Miracle-dz/UniFAR-FTUs huggingface dataset:
Engaging Elementary Students in Computer Science Education Through Project-Based Learning

As interests and initiatives for accessible computer science education continue to grow, efforts to integrate computer science (CS) instruction into K-12 classrooms in the US are dramatically increasing. Curriculum, legislation, and standards across the nation are quickly evolving as they seek to incorporate CS instruction and related concepts into classrooms in order to make computer science education accessible for all K-12 students. In the state of XXXXX specifically, each public school is required to include computer science in the school's curriculum for students in grades K-12 beginning July 2021 (SEA 172 (2018)) (making it one of only seven states with formal statewide computer science standards). This work in progress describes an effort to provide students and teachers with a developmentally appropriate and engaging project to satisfy this legislative mandate, and introduce young students to related CS concepts within a classroom setting. We describe the 13-week in-class project-based program, including its modules, sequencing and present a student’s lived experience through the intervention as they designed, built and automated model clubhouses. Within the classroom setting, students were eager to show off their designs and talk about how they overcame various setbacks, obstacles, and difficulties along the way. An emphasis on these types of challenging activities and the results of this intervention may provide insight into students’ perceptions of, and abilities related to computer science and related STEM (Science, Technology and Engineering, and Mathematics) skills, which can aid educators in understanding how to best-prepare students for future success as technologically literate citizens, while helping move them towards a greater interest and engagement in computer science.
EXPLICATING THE NARRATIVES OF ELEMENTARY TEACHERS IN HANDLING GRADE 2 STUDENTS WITHOUT PRIOR IN-PERSON INSTRUCTION

The purpose of this qualitative study employing the approach of narratology was to explore the narratives of elementary teachers in dealing with Grade 2 students without prior in-person instruction in the Division of Tagum City. Three elementary teachers were selected through purposive sampling, and they were interviewed to glean the narratives relevant to the research topic of the study. Their narratives were similar which showed the problems that emerged among the Grade 2 learners after the pandemic which include the learning gaps in literacy and numeracy, socio-emotional problems of the pupils, and lack of parental involvement during the pandemic. In response to these perceived challenges, the teachers focused first on the recovery of the expected foundational skills of the learners and exposed them to lots of interactions with their peers. Moreover, remediation as an intervention was made available for the learners to cope with their learning gaps in consonance with asking the learners parents for their collaboration and support. The elementary teachers realized that the curriculum should be adjusted to accommodate these learners who admittedly had learning loss during the pandemic. Support of teachers, educational leaders, parents, and stakeholders was perceived to be crucial to immediately address this serious problem in the society today. KEYWORDS: education, elementary teachers, narrative research, purposive sampling, Division of Tagum City
Development of a Cation Exchange SPE-HILIC-MS/MS Method for the Determination of Ningnanmycin Residues in Tea and Chrysanthemum

Ningnanmycin is a widely used antibiotic in agricultural production that effectively controls fungal and viral diseases in tea trees and chrysanthemums. The polarity characteristic of ningnanmycin has posed limitations on the development of robust detection methods, thereby hindering effective monitoring and control measures. By combining cation exchange solid phase extraction (SPE) with hydrophilic interaction chromatography tandem mass spectrometry (HILIC-MS/MS), we have effectively tackled the issue pertaining to the separation and retention of ningnanmycin. The average recoveries of ningnanmycin in green tea, black tea, and chrysanthemum were 77.3–82.0%, 80.1–81.5%, and 74.0–80.0%, respectively. The intraday and interday relative standard deviations (RSDs) were below and equal to 7.7%. Good linearity was observed in the concentration range of 1–1000 μg/L (R2 > 0.998). The limits of detection (LODs) ranged from 1.1 μg/kg to 7.1 μg/kg, and the limits of quantification (LOQs) ranged from 3.6 μg/kg to 23.7 μg/kg for ningnanmycin. These results indicate the good accuracy, repeatability, reproducibility, and sensitivity of the method. It is suitable for detecting ningnanmycin in tea and chrysanthemum.
Distribution network reconfiguration utilizing the particle swarm optimization algorithm and exhaustive search methods

The load level for each period in the distribution network can be considered non-identical due to the increasing demand for loads and the bigger distribution network. The main problem in the transmission and distribution network system is power losses and voltage profiles, affecting the quality of service and operating costs. This study compares the reconfiguration of the network using exhaustive search techniques and particle swarm optimization (PSO) algorithms on the IEEE 33 bus distribution network system. The study’s results compare the study of power flow before and after network reconfiguration, which is a decrease in the value of power losses from 202.7 kW to 139.6 kW. Then voltage profile improved from 91.309% to 93.782%. The simulation results also found that this reconfiguration can improve the system voltage profile, which initially contained 21 buses outside the standard limits of IEEE Std 1159-1995 to 7 buses.
Real-time irrigation forecasting for ecological water in artificial wetlands in the Dianchi Basin

Abstract It is important to understand the real-time irrigation demands of wetland plants in areas experiencing ecological water shortages. The Levenberg-Marquardt algorithm (L-M) in an Artificial Neural Network (ANN) was used to train and forecast daily reference crop evapotranspiration (ET0), using a polynomial fuzzy daily precipitation function, based on short-term meteorological predictions. This method allowed simulation of a real-time irrigation schedule based on field water balance, and was applied to a variety of wetland plants including reeds, Typha orientalis and paddy. The results showed that the determinant coefficient of daily ET0 forecast was 0.945. More than 75% of the sampling error was below 10% and 96% of the sampling error was below 20%. The mean-error (ME) and root mean square error (RMSE) for the daily field water level simulated with reeds, T. orientalis and paddy were less than 6.6 mm, while the value of Index of agreement (IA), and RMSE were greater than 0.986 and 0.946, respectively. The difference in ME, RMSE, IA, and Nash-Sutcliffe efficiency factor (NSE) for reeds and T. orientalis was not significant, but it was twice as high for paddy. For real-time irrigation for paddy in the Dianchi Basin, the values of ME, RMSE, IA, NSE, and R were 0.36–0.91mm, 2.85–4.92mm, 0.986–0.996, 0.946–0.985, and 0.938, respectively. The method can meet the needs of regional water resources allocations and operations.
Enhanced Postsurgical Cancer Treatment Using Methacrylated Glycol Chitosan Hydrogel for Sustained DNA/Doxorubicin Delivery and Immunotherapy

Background: Cancer recurrence and metastasis are major contributors to treatment failure following tumor resection surgery. We developed a novel implantable drug delivery system utilizing glycol chitosan to address these issues. Glycol chitosan is a natural adjuvant, inducing dendritic cell activation to promote T helper 1 cell immune responses, macrophage activation, and cytokine production. Effective antigen production by dendritic cells initiates T-cell-mediated immune responses, aiding tumor growth control. Methods: In this study, we fabricated multifunctional methacrylated glycol chitosan (MGC) hydrogels with extended release of DNA/doxorubicin (DOX) complex for cancer immunotherapy. We constructed the resection model of breast cancer to verify the anticancer effects of MGC hydrogel with DNA/DOX complex. Results: This study demonstrated the potential of MGC hydrogel with extended release of DNA/DOX complex for local and efficient cancer therapy. The MGC hydrogel was implanted directly into the surgical site after tumor resection, activating tumor-related immune cells both locally and over a prolonged period of time through immune-reactive molecules. Conclusions: The MGC hydrogel effectively suppressed tumor recurrence and metastasis while enhancing immunotherapeutic efficacy and minimizing side effects. This biomaterial-based drug delivery system, combined with cancer immunotherapy, can substantial improve treatment outcomes and patient prognosis.
Research on Algorithm of Light Strip Center Extraction Based on Deep Learning

In view of the phenomena such as under-exposure of light strips and noise interference caused by complex surfaces of objects, it is difficult for traditional light strip center extraction algorithm to achieve light strip center extraction. Therefore, this paper studies the extraction of light strip center line based on semantic segmentation network algorithm based on deep learning, uses deep learning algorithm to presegment light strips, and then uses gray prime-core method to extract light strips subpixel. Improve the stability and accuracy of center line extraction.
A Polyherbal Mixture with Nutraceutical Properties for Ruminants: A Meta-Analysis and Review of BioCholine Powder.

BioCholine Powder is a polyherbal feed additive composed of Achyrantes aspera, Trachyspermum ammi, Azadirachta indica, and Citrullus colocynthis. The objective of this study was to analyze published results that support the hypothesis that the polyherbal product BioCholine Powder has rumen bypass choline metabolites through a meta-analysis and effect size analysis (ES). Using Scopus, Web of Science, ScienceDirect, PubMed, and university dissertation databases, a systematic search was conducted for experiments published in scientific documents that evaluated the effects of BioCholine supplementation on the variables of interest. The analyzed data were extracted from twenty-one publications (fifteen scientific articles, three abstracts, and three graduate dissertations available in institutional libraries). The studies included lamb growing-finishing, lactating ewes and goats, calves, and dairy cows. The effects of BioCholine were analyzed using random effects statistical models to compare the weighted mean difference (WMD) between BioCholine-supplemented ruminants and controls (no BioCholine). Heterogeneity was explored, and three subgroup analyses were performed for doses [(4 (or 5 g/d), 8 (10 g/d)], supplementation in gestating and lactating ewes (pre- and postpartum supplementation), and blood metabolites by species and physiological state (lactating goats, calves, lambs, ewes). Supplementation with BioCholine in sheep increased the average daily lamb gain (p < 0.05), final body weight (p < 0.01), and daily milk yield (p < 0.05) without effects on intake or feed conversion. Milk yield was improved in small ruminants with BioCholine prepartum supplementation (p < 0.10). BioCholine supplementation decreased blood urea (p < 0.01) and increased levels of the liver enzymes alanine transaminase (ALT; p < 0.10) and albumin (p < 0.001). BioCholine doses over 8 g/d increased blood glucose, albumin (p < 0.10), cholesterol, total protein, and globulin (p < 0.05). The ES values of BioCholine in retained energy over the control in growing lambs were +7.15% NEm (p < 0.10) and +9.25% NEg (p < 0.10). In conclusion, adding BioCholine Powder to domestic ruminants' diets improves productive performance, blood metabolite indicators of protein metabolism, and liver health, showing its nutraceutical properties where phosphatidylcholine prevails as an alternative that can meet the choline requirements in ruminants.
Chinese satellite photogrammetry without ground control points based on a public DEM using an efficient and robust DEM matching method

ABSTRACT Photogrammetry based on high-resolution satellite image can acquire geospatial information within a large area rapidly and timely, but its geopositioning accuracy is highly dependent on ground control points. Under the background of global mapping, a public digital elevation model (DEM) assisted Chinese satellite image geopositioning scheme was proposed to realize satellite photogrammetry without ground control points. To make full use of public DEM advantages of consistent and high accuracy, public DEM was regarded as reference data and matched with the DEM extracted from image, and then the determined transformation parameters were applied to correct direct georeferencing results in object space. A fast least Z-difference method combined with least trimmed squares estimator was proposed to achieve DEM matching, which can not only automatically select corresponding point determination model, but also self-adaptively detect and eliminate difference between DEMs. Multi-groups of comparative experiments using Mapping Satellite-1 and ZiYuan-3 surveying satellite images were designed. Experimental results show that the DEM assisted geopositioning scheme exploits advantages of reference DEM, which can greatly improve the accuracy of photogrammetry without ground control points to a relatively high level. The geopositioning accuracy of image is largely determined by, but not confined to, the accuracy of reference DEM, but it is slightly affected by the resolution of reference DEM. If target DEM resolution is relatively high, the geopositioning accuracy of a single image assisted by Shuttle Radar Topography Mission (SRTM) DEM can satisfy the accuracy requirements of 1:50,000 scale mapping perfectly. This scheme also has good robustness and high computational efficiency.
Metabolic Syndrome Prevalence in Women with Gestational Diabetes Mellitus in the Second Trimester of Gravidity

Background: Women with gestational diabetes (GDM) have an increased risk of metabolic syndrome (MS) after delivery. MS could precede gravidity. The aims of this study were (i) to detect the prevalence of MS in women at the time of GDM diagnosis, (ii) to detect the prevalence of MS in the subgroup of GDM patients with any form of impaired glucose tolerance after delivery (PGI), and (iii) to determine whether GDM women with MS have a higher risk of peripartal adverse outcomes. Methods: A cross-sectional observational study comprised n = 455 women with GDM. International Diabetes Federation (IDF) criteria for MS definition were modified to the pregnancy situation. Results: MS was detected in 22.6% of GDM patients in those with PGI 40%. The presence of MS in GDM patients was associated with two peripartal outcomes: higher incidence of pathologic Apgar score and macrosomia (p = 0.01 resp. p = 0.0004, chi-square). Conclusions: The presence of MS in GDM patients is a statistically significant risk factor (p = 0.04 chi-square) for PGI. A strong clinical implication of our findings might be to include MS diagnostics within GDM screening using modified MS criteria in the second trimester of pregnancy.
Role of leucine-rich repeat kinase 2 in severe acute pancreatitis

Introduction Intrapancreatic activation of trypsinogen caused by alcohol or high-fat intake and the subsequent autodigestion of the pancreas tissues by trypsin are indispensable events in the development of acute pancreatitis. In addition to this trypsin-centered paradigm, recent studies provide evidence that innate immune responses triggered by translocation of intestinal bacteria to the pancreas due to intestinal barrier dysfunction underlie the immunopathogenesis of acute pancreatitis. Although severe acute pancreatitis is often associated with pancreatic colonization by fungi, the molecular mechanisms linking fungus-induced immune responses to the development of severe acute pancreatitis are poorly understood. Leucine-rich repeat kinase 2 (LRRK2) is a multifunctional protein that mediates innate immune responses to fungi and bacteria. Mutations in Lrrk2 is a risk factor for Parkinson’s disease and Crohn’s disease, both of which are driven by innate immune responses to gut organisms. Discussion In this Minireview article, we discuss how activation of LRRK2 by the recognition of fungi induces severe acute pancreatitis.
Tribological interactions of modern biomaterials used in total hip arthroplasty (THA)

When two surfaces in contact are subjected to a relative motion and material is released, wear occurs. Wear is a process that involves the interactions between surfaces and, more specifically, the removal and deformation of material from a surface as a result of mechanical action of the contacting object through motion. The effectiveness of lubrication determines both the nature and magnitude of wear, and the level of friction in bearings.
Model Development for Life Cycle Assessment of RiceYellow Stem Borer under Rising Temperature Scenarios

Yellow stem borer (YSB) is the most destructive and widely distributed insect-pest of rice. It causes dead heart or white head, depending on infestation time and significantly reduces rice yields by 5-10% and even up to 60% under localized outbreak conditions [1]. It can grow in places having temperature >12 oC and annual rainfall around 1000mm. Generally, temperature and high relative humidity (RH) in the evening favors stem borer growth and development [2]. The female moth oviposits from 1900 to 2200hr in summer, 1800 to 2000 hr in spring and autumn, and deposits one egg mass in a night and up to five nights after emergence. Optimum temperature is 29 oC having 90% RH for maximum number of eggs deposition. Optimum temperature for egg hatching is 24-29 oC with 90-100% RH. Larvae die at 35 oC and hatching is severely reduced when RH goes to below 70% [1]. Larvae can’t molt at 12 oC or below and they die. The last instar larvae can survive unfavorable growth condition as diapauses, which is broken by rainfall or flooding. In multiple rice cropping, no diapauses takes place. The pupal period can last for 9-12 days and the threshold temperature for its development is 15-16 oC.
Enhancing Laparoscopic Video Quality Assessment: A Model Addressing Sensor and Channel Distortions

This letter presents a supervised quality assessment (QA) model for medical laparoscopic videos (LV) affected by sensor and channel distortions. The quality discerning features of LVs are computed based on the statistical properties of the singular, left, and right eigenmatrices of the singular value decomposition (SVD). Specifically, inspired by the perceptual characteristics of the human visual system, the LV frames are decomposed into multiple subbands using a two-level discrete Haar wavelet transform. Then, the maximum value of SVD matrices across columns of each decomposed subband is computed to estimate the frame level quality discriminative features of the LV. Further, the frame level features are averaged over the number of frames to estimate the quality aware feature set of the LV. The top-ranked features computed from the ReliefF algorithm and the expert opinion subjective scores are given to the support vector regressor to estimate the quality score of a test LV. Experimental results on the LVQA dataset demonstrated that predictions of the proposed LVQA model correlate well with expert subjective ratings and outperformed the performance numbers of existing image and video QA models.
FABP2 is Involved in Intestinal α-Synuclein Pathologies.

BACKGROUND Recently, the hypothesis that pathological α-Synuclein propagates from the gut to the brain has gained attention. Although results from animal studies support this hypothesis, the specific mechanism remains unclear. This study focused on the intestinal fatty acid-binding protein (FABP2), which is one of the subtypes of fatty acid binding proteins localizing in the gut, with the hypothesis that FABP2 is involved in the gut-to-brain propagation of α-synuclein. The aim of this study was to clarify the pathological significance of FABP2 in the pathogenesis and progression of synucleinopathy. METHODS We examined the relationship between FABP2 and α-Synuclein in the uptake of α-Synuclein into enteric neurons using primary cultured neurons derived from mouse small intestinal myenteric plexus. We also quantified disease-related protein concentrations in the plasma of patients with synucleinopathy and related diseases, and analyzed the relationship between plasma FABP2 level and progression of the disease. RESULTS Experiments on α-Synuclein uptake in primary cultured enteric neurons showed that following uptake, α-Synuclein was concentrated in areas where FABP2 was localized. Moreover, analysis of the plasma protein levels of patients with Parkinson's disease revealed that the plasma FABP2 and α-Synuclein levels fluctuate with disease duration. The FABP2/α-Synuclein ratio fluctuated more markedly than either FABP2 or α-Synuclein alone, depending on the duration of disease, indicating a higher discriminant ability of early Parkinson's disease patients from healthy patients. CONCLUSIONS These results suggest that FABP2 potentially contributes to the pathogenesis and progression of α-synucleinopathies. Thus, FABP2 is an important molecule that has the potential to elucidate the consistent mechanisms that lead from the prodromal phase to the onset and subsequent progression of synucleinopathies.
Impact of frontal ablation on the ice thickness estimation of marine-terminating glaciers in Alaska

Abstract. Frontal ablation is a major component of the mass budget of calving glaciers, strongly affecting their dynamics. Most global-scale ice volume estimates to date still suffer from considerable uncertainties related to (i) the implemented frontal ablation parameterization or (ii) not accounting for frontal ablation at all in the glacier model. To improve estimates of the ice thickness distribution of glaciers, it is thus important to identify and test low-cost and robust parameterizations of this process. By implementing such parameterization into the ice thickness estimation module of the Open Global Glacier Model (OGGM v1.1.2), we conduct a first assessment of the impact of accounting for frontal ablation on the estimate of ice stored in glaciers in Alaska. We find that inversion methods based on mass conservation systematically underestimate the mass turnover and, therefore, the thickness of tidewater glaciers when neglecting frontal ablation. This underestimation can amount to up to 19 % on a regional scale and up to 30 % for individual glaciers. The effect is independent of the size of the glacier. Additionally, we perform different sensitivity experiments to study the influence of (i) a constant of proportionality (k) used in the frontal ablation parameterization, (ii) Glen's temperature-dependent creep parameter (A) and (iii) a sliding velocity parameter (fs) on the regional dynamics of Alaska tidewater glaciers. OGGM is able to reproduce previous regional frontal ablation estimates, applying a number of combinations of values for k, Glen's A and fs. Our sensitivity studies also show that differences in thickness between accounting for and not accounting for frontal ablation occur mainly at the lower parts of the glacier, both above and below sea level. This indicates that not accounting for frontal ablation will have an impact on the estimate of the glaciers' potential contribution to sea-level rise. Introducing frontal ablation increases the volume estimate of Alaska marine-terminating glaciers from 9.18±0.62 to 10.61±0.75 mm s.l. e, of which 1.52±0.31 mm s.l. e (0.59±0.08 mm s.l.e when ignoring frontal ablation) are found to be below sea level.