Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the cytotoxic effects of sodium hypochlorite on human dental stem cells

Purpose: To investigate the influence of sodium hypochlorite (NaOCl) on human dental stem cell proliferation and differentiation. Method: Dental pulp stem cells (DPSCs), periodontal ligament stem cell (PDLSCs), and gingival mesenchymal stem cells (GMSCs) were treated with NaOCl. Cell viability was evaluated with cellular counting kit-8 (CCK8), and cellular adenosine triphosphate (ATP) levels were analyzed by bromodeoxyuridine (BrdU) incorporation and subsequent flow cytometry. Quantitative polymerase chain reaction (qPCR) and western blotting were performed to detect the expressions of differentiation markers. Results: The viability and ATP levels of all three stem cells types were impaired by NaOCl in a concentration- and time-dependent manners. However, the decrease ATP in GMSCs was less than the other two stem cell population (p < 0.05). NaOCl treatment significantly suppressed the proliferation of dental stem cells (p < 0.05). With regard to differentiation marker expression levels, the decrease in Stro-1 was greater in treatment groups when compared to control on Day 7, while increase in levels of dentin sialophosphoprotein (DSPP), bone sialoprotein (BSP), and osteocalcin (OC) was smaller (p < 0.05). The expressional changes of Stro-1, DSPP, BSP, and OC were more prominent in DPSMs and PDLSCs than in GMSCs. Conclusion: NaOCl dose-dependently impairs the viability, proliferation and differentiation of dental stem cells. Thus, its toxicity to dental stem cells needs to be considered in clinical application. Keywords: Dental stem cells, Sodium hypochlorite, Viability, Proliferation, Differentiation
On The Time-Dependent Scour-Hole Volume Evolution At A Circular Pier In Uniform Coarse Sand

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Late quaternary speleogenesis and landscape evolution in the northern Apennine evaporite areas

Gypsum beds host the majority of the caves in the north‐eastern flank of the Apennines, in the Emilia Romagna region (Italy). More than six hundred of these caves have been surveyed, including the longest known epigenic gypsum cave systems in the world (Spipola‐Acquafredda, ~11 km). Although this area has been intensively studied from a geological point of view, the age of the caves has never been investigated in detail. The rapid dissolution of gypsum and uplift history of the area have led to the long‐held view that speleogenesis commenced only during the last 130 000 years.
Optimizing window size and directional parameters of GLCM texture features for estimating rice AGB based on UAVs multispectral imagery

Aboveground biomass (AGB) is a crucial physiological parameter for monitoring crop growth, assessing nutrient status, and predicting yield. Texture features (TFs) derived from remote sensing images have been proven to be crucial for estimating crops AGB, which can effectively address the issue of low accuracy in AGB estimation solely based on spectral information. TFs exhibit sensitivity to the size of the moving window and directional parameters, resulting in a substantial impact on AGB estimation. However, few studies systematically assessed the effects of moving window and directional parameters for TFs extraction on rice AGB estimation. To this end, this study used Unmanned aerial vehicles (UAVs) to acquire multispectral imagery during crucial growth stages of rice and evaluated the performance of TFs derived with different grey level co-occurrence matrix (GLCM) parameters by random forest (RF) regression model. Meanwhile, we analyzed the importance of TFs under the optimal parameter settings. The results indicated that: (1) the appropriate window size for extracting TFs varies with the growth stages of rice plant, wherein a small-scale window demonstrates advantages during the early growth stages, while the opposite holds during the later growth stages; (2) TFs derived from 45° direction represent the optimal choice for estimating rice AGB. During the four crucial growth stages, this selection improved performance in AGB estimation with R2 = 0.76 to 0.83 and rRMSE = 13.62% to 21.33%. Furthermore, the estimation accuracy for the entire growth season is R2 =0.84 and rRMSE =21.07%. However, there is no consensus regarding the selection of the worst TFs computation direction; (3) Correlation (Cor), Mean, and Homogeneity (Hom) from the first principal component image reflecting internal information of rice plant and Contrast (Con), Dissimilarity (Dis), and Second Moment (SM) from the second principal component image expressing edge texture are more important to estimate rice AGB among the whole growth stages; and (4) Considering the optimal parameters, the accuracy of texture-based AGB estimation slightly outperforms the estimation accuracy based on spectral reflectance alone. In summary, the present study can help researchers confident use of GLCM-based TFs to enhance the estimation accuracy of physiological and biochemical parameters of crops.
Opioid, methamphetamine, and polysubstance use: perinatal outcomes for the mother and infant

The escalation in opioid pain relief (OPR) medications, heroin and fentanyl, has led to an increased use during pregnancy and a public health crisis. Methamphetamine use in women of childbearing age has now eclipsed the use of cocaine and other stimulants globally. Recent reports have shown increases in methamphetamine are selective to opioid use, particularly in rural regions in the US. This report compares the extent of our knowledge of the perinatal outcomes of OPRs, heroin, fentanyl, two long-acting substances used in the treatment of opioid use disorders (buprenorphine and methadone), and methamphetamine. The methodological limitations of the current research are examined, and two important initiatives that will address these limitations are reviewed. Current knowledge of the perinatal effects of short-acting opioids, OPRs, heroin, and fentanyl, is scarce. Most of what we know about the perinatal effects of opioids comes from research on the long-acting opioid agonist drugs used in the treatment of OUDs, methadone and buprenorphine. Both have better perinatal outcomes for the mother and newborn than heroin, but the uptake of these opioid substitution programs is poor (<50%). Current research on perinatal outcomes of methamphetamine is limited to retrospective epidemiological studies, chart reviews, one study from a treatment center in Hawaii, and the US and NZ cross-cultural infant Development, Environment And Lifestyle IDEAL studies. Characteristics of pregnant individuals in both opioid and MA studies were associated with poor maternal health, higher rates of mental illness, trauma, and poverty. Infant outcomes that differed between opioid and MA exposure included variations in neurobehavior at birth which could complicate the diagnosis and treatment of neonatal opioid withdrawal (NOWs). Given the complexity of OUDs in pregnant individuals and the increasing co-use of these opioids with MA, large studies are needed. These studies need to address the many confounders to perinatal outcomes and employ neurodevelopmental markers at birth that can help predict long-term neurodevelopmental outcomes. Two US initiatives that can provide critical research and treatment answers to this public health crisis are the US Environmental influences on Child Health Outcomes (ECHO) program and the Medication for Opioid Use Disorder During Pregnancy Network (MAT-LINK).
Influence of Model Structures on Predictors of Protein Stability Changes from Single-Point Mutations

Missense variation in genomes can affect protein structure stability and, in turn, the cell physiology behavior. Predicting the impact of those variations is relevant, and the best-performing computational tools exploit the protein structure information. However, most of the current protein sequence variants are unresolved, and comparative or ab initio tools can provide a structure. Here, we evaluate the impact of model structures, compared to experimental structures, on the predictors of protein stability changes upon single-point mutations, where no significant changes are expected between the original and the mutated structures. We show that there are substantial differences among the computational tools. Methods that rely on coarse-grained representation are less sensitive to the underlying protein structures. In contrast, tools that exploit more detailed molecular representations are sensible to structures generated from comparative modeling, even on single-residue substitutions.
Experiments with lake phytoplankton in large enclosures

The use of large plastic enclosures, or 'Lund tubes', in lakes as a semi-natural basin for experiments, approximating to lakes within lakes, is discussed. The advantages and disadvantages of the tubes were studied, and the results of investigations into the validity of studies using such tubes and the effects of fertilisers on phytoplankton are presented.
Towards Optically Semi-Transparent Planar Endfire Antennas for CubeSats and Other Small Satellites

An endfire high-gain planar antenna design is proposed by including a dense array of air-vias (with varying diameter) within an ungrounded substrate. This makes the structure semi-transparent and supports simple solar cell placement underneath the PCB-based antenna. Moreover, by gradually altering the diameter of the air-vias the effective relative permittivity for the substrate is controlled and this enables a smooth transition and reduced reflections at the edge of the substrate for more efficient radiation into the air region. Initial simulation results demonstrate a directive endfire pattern of more than 20 dBi at 24 GHz. In addition, the 1U antenna size makes the design suitable for placement on CubeSats and other small satellites, and can be conveniently integrated on top of a solar panel. This can support dual-functionality for the space utilized by the antenna, leading to more solar power harvesting. The result is also that more space can be made available on the satellite structure itself for additional communication equipment, sensors, solar cells, etc. and this approach can foster more advanced mission capabilities.
Alternative Financing Model of Micro Small Medium Business (UMKM) Based on Productive Zakat by Amil Zakat Institution (LAZ) in Surabaya

This article discusses the problems that arise in micro, small, and medium enterprises (UMKM) in Indonesia in general, namely capital problems, income distribution, and the quality of the products offered. Which of these problems can reduce the productivity of UMKM and ultimately cannot guarantee the welfare of the local community. The research method used is a qualitative descriptive approach. The author looks at the existing problems and proposes solutions by optimizing the means of productive zakat funds that have been collected by the Amil Zakat Institute (LAZ). The distribution of productive zakat funds as a source of funding is the main instrument in this article. The financing and development of UMKM by the Amil Zakat Institution (LAZ) is a solution to the problems of UMKM that have been going on for so long. As the Amil Zakat Institution, LAZ will provide business capital from productive zakat funds, foster entrepreneurship, and human resources, as well as aid and control UMKM actors who have received capital from the Amil Zakat Institution (LAZ). The pattern for developing UMKM is through productive zakat funds that have been collected by the Amil Zakat Institution (LAZ) for UMKM. The author will describe the mechanism and role of the Amil Zakat Institution (LAZ) in distributing productive zakat funds so that through this they can overcome the problems of UMKM. Based on this thought, the output expected by the author is to improve product quality, good distribution, and prosperity for UMKM and ultimately be able to create better economic conditions for the community.
Analysis of the Effectiveness of Periodontitis Treatment Using Antimicrobial Agents

A combination of systemic antibiotics with scaling may provide an additional advantage over scaling alone in the periodontitis treatment in terms of clinical loss of attachment and change in pocket depth. The use of antibiotics should be justified by a determined need and should not replace adequate local treatment. Different treatment protocols have been proposed, but their indications and efficacy remain controversial. The study aims to analyse the literature on the use of antimicrobial agents for non-surgical periodontal therapy and to compare different protocols for prescribing antimicrobial agents. A search in MEDLINE and EBSCOhost electronic databases was conducted using relevant MeSH words. Targeted studies had to be published within the last five years. Studies were selected based on inclusion and exclusion criteria. Data from selected studies were extracted and analysed. Ten randomized clinical trials were included in the review. The general conclusions of this review indicate a positive effect of antibiotics as an adjunct to non-surgical treatment of chronic periodontitis, regardless of antimicrobial drugs used in the reviewed studies. A prospect for further research is a comparative analysis of the effectiveness of the use of antimicrobial agents and probiotics as an adjunct to the non-surgical treatment of chronic periodontitis.
The Vatican-Al-Azhar Dialogues: Implications for Socioeconomic Empowerment in Muslim-Christian Interactions

The Vatican-Al-Azhar Dialogues symbolize optimism within an ever more integrated international society, demonstrating the possibilities for productive interfaith dialogue. The partnership between the Holy See and Al-Azhar is a pioneering in surpassing ideological differences in order to prioritise commonly held principles. The forum has facilitated significant dialogues that have resulted in favourable outcomes regarding the relationships between those who identify as Muslims and Christians. Significantly, the conversations have resulted in significant socio-economic empowerment by addressing poverty-related concerns and promoting the inclusive involvement of all segments of society. In addition to religious factors, that has emerged as a significant driver of constructive social transformation. The Vatican-Al-Azhar Dialogues play a crucial role in fostering authentic interfaith communication. The dialogue platform, formed by the Holy See and Al-Azhar, exemplifies a paradigm for fostering healthy discourse among diverse religious groups. The concept surpasses the limitations associated with religious beliefs, emphasizing mutually held principles and collective objectives, hence creating a setting that is favourable to productive interactions. The Dialogues facilitate the establishment of stronger links between Muslims and Christians by emphasizing areas of agreement rather than focusing on ideological disagreements. The relationship has a noteworthy influence on socio-economic empowerment. The Dialogues have shown a steadfast dedication to tackling matters about poverty and pushing for the incorporation of all individuals into society, irrespective of their religious beliefs.
What goes in must come out: the oceanic outgassing of anthropogenic carbon

About 25% of the emitted anthropogenic CO2 is absorbed by the ocean and transported to the interior through key gateways, such as the Southern Ocean or the North Atlantic. Over the next few centuries, anthropogenic CO2 is then redistributed by ocean circulation and stored mostly in the upper layers of the subtropical gyres. Because of the combined effects of (i) weakening buffering capacity, (ii) warming-induced lower solubility, (iii) changes in wind stress and (iv) changes in ocean circulation, there is a high confidence that the ocean sink will weaken in the future. Here, we use IPCC-class Earth System Model (ESM) simulations following the SSP1-2.6 and SSP5-8.5 climate change scenarios extended to the year 2300 to reveal that anthropogenic CO2 begins to outgas in the subtropical gyres of both hemispheres during the summer months of the 21st century. In 2100, about 53% of the surface ocean experience outgassing at least one month in a year in SSP1-2.6, against 37% in SSP5-8.5. After 2100, this fraction keeps increasing, reaching 63% by 2300 in SSP5-8.5 while stabilizing at 55% in SSP1-2.6. This outgassing pattern is driven by the rapid increase in oceanic pCO2, faster than the atmospheric pCO2, due to the combined effect of both rapid warming and long-term accumulation of anthropogenic carbon in these regions. These findings call for increased observation efforts in these areas, particularly in the subtropical gyres of the Southern Hemisphere, in order to detect future release of anthropogenic carbon and accurately constrain the future carbon budget.
Identification and Classification of Medicinal Leaves and their Medicinal Values

The traditional knowledge systems about medicinal properties of plant species have started to disappear with the passage of time due to the scarcity of written documents. Due to resemblance in the visual properties among plants, sorting and classification are complicated to carry out, especially in large area. The main objective of this work is to develop a machine learning based system for classifying different Indian medicinal plants, which will be useful in drug discovery process and provide a platform for future research. This work on identifying plant species and determining their medicinal value using the VGG-16 convolutional neural network model. We embarked on the task of collecting a comprehensive dataset by conducting fieldwork. The work involved visiting botanical gardens to collect plant specimens along with their associated information, such as species, habitat, and traditional medicinal uses. The collected images were labelled ensuring its quality and relevance for training our model. The collected dataset was then utilized to train the VGG-16 model. Techniques such as data augmentation and transfer learning to enhance the model’s performance and optimize training efficiency. Throughout the training process the model’s parameters and hyper parameters were fine-tuned, striving to achieve optimal accuracy and robustness. After conducting extensive research and comparison between VGG 16, Resnet 50, Sequential Model. VGG-16 yielded superior results based on our findings. The VGG-16 model achieved an impressive accuracy of 98%, outperforming other models.
Time-series Data Imputation for Improved Prediction of PM10 Pollutant in Northern Thailand

Air pollution has become a big issue in the Northern part of Thailand due to forest fires, human activities, and seasonal climate. The air pollutant particulate matter (PM10) measurements from the Pollution Control Department (PCD) stations contain some missing values, which limit the capability in time-series prediction of future pollutant quantity. This research performs a preliminary study of PM10 time-series data imputation in three provinces in Thailand, including Chiang Mai, Lampang, and Nan. The evaluation was performed using three imputation methods: k-nearest neighbours (KNN), last observation carried forward (LOCF), and nearest observation carried backward (NOCB). NOCB obtains the highest R2, the lowest mean absolute error (MAE), and the lowest root mean squared error (RMSE) when tested with mimic missing data at varied proportions, ranging from 5% to 25% of the entire data. Imputed data as a result of NOCB underwent time-series data prediction of PM10 using long short-term memory (LSTM)-based neural networks. Prediction models were trained and tested based on the data splitting ratio of 80:20 from 2019 to 2020. The PM10 prediction model trained using imputed data leads to accurate prediction of unseen future data, achieving the R2 values of approximately 0.92.
Research on teacher education and implications for improving the quality of teacher education in Cambodia

This article aims to provide a review of important findings from previous research on teacher education and the quality of teaching to offer the way forward for improving the quality of teacher education in Cambodia. The article begins by highlighting key findings from several studies on teacher education before examining the quality teaching model (QTM) developed by Australian researchers. The article then discusses key factors influencing teacher quality and teaching quality. It also discusses major issues concerning teacher education in Cambodia and offers suggestions for improving teacher education quality in the Cambodian context. The article argues that significant efforts are required to enhance teacher education in Cambodia. In particular, QTM may be worth considering in refining the quality of teacher preparation, teaching quality, and educational reform in the Cambodian teacher education context.
ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions

For the first time in the International Terrestrial Reference Frame (ITRF) history, the ITRF2014 is generated with an enhanced modeling of nonlinear station motions, including seasonal (annual and semiannual) signals of station positions and postseismic deformation for sites that were subject to major earthquakes. Using the full observation history of the four space geodetic techniques (very long baseline interferometry (VLBI), satellite laser ranging (SLR), Global Navigation Satellite Systems (GNSS), and Doppler orbitography and radiopositioning integrated by satellite (DORIS)), the corresponding international services provided reprocessed time series (weekly from SLR and DORIS, daily from GNSS, and 24 h session‐wise from VLBI) of station positions and daily Earth Orientation Parameters. ITRF2014 is demonstrated to be superior to past ITRF releases, as it precisely models the actual station trajectories leading to a more robust secular frame and site velocities. The ITRF2014 long‐term origin coincides with the Earth system center of mass as sensed by SLR observations collected on the two LAGEOS satellites over the time span between 1993.0 and 2015.0. The estimated accuracy of the ITRF2014 origin, as reflected by the level of agreement with the ITRF2008 (both origins are defined by SLR), is at the level of less than 3 mm at epoch 2010.0 and less than 0.2 mm/yr in time evolution. The ITRF2014 scale is defined by the arithmetic average of the implicit scales of SLR and VLBI solutions as obtained by the stacking of their respective time series. The resulting scale and scale rate differences between the two solutions are 1.37 (±0.10) ppb at epoch 2010.0 and 0.02 (±0.02) ppb/yr. While the postseismic deformation models were estimated using GNSS/GPS data, the resulting parametric models at earthquake colocation sites were applied to the station position time series of the three other techniques, showing a very high level of consistency which enforces more the link between techniques within the ITRF2014 frame. The users should be aware that the postseismic deformation models are part of the ITRF2014 products, unlike the annual and semiannual signals, which were estimated internally with the only purpose of enhancing the velocity field estimation of the secular frame.