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Case-based reasoning (CBR), which is a classical reasoning methodology, has been put to use. Its application has allowed significant progress in resolving problems related to the diagnosis, therapy, and prediction of diseases. However, this methodology has shown some complicated problems that must be resolved, including determining a representation form for the case (complexity, uncertainty, and vagueness of medical information), preventing the case base from the infinite growth of generated medical information and selecting the best retrieval technique. These limitations have pushed researchers to think about other ways of solving problems, and we are recently witnessing the integration of CBR with other techniques such as data mining. In this article, we develop a new approach integrating clustering (Fuzzy C-Means (FCM) and K-Means) in the CBR cycle. Clustering is one of the crucial challenges and has been successfully used in many areas to develop innate structures and hidden patterns for data grouping [1]. The objective of the proposed approach is to solve the limitations of CBR and improve it, particularly in the search for similar cases (retrieval step). The approach is tested with the publicly available immunotherapy dataset. The results of the experimentations show that the integration of the FCM algorithm in the retrieval step reduces the search space (the large volume of information), resolves the problem of the vagueness of medical information, speeds up the calculation and response time, and increases the search efficiency, which further improves the performance of the retrieval step and, consequently, the CBR system.

Emotions are caused by a human brain reaction to objective events. The purpose of this study is to investigate emotion identification by machine learning using electroencephalography (EEG) data. Current research in EEG-based emotion recognition faces significant challenges due to the high-dimensionality and variability of EEG signals, which complicate accurate classification. Traditional methods often struggle to extract relevant features from noisy and high-dimensional data, and they typically fail to capture the complex temporal dependencies within EEG signals. Recent progress in machine learning by deep neural networks has opened up opportunities to develop methods highly efficient and practicable as to serve useful real-world applications. The purpose of this study is to investigate a novel end-to-end deep learning method of emotion recognition using EEG data, which prefaces a combination of two-dimensional (2D) convolutional network (CNN) and Long short-term memory network (LSTM) by an autoencoder. The autoencoder layers seek a lower dimensionality encoding for optimal input signal reconstruction, and the 2D CNN/LSTM combination layers capture both spatial and temporal features that best describe the emotion classes present in the data. Experiments in four-category classification of emotions, using the public and freely available DEAP dataset, revealed that the method reached superior performance: 90.04% for the “arousal” category, 89.97% for “valence”, 87.73% for “dominance,” and 90.84% for liking”, as measured by the accuracy metric.

Apple vinegar is commonly made from fermented apple juice, which involves two consecutive stages of fermentation: alcoholic and acetic acid fermentation. Both Saccharomyces cerevisiae and Acetobacter acetii are involved in fermentation. Apple vinegar has various benefits, such as stabilizing blood pressure, treating rheumatism, and detoxifying toxins. Excessive consumption of this product may cause damage to the esophagus, low blood potassium levels or hypokalemia, diarrhoea, and ulcers due to the high acetic acid content. Moreover, the ethanol content also needs to be determined. It should be lower than 0,5% to fulfil the halal requirements for certification. The local brands of apple vinegar in Indonesia are generally produced by small-medium enterprises (SMEs), especially in Malang, Indonesia. Commercial brands of various apple vinegar, XCJO, YSW, THT, NTF, and BST, were sampled for their ethanol and acetic acid content in one method of analysis: gas chromatography, utilizing the high volatility properties of ethanol and acetic acid. The samples contain 17.73%, 11.45%, 6.43%, 2.67%, and 1.49% v/v of acetic acid, respectively, for XCJO, YSW, THT, NTF, and BST. At the same time, the ethanolic content is 0.11 and 0.02% v/v for XCJO and YSW, respectively, which are lower than the label value informed. Meanwhile, the rest of the brands' content is 4.00%, 2.39%, and 3.21% ethanol for THT, NTF, and BST, respectively. In addition, the acetic acid content of XCJO is high. A consumer should be aware of dilution before consuming the XCJO apple vinegar. It is unnecessary in the case of YSW, THT, NTF, and BST. Keywords: Analysis, Fermentation, Halal, Small-medium enterprises

Background: Cathepsin-L (FhCL) is a group of enzymes that most flukes express and secreted significantly in parasite-host interactions. Researches are focusing on antigens released by Fasciola gigantica as one of the keys for understanding immunologic pathway in parasite infection and targets for anthelmintics. Efforts to suppress FhCL function through vaccination or therapy using anthelmintic drugs are key factors in controlling field level trematode infections. A molecular docking method can be used to observe the interaction between FhCL and some anthelmintic drugs to better understand the effect of these anthelmintics on FhCL. Furthermore, it is necessary to carry out molecular dynamics method to observe the dynamic pattern of the interaction of the enzyme-ligand when the dynamics simulation is in progress. Aim: This study was carried out to screen six commercial anthelmintic drugs against cathepsin-2L (FhCL-2) and cathepsin 5L (FhCL-5) using in silico and molecular dynamics approach. Methods: The three-dimensional (3D) crystal structure of FhCL-2 and FhCL-5 enzymes were constructed based on the crystal structure of ProCathepsin 1L (pdb id. 2O6X) as a template, while six anthelmintic agents ("SMILES" format) were downloaded from PubChem and converted to 3D format using the MOE Builder tool. The enzyme modelling results were evaluated using the "Ramachandran Plot". Results: Molecular docking results showed that all tested ligands had affinity for FhCL-2 and FhCL-5. The best ∆Gbinding value for FhCL-2 was clorsulon ligand (-15.21 kcal/mol) with pKi of 32.25 µM, which was significantly different compared to other drugs (p [Open Vet J 2024; 14(11.000): 2754-2761]

embelajaran materi teks eksplanasi ini membutuhkan model yang sesuai dengan sistem pendidikan di Indonesia yang mengharuskan siswa memahami banyak konsep keilmuan dengan waktu yang terbatas. Penelitian ini bertujuan menegatahui adakah Pengaruh Model Pembelajaran Radec (Read, Answer, Discuss, Explain, Create) Terhadap Kemampuan Berpikir Kritis Siswa Pada Mata Pelajaran Bahasa Indonesia Kelas V Sd IT Salsabila Palembang. Penelitian ini menggunkan metode penelitian Quasi Experimental Design dengan rencana penelitian PreTest dan PostTest Design. Populasi dalam penelitian ini adalah seluruh peserta didik kelas V SD IT Salsabila palembang. Sample pada penelitian ini adalah kelas V Baghdad dengan jumlah peserta didik 22 peserta didik sebagai kelas kontrol, sedangkan kelas V Jeddah dengan jumlah peserta didik 22 peserta didik sebagai kelas eksperimen. Teknik pengumpulan data yang digunakan dalam kegaiatan penelitian ini adalah test dan dokumentasi. Teknik analisis data yang digunakan adalah uji independent simple t-test. Pada hasil pretest dan posttest kelas kontrol dan kelas eksperimen yang menunjukkan adanya perbedaan yang signifikan setelah menerapkan model pembelajaran PMRI, analisis data yang diperoleh 0,041 < 0,05 maka Ho ditolak dan Ha diterima. Jadi setelah melakukan pengujian dapat disimpulkan bahwa terdapat pengaruh Model Pembelajaran Radec (Read, Answer, Discuss, Explain, Create) Terhadap Kemampuan Berpikir Kritis Siswa Pada Mata Pelajaran Bahasa Indonesia Kelas V Sd IT Salsabila Palembang Kata Kunci: Model Pembelajaran RADEC, Kemampuan Berpikir Kritis, Materi Teks Eksplanas

Currently, the leatherback turtle population in Indonesia tends to decline. One of the factors that cause turtles' existence is the turtle eggs that fail to hatch because bacteria contaminate them, 80% of the reasons turtle eggs fail to hatch are due to infection by microorganisms found on the eggshell. Turtle eggs have a soft structure and there are pores that function for gas exchange and water absorption. Microorganisms in sand can infect turtle eggs through the pores and cause hatching failure. This study aims to isolate and identify pathogenic bacteria found in leatherback turtle eggshell (Dermochelys coriacea) from Lampuuk Beach, Aceh Besar, based on the 16S rRNA gene analysis. Eight eggshell samples from leatherback turtle eggs that failed and hatched were cultured on Nutrient Agar (NA) medium. Then, the samples were inoculated on a blood agar medium for haemolysis test. Molecular identification of the 16S rRNA gene was also carried out to determine bacterial species. A total of five bacterial colonies from leatherback turtle eggshells were successfully isolated consisting of two Gram-negative bacteria (Penyu Belimbing Aceh (PBA) = PBA-1 and PBA-2 and three Gram-positive bacteria (PBA-3, PBA-4, and PBA-5). Based on the haemolysis test, the five bacterial isolates were unable to haemolyze blood. Bacterial DNA of PBA-1 and PBA-2 were successfully isolated and amplified using polymerase chain reaction (PCR) with a DNA target of ~1500 bp. Analysis using BLASTN and phylogenetic tree construction showed that PBA-1 isolate had 98.64% similarity with Acinetobacter baumannii, while PBA-2 isolate had 97.82% similarity with Enterobacter kobei. Both bacteria are members of the Enterobacteriaceae family. It can be concluded that, there were two pathogenic bacteria can potentially be opportunistic pathogens found in leatherback turtle eggshells that failed or succeeded in hatching, namely A. baumannii and E. Kobei

Bakgrunn: Tidligere forskning viser at selv om pasienter får mye informasjon vedrørende anestesi i forbindelse med et kirurgisk inngrep, har ikke pasientenes erfaringer og ønsker blitt tatt hensyn til ved utveksling av informasjon. Forskning indikerer også et behov for mer kunnskap om pasientenes erfaringer med utveksling av informasjon mellom helsepersonell og pasient. Hensikt: Å undersøke pasientenes erfaringer med informasjon om regionalanestesi i tilknytning til et kirurgisk inngrep. Metode: Ti pasienter ble intervjuet etter et kirurgisk inngrep. Det ble gjort lydopptak som ble transkribert verbatimt. Gjennom en kvalitativ innholdsanalyse ble data bearbeidet for å identifisere subkategorier, kategorier og felles tema på tvers av intervjuene. COREQ sjekkliste er fulgt for å sikre studiens kvalitet. Resultat: Informantenes erfaringer kan relateres til 1) varierende innhold i informasjon om anestesiform ved kirurgi, 2) betraktninger som påvirker holdning til kirurgi og anestesi, 3) usikkerhet rundt medvirkning ved valg av anestesiform og 4) varierende erfaring med regionalanestesi. Informantene hadde ulik grad av informasjonsbehov i forkant av det kirurgiske inngrepet. Informasjonen de fikk i forbindelse med prosedyrer ble omtalt som tilfredsstillende og beroligende. Informantene synes det var utfordrende å stille spørsmål om noe de ikke kjente til, og opplevde at det var helsepersonellet som var de beste til å ta avgjørelsene for dem. Tidligere erfaringer med kirurgi og anestesi hadde innvirkning på preferanser for det nåværende sykehusoppholdet. Det midlertidige funksjonstapet relatert til nerveblokaden skapte mye uro ettersom dette var ukjent for flere av informantene. Konklusjon: Informantene hadde opplevelse av å ikke være godt nok informerte. Mangelen på informasjon hemmet medvirkning, men informantene var allikevel fornøyde. Dette synliggjør at dialogen mellom helsepersonellet og pasientene kan struktureres bedre, slik at pasientene får dekket sitt behov for informasjon. ENGLISH ABSTRACT Patients’ Experiences with Information About Regional Anesthesia Related to a Surgical Procedure – A Qualitative Study Purpose: To investigate patients’ experiences with information about regional anesthesia related to a surgical procedure. Method: Ten patients were interviewed after undergoing a surgical procedure. Audio recordings were made and transcribed verbatim. Through a qualitative content analysis, the data were processed to identify subcategories, categories, and themes common for all across the interviews. The COREQ checklist was followed to ensure the quality of the study. Result: The informants’ experiences can be related to 1) varying content in information about the type of anesthesia used in surgery, 2) considerations influencing attitudes toward surgery and anesthesia, 3) uncertainty regarding participation in the choice of anesthesia type, and 4) varying experiences with regional anesthesia. The informants had different levels of information needs prior to the surgical procedure. The information they received in connection with the procedures was described as satisfactory and reassuring. The informants found it challenging to ask questions about something they were unfamiliar with and felt that the healthcare personnel were best positioned to make decisions for them. Previous experiences with surgery and anesthesia influenced preferences for the current hospital stay. The temporary loss of function related to the nerve block created a lot of anxiety since it was unknown to several of the informants. Conclusion: The informants felt they were not sufficiently informed. The lack of information hindered participation, but the informants were nevertheless satisfied. This highlights that the dialogue between healthcare personnel and patients can be better structured so that patients’ needs for information are met.

Masalah gizi pada periode balita dengan atau tanpa sakit yang berulang akan berdampak pada kondisi fisik tubuh anak (stunting). Malnutrisi pada balita dapat terjadi disebabkan oleh faktor budaya, kebiasaan dan sosial masyarakat. Masyarakat di wilayah operasional Puskesmas Betungan dikenal sebagai masyarakat patriarki yang sangat menghargai budaya sebagai salah satu penentu perilaku, khususnya perilaku kesehatan terkait makanan. Tujuan penelitian ini adalah menganalisis faktor kejadian stunting pada balita berbasis Transcultural Nursing. Studi ini menggunakan rancangan kuantitatif dengan pendekatan cross-sectional. Populasi dalam penelitian ini adalah seluruh ibu yang mempunyai balita, sampel diambil dengan teknik simple random sampling. Data yang terkumpul dianalisis univariat dan bivariat. Hasil : Terdapat hubungan antara kejadian stunting pada balita dengan variabel teknologi (p=0.045), faktor dukungan keluarga dan sosial (p=0.048), nilai budaya dan gaya hidup (p=0.013), serta faktor ekonomi ( p = 0,034). Kesimpulan : Meskipun tidak ada korelasi antara karakteristik pendidikan dengan terjadinya stunting, namun tingkat pendidikan yang dimiliki seorang perempuan merupakan salah satu komponen mendasar yang berkontribusi terhadap permasalahan gizi, khususnya stunting.

Background: Black rats (Rattus rattus; Rodentia: Muridae) cause significant damage to agricultural and human health, and they are considered a reservoir for a variety of diseases. Objectives: The current study aimed to evaluate the toxicity of oral anticoagulants derived from Halocnemum strobilaceum (Pall.) M. Bieb. to these dangerous animals. Method: Four selected doses (100, 150, 200 and 300 mg/day/kg of individual weight) and one control were utilized, with 10 repetitions of each dose (5 ♂ and 5 ♀). The extract was powdered on dates as bait. Results: UPLC-ESI/MS-MS chromatography identified three distinct coumarins (coumaric acid, p-coumaric acid and 4-hydroxycoumarin). The results showed that the fourth dose used caused the highest number of deaths (100 % after three days of treatment). In contrast, after 48 h of therapy, all rats examined showed lethargy, anorexia and unconsciousness, followed by rapid death at 72 h in the treated individuals. The LD50 was recorded at 146.4 mg.kg−1 with a LT50 of 59.37 h. At the end of the experiment, the autopsies of all deceased individuals allowed us to observe the bleeding of their internal organs. The analysis of PT and aPTT demonstrated that the halophyte under investigation possesses anticoagulant activity that increased with the concentration. Histological sections of the liver revealed cellular alteration and significant necrosis. As well, the kidneys had vascular occlusion with an inflammatory filtrate. Conclusions: To reduce food losses and wastes caused by these pests, H. strobilaceum will be an important plant for use in protecting against invasive rodents, especially in environmental and stored product programs focused at eradicating rodent pests.

BackgroundImbalanced datasets pose challenges for developing accurate seizure detection systems based on electroencephalogram (EEG) data. Generative AI techniques may help augment minority class data to facilitate automatic epileptic seizure detection.New methodThis study investigates the impact of various data augmentation (DA) approaches, including Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP), Vanilla GAN, Conditional GAN (CGAN), and Cramer GAN, on classification performance with Random Forest models. The best-performing GAN variant, WGAN-GP, was then integrated with a bidirectional Long Short-Term Memory (LSTM) architecture and compared against traditional and synthetic oversampling methods.ResultsThe evaluation of different GAN variants for data augmentation with Random Forest classifiers identified WGAN-GP as the most effective approach. The integration of WGAN-GP with bidirectional LSTM yielded substantial performance improvements, outperforming traditional oversampling methods and achieving an accuracy of 91.73% on the augmented data, compared to 86% accuracy on real data without augmentation.Comparison with existing methodsThe proposed generative AI approach combining WGAN-GP and recurrent neural network models outperforms comparative synthetic oversampling methods on metrics relevant for reliable seizure detection from imbalanced EEG datasets.ConclusionsIncorporating the WGAN-GP generative AI technique for data augmentation and integrating it with bidirectional LSTM elevates seizure detection accuracy for imbalanced EEG datasets, surpassing the performance of traditional oversampling and class weight adjustment methods. This approach shows promise for improving epilepsy monitoring and management through enhanced automated detection system effectiveness.

Culicoides are vectors that can transmit many different pathogens to mammals — including humans, and domestic and wild animals — and birds. In order to take preventive measures against any vector-borne disease, it is important to gather information on both the host and vector species. Culicoides species are mainly mammalophilic, ornithophilic or ornithophilic/mammalophilic, but females have also been found to occasionally feed on engorged insects. A recent systematic review based on three groups of key words investigated Culicoides on farms, and asserted that 92 species (including four not present species) have been reported among cattle in mainland France and Corsica. We have re-evaluated the presence of Culicoides species in cattle in France using the same data of the review. Our data show that only 18 species are reported among cattle. Furthermore, our research used molecular and indirect investigations to analyse Culicoides species that had been feeding on cattle. Our results demonstrate that 45 species feed on cattle out of 92 species present in France. The paper discusses the relevance of data in the literature when investigating hosts of Culicoides species.

The low numeracy of students is still an emerging topic of discussion and has not yet made progress. Research from PISA and OECD shows that Indonesia ranks low for numeracy skills. Many efforts have been made to improve numeracy, one of which is the implementation of the Christian teacher's role as a guide. Therefore, this article is written with the aim of examining the role of Christian teachers as guides to improve student numeracy. This research was conducted using a literature review. The Christian teacher as a guide means that the teacher plays a role in directing and providing guidance for students. In improving numeracy, Christian teachers play a role in directing students to the right mindset towards numeracy content. Christian teachers make Jesus as a shepherd an example in carrying out their role as a guide to improve numeracy. Christian teachers help students to improve numeracy according to numeracy indicators while keeping the Bible as the source of truth. Christian teachers will make Christ the center of education, which means that all aspects of education are worked on and focused on Christ. Thus students can utilize numeracy skills in accordance with biblical truth and glorify God. Future researchers are advised to examine more deeply the factors that influence numeracy and find solutions to the appropriate role of Christian teachers to improve numeracy skills. BAHASA INDONESIA ABSTRACT Rendahnya kemampuan berhitung siswa masih menjadi perbincangan yang muncul dan belum mengalami kemajuan. Penelitian dari PISA dan OECD menunjukkan bahwa Indonesia berada di peringkat rendah untuk kemampuan berhitung. Banyak upaya yang telah dilakukan untuk meningkatkan kemampuan berhitung, salah satunya adalah dengan menerapkan peran guru Kristen sebagai penuntun. Oleh karena itu, artikel ini ditulis dengan tujuan untuk mengkaji peran guru Kristen sebagai penuntun untuk meningkatkan kemampuan berhitung siswa. Penelitian ini dilakukan dengan menggunakan studi literatur. Guru Kristen sebagai penuntun berarti guru berperan untuk mengarahkan dan memberikan tuntunan kepada siswa. Dalam meningkatkan kemampuan berhitung, guru Kristen berperan dalam mengarahkan siswa agar memiliki pola pikir yang benar terhadap materi berhitung. Guru Kristen menjadikan Yesus sebagai gembala sebagai teladan dalam menjalankan perannya sebagai penuntun untuk meningkatkan kemampuan berhitung. Guru Kristen menolong siswa untuk meningkatkan kemampuan berhitung sesuai dengan indikator-indikator berhitung dengan tetap menjadikan Alkitab sebagai sumber kebenaran. Guru Kristen akan menjadikan Kristus sebagai pusat dalam pendidikan, yang berarti semua aspek pendidikan dikerjakan dan difokuskan pada Kristus. Dengan demikian siswa dapat menggunakan kemampuan berhitung sesuai dengan kebenaran Alkitab dan memuliakan Tuhan. Peneliti selanjutnya disarankan untuk meneliti lebih dalam lagi mengenai faktor-faktor yang mempengaruhi kemampuan berhitung dan mencari solusi mengenai peran guru Kristen yang tepat untuk meningkatkan kemampuan berhitung.

Abstract In modern power systems, predicting the time when peak loads will occur is crucial for improving efficiency and minimising the possibility of network sections becoming overloaded. However, most works in the load forecasting field are not focusing on a dedicated peak time forecast and are not dealing with load data privacy. At the same time, developing methods for forecasting peak electricity usage that protect customers' data privacy is essential since it could encourage customers to share their energy usage data, leading to more data points for the effective management and planning of power grids. Hence, the authors employ a dedicated Learning to Rank XGBoost algorithm to forecast peak times with only ranks of loads instead of absolute load magnitudes as input data, thereby offering potential privacy‐preserving properties. We show that the presented Learning to Rank XGBoost model yields comparable results to a benchmark XGBoost load forecasting model. Additionally, we describe our extensive feature engineering process and a state‐of‐the‐art Bayesian hyperparameter optimisation for selecting model parameters, which leads to a significant improvement of forecasting accuracy. Our method was used in the context of the final round of the international BigDEAL load forecasting challenge 2022, where we consistently achieved high‐ranking results in the peak time track and an overall fourth rank in the peak load forecasting track with our general XGBoost model.

Nav Arbeidslivssenter bistår virksomheter som har utfordringer med sykefravær og arbeidsmiljø. Vi har studert hvordan arbeidslivssentrenes prosessbistand utformes, og hva slags læring den genererer. Datamaterialet består av intervjuer med ledere, tillitsvalgte/verneombud og IA-rådgivere i fem virksomheter. Prosessbistand handler om å kartlegge årsaker til sykefravær, tilføre kunnskap, identifisere bedriftstilpassede tiltak og støtte virksomheten i gjennomføringsprosessen. Å forstå utfordringene, finne egnete tiltak og skape et forebyggende arbeidsmiljø, framstår som utviklingsprosesser som må jobbes med over tid. Prosessbistanden ser ut til å kunne skape et «rom for læring» i virksomhetene med potensial for dypere læring/endring som varer også etter at bistanden er opphørt (såkalt «dobbellooplæring»).

In the study of employee performance management, this is an issue that requires important attention, where the performance of individual employees in the organization is part of organizational performance and can determine organizational performance. The increasing use of the internet among employees in various companies and agencies in Indonesia will certainly affect employee performance, both positively and negatively. This study aims to determine the effect of browsing and e-mail on employee work productivity at the Plantation and Animal Husbandry Service of Central Sulawesi Province. This study used a sample of 73 respondents and quantitative research type. Data collection techniques using questionnaires. Data analysis techniques using multiple linear regression tests. The results showed that variables browsing activities (X1) do not have a significant effect on employee performance and activity of sending emails (X2) has a positive effect on employee performance. If these two activities are examined simultaneously, it turns out that they have a significant effect on employee performance.

The current study proposed a novel simple and environmentally friendly approach for producing silver nanoparticles (AgNPs) using an extract of Moringa oleifera leaves (MOL) and optimizing the different experimental factors required for the formation and stability of AgNPs. The formation of nanoparticles was confirmed by a color change from yellow to reddish-brown with a surface plasmon resonance band at 412 nm. The morphology, size, and elemental composition of AgNPs were investigated by zeta potential dynamic light scattering, field emission scanning electron microscopy, energy dispersive X-ray, X-ray diffraction, and transmission electron microscopy analysis, which showed crystalline and spherical AgNPs. The identification of functional groups was supported by Fourier-transform infrared spectroscopy. The photocatalytic activities of AgNPs were assessed in the degradation of organic Malachite green (MG) dye in the aqueous solution. Two kinetic adsorption models, the pseudo-first-order model and the pseudo-second-order model, and three isotherm models, the Langmuir, Freundlich, and Temkin, were used to mathematically characterize the MG degradation process. The pseudo-second-order kinetics and the Freundlich isotherm model were found to be in good agreement with the experimental data. As a result of their synergistic interaction with the MOL extract solution, the photocatalytic activity of AgNPs increases and they can successfully adapt to the photodegradation of organic dyes in industrial effluents.

Access to clean and reliable water has become a critical concern due to the global water crisis. High sulfate levels in drinking water raise health concerns for humans and animals and can cause serious corrosion in industrial systems. Sulfated waters represent a major challenge on the Canadian prairies, leading to many cattle deaths. While reverse osmosis (RO) membranes effectively remove sulfates, they are costly due to high-pressure requirements. Nanofiltration (NF) membranes present a more affordable alternative, outperforming traditional methods like adsorption, desalination, and ion exchange. Developing low-pressure ultrafiltration (UF) and microfiltration (MF) membranes could also reduce costs. This review explores advancements in polymeric materials and membrane technology to enhance sulfate removal, focusing on methods used to reduce fouling and improve permeate flux. Techniques discussed include phase inversion (PI), thin-film composite (TFC), and thin-film nanocomposite (TFN) membranes. The review also highlights recent fabrication methods for pristine and nanomaterial-enhanced membranes, acknowledging both benefits and limitations. Continued innovations in polymer-based membranes are expected to drive further performance and cost-efficiency improvements. This review found that studies in the literature dealt mainly with sulfate concentrations below 2000 mg/L, indicating a need to address higher concentrations in future studies.