sensors to determine scapular position

ABSTRACT Ultrasonic imaging is a safe, established, and non-invasive method to visualise the locations of structures within the body. Coupling existing skin mounted motion capture markers to ultrasound sensors could allow for precise measurement of positions and orientations of bones hidden under the skin, mitigating the effects of relative displacement between skin and bone that occurs in standard motion capture techniques. This is especially important in motions where skin-mounted markers are inaccurate, such as when tracking scapular position while shoulder abduction is greater than 80 degrees. Previous in silico research has shown that five ultrasound-coupled motion capture clusters could provide sub-millimetre levels of scapular RMS error. This study builds upon those results. The position of a scapular phantom measured by the motion capture plus ultrasound (MC+U) technique was compared to the phantom position as quantified by CT. The root mean squared measurement error in overall scapular position was . Mean translational and rotational errors were 0.74 mm and 0.42°, respectively. This level of accuracy would make MC+U a valuable new tool for quantifying scapular position and motion in vivo. The results of this study confirm that the further development of the MC+U technique is warranted and establish a reasonable target for the accuracy of this technique for future in vivo studies.