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The migration to online learning has brought about several new problems. Poor signal quality, large Internet quotas, and device compatibility with learning applications are the most common complaints among students. Additionally, students' poor self-directed learning skills, the excessive number of assignments given by teachers, and the use of monotonous teaching methods and media are also identified as issues. Therefore, the development of learning media that facilitate students' learning processes and support their active engagement becomes crucial. This research aimed to develop PDF hyperlink learning media for online Arabic language learning at Madrasah Aliyah Negeri 4 in Hulu Sungai Tengah District, South Kalimantan, Indonesia (MAN 4 HST). The research model used in this study is the 4D model, consisting of four stages: define, design, develop, and disseminate. In this research, layout and accessibility received good validation scores of 4.3, and the presentation of the contents received a good validation score of 4.2. Additionally, the Wilcoxon test results indicated that the use of PDF hyperlink media significantly influences learning outcomes and receives positive feedback from students. Thus, the use of PDF hyperlink media is recommended for educational institutions experiencing digital divides, as well as those implementing asynchronous learning.

Secondary organic aerosol (SOA) constitutes an important component of atmospheric particulate matter, with a substantial influence on air quality, human health and the global climate. The volatility basis set (VBS) framework has provided a valuable tool for better simulating the formation and evolution of SOA where SOA precursors are grouped by their volatility. This is done in order to avoid the computational cost of simulating possibly hundreds of atmospheric organic species involved in SOA formation. The accuracy of this framework relies upon the accuracy of the volatility distribution of the oxidation products of volatile organic compounds (VOCs) used to represent SOA formation. However, the volatility distribution of SOA-forming vapours remains inadequately constrained within global climate models, leading to uncertainties in the predicted aerosol mass loads and climate impacts. This study presents the results from simulations using a process-scale particle growth model and a global climate model, illustrating how uncertainties in the volatility distribution of biogenic SOA precursor gases affect the simulated cloud condensation nuclei (CCN). We primarily focused on the volatility of oxidation products derived from monoterpenes as they represent the dominant class of VOCs emitted by boreal trees. Our findings reveal that the particle growth rate and their survival to CCN sizes, as simulated by the process-scale model, are highly sensitive to uncertainties in the volatilities of condensing organic vapours. Interestingly, we note that this high sensitivity is less pronounce in global-scale model simulations as the CCN concentration and cloud droplet number concentration (CDNC) simulated in the global model remain insensitive to a 1-order-of-magnitude shift in the volatility distribution of organics. However, a notable difference arises in the SOA mass concentration as a result of volatility shifts in the global model. Specifically, a 1-order-of-magnitude decrease in volatility corresponds to an approximate 13 % increase in SOA mass concentration, while a 1-order-of-magnitude increase results in a 9 % decrease in SOA mass concentration over the boreal region. SOA mass and CCN concentrations are found to be more sensitive to the uncertainties associated with the volatility of semi-volatile compounds, with saturation concentrations of 10−1 µg m−3 or higher, than the low-volatility compounds. This finding underscores the importance of having a higher resolution in the semi-volatile bins, especially in global models, to accurately capture SOA formation. Furthermore, the study highlights the importance of a better representation of saturation concentration values for volatility bins when employing a reduced number of bins in a global-scale model. A comparative analysis between a finely resolved nine-bin VBS setup and a simpler three-bin VBS setup highlights the significance of these choices. The study also indicates that radiative forcing attributed to changes in SOA over the boreal forest region is notably more sensitive to the volatility distribution of semi-volatile compounds than low-volatility compounds. In the three-bin VBS setup, a 10-fold decrease in the volatility of the highest-volatility bin results in a shortwave instantaneous radiative forcing (IRFari) of −0.2 ± 0.10 W m−2 and an effective radiative forcing (ERF) of +0.8 ± 2.24 W m−2, while a 10-fold increase in volatility leads to an IRFari of +0.05 ± 0.04 W m−2 and an ERF of +0.45 ± 2.3 W m−2 over the boreal forest region. These findings underscore the critical need for a more accurate representation of semi-volatile compounds within global-scale models to effectively capture the aerosol loads and the subsequent climate effects.

Hexaferrites are in high demand due to their unique properties, such as absorbing harmful electromagnetic radiation, which is a result of the development of wireless technology and electronic and electrical gadgets. In meantime, U-type hexaferrites whose chemical formula is Ba4Me2Fe36O60, one of the least explored hexaferrite types getting attention from researchers, and getting explored as a micro-absorbing material and magnetic material due to their complex crystalline structure and increased intrinsic magneto crystallographic anisotropy for wider range of frequency. Several synthesis methods, such as solid-state, sol-gel, chemical co-precipitation, and high-energy milling, are analyzed in this review study, along with their annealing/sintering temperatures and times, for forming several forms of U-type hexaferrite. Additionally, this review paper's emphasized discussion topics include crystal structure, characterization methods, magnetic, microwave-absorbing, and electromagnetic properties. It looked at how substituting other elements could affect the structural, magnetic, and microwave absorption capabilities of U-type hexaferrite. In order to figure out microwave absorber devices spanning an extensive range of frequencies, most researchers have focused on the magnetic and microwave absorbing capabilities of U-type.

This research delves into the obstacles and difficulties associated with predicting cryptocurrency movements in the volatile global financial market. This study develops and evaluates an advanced Deep Learning-Enhanced Temporal Fusion Transformer (ADE-TFT) model to estimate Bitcoin values more accurately. This research employs cutting-edge artificial intelligence (AI) and machine learning (ML) techniques to comprehensively examine various aspects of cryptocurrency forecasting, including geopolitical implications, market sentiment analysis, and pattern detection in transactional datasets. The study demonstrates that the ADE-TFT model outperforms its lower-layer counterparts in terms of forecasting accuracy, with reduced Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE) values, particularly when using a higher hidden layer configuration (h=8). The study emphasizes the importance of experimenting with different normalization strategies and utilizing various market-related data to enhance the model's performance. The results suggest that improving forecasting accuracy may require addressing these limitations and incorporating additional factors, such as market sentiment. By providing investors with more precise market predictions, the techniques and information presented in this research have the potential to significantly increase investor power in an unpredictable digital currency market, enabling wise investment choices.

Abstract The use of saline water under drought conditions is critical for sustainable agricultural development in arid regions. Biochar is used as a soil amendment to enhance soil properties such as water-holding capacity and the source of nutrition elements of plants. Thus, the research was carried out to assess the impact of biochar treatment on the morphological and physiological characteristics and production of Solanum lycopersicum in greenhouses exposed to drought and saline stresses. The study was structured as a three-factorial in split-split-plot design. There were 16 treatments across three variables: (i) water quality, with freshwater and saline water, with electrical conductivities of 0.9 and 2.4 dS m− 1, respectively; (ii) irrigation level, with 40%, 60%, 80%, and 100% of total evapotranspiration (ETC); (iii) and biochar application, with the addition of biochar at a 3% dosage by (w/w) (BC3%), and a control (BC0%). The findings demonstrated that salt and water deficiency hurt physiological, morphological, and yield characteristics. Conversely, the biochar addition enhanced all characteristics. Growth-related parameters, such as plant height, stem diameter, leaf area, and dry and wet weight, and leaf gas exchange attributes, such rate of transpiration and photosynthesis, conductivity, as well as leaf relative water content were decreased by drought and salt stresses, especially when the irrigation was 60% ETc or 40% ETc. The biochar addition resulted in a substantial enhancement in vegetative growth-related parameters, physiological characteristics, efficiency of water use, yield, as well as reduced proline levels. Tomato yield enhanced by 4%, 16%, 8%, and 3% when irrigation with freshwater at different levels of water deficit (100% ETc, 80% ETc, 60% ETc, and 40% ETc) than control (BC0%). Overall, the use of biochar (3%) combined with freshwater shows the potential to enhance morpho-physiological characteristics, support the development of tomato plants, and improve yield with higher WUE in semi-arid and arid areas.

Abstract In recent years, the proliferation of Massive Open Online Courses (MOOC) platforms on a global scale has been remarkable. Learners can now meet their learning demands with the help of MOOC. However, learners might not understand the course material well if they have access to a lot of information due to their inadequate expertise and cognitive ability. Personalized Recommender Systems (RSs), a cutting-edge technology, can assist in addressing this issue. It greatly increases resource acquisition through personalized availability for various people of all ages. Intelligent learning methods, such as machine learning and Reinforcement Learning (RL) can be used in RS challenges. However, machine learning needs supervised data and classical RL is not suitable for multi-task recommendations in online learning platforms. To address these challenges, the proposed framework integrates a Deep Reinforcement Learning (DRL) and multi-agent approach. This adaptive system personalizes the learning experience by considering key factors such as learner sentiments, learning style, preferences, competency, and adaptive difficulty levels. We formulate the interactive RS problem using a DRL-based Actor-Critic model named DRR, treating recommendations as a sequential decision-making process. The DRR enables the system to provide top-N course recommendations and personalized learning paths, enriching the student's experience. Extensive experiments on a MOOC dataset such as the 100 K Coursera course review validate the proposed DRR model, demonstrating its superiority over baseline models in major evaluation metrics for long-term recommendations. The outcomes of this research contribute to the field of e-learning technology, guiding the design and implementation of course RSs, to facilitate personalized and relevant recommendations for online learning students.

High-precision microfabrication of functional ceramics with complex shapes and tailored properties currently arouse significant attention, but maintaining dimensional accuracy is still a research challenge. Herein, an innovative digital light processing (DLP) 3D technology is employed to fabricate calcined kaolin (Al2O3·2SiO2) ceramic with intricate structures, achieving high precision and densification. To illustrate the potential of different solid content slurries (43, 45, 46.2, and 47.5 vol%), and the curing thickness with tuned exposure time (8s, 10s, and 12s), we investigated their impact on physical properties and microstructures. The results show that the optimal sintering at 1200 °C achieved an exceptionally high density 2.38 g/cm3, with low shrinkage (17.35 %) along XY-direction and porosity reaching up to 15.53%. The highest level of solids slurry at 47.5 vol% increased the densification and open porosity. For all solid contents, the shrinkage along the Z-direction was exceeded compared to the XY-direction. A comprehensive evaluation of sintered morphologies, including their topography and chemical composition. The EDX mapping showed that kaolin ceramics have excellent stability at high temperatures. The highest flexural strength of DLP printed specimen at temperature (1200 °C) is 71.60 MPa, whereas that of the diamond porous structure is 6.66 MPa. Our work sheds light on high-precision microfabrication of complex shapes with unparalleled accuracy and efficiency, paving the way for high-performance functional ceramic materials.

Owing to enhanced features of nanomaterials, various applications of such materials have been suggested in the thermal systems, heat exchanges, electronic cooling systems, coolant processes, energy production etc. Following to such motivated applications, the objective of current analysis is to presents the bioconvective double stratification flow of Sutterby nanofluid due to bidirectional moving surface. The thermal interpretation of problem is subject to utilization of radiative effects, activation energy and heat source. The observations for heat, mass and microorganism's assessment are performed by using the convective boundary conditions. Shooting numerical simulations are performed for modeled problem. It is noticed that heat transfer enhances due to thermal stratification parameter. An increment in mass transfer is subject to larger values of mass stratification Biot number. The claimed results offer significance in controlling the heating and cooling processes, thermal devices, energy generation, manufacturing developments, solar systems etc.

We present a case of a symptomatic, giant, left upper back arteriovenous malformation that was treated through a staged endovascular and open approach. Through a series of embolizations, followed by resection, we were able to preserve the limb and upper back neurovascular supply, demonstrating an approach to preserve sensation and function and improving quality of life.

Penelitian ini mengembangkan sistem deteksi otomatis kata-kata baku dan non-baku pada data Twitter berbasis Kamus Besar Bahasa Indonesia (KBBI). Twitter merupakan platform media sosial yang populer, namun sering kali digunakan dengan kata-kata tidak baku yang mengganggu komunikasi. Normalisasi kata-kata tidak baku diperlukan untuk pemrosesan dan analisis tweet. Penelitian sebelumnya menggunakan metode Levenshtein Distance dan pengklasifikasi Naïve Bayes, serta Term Based Random Sampling dalam proses Stopword Removal. Preprocessing penting dalam klasifikasi teks di media sosial. Penelitian ini fokus pada preprocessing dan deteksi kata-kata baku dan non-baku pada data Twitter menggunakan KBBI. Sistem otomatis ini membantu peneliti mencari kata-kata non-baku atau slang dengan mudah, meningkatkan kualitas komunikasi, dan pemahaman pesan di data Twitter yang mencerminkan tren bahasa yang berkembang. Penelitian ini juga memperkenalkan pendekatan yang terstruktur untuk mengotomatisasi deteksi kata-kata baku dan non-baku, dengan langkah-langkah yang meliputi pengumpulan data, preprocessing data, identifikasi bahasa tidak baku, penghapusan kata berimbuhan, dan identifikasi kata slang. Metode ini mendukung analisis sentimen dalam text mining dan memastikan hasil klasifikasi sentimen yang lebih akurat dalam data Twitter. Berdasarkan pengujian, langkah-langkah preprocessing meningkatkan performa metode penentuan polarity dengan accuracy InSet sebesar 66,66% dan F1-score sebesar 61,40%.

Introduction. Safety holds paramount importance in inclusive school environments that accommodate all students. The UNICEF report emphasizes that, regrettably, both peer sand teachers may engage in physical abuse against children in early childhood education (ECE). Objective. This paper aims to assess early childhood education teachers' perspectives on school safety, their strategies to ensure a safe environment, and the supporting rules for school environmental safety. Method. This research employed a quantitative descriptive approach, gathering numerical data through a survey questionnaire. The study included 52 ECE teachers who had undergone anti-violence education training in Banjarmasin and Banjarbaru, two inclusive cities in South Kalimantan, Indonesia. Results. Findings reveal that teachers reported instances of physical aggression, cyberbullying, verbal insults, and sexual harassment as infrequent occurrences. However, addressing social manipulation and physical aggression through corrective measures is recognized as necessary. Teachers implemented diverse strategies to maintain a safe and respectful classroom atmosphere, including reinforcing norms, promoting civility, teaching non-violent conflict resolution, and acknowledging students who intervened to protect victims. Importantly, teachers affirmed their commitment to transparency by refusing to conceal unethical behaviors by staff or students, thereby strengthening school safety protocols. Nevertheless, the evaluation of school environmental safety activities and regulations identified significant opportunities for improvement. Conclusion. The majority of ECE institutions lack clear protocols for conflict resolution, diversity promotion, bullying prevention, parental involvement, teacher training, and safety assessment. Addressing these shortcomings is crucial to establishing a more secure and inclusive learning environment that meets the needs of all children.

Ectopic kidneys, with a prevalence of 1/1000-4000, often manifest in the pelvic region, can be complicated with problems such as ureteropelvic junction (UPJ) obstruction. This video article presents a case of open pyeloplasty in a 15-month-old infant with a pelvic kidney, emphasizing technical details for educational purposes. The patient was prenatally diagnosed with pelvic kidney hydronephrosis at 22 weeks of gestation, progressing to grade 4 postnatally. MAG-3 scintigraphy confirmed UPJ obstruction, warranting open pyeloplasty. A Pfannenstiel incision provided access to the Retzius space. The ureter was dissected, revealing the adhered renal pelvis. Stay sutures facilitated dissection, and 5/0 polyglactin sutures were strategically placed due to anatomical anomalies. Ureteropelvic anastomosis was performed using 6/0 PDS sutures. A 3-Fr Double J catheter preceded the closure of the renal pelvis. The procedure was concluded with meticulous layer closure. The operation lasted for 50 min, with minimal blood loss (10 mL). Drain was removed on postoperative day 2, and the patient was discharged. Ureteral stent was removed at 4 weeks. A 3-month follow-up ultrasound revealed a notable reduction in hydronephrosis, with an anteroposterior diameter of 6 mm. This video article elucidates the nuances of open pyeloplasty in pelvic kidneys and serves as a valuable resource for residents and fellows. The concise procedure, with a brief operative time and minimal blood loss, indicates the efficacy of the surgery.

The worldwide prevalence of Diabetes Mellitus (DM) associated with Hepatitis C Virus (HCV) infection are reported with higher rates of morbidity and mortality. The frequency of HCV is approximately 3-4 million cases each year and in parallel the incidence of DM is increasing alarmingly. World Health Organization (WHO) has specified that DM will be the 7th leading cause of mortality by 2030. The increasing association between HCV and DM has been indicated by some significant reports recently. HCV infection leads to hepatic steatosis and rapid insulin resistance, which in turn upsurges the risk factors for hepatic fibrosis and hepatocellular carcinoma. This study is designed to examine the association between HCV and DM, and different risk factors associated with HCV infection in Qassim region, Kingdom of Saudi Arabia (KSA). A total of 634 blood samples were obtained from diabetic and non-diabetic patients. These blood samples were first screened for HCV infection by enzyme-linked immunosorbent assay (ELISA) and positive samples were again confirmed by TaqMan HCV quantitative test and the viral load in different samples was estimated. The HCV prevalence was identified as 2.5% in diabetic patients with a positive association between HCV and DM (RR= 1.24, OR= 1.77) which is not significant statistically. However, the HCV prevalence among diabetic females was significantly different from males (p

This study aims: 1) To find out how the motor skills of Syekh Yusuf's football school (SSB) students in Gowa Regency. 2) To find out how the ability to kick a football school student (SSB) Syekh Yusuf, Gowa Regency. 3) To find out the relationship between motor skills and the ability to kick a ball, SSB Syekh Yusuf students, Gowa Regency. The method used in this research is descriptive method with a quantitative approach to the type of correlational research. The population in this study were all students of SSB Syekh Yusuf, Gowa Regency. The sampling technique used simple random sampling consisting of 27 people. The results of this study: 1) The motor skills of Syekh Yusuf Gowa Regency Football School Students (SSB) tend to be in the very good category. 2) The ability to kick the ball in Syekh Yusuf's Football School Students (SSB) in Gowa Regency tends to be in the good category. 3) Motoric ability has a significant correlation with the ability to kick a ball in Syekh Yusuf's Football School Students (SSB), Gowa Regency, amounting to 20.2% with an R value of 0.449 and an Fcount of 6.311.

The purpose of this research is to produce a test tool and measurement of standing stork test based on Android. The type of research used in this research is development research with Research & Development (R&D) research design from Borg and Gall. This research was conducted with 9 research stages namely, (1) Research and information collecting, (2) Planning, (3) Develop preliminary form of product, (4) Preminary field testing, (5) Main product revision, (6) Main field testing, (7) Operational product revision, (8) Operational field testing, (9) Final product revision. The population in this study used Sports Science Faculty Students and Aceh-North Sumatra PON Pelatda Athletes. The sampling technique used purposive sampling with Phase I trials of 20 FIK students and Phase II trials of 30 athletes of Pelatda Taekwondo Sumut. Furthermore, from the Phase I trial, totaling 20 people showed a figure of 89% with Very Eligible criteria, then from the Phase II trial, totaling 30 Aceh-North Sumatra PON Pelatda athletes showed a figure of 91% with the Very Eligible category. From the results of the research/feasibility test carried out by test and measurement experts, IT experts and sports academic experts, it shows a score of 96% in the Very Eligible category, so it can be used. On the basis of the data obtained, the development of an Android-based standing stork test and measurement tool was declared feasible to be developed as a test and measurement tool for balance.

The present study was done on the hypothesis that excess sodium chloride (NaCl) in the soil decreases the growth and yield of Cichorium intybus L. To investigate this hypothesis, a pot experiment was conducted in which chicory seeds were sown in garden soil-filled earthen pots and treated with three different doses of sodium chloride (45, 75, and 105 mM kg-1 soil) except the control, and each treatment was replicated three times. The results revealed that all the saline treatments significantly (p≤0.05) reduced the vegetative (including root and shoot length, dry weight, number of leaves, leaf area, number of branches, and photosynthetic pigments) and reproductive (mean fruit number/plant, mean seed number/fruit, and total seed yield/plant) growth parameters of Cichorium intybus. On increasing NaCl concentration in the soil, chlorophyll content significantly (p≤0.05) decreased while proline content in the fresh leaves increased significantly (p≤0.05). From the results, it is concluded that Cichorium intybus L. can tolerate a moderate level of sodium chloride stress (45-75 mM NaCl kg-1 soil) but is sensitive to high doses of sodium chloride stress (105 mM NaCl kg-1 soil).

Background: The term glass ceiling coined by Loden in 1978 is commonly used to describe difficulties faced by minorities and women when trying to move into senior roles. Objective: To analyse trends and patterns for female representation at the European Association of Urology (EAU) and European Society for Paediatric Urology (ESPU) annual general meetings over the past decade. Design, setting, and participants: We used objective data on female representation in the roles of chairs, moderators, and lecture speakers at the EAU and ESPU meetings from 2012 to 2022. Outcome measurements and statistical analysis: We evaluated gender based representation in paediatric urology sessions at the EAU and ESPU meetings, collecting data on the overall number of sessions, lectures, symposiums, abstract/poster sessions, and courses, and analysed the male/female ratio. Data were derived from printed and digital programmes for the relevant meetings. Results and limitations: During the period from 2012 to 2022, the percentage female representation varied from 0% (2012) to a maximum of 35% (2022) at EUA paediatric urology sessions, and from 13.5% (2014) to a maximum of 32% (2022) at ESPU meetings. Both associations show clear progression towards equality. Conclusions: Female representation at EAU and ESPU meetings has risen over the years, reaching 35% and 32%, respectively, in 2022, which is in line with the number of female members. We hope that this motivates a move towards the equality objectives for 2030. A clear and fundamental societal change is needed, with fair and more consistent institutional policies and framework commitments in the areas of science, medicine, and global health. Gender equality and diversity taskforces are essential to achieve these goals. Patient summary: We analysed the male/female ratio for participants in annual meetings held by the European Association of Urology and the European Society for Paediatric Urology. From a low level in 2012, the ratio increased to over 30% in 2022, in line with the female membership of the societies. Focus on fair and consistent policies is needed to ensure that women are well represented in medicine.

This study aims to determine the educational values ​​in the Qur'an surah Ali 'Imran verse 159 and Qur'an surah At-Taubah verses 128-129: A study of the perspective of Ibnu Katsir's interpretation. This research includes library research (library research). Primary data sources and secondary data sources are two categories into which researchers divide data sources. As the main source, used in the Qur'an surah Ali 'Imran verse 159 and in the Qur'an surah At-Taubah verses 128-129perspective of Ibn Kathir's commentary. Meanwhile, secondary data sources include books related to research and scientific journals. Based on the research results obtained that education contained in the Qur'an surah Ali 'Imran verse 159 and Qur'an surah At-Taubah verses 128-129, namely being gentle; sincere in forgiving others; respect the opinions of others; put your trust in Allah; have sympathy and empathy for others; be compassionate to others; always do good and put others first; make God a place to lean on.

This study aims to determine the ability of footwork in badminton games for children aged 10-12 years at the Yanti Jaya Badminton Club. The type of research used in this research is descriptive quantitative research. Quantitative descriptive analysis is used to collect, summarize and interpret the data obtained, which is then reprocessed so that it is expected to produce a clear, holistic picture of the problem that is the object of research. The population in this study were 20 members of the Yanti Jaya badminton club. The sample used was 20 people using a sampling technique, namely Saturated Sampling (census). The results of the study obtained the proportion of the effects of the ability to walk from 20 people or (100%); the results of the excellent category were four people or (20%); the moderate type was 14 people or (70%), and the poor class was two people or (10 % ). Thus, the ability to footwork in badminton games for children aged 10-12 years at the Yanti Jaya badminton club is in the moderate category with a proportion of 70%. This proves that the analysis of footwork ability at the Yanti Jaya badminton club is already good and needs to be improved again to achieve more on the badminton sports field.

The presence of chemicals, heavy metals, and colorants from textile effluents in water represent a significant health risk. To address this, a range of treatment methods, including ion exchange, membrane processes, physicochemical approaches, and biological techniques, are employed to eliminate these contaminants. Activated carbon, distinguished by its porous structure and effective pollutant, is a notable solution. An environmentally sustainable method involves producing activated carbon from agricultural and industrial waste to combat water pollution. For instance, the recycling of industrial waste, like glass fiber-reinforced plastic, can be used for water treatment via pyrolysis with a ZnCl2 activation process. The quality of the activated carbon is confirmed through characterization methods such as XRD, FTIR, SEM, and Raman spectroscopy, suggesting potential applications extending beyond water filtration, encompassing supercapacitors, fuel storage, and CO2 absorption. This study underscores the environmentally friendly potential of repurposing industrial waste for efficient and eco-conscious water purification.

This study aimed to estimate the genetic parameters for lactation milk yield (LMY), lactation fat yield (LFY), and lactation protein yield (LPY) in the Sahiwal cattle breed of Pakistan. Performance data of 3364 purebred Sahiwal cattle with 9964 herd test records were collected from the public and/or private herds. Various edits were applied, such as herd test day records < 3, unknown calving and drying dates, etc., which reduced the data set to 1039 animals with 4489 herd test records. Lactation yields for milk, fat, and protein were calculated using the test interval method. Preliminary data analysis was performed using PROC MIXED in SAS. The animal model under the REML method was used to estimate the genetic parameters of the milk yield, milk fat, and milk protein. A multivariate model (3-traits) was fitted, which included the fixed effects of parity besides random effects of herd-year-season of calving (HYS), animal and residuals for all three traits. Mean ± SD (kg) of LMY, LFY, and LPY were 1444.07±554.51, 60.48±25.18, and 48.26±19.39, respectively. Parity and HYS significantly varied (p

This manuscript focuses on the development of coated sand granules, consisting of a thin layer of graphite doped with activated carbon (AC) and titanium oxide (TiO2) for continuous removal of methylene blue dye. The coating process was carrried out by using polyvinylpyrrolidone (PVP), AC and titanium isopropoxide (TiP). The graphitic surface was activated using 1.0 M KOH solution. Increasing the sand granules' weight from 5 to 10 g considerably enhanced adsorption capacity, with minimal improvements observed at 20 g. Calcination temperatures above 500 °C exhibited no significant impact on adsorption capacity, as samples prepared at 650 and 800 °C showed similar dye removal efficiency to the 500 °C sample. Increasing the amounts of TiP and PVP linearly improved adsorption capacity, albeit at a modest rate. The incoorporation of AC particles distinctly enhanced dye removal process, with the highest enhancement observed at 1 g AC content, further augmented by light irradiation. Flow rate studies revealed that maintaining a flow rate of 4 ml/min.cm2 resulted in continuous and stable removal (90 % removal for 90min). Increasing the flow rate to 8 ml/min.cm2 led to a linear reduction in removal rate (77 % removal after 90min), while a flow rate of 18 ml/min.cm2 showed an S-shaped adsorption isotherm, reaching 35 % removal after 90min.

After around two years of having online learning, students in the universities have to come back to face-to-face learning mode as it was before the pandemic. This setting also applied to the biology education study program of Universitas Sulawesi Barat. The current study investigated the students’ perspective on changing online to face-to-face learning after COVID-19. It is a qualitative descriptive study with nine students as respondents from the classes of 2019, 2020, and 2021. The instrument used was an interview guide consisting of indicators regarding online teaching and learning features, assessment, and interactions that students needed to experience in face-to-face settings but would like to. In addition, students' perceptions of the advantages and disadvantages of the shift from online to offline learning were also assessed. The data analysis was performed in three stages: data reduction, data display, and drawing a conclusion or data verification. The result showed that several things they would like to have as it was during online learning were (1) have electronic materials, online-games-based learning, and more time to complete the assignments, (2) get various types of assessments including via online platforms (3) to have online applications or media to discuss learning materials and submit assignments. (4) In addition, for the advantages, the practicums could be conducted in laboratories, they felt more concentrated during offline classes, and became more confident to apply IT skills during offline settings, while the disadvantages were feeling anxious and fear to interacting during offline class and trouble to listen to lecturers’ class while having masks. Overall, students feel face-to-face learning is way more effective and efficient but suggested blended learning as an interesting mode in the learning and teaching implementation.

Purpose: To investigate potential beneficial effects of tocotrienols which have been suggested to inhibit hypoxia-inducible factor (HIF) pathway, on partial bladder outlet obstruction (PBOO)-induced bladder pathology. Materials and Methods: PBOO was surgically created in juvenile male mice. Sham-operated mice were used as controls. Animals received daily oral administration of either tocotrienols (T3) or soybean oil (SBO, vehicle) from day 0 to 13 post-surgery. Bladder function was examined in vivo by void spot assay. At 2 weeks post-surgery, the bladders were subjected to physiological evaluation of detrusor contractility in vitro using bladder strips, histology by H&E staining and collagen imaging, and gene expression analyses by quantitative PCR. Results: A significant increase in the number of small voids was observed after 1 week of PBOO compared to the control groups. At 2 weeks post-surgery, PBOO+SBO mice showed a further increase in the number of small voids, which was not observed in PBOO+T3 group. PBOO-induced decrease in detrusor contractility was similar between two treatments. PBOO induced bladder hypertrophy to the same degree in both SBO and T3 treatment groups, however, fibrosis in the bladder was significantly less prominent in the T3 group than the SBO group following PBOO (1.8- vs. 3.0-fold increase in collagen content compared to the control). Enhanced levels of HIF target genes in the bladders were observed in PBOO+SBO group, but not in PBOO+T3 group compared to the control. Conclusions: Oral tocotrienol treatment reduced the progression of urinary frequency and bladder fibrosis by suppressing HIF pathways triggered by PBOO.

Smart strategies and intelligent technologies are enabling the designing of a smart learning environment that successfully supports the development of personalized learning and adaptive learning. This trend towards integration is in line with the growing prevalence of Internet of Things (IoT)-enabled smart education systems, which can leverage Machine Learning (ML) techniques to provide Personalized Course Recommendations (PCR) to students. Current recommendation techniques rely on either explicit or implicit feedback, often failing to capture changes in learners’ preferences effectively as they integrate both types of feedback. This paper proposes a new model for personalized learning and PCR that is enabled by a smart E-Learning (EL) platform. The model aims to gather data on students’ academic performance, interests, and learning preferences, using this information to recommend the most beneficial courses for each student. Our approach suggests courses based on the learner’s interactions with the system and the cosine similarity of related content, combining explicit (user ratings) and implicit (views and behavior) methodologies. The method employs various ML algorithms and an EL Recommender System (RecSys) based on Collaborative Filtering (CF), including Random Forest Regressor (RFR), Decision Tree Regressor (DTR), K-Nearest Neighbors (KNN), Singular Value Decomposition (SVD), eXtreme Gradient Boosting Regressor (XGBR), and Linear Regression (LR). To evaluate our proposed solution, we benchmark it against existing approaches in terms of predictive accuracy and running time. Experiments are conducted using two benchmark datasets from Coursera and Udemy. The proposed model outperforms existing top-K recommendation techniques in terms of accuracy metrics such as precision@k, Mean Average Precision (MAP)@k, recall@k, Normalized Discounted Cumulative Gain (NDCG)@k, Mean Squared Error (MSE)@k, Root Mean Squared Error (RMSE)@k, and Mean Absolute Error (MAE)@k for PCR. The results show that SVD performs particularly well, demonstrating higher precision, recall, MAP, and NDCG along with lower MAE, RMSE, and MSE values compared to other proposed algorithms. This success can be attributed to SVD’s ability to capture complex interactions between students and courses. Our proposed solutions exhibit promise across two datasets and can be applied to various RecSys domains.

Learning activities are considerably supported and improved by the rapid advancement of e-learning systems. This gives students a tremendous chance to participate in learning activities worldwide. The Massive Open Online Courses (MOOCs) platform has emerged as one of the most significant platforms for e-learning as a result of the rapid growth of network information technologies. Due to the increased number of online courses available, it is harder for individual learners to choose the appropriate courses, activities, and learning paths for the actual necessities they want, which reduces their learning performances. Moreover, a sequential Recommender System (RS) can identify the learner’s future interest and suggest the subsequent item or learning content given a sequence of past interactions. This is in contrast to interactive recommendation methods that can create recommendations based on the learner’s feedback via constant interactions. To address these challenges, the goal of this paper is to propose a Reinforcement Learning (RL) based smart e-learning framework with Markov Decision Process (MDP) that has the potential to enhance the learning experience for each student by providing them with a personalized and effective learning path. Applying the MDP and RL-based techniques such as Q-learning for Sequential Path Recommendation (SPR) and learning development is more achievable. This is because the MDP allows for adjusting the recommendations method to find new activities and learning paths based on the learners’ feedback on recommendations results. Experimental findings reveal that the suggested model obtains significant improvements and provides viable performance under different parameters optimization. Furthermore, we also show that the proposed method outperforms a long session (long-term rewards such that they maximize learning progress while minimizing frustration and disengagement). This demonstrates the model’s improvements in simulating the learner’s sequential behavior, learning activities, various learning materials, and learning paths simultaneously. These promising initial results provide a possible solution to assess this challenge further in future work.