Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of traditional fire management on soil carbon and nitrogen pools in a montane forest, southern Ethiopia

We conducted studies to assess the impact of traditional fire management on soil organic carbon and total nitrogen pools. We compared organic carbon and total nitrogen pools in forest floor and mineral soil (0–100-cm depth) in three areas burned by local communities (B) with adjacent unburned areas (UB) (three paired sites; 1, 5 and 9 years since fire; hereafter B1-UB, B5-UB and B9-UB) in a montane forest in southern Ethiopia. Despite differences in time since fire and dominant post-fire vegetation, forest floor and mineral soil organic carbon and total nitrogen concentrations and pools were not significantly different between burned and unburned pairs or across sites. However, mineral soil carbon : nitrogen ratio was significantly higher in the burned area of B9-UB (0–10 cm) and B5-UB (10–20 cm), indicating small losses of nitrogen relative to carbon, likely from plant uptake or possibly leaching of nitrogen post fire. Combined, the data suggest that traditional fire management did not dramatically affect forest floor and mineral soil organic carbon and total nitrogen dynamics at these sites.
Self-Efficacy, Teaching Practice, and Teacher Readiness: Mediating Role Teacher Interest

Objective: In the realm of education, the effectiveness of teaching practices and the readiness of teachers to navigate the challenges of the classroom environment have garnered substantial attention. One pivotal aspect that has emerged in educational research is the concept of self-efficacy – the belief in one's capabilities to accomplish tasks and produce desired outcomes. Self-efficacy is known to significantly influence various aspects of an individual's professional life, including teaching. The correlation between self-efficacy, teaching practice, and teacher readiness has been a subject of interest for educators and researchers alike. This research aims to determine the effect of self-efficacy and teaching practice on readiness to be a teacher through interest in becoming a teacher as a mediation variable. We used an online questionnaire to identify 435 college students for this study. Method: We applied partial least squares structural equation modelling (PLS-SEM) to analyze the research model. Results: The results showed that the exogenous variables, namely self-efficacy and teaching practice, significantly affected the readiness to become teachers directly. Novelty: Whereas indirectly, self-efficacy does not affect readiness to become a teacher through an interest in becoming a teacher. However, it differs from the teaching practice variable, which indirectly affects readiness to become a teacher through an interest in becoming a teacher.
Audio Visual Media about The Importance of Vulva Hygiene Increases The Knowledge of Pregnant Women

Pregnant women tend to experience vaginal discharge more often than when they are not pregnant. This disorder is caused by poor hygiene of the genital organs. Knowledge is an important component in shaping a person's behavior. This research aims to determine the effectiveness of audio-visual media in increasing pregnant women's knowledge about vulva hygiene. This research uses a quantitative method, pre-experiment, one group pre-posttest. The sample used was 36 respondents using an accidental sampling technique. Bivariate analysis used the Wilcoxon test. There was an increase in the average knowledge score of pregnant women after being given audio-visual media about vulva hygiene with a p value <0.001. This educational media can be used by health facilities to provide education to pregnant women. Suggestions from researchers for research sites can utilize audio-visual media during health education, especially to pregnant women regarding vulva hygiene.
Pten knockout in mouse preosteoblasts leads to changes in bone turnover and strength

Abstract Bone development and remodeling are controlled by the phosphoinositide-3-kinase (Pi3k) signaling pathway. We investigated the effects of downregulation of phosphatase and tensin homolog (Pten), a negative regulator of Pi3k signaling, in a mouse model of Pten deficiency in preosteoblasts. We aimed to identify mechanisms that are involved in the regulation of bone turnover and are linked to bone disorders. Femora, tibiae, and bone marrow stromal cells (BMSCs) isolated from mice with a conditional deletion of Pten (Pten cKO) in Osterix/Sp7-expressing osteoprogenitor cells were compared to Cre-negative controls. Bone phenotyping was performed by μCT measurements, bone histomorphometry, quantification of bone turnover markers CTX and procollagen type 1 N propeptide (P1NP), and three-point bending test. Proliferation of BMSCs was measured by counting nuclei and Ki-67–stained cells. In vitro, osteogenic differentiation capacity was determined by ALP staining, as well as by detecting gene expression of osteogenic markers. BMSCs from Pten cKO mice were functionally different from control BMSCs. Osteogenic markers were increased in BMSCs derived from Pten cKO mice, while Pten protein expression was lower and Akt phosphorylation was increased. We detected a higher trabecular bone volume and an altered cortical bone morphology in Pten cKO bones with a progressive decrease in bone and tissue mineral density. Pten cKO bones displayed fewer osteoclasts and more osteoblasts (P = .00095) per trabecular bone surface and a higher trabecular bone formation rate. Biomechanical analysis revealed a significantly higher bone strength (P = .00012 for males) and elasticity of Pten cKO femora. On the cellular level, both proliferation and osteogenic differentiation capacity of Pten cKO BMSCs were significantly increased compared to controls. Our findings suggest that Pten knockout in osteoprogenitor cells increases bone stability and elasticity by increasing trabecular bone mass and leads to increased proliferation and osteogenic differentiation of BMSCs.
Simulation of Delta and Omicron Variants Detection Using Surface Plasmon Resonance Based on Kretschmann-Raether Configuration

COVID-19 caused by SARS-CoV-2 has been mutated and emerged into different types of variants. Delta and Omicron variants remained as variants of concern as the Delta variant severely infects the unvaccinated individual, while the Omicron variant is the dominant variant circulating globally. Therefore, it is vital to identify these variantsby developing a simpler method that detects both variants based on the antibody-antigen interactions. The Surface Plasm on Resonance (SPR) sensor based on the Kretschmann-Raether configuration provides label-free detection of SARS-CoV-2 variants by the antibody-antigen interaction. However, to date, there is no multiple SARS-CoV-2variants detection methods have been implemented using SPR sensors based on the Kretschmann-Raether configuration. Therefore, this study is carried out to design anPR sensor based on the Kretschmann-Raether configuration and to simulate the detection of these variants by this sensor using COMSOL Multiphysics software. In this study, an SPR sensor was designed with two detecting cells named Cell 1 and Cell 2, where each cell contains a 2E8 monoclona antibody and COV2-06 monoclonal antibody respectively. The results show that the designed SPR sensor can distinguish and detect the Delta and Omicron variants successfully based on the antibody-antigen interaction with the sensitivities of 3.3968 deg RIU−1 for Cell 1 and 4.5803 deg RIU−1 for Cell 2. Therefore, this SPR sensor based on the Kretschmann-Raether configuration could be a potential alternative tool for currently available multiple SARS CoV2 variants detection methods as it provides label-free detection that is based on antigen-antibody interaction.
Experience-Based Universal Design for Learning (UDL) Applications: Building Bridges to Overcome Barriers

The purpose of this phenomenological study was to examine the autobiographical memory narrative through which graduate teacher candidates (TCs) identified (1) barriers to learning, (2) Universal Design for Learning (UDL) checkpoints to remove these barriers, and (3) strategies for addressing the UDL checkpoints to remove the barriers. This study explored lived experiences among graduate TCs in relation to (a) UDL training in the graduate teacher preparation programs, (b) barriers to learning among their past experience, and (c) UDL checkpoints’ applications to removing the self-identified barriers to learning. Emerging themes and subthemes indicated that the participants used specific UDL checkpoints to overcoming specific types of barriers to learning in the past experience in K-16 education. This indicates their recognitions of specific types of barriers to learning, identifications of specific UDL checkpoints for overcoming the barriers, and considerations of specific strategies based on the identified UDL checkpoints. Implications for the future study includes having autobiographical memory narratives as a practical learning tool for graduate TCs to put themselves into perspectives of (A) students experiencing barriers to learning and (B) teachers applying UDL checkpoints to removing the barriers to learning.
Examining the e-learning attitudes of Indonesian students during the COVID-19 pandemic

The COVID-19 epidemic has impacted higher education institutions across the country by switching traditional teaching practices to online learning. The attitudes of students towards e-learning are essential to research in order to determine the extent to which successful implementation of online learning. Thus, this research aims to evaluate the attitudes of Indonesian students towards e-learning throughout the pandemic. The study adopted a quantitative research approach through a survey questionnaire. The attitude of students was evaluated using the attitude scale towards e-learning. The questionnaire comprised 20 items assessing students’ attitudes towards remote learning. A questionnaire was distributed to 342 (255 female and 87 male) undergraduate students who took online courses at an Indonesian state university. The statistical analyses including descriptive statistics, t-tests and one-way ANOVA were used in the present study. The results suggested that students’ e-learning attitudes tend to be neutral. The t-test and ANOVA indicated that there was no statistically significant gap in students’ attitudes with respect to gender, daily internet usage time or level of COVID-19. Meanwhile, age, study year and personal computer ownership exerted a statistically significant impact on e-learning attitudes. Teachers can better prepare for the adoption of online learning during COVID-19 and beyond by using the valuable insights provided by the findings.
MOTHERS ON TWITTER (X): EXCHANGING SUPPORT AND NARRATING MOTHERHOOD

As almost all aspects of our lives, motherhood in the 21st century also is influenced and transformed by new media. Parents, especially mothers, use the Facebook, Instagram and even Twitter (X) as digital diaries, as stages for performing an ideal mother’s role, or even “safe spaces” to gain support and the feeling of empowerment. Recent research of motherhood discourses and mothering practices in social media has mainly focused on the evidence of mediation and mediatization. However, limited attention has been brought to examining Twitter in context of mothering. Therefore, this paper focuses on the narratives of a particular cluster of Latvian-speaking mothers on Twitter who use Twitter as a platform for exchanging informational, emotional and physical support, forming a “portable” community. The case study consists of a narrative analysis of 11 in-depth semi-structured interviews with mothers and a thematic analysis of 1111 tweets, gathered from 9 other public Twitter accounts (covering a period of 2 weeks), that have been identified by interviewees as part of this particular Twitter-bubble. The paper provides an insight into the narratives of women, voicing their motherhood struggles and victories in the “safe space” of Twitter’s “bubble” of new Latvian mothers, illuminating also a unique and unlikely use for an asymmetric and decentralized social media platform.
Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.
Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher power due to larger memory bitcells. Gain-cell eDRAM is a high-density alternative for multi-ported operation with a small silicon footprint. However, conventional gain-cell memories have limited data availability, as they require periodic refresh operations to maintain their data. In this paper, we propose a novel multi-ported gain-cell design, which provides up-to N read ports and M independent write ports (NRMW). In addition, the proposed design features a configurable mode of operation, supporting a hidden refresh mechanism for improved memory availability, as well as a novel opportunistic refresh port approach. An 8kbit memory macro was implemented using a four-transistor bitcell with four ports (2R2W) in a 28 nm FD-SOI technology, offering up-to a 3× reduction in bitcell area compared to other dual-ported SRAM memory options, while also providing 100% memory availability, as opposed to conventional dynamic memories, which are hindered by limited availability.
Relationships among cost, citation, and access in journal publishing by an ecology and evolutionary biology department at a U.S. university

Background Optimizing access to high-quality scientific journals has become an important priority for academic departments, including the ability to read the scientific literature and the ability to afford to publish papers in those journals. In this contribution, we assess the question of whether institutional investment in scientific journals aligns with the journals where researchers send their papers for publication, and where they serve as unpaid reviewers and editors. Methods We assembled a unique suite of information about the publishing habits of our Department of Ecology and Evolutionary Biology, including summaries of 3,540 journal publications by 35 faculty members. These data include economic costs of journals to institutions and to authors, benefits to authors in terms of journal prestige and citation rates, and considerations of ease of reading access for individuals both inside and outside the university. This dataset included data on institutional costs, including subscription pricing (rarely visible to scholars), and “investment” by scholars in supporting journals, such as time spent as editors and reviewers. Results Our results highlighted the complex set of relationships between these factors, and showed that institutional costs often do not match well with payoffs in terms of benefits to researchers (e.g., citation rate, prestige of journal, ease of access). Overall, we advocate for greater cost-benefit transparency to help compare different journals and different journal business models; such transparency would help both researchers and their institutions in investing wisely the limited resources available to academics.
Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer’s disease: a cross-sectional metabolomic analysis

Background In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis. Methods A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data. Results The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809–0.996; sensitivity = 0.90; specificity = 0.90). Discussion Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.
An Empirical Analysis of Livelihood Strategies and Food Insecurity in Turkana County, Kenya

The pastoral communities of Turkana in northern Kenya have for ages satisfied their economic, social and cultural needs through nomadic pastoralism. But due to increasing frequency of drought and market shocks, the ability of age-old strategies to shield these pastoralists from poverty and food insecurity has declined. With only livestock and social capital as the main assets in a communal property regime, it is not clear which of the various livelihood strategies that these pastoralists pursue can shield households from drought and market shocks and guarantee their food security. This study investigates the livelihood strategies as pursued by pastoralists in Turkana County with a view to identify strategies that can effectively shield households from shocks. Data for the study is sourced from the Kenya Integrated Household Budget Survey (KIHBS) 2005/06. Available literature is used to identify livelihood strategies in Turkana, while the KIHBS data is used to establish the population of people pursuing each strategy. Anova and Bonferroni tests give evidence of the existence of four livelihood strategies using food expenditure ratio as the categorizing variable. Probit regression is used to estimate the determinants of food insecurity in Turkana, while multinomial logit regression is used to do further analysis on the determinants of livelihood strategies. The findings suggest correlation between food insecurity and livelihood strategies. Policies that target livelihood strategies may have implications on food security in Turkana. However, further analysis is required to confirm the reverse causality between livelihood strategies and food insecurity.
Evaluation of UAV imagery for mapping Silybum marianum weed patches

ABSTRACT Silybum marianum (L.) Gaertn weed has the tendency to grow in patches. In order to perform site-specific weed management, determining the spatial distribution of weeds is important for its eradication. Remote sensing has been used to perform species discrimination and it offers promising techniques for operational weed mapping. In the present study, the feasibility of high-resolution imaging for S. marianum detection and mapping is reported. A multispectral camera (green–red–near-infrared) mounted on a fixed wing unmanned aerial vehicle (UAV) was used for the acquisition of high-resolution images with pixel size of 0.1 m. The maximum likelihood (ML) classifier was used to classify the S. marianum among other weed species present in a field, with Avena sterilisL. being predominant. As input to the classifier, the three spectral bands and the texture were used. The scale of the mapping was varied by degrading the image resolution to evaluate classification performance, with 1 m resolution providing the highest classification accuracy. The classification rates obtained using ML reached an overall accuracy of 87.04% with a K-hat statistic of 74%. The results prove the feasibility of operational S. marianum mapping using UAV and multispectral imaging.
Simultaneous Volatility Transmissions and Spillover Effects

Simultaneous Volatility models are developed and shown to be separate from Multivariate GARCH estimators. An example is provided that allows for simultaneous and uni-directional volatility and volume of trade effects. These effects are tested using intra-day data from the Australian cash index and index futures markets. Overnight volatility spillover effects from the S&P500 index futures markets are tested using alternative estimates of this U.S. market volatility. The simultaneous volatility model proves to be robust to alternative specifications of returns equations and to mis-specification of the direction of volatility causality.