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Tine Bichel Lauritsen,1 Jan Maxwell Nørgaard,1 Kirsten Grønbæk,2– 4 Anders Pommer Vallentin,5 Syed Azhar Ahmad,6 Louise Hur Hannig,7 Marianne Tang Severinsen,8,9 Kasper Adelborg,10,11 Lene Sofie Granfeldt Østgård11,12 1Department of Hematology, Aarhus University Hospital, Aarhus, Denmark; 2Department of Hematology, Rigshospitalet, Copenhagen, Denmark; 3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark; 4Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; 5Zealand University Hospital, Roskilde, Denmark; 6Department of Hematology, Herlev Hospital, Herlev, Denmark; 7Department of Hematology, Vejle Hospital, Vejle, Denmark; 8Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark; 9Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; 10Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark; 11Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 12Department of Hematology, Odense University Hospital, Odense, DenmarkCorrespondence: Tine Bichel LauritsenDepartment of Hematology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, 8200 Email tinelaur@rm.dkBackground: The Danish Myelodysplastic Syndromes Database (DMDSD) comprises nearly all patients diagnosed with myelodysplastic syndromes (MDS) in Denmark since 2010. The DMDSD has not yet been used for epidemiological research and the quality of registered variables remains to be investigated.Objective: To describe characteristics of the patients registered in the DMDSD and to calculate predictive values and the proportion of missing values of registered data records.Methods: We performed a nationwide cross-sectional validation study of recorded disease and treatment data on MDS patients during 2010– 2019. Patient characteristics and the proportion of missing values were tabulated. A random sample of 12% was drawn to calculate predictive values with 95% confidence intervals (CIs) of 48 variables using information from medical records as a reference standard.Results: Overall, 2284 patients were identified (median age: 76 years, men 62%). Of these, 10% had therapy-related MDS, and 6% had an antecedent hematological disease. Hemoglobin level was less than 6.2 mmol/L for 59% of patients. Within the first two years of treatment, 59% received transfusions, 35% received erythropoiesis-stimulating agents, and 15% were treated with a hypomethylating agent. For the majority of variables (around 80%), there were no missing data. A total of 260 medical records were available for validation. The positive predictive value of the MDS diagnosis was 92% (95% CI: 88– 95). Predictive values ranged from 64% to 100% and exceeded 90% for 36 out of 48 variables. Stratification by year of diagnosis suggested that the positive predictive value of the MDS diagnosis improved from 88% before 2015 to 95% after.Conclusion: In this study, there was a high accuracy of recorded data and a low proportion of missing data. Thus, the DMDSD serves as a valuable data source for future epidemiological studies on MDS.Keywords: myelodysplastic syndromes, cohort, validation, accuracy, database

Sk Akhtar Ahmad,1 Manzurul Haque Khan,2 Mushfiqul Haque2 1Department of Occupational and Environmental Health, Bangladesh University of Health Sciences, Mirpur, Dhaka 1216, Bangladesh; 2Department of Occupational and Environmental Health, National Institute of Preventive Medicine, Mohakhali, Dhaka 1212, Bangladesh Abstract: Arsenic contamination of groundwater in Bangladesh has been recognized as a major public problem. The arsenic contamination was first identified in the tubewell water in 1993 in a northern district of Bangladesh. Tubewells are the main source of drinking water in rural areas, and except hilly and terrace upland throughout the Bangladesh, the arsenic-contaminated tubewells are distributed. Fifty million people of Bangladesh were estimated to be at risk of exposure to arsenic through consumption of water from contaminated tubewells. Chronic exposure to arsenic causes arsenicosis and may include multi-organ pathologies. Many of the health effects of chronic toxicity are evident in Bangladesh. Besides dermatological manifestations, noncommunicable diseases including cancer, adverse pregnancy outcomes, and decreased intelligence quotient among the children are reported to be increasing. Cancer due to long-term low-dose arsenic exposure through consumption of contaminated water is now an important concern of Bangladesh as it is being increasingly reported from arsenic-exposed individuals. Stoppage of consumption of the arsenic-contaminated water is the mainstay of arsenicosis prevention and case management. At present, a higher proportion of the people are still consuming arsenic-contaminated water because of the lack of sustainable arsenic-safe water supply. In providing sustainable arsenic-safe water options, any option advocated should be cheap, easy to use, locally maintainable, and owned by the community. In addressing arsenic-related health issues, arsenic-exposed population needs to be brought under the coverage of the regular surveillance program for detection and subsequent management of noncommunicable diseases and cancers. Keywords: arsenic, arsenic contamination, ground water, tubewell, arsenicosis, Bangladesh

Al-Qur`an mengungkapkan kisah-kisah umat terdahulu, baik sebagai ibrah, penukilan hukum dan penjelasan ketauhidan serta pengungkapan kisah yang sebenarnya. Namun pengungkapan al-Qur`an tentang kisah itu sangat sederhana, tidak sedetail kitab-kitab terdahulu karena al-Qur`an bukan kitab dongeng, melainkan kitab suci. Kisah tersebut disebut isrāīlīyāt. Penuturan isrāīlīyāt menjadi berkembang pesat setelah orang Yahudi dan Nasrani ba-nyak memeluk agama Islam, mereka banyak mengintrodusir pe-ngetahuan agama yang mereka anut sebelumnya ke dalam Islam (Tafsir al-Qur`an).Pada kurun atbā‘ al-tābi‘īn, merupakan puncak perkembangan isrāīlīyāt dalam mewarnai tafsir al-Qur`an. Peng-ungkapan isrāīlīyāt secara tidak selektif akan berdampak pada kemurnian ajaran Islam, aqidah umat Islam dan maksud yang ter-kandung dalam al-Qur`an. Para ulama berbeda pendapat dalam ke-bolehan mengisahkan isrāīlīyāt, antara yang melarang dan yang membolehkannya, yang kesemuanya demi menjaga kemurnian dari ajaran Islam (al-Qur`an).

Gunasekaran Baskaran,1 Shamala Salvamani,1 Siti Aqlima Ahmad,1 Noor Azmi Shaharuddin,1 Parveen Devi Pattiram,2 Mohd Yunus Shukor1 1Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, 2Department of Food Technology, Faculty of Food Science and Technology, Universiti Putra Malaysia, Selangor, Malaysia Abstract: The enzyme 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase is the key enzyme of the mevalonate pathway that produces cholesterol. Inhibition of HMG-CoA reductase reduces cholesterol biosynthesis in the liver. Synthetic drugs, statins, are commonly used for the treatment of hypercholesterolemia. Due to the side effects of statins, natural HMG-CoA reductase inhibitors of plant origin are needed. In this study, 25 medicinal plant methanol extracts were screened for anti-HMG-CoA reductase activity. Basella alba leaf extract showed the highest inhibitory effect at about 74%. Thus, B. alba was examined in order to investigate its phytochemical components. Gas chromatography with tandem mass spectrometry and reversed phase high-performance liquid chromatography analysis revealed the presence of phenol 2,6-bis(1,1-dimethylethyl), 1-heptatriacotanol, oleic acid, eicosyl ester, naringin, apigenin, luteolin, ascorbic acid, and a-tocopherol, which have been reported to possess antihypercholesterolemic effects. Further investigation of in vivo models should be performed in order to confirm its potential as an alternative treatment for hypercholesterolemia and related cardiovascular diseases. Keywords: HMG-CoA reductase, Basella alba, phytochemical, GC-MS/MS, RP-HPLC, hypercholesterolemia

Noor Kamal Al-Qazzaz,1,2 Sawal Hamid Ali,1 Siti Anom Ahmad,3 Shabiul Islam41Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia; 2Department of Biomedical Engineering, Al-Khwarizmi College of Engineering, Baghdad University, Baghdad, Iraq; 3Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia; 4Institute of Microengineering and Nanoelectronics (IMEN), UKM, Bangi, Selangor, MalaysiaAbstract: The early detection of poststroke dementia (PSD) is important for medical practitioners to customize patient treatment programs based on cognitive consequences and disease severity progression. The aim is to diagnose and detect brain degenerative disorders as early as possible to help stroke survivors obtain early treatment benefits before significant mental impairment occurs. Neuropsychological assessments are widely used to assess cognitive decline following a stroke diagnosis. This study reviews the function of the available neuropsychological assessments in the early detection of PSD, particularly vascular dementia (VaD). The review starts from cognitive impairment and dementia prevalence, followed by PSD types and the cognitive spectrum. Finally, the most usable neuropsychological assessments to detect VaD were identified. This study was performed through a PubMed and ScienceDirect database search spanning the last 10 years with the following keywords: “post-stroke”; “dementia”; “neuro-psychological”; and “assessments”. This study focuses on assessing VaD patients on the basis of their stroke risk factors and cognitive function within the first 3 months after stroke onset. The search strategy yielded 535 articles. After application of inclusion and exclusion criteria, only five articles were considered. A manual search was performed and yielded 14 articles. Twelve articles were included in the study design and seven articles were associated with early dementia detection. This review may provide a means to identify the role of neuropsychological assessments as early PSD detection tests.Keywords: poststroke dementia, vascular dementia, neuropsychological assessments, early dementia detection

Noor Kamal Al-Qazzaz,1,5 Sawal Hamid Ali,1 Siti Anom Ahmad,2 Shabiul Islam,3 Khairiyah Mohamad41Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia; 2Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia; 3Institute of Microengineering and Nanoelectronics (IMEN), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia; 4Neurology Unit, Department of Medicine, Universiti Kebangsaan Malaysia Medical Center, Cheras, Kuala Lumpur, Malaysia; 5Department of Biomedical Engineering, Al-Khwarizmi College of Engineering, Baghdad University, Baghdad, IraqAbstract: Cognitive impairment and memory dysfunction following stroke diagnosis are common symptoms that significantly affect the survivors’ quality of life. Stroke patients have a high potential to develop dementia within the first year of stroke onset. Currently, efforts are being exerted to assess stroke effects on the brain, particularly in the early stages. Numerous neuropsychological assessments are being used to evaluate and differentiate cognitive impairment and dementia following stroke. This article focuses on the role of available neuropsychological assessments in detection of dementia and memory loss after stroke. This review starts with stroke types and risk factors associated with dementia development, followed by a brief description of stroke diagnosis criteria and the effects of stroke on the brain that lead to cognitive impairment and end with memory loss. This review aims to combine available neuropsychological assessments to develop a post-stroke memory assessment (PSMA) scheme based on the most recognized and available studies. The proposed PSMA is expected to assess different types of memory functionalities that are related to different parts of the brain according to stroke location. An optimal therapeutic program that would help stroke patients enjoy additional years with higher quality of life is presented.Keywords: dementia, vascular dementia, memory, neuropsychological assessment

Leishmaniasis is one of the global health issues and is still being handled with costly and sometimes unsuccessful compounds having serious side effects, highlighting the importance of seeking new potent antileishmanial compounds. Herbal medicines have been considered as the main source of prevention and treatment for a wide variety of diseases as well as other photogenetic diseases over the last few centuries. The current study was designed to investigate the in vitro and in vivo antileishmanial efficacy of ethanolic and methanolic extracts of Berberis vulgaris root collected from Kurez region of District Orakzai, Khyber Pakhtunkhwa, Pakistan. Stationary growth-phase metacyclic promastigotes form of Leishmania tropica was incubated in vitro in methanolic and ethanolic extracts using amphotericin B as a positive control. The antileishmanial activity of B. vulgaris extracts was measured after the incubation period using methoxynitrosulfophenyl-tetrazolium carboxanilide assay. For the in vivo study, BALB/c mice were infected with metacyclic L. tropica promastigotes, and lesions appeared after 28 days of inoculum. The results of study research showed that B. vulgaris extract had a powerful antileishmanial activity on promastigotes of L. tropica at different concentrations (5, 10, 25, 50, and 75 μg/mL). The inhibition concentration 50 values for ethanolic and methanolic extracts of B. vulgaris were determined to be 15.37 and 17.55 μg/mL, respectively. In the in vivo activity, it was observed that B. vulgaris ethanolic extract at the concentration of 1.5 mg/kg decreased the lesion diameter in BALB/c infected mice. The ethanolic extract topically and orally reduced the lesion size 0.51 ± 0.023 and 0.56 ± 0.008 mm, while methanolic extract both topically and orally decrease the lesion diameter of 0.63 ± 0.008 and 0.68 ± 0.009 mm relatively, in comparison with negative control (1.45 ± 0.016 mm). Hematological parameters of mice including blood red blood cells, hematocrit, and hemoglobin in mice groups (infected non-treated) were found to be decreased, while the mice group treated with extract demonstrated nearly similar results to non-infected group. It is concluded from the current study that antileishmanial activity of B. vulgaris from Pakistan against L. tropica in both in vitro and in vivo showed a promising antileishmanial activity. This study might be helpful in the control strategies of cutaneous leishmaniasis caused by L. tropica.

Penyakit pada tanaman cabai dapat mengancam produktivitas dan kualitas hasil panen jika tidak terdeteksi dan diatasi secara tepat waktu. Untuk meningkatkan deteksi dini penyakit pada tanaman cabai, kami mengembangkan sistem klasifikasi menggunakan arsitektur VGG16, sebuah jaringan saraf konvolusional yang telah terbukti efektif dalam pengolahan gambar kompleks. Penelitian ini memanfaatkan dataset citra daun cabai yang terdiri dari beberapa kelas penyakit yang umum dijumpai, termasuk Healthy, Yellowish, whitefly, leafcurl dan leafspot. Citra-citra ini diolah dan dinormalisasi untuk pelatihan dan pengujian model. Arsitektur VGG16 digunakan sebagai model dasar, yang telah dipre-trained pada dataset ImageNet untuk meningkatkan kinerja klasifikasi. Proses pelatihan model dilakukan dengan memanfaatkan teknik transfer learning, di mana lapisan-lapisan akhir dari VGG16 disesuaikan dengan dataset penyakit daun cabai. Selama pengujian, sistem berhasil mengenali dan mengklasifikasikan penyakit pada daun cabai dengan tingkat akurasi yang tinggi. Hasil evaluasi menunjukkan bahwa arsitektur VGG16 mampu mengenali berbagai penyakit dengan akurasi rata-rata sebesar 0.9962%. sedangkan waktu komputasi yang dibutukan adalah 7 detik.

Abstract Wheat commands attention due to its significant impact on culture, nutrition, the economy, and the guarantee of food security. The anticipated rise in temperatures resulting from climate change is a key factor contributing to food insecurity, as it markedly reduces wheat harvests. Terminal heat stress mostly affects spike fertility in wheat, specifically influencing pollen fertility and anther morphology. This research especially focuses on the shape of anthers and examines the effects of heat stress. The DinoLite Microscope’s high-resolution images are used to measure the length and width of wheat anthers. By using object identification techniques, the research accurately measures the length and width of each anther in images, offering valuable insights into the differences between various wheat varieties. Furthermore, Deep Learning (DL) methodologies are utilized to enhance agriculture, specifically employing record categorization to advance plant breeding management. Given the ongoing challenges in agriculture, there is a belief that incorporating the latest technologies is crucial. The primary objective of this study is to explore how Deep Learning algorithms can be beneficial in categorizing agricultural records, particularly in monitoring and identifying variations in spring wheat germplasm. Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. LeNet demonstrates optimized accuracy in classifying the records, outperforming CNN by 52% and Inception-V3 by 70%. Moreover, Precision, Recall, and F1 Measure are utilized to ascertain accuracy levels. The investigation also enhances our comprehension of the distinct roles played by various genes in abiotic stress tolerance among diverse wheat varieties. The outcomes of the research hold the potential to transform agricultural practices by introducing a more effective, data-driven approach to plant breeding management.

Abstract Mental health is affected by tryptophane (TRP) metabolism regulation. Diet-influenced gut microbiome regulates TRP metabolism. Thus, the present study aimed to explore the relationship between type of dietary protein intake, gut microbiota, TRP metabolites homeostasis, and mental well-being in healthy women. 91 healthy females aged 18–50 were recruited based on the study protocol. Validate and reliable questionnaires assessed dietary intake and mental health. Biochemical tests and gut microbiota composition were analyzed following the manufacturer’s instructions for each enzyme-linked immune sorbent assay (ELISA) kit and Real-time quantitative polymerase chain reaction (qPCR) methods respectively. Regression methods were used to estimate the considered associations. The results show that in the fully adjusted model, plant protein consumption was partially inversely associated with depression risk (OR = 0.27; 95% CI: 0.06, 1.09; P = 0.06). Higher dietary animal protein intake was marginally associated with psychological distress (OR = 2.59; 95% CI: 0.91, 7.34; P = 0.07). KYN to serotonin ratio was inversely associated with animal protein consumption (ß = 1.10; 95% CI: -0.13, 2.33; P = 0.07). Firmicutes/Bacteriodetes ratio (β = -1.27 × 103, SE = 5.99 × 102, P = 0.03) was lower in the top tertile of plant protein. A partially negative correlation was found between dietary animal protein and Prevotella abundance (β = -9.20 × 1018, SE = 5.04 × 1018, P = 0.06). Overall, significant inverse associations were found between a diet high in plant protein with mental disorders, KYN levels, and Firmicutes to Bacteroidetes ratio while adhering to higher animal protein could predispose women to psychological stress.

Abstract Diabetes is a persistent health condition led by insufficient use or inappropriate use of insulin in the body. If left undetected, it can lead to further complications involving organ damage such as heart, lungs, and eyes. Timely detection of diabetes helps obtain the right medication, diet, and exercise plan to lead a healthy life. ML approach has been utilized to obtain rapid and reliable diabetes detection, however, existing approaches suffer from the use of limited datasets, lack of generalizability, and lower accuracy. This study proposes a novel feature extraction approach to overcome these limitations by using an ensemble of convolutional neural network (CNN) and long short-term memory (LSTM) models. Multiple datasets are combined to make a larger dataset for experiments and multiple features are utilized for investigating the efficacy of the proposed approach. Features from the extra tree classifier, CNN, and LSTM are also considered for comparison. Experimental results reveal the superb performance of CNN-LSTM-based features with random forest model obtaining a 0.99 accuracy score. This performance is further validated by comparison with existing approaches and k-fold cross-validation which shows the proposed approach provides robust results.

Ikan gabus (C. striata) merupakan salah satu komoditas jenis ikan air tawar yang hidup di daerah rawa-rawa maupun sungai yang memiliki nilai ekonomis tinggi dengan harga jual per centimeter dari panjang tubuhnya dan sangat bermanfaat dalam dunia medis dan industri. Ikan gabus memiliki kandungan nutrisi yang baik terutama albumin. Pertumbuhan ikan gabus sangat ditentukan oleh pakan agar dapat memaksimalkan pertumbuhan benih ikan gabus. Penelitian ini bertujuan untuk menganalisis tingkat pertumbuhan C. striata dengan pemberian pakan tambahan berupa Tubifex sp. Alat yang digunakan yaitu empat akuarium plastik dengan ukuran 40 x 30 x 30 cm, jangka sorong, timbangan digital, DO meter, TDS, dan pH meter. Bahan yang digunakan pada eksperimen yaitu air tawar, pelet ikan (PF 1000) diproduksi oleh prima feed, serta ikan gabus dan cacing sutra. Metode penelitian menggunakan Rancangan Acak Lengkap (RAL) dengan 4 perlakuan yaitu dosis P1 (pelet 100%), P2 (pelet 75% + cacing sutra 25%), P3 (pelet 50% + cacing sutra 50%), dan P4 (pelet 25% + cacing sutra 75%). Hasil penelitian menunjukkan bahwa penambahan cacing sutra memberikan pengaruh yang nyata terhadap pertambahan berat, panjang, dan lebar benih ikan gabus. Pertumbuhan terbaik diperoleh pada perlakuan P4 (pelet 25% + cacing sutra 75%) dengan panjang mutlak rata-rata 24,31±9,89 mm, lebar mutlak rata-rata 3,41±1,66 mm, dan berat mutlak rata-rata 18,28±6,40 g.

Abstract Trajectory mapping techniques have widespread applications in diverse fields, including robotics, localization, smart environments, gaming, and tracking systems. However, existing free devices encounter challenges in representing trajectories, thereby limiting the effectiveness of applications such as robotics, localization, and tracking systems. The imprecise mappings generated by these methods lead to suboptimal performance and unreliable results. The proposed approach leverages WiFi sensing through channel state information (CSI), triangulation techniques, and a fine-tuning mechanism to enhance trajectory precision within indoor environment trajectory mapping. The proposed solution employs a domain adapter fine-tuning technique to enable location-independent tracking via CSI, minimizing errors. The use of CSI MIMO signals for trajectory mapping offers enhanced spatial resolution, robust multipath handling, and improved accuracy in tracking movement by leveraging multiple antenna channels and exploiting the rich information embedded in signal reflections and scattering, while triangulation aids in accurately determining the location of objects or targets. Furthermore, incorporating a fine-tuning mechanism refines the generated trajectories. The findings demonstrate substantial enhancements in mapping precision, with an accuracy of 95.5% in tracking 13 paths within the new domain. These results underscore the effectiveness of the proposed approach in overcoming the limitations of existing methods and achieving highly accurate trajectory mapping.

The management of obstetric brachial plexus palsy (OBPP) can be challenging, particularly in neglected patients. We report the long-term results of the surgical management of a late-presenting adolescent girl with severe left shoulder and elbow flexor paralysis secondary to OBPP. She was subjected to staged shoulder and elbow reconstruction in the form of trapezius transfer and latissimus and teres major transfer to enhance shoulder abduction and lateral rotation, and flexor-pronator transfer to the anterior distal humerus to enhance elbow flexion. Flexor-pronator plasty was successful in restoring elbow flexion and function and maintaining joint stability in the long term in a patient with severe OBPP. This further consolidates its role as a feasible secondary reconstructive procedure in carefully selected patients with elbow flexor paralysis. Shoulder function improved less remarkably, yet it augmented the overall upper extremity function and correlated with pre-operative residual shoulder function. Fulfilling the candidacy for each surgical procedure is important to a successful outcome.

Abstract The emerging expanding scope of the Internet of Things (IoT) necessitates robust intrusion detection systems (IDS) to mitigate security risks effectively. However, existing approaches often struggle with adaptability to emerging threats and fail to account for IoT-specific complexities. To address these challenges, this study proposes a novel approach by hybridizing convolutional neural network (CNN) and gated recurrent unit (GRU) architectures tailored for IoT intrusion detection. This hybrid model excels in capturing intricate features and learning relational aspects crucial in IoT security. Moreover, we integrate the feature-weighted synthetic minority oversampling technique (FW-SMOTE) to handle imbalanced datasets, which commonly afflict intrusion detection tasks. Validation using the IoTID20 dataset, designed to emulate IoT environments, yields exceptional results with 99.60% accuracy in attack detection, surpassing existing benchmarks. Additionally, evaluation on the network domain dataset, UNSW-NB15, demonstrates robust performance with 99.16% accuracy, highlighting the model’s applicability across diverse datasets. This innovative approach not only addresses current limitations in IoT intrusion detection but also establishes new benchmarks in terms of accuracy and adaptability. The findings underscore its potential as a versatile and effective solution for safeguarding IoT ecosystems against evolving security threats.

Abstract Twitter’s trending topics enable users to view the topics currently being discussed on the platform. Users can stay up to date with news, events, and conversations. However, the platform’s method of sorting tweets by time can make it hard to gather semantic information. To fully comprehend the various dimensions of trends and the diverse opinions surrounding them, users need to sift through a substantial number of results. Traditional techniques for content summarization, such as multi-document summarization, can facilitate information aggregation, categorization, and visualization of events, but there are two challenges. First, they fail to consider the topic’s polarity, which is essential to covering all aspects of the subject and incorporating less popular opinions. Second, some techniques only provide summaries at the topic level, potentially leaving out crucial dimensions that require representation in this summary. This research developed a novel summarization approach on Twitter which is known as ARAbic Trending SUMmarization (AraTSum). The proposed system generates the summary based on the extracted topics and aspects from the trend. The approach involves a topic sentiment-based technique that combines generative statistical Latent Dirichlet Allocation with a pre-trained model to automatically reflect the sentiments (negative or positive) of tweets in each topic; followed by extractive summarization algorithms in each cluster. The AraTSum was evaluated through several experiments on five different X datasets. The obtained results showed that AraTSum outperformed existing approaches on the ROUGE evaluation metric compared to state-of-the-art Twitter event summarizing algorithms. To ensure a comprehensive and accurate evaluation, three human experts were tasked with manually summarizing the utilized five datasets. The results demonstrated that the proposed AraTSum method is dependent on sentiment topical aspect analysis, and it enhances the summarization's performance.

Objective To determine the effects of Dextrose 5% for maintenance and creep fluids on cumulative fluid balance (CFB) for septic shock concerning adult people.Design An open-label randomized clinical trial with a single center and parallel groups.Setting ICUs of a tertiary care academic medical center.Patients Adult individuals who have developed septic shock as described by the Sepsis 3 criteria.Interventions Dextrose 5% (n = 50) versus Saline 0.9% (n = 50) for maintenance and creep fluid for 72 hours.Main variables of interest The primary outcome measured was the CFB at 72 hours. Secondary outcomes assessed included mortality within 28 days, the number of days patients were free from (coma and delirium, ICU, mechanical ventilation, vasopressors), the occurrence of acute kidney injury, and disturbances in electrolyte levels.Results The CFB was significantly lower in Dextrose group vs Saline group (4.46 versus 6.75 L, median difference; −2.06 L; 95% CI, −2.63 to −1.35; p = P

Penelitian ini mengeksplorasi penerapan arsitektur deep learning berbasis transformer untuk mengidentifikasi emosi dari ulasan pelanggan e-commerce berbahasa Indonesia. Menggunakan dataset yang terdiri dari 5.400 ulasan pelanggan, model ini dirancang untuk mengklasifikasikan lima kategori emosi: Happy, Sadness, Anger, Love, dan Fear. Hasil analisis menunjukkan kecenderungan pelanggan untuk berbagi pengalaman positif dengan dominasi emosi Happy dalam ulasan. Model Transformer berhasil mencapai akurasi klasifikasi keseluruhan sebesar 77,2%, dengan efisiensi waktu pelatihan yang optimal sekitar 90 detik. Evaluasi performa menggunakan confusion matrix dan metrik presisi, recall, dan F1-score memberikan wawasan tentang keefektifan model dalam membedakan emosi kompleks. Temuan ini merefleksikan potensi pemanfaatan teknologi deep learning dalam meningkatkan pemahaman terhadap perilaku pelanggan dan mendukung pengembangan strategi bisnis yang responsif. Kata kunci: Transformer, Ulasan Pelanggan, Klasifikasi Emosi

Abstract Background Final infarct size (IS) after ST segment elevation myocardial infarction (STEMI) is a major predictor of mortality. Seeking early predictors for final IS can guide individualized therapeutic strategies for those recognized to be at higher risk. Results Eighty STEMI patients successfully treated with primary percutaneous coronary intervention (pPCI) underwent baseline (within 48 h) 2D, 3D echocardiography with speckle tracking and then underwent cardiac magnetic resonance (CMR) at 3 months to assess the final IS. After recruitment, 4 patients were excluded for uncontainable claustrophobia while 76 patients completed the final analysis. The mean ± standard deviation age was 54.1 ± 10.9 years, 84% were males, 25% had diabetes, 26% were hypertensives, 71% were current smokers, 82% had dyslipidemia, and 18% had a family history of premature coronary artery disease. By 3 months, CMR was performed to accurately evaluate the final IS. In univariate regression analysis, the admission heart rate, baseline and post-pPCI ST elevation, STEMI location (anterior vs. inferior), highest peri-procedural troponin, large thrombus burden, baseline thrombolysis in myocardial infarction flow grade, the final myocardial blush grade, the 2D and 3D left ventricular ejection fraction (LVEF), and the 2D and 3D global longitudinal strain (GLS) parameters were significant predictors for the final IS. In the multivariate regression analysis, four models were constructed and recognized the residual post-PCI ST segment elevation, the highest peri-procedural troponin, the 2D-LVEF, 3D-LVEF, and 2D-GLS as significant independent predictors for final IS. Conclusions In STEMI patients who underwent successful pPCI, early predictors for the final IS are vital to guide therapeutic decisions. The residual post-pPCI ST elevation, the highest peri-procedural troponin, and the baseline 2D-LVEF, 3D-LVEF, and 2D-GLS can be excellent and timely tools to predict the final IS.

Abstract Background Heart failure (HF) poses a major health problem, where frequent HF rehospitalizations (HFH) heavily burden national health systems. HFH are predominantly linked to inadequate decongestion before discharge. It is uncertain if systematic implementation of cardio-pulmonary ultra-sound imaging (CPUSI) to standard HF management can improve outcomes and reduce HFH. Results This study recruited 50 patients admitted with acute decompensated heart failure (ADHF). Besides the conventional daily assessment, CPUSI was systematically performed to guide treatment decisions, focusing on ventricular filling pressure and 8-zone lung ultrasound (LUS) score. On-admission and predischarge LUS scores were correlated to clinical outcomes. The mean age of the study group was 55.7 ± 10.59 years, with predominance of male gender. Supplementing clinical judgment, CPUSI modified therapeutic strategy in 57 out of 241 assessments (24%), improving patients’ care. Besides its value in guiding therapeutic decisions, the LUS score on admission had a significant positive correlation to the length of ICU stay and the total hospitalization length. Also, LUS score > 12 at discharge predicted 90-day HFH with sensitivity and specificity of 100% and 98%, respectively. Conclusions Systematic CPUSI can improve HF management by complementing the often challenging judgment of pulmonary congestion. Adding periodic evaluation of ventricular filling pressures and LUS scores to clinical assessment can optimize treatment decisions and improve patient care. LUS score was a significant predictor for in-hospital and post-discharge clinical outcomes. Graphical abstract

This study aims to find out how the development of the Curriculum 2013 SIT (Integrated Islamic School), and the typical 8th grade curriculum at SMPIT Al Uswah Bangil. This research is qualitative descriptive field research, the data collection techniques used are interviews, observations, and documentation using Miles and Huberman data analysis techniques, namely data reduction, data presentation, and drawing conclusions. The results showed that curriculum development at SMPIT Al Uswah Bangil was developed in all school curricular activities, namely intracurricular, co-curricular and extracurricular activities. SMPIT Al Uswah Bangil also uses the concept of Islamization of science, and the implementation of evaluation is carried out in the form of curriculum supervision techniques.

Abstract Introduction Non-nursing tasks (NNTs) have become a prevalent issue among healthcare professionals, affecting nurses globally. This study delves into the experiences of Jordanian nurses regarding NNTs, aiming to uncover challenges and propose solutions within the Jordanian healthcare context. Objective Explore the impact of NNTs on Jordanian nurses’ roles, workload, and satisfaction. Additionally, the study aims to identify various types of NNTs performed by nurses, understand their impact, and propose solutions to mitigate challenges associated with these tasks. Methods A qualitative-exploratory research design was employed for this study. Semi-structured interviews were conducted with Jordanian nurses using a purposeful sampling approach to ensure a diverse representation of experiences and perspectives. Thematic analysis was used to identify recurring themes and patterns related to NNTs, their challenges, and potential solutions. Ethical guidelines were strictly followed to maintain participant confidentiality and ensure the integrity of the data collected. Results Analysis of the interviews revealed four major themes: challenges of NNTs, types of NNTs, impact of NNTs, and proposed solutions. Nurses faced significant difficulties due to task ambiguity, role confusion, and increased workload from NNTs, which included administrative duties, clerical work, and tasks typically performed by other healthcare professionals. These NNTs negatively impacted nurses’ effectiveness, productivity, and job satisfaction by diverting time and energy from primary nursing responsibilities, causing professional strain. To address these issues, participants suggested clearer job descriptions, stricter task assignment protocols, and systemic changes to tackle the root causes of NNTs. Conclusion This study sheds light on the pervasive challenges posed by NNTs among Jordanian nurses and emphasizes the importance of addressing these issues to enhance nursing care quality and nurse well-being. By proposing actionable solutions tailored to the Jordanian context, this research contributes to the global discourse on NNTs and underscores the need for organizational support and advocacy to optimize nurses’ roles and improve patient care outcomes.

Abstract Background Cucumber plants are susceptible to several economically damaging pests, including whiteflies, aphids, thrips and spider mites. This study aimed to evaluate the efficacy of two biological control programs, utilizing different releases of bio-agents, in comparison with chemical control method. The bio-agents used were the aphid parasitoid Aphelinus albipodus Hayat and Fatima (Hymenoptera: Aphelinidae), the green lacewing Chrysoperla carnea (Steph.) (Neuroptera: Chrysopidae) and the predatory mite Phytoseiulus persimilis Athias-Henriot (Acari: Phytoseiidae) in two release rates; low and high. Additionally, a chemical pesticides treatment was included for comparison in managing the pests in cucumber greenhouses during the winter seasons of 2022 and 2023, in Egypt. Abundances of whitefly, aphids, thrips and spider mites were recorded weekly throughout the study. Results The aphid population in the greenhouse with high release rate (BIO 2) showed the highest reduction, with percentages of 84.55 and 89.88% in 2022 and 2023, respectively. Both greenhouse with low release rate (BIO 1) and BIO 2 exhibited significant reductions in the whitefly population, with proportions of 71.31 and 72.01% in 2022, and 82.05 and 85.94% in 2023, respectively. The thrips population also experienced notable reductions in both BIO 1 and BIO 2 greenhouses, with percentages of 72.08 and 75.71% in 2022, and 59.93 and 61.38% in 2023, respectively. However, the pesticide treatment demonstrated the lowest reduction in populations of aphids, whitefly and thrips in both seasons. Nevertheless, in all treatments in the two evaluated seasons, the high release rate of the predatory mite, P. persimilis (15 individuals/m2), proved to be highly effective in maintaining the mite populations below the economic threshold level. However, the population density of the two-spotted spider mite, Tetranychus urticae Koch. (Acari: Tetranychidae), increased in the pesticide-treated greenhouse, indicating the development of resistance to pesticides. Although the tested programs resulted in similar yields, the biological control approach offered the advantage of pesticide-free produce and reduced production costs. Conclusion For pest management in cucumber growing in greenhouses during winter, it is recommended to use biological control agents at a low release rate at the early occurrence of pests. This approach can help minimize pest populations effectively.

Gamma secretase (GS) is an intramembranous enzyme that acts on the amyloid precursor protein and Notch inside lipid membranes. The enzyme is responsible for amyloid-β propagation, one of the well-known causes of Alzheimer's disease. However, the effects of lipids on GS activity and structural dynamics are unknown. Therefore, in this study, we performed coarse-grained molecular dynamics simulations to probe the effects of five individual lipids on GS. These lipids included 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1,2-dipalmitoyl-sn-phosphatidylcholine (DOPC), 2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC). These lipids are structurally characterized by different heads (i.e., NH3 [PE] for POPE vs. NC3 [PC] for POPC), number of double bonds (one for POPC vs. two for DOPC), and alkyl tail chain lengths (16:1/18:1 for DOPC vs. 14:0/14:0 for DMPC vs. 12:0/12:0 for DLPC). This indicates distinct microenvironments and adjustable structural elements for catalytic function when GS is embedded. Our results revealed that the presence of more unsaturated bonds in DOPC than in POPC resulted in greater GS stability. Moreover, lipids with short alkyl tail chains or with PC heads instead of PE heads had improved mobility of the sixth transmembrane helix of GS, which is responsible for the considerable active site flexibility and presenilin 1 subunit plasticity. The length of the DMPC alkyl tail chain was between that of DOPC and DLPC because the up-down and cross-correlation motions of GS in DMPC was the lowest among the three lipids, and GS mobility in DMPC was the lowest among all five lipids. This may be because the alkyl tail chain length (i.e., 3. 8 nm thickness of the DMPC bilayer) was suitable for GS embedding, thereby restraining more GS motions than that of the long (DOPC) or short lipids (DLPC). Collectively, these results indicated that GS activity can be modulated through changes in conformational fluctuations, structural perturbations, molecular motion, and cross-correlation motion when embedded in different lipids. Exploration of such fundamental information can reveal the possible mechanisms by which GS is affected by individual lipid species.

Abstract Background Ovarian cancer has the worst prognosis among all gynaecological cancers. The pre-operative and intraoperative diagnosis of ovarian tumours is imperative to ensure the right operation is performed and to improve patients’ outcomes. Methodology A retrospective review of cases with a confirmed histological diagnosis of ovarian cases was undertaken from January 2017 to December 2021. Comparison was undertaken between this final diagnosis and the pre-operative ultrasound, MRI and frozen section (FS) to assess diagnostic accuracy of each. In the ultrasound cases, the level of the examiner was collected. Statistical analysis was performed using Stata MP v17.0 software (USA, 2023). Results In total, 156 ovarian masses were examined by FS. In the histopathological examination, 123/156 of these tumours were epithelial tumours. Pre-operative US subjective impression was made in 63/156 cases and preoperative MRI subjective impression was made in 129/156 cases. For benign, borderline and malignant tumours, FS demonstrated a sensitivity of 90.8% (95%CI:81.9–96.2), 86.8% (95%CI:71.9–95.6) and 97.6% (95%CI:87.4–99.9) respectively. Ultrasound’s sensitivities were 95.2% (95%CI:76.2–99.9), 20% (95%:4.33–48.1), 57.1% (95%CI:28.9–82.3) and MRI’s sensitivities were 100% (95%CI:80.5–100), 31.5% (95%CI:19.5–45.6) and 63.2% (95%CI:46–78.2) respectively. Conclusions FS remains an accurate tool for diagnosing ovarian malignancy. However, across both imaging modalities and FS, the diagnosis of borderline ovarian tumours remains challenging.

Abstract Most high‐gain step‐up dc‐dc structures operate with a limited duty cycle and suffer from a high component count, limiting their application. This paper addresses these problems by proposing a new step‐up dc‐dc converter that provides a high conversion ratio with few elements. Two coupled inductors are used instead of conventional voltage multiplier cells to improve the gain without excessive components. The topology includes one switch whose duty cycle is not limited and can vary between zero and one according to the output voltage condition. It has been placed on the low‐voltage side of the converter that encounters low‐voltage stress. It is selected from low‐voltage rating switches with small on‐resistance, which reduces the conduction loss of the switch and improves the efficiency. High boost factor, high efficiency, reasonable component counts, improved gain‐to‐element ratio, and low voltage stress on the switch distinguishe the converter from their counterparts. The topology also benefits from the common‐ground feature. However, its input current waveform is pulsating. This article describes the theory and operation principle of the topology in detail. Experimental results are represented to evaluate the converter's performance and operation. In this case, a 240 W prototype has been designed and fabricated. Results confirm the above claims.

This article aims to analyze the symbolic communication of adherents of the Tariqah Qadiriyah wa Naqsyabandiyah Khathibiyah in Sambas. The paradigm in this study is interpretive with a sociological approach. The method used is phenomenology. Data collection was conducted from March to June 2023. Data were collected by conducting observations, interviews, and documentation. The informants in this study totaled 13 people using the snowball sampling technique. The data obtained were analyzed using qualitative analysis procedures: data reduction, data display, and conclusion. This study found that the symbolic communication of adherents of the Tariqah Qadiriyah wa Naqsabandiyah Khathibiyah Sambas is not formed by itself but through an interrelated process between the meaning of the adherents of the tariqah, the formation of self-concept, and represented in communication patterns. The process is initiated from the adherent's interpretation of the doctrines of the tariqah to form the adherent's self-concept. Then, the self-concept has implications for adherents' behavior and social interactions. Based on the findings, it is concluded that the symbolic communication that occurs among adherents is an implication and symbolic representation of the doctrines and spirituality experiences of adherents of the Tariqah Qadiriyah wa Naqsabandiyah Khathibiyah Sambas. Keywords: Symbolic Communication; Tariqah Qadiriyah wa Naqsabandiyah; Sambas

This research introduces an innovative methodology for evaluating and predicting soundboard quality in the intricate craftsmanship of sape instruments. Despite the sape’s profound cultural significance, the process of selecting soundboard wood has been inadequately explored, resulting in uncertainties within the crafting community. Addressing this research gap, this study integrates advanced machine learning techniques and devises a specialized Graphical User Interface (GUI) tailored for sape makers. The methodology encompasses a thorough acoustic analysis of three distinct hardwoods—adau, merbau, and tapang—employing machine learning classification through Support Vector Machine with a Gaussian kernel. The study culminates in the development of a user-friendly GUI for soundboard quality assessment. Results underscore the model’s proficiency for achieving an optimized accuracy of 87.8% in classifying sape audio samples. The MATLAB App Designer-based GUI streamlines the evaluation process, offering a practical and accessible tool for craftsmen. This integrated approach, harmonizing traditional craftsmanship with cutting-edge technology, holds the potential to revolutionize sape instrument manufacturing, ensuring the preservation and progressive evolution of this rich cultural heritage.

Artikel ini dilatarbelakangi adanya degradasi moral yang disebabkan adanya banyak perbedaan yang justru tidak menjadi media persatuan namun menjadi celah adanya Iftiraq. Perpecahan ini secara urgen dan mendesak perlu untuk segera diatasi dengan metode dan cara yang sudah teruji untuk kemudian dapat diaktualisasikan di kehidupan. KH. Hasyim Asy’ari dalam kitab Al-Tibyan menawarkan usaha rekonsiliasi Nasional yang dalam penelitian ini dipaparkan kandungan dan nilai yang tersimpan. Penulis menggunakan metode Library Research dengan memanfaatkan beberapa sumber pustaka yang valid. Dalam penelitian ini penulis setidaknya menemukan tiga hasil temuan. Pertama, terdapat nilai persaudaraan yang kuat menjadi tonggak rekonsiliasi Nasional dalam kitab Al-Tibyan. Kedua, dalam kitab Al-Tibyan nilai persatuan dan perdamaian menjadi orientasi pokok terhadap usaha rekonsiliasi Nasional KH. Hasyim Asy’ari. Ketiga, aktualisasi nilai persaudaraan dan persatuan serta perdamaian secara aktif dan dinamis dapat diimplementasikan dengan pendekatan zaman kekinian salah satunya memanfaatkan dunia digitalisasi. Ketiga nilai rekonsiliasi dalam kitab ini dapat diaktualisasikan artinya kitab ini masih relevan dengan zaman dan problematika kekinian.

Abstract State estimation stands as one of the most crucial applications in energy management systems of control centres, ensuring the secure operation of the power system. The real‐time availability of accurate system variables, including voltages, currents, and power flows, presents an excellent opportunity to consider the actual network characteristics, including imbalances. This paper presents a linear and non‐iterative method to solve the three‐phase state estimation problem in transmission systems with unbalanced loading. The method utilises supervisory control and data acquisition measurements obtained from remote terminal units. The formulation is based on complex variables derived from traditional supervisory control and data acquisition measurements, with assumptions made regarding the availability of certain three‐phase bus voltages, as well as a number of three‐phase currents and active and reactive power flows. The proposed algorithm employs the classical weighted least squares technique for solving the three‐phase state estimation problem. Due to its straightforward and linear nature, the method ensures no convergence issues. To validate its effectiveness, the proposed method is validated on a three‐bus network and the IEEE 39‐bus network simulated using the three‐phase model within the DIgSILENT Power Factory environment.

Abstract Background The historical use of Laurus nobilis L., the plant is native to the Mediterranean region and has been cultivated for its aromatic leaves, which are used as a flavoring agent in cooking and for their potential therapeutic properties. Methods The purpose of the current investigation was to characterize the essential oil composition of the fresh L. nobilis leaves from Palestine by using the gas chromatography-mass spectrometry (GC-MS) technique. DPPH (2,2-diphenyl-1-picrylhydrazyl), p-nitrophenyl butyrate, and 3,5-dinitro salicylic acid (DNSA) methods were employed to estimate the antioxidant, antiobesity, and antidiabetic effects of the essential oil. While MTS assay were used to evaluate their antiproliferative activities on panels of cell lines. Moreover, the docking studies were aided by the Prime MM GBSA method for estimating binding affinities. Results The GC-MS investigation demonstrated that the fresh L. nobilis leaves essential oil has a variety of chemicals, about 31 different biochemicals were identified, and the major compounds were 1,8-cineole (48.54 ± 0.91%), terpinyl acetate (13.46 ± 0.34%), and α-terpinyl (3.84 ± 0.35%). Furthermore, the investigated oil demonstrated broad-spectrum antimicrobial activity against all tested bacterial and candidal strains and significantly inhibited the growth of MCF-7 cancerous cells more than the chemotherapeutic drug Doxorubicin. Furthermore, it contains robust DPPH free radicals, as well as porcine pancreatic α-amylase and lipase enzymes. Using the 1,8-cineole compound as the predominant biomolecule found in the L. nobilis essential oil, molecular docking studies were performed to confirm these observed fabulous results. The molecular docking simulations proposed that these recorded biological activities almost emanated from its high ability to form strong and effective hydrophobic interactions, this led to the getting of optimal fitting and interaction patterns within the binding sites of the applied crystallographic protein targets. Conclusion The results of these experiments showed that the fresh L. nobilis leaves essential oil has outstanding pharmacological capabilities, making this oil a potential source of natural medications.

Alkylating agents such as N-Ethyl-N-Nitrosourea (ENU) are ubiquitous within living cells and in the environment. This study designed to evaluate the chemopreventive activity of vanillic acid on ENU-induced toxicity and carcinogenesis in mice as an animal model of chronic lymphocytic leukemia (CLL). The female, Swiss albino mice were divided into three groups each with 7 mice, group I received normal saline, group II, mice received ENU at a dose of 80 mg/kg body weight i.p. to induce CLL on the 31th day of the study, and group III, the mice pretreated with vanillic acid at a dose of 20 mg/kg body weight/day, i.p. up to 30 days and received ENU. The animals were monitored for weight changes and mortality during 120 days, and then were sacrificed for isolation of lymphocytes, as target cells in CLL. Cellular parameters like reactive oxygen species (ROS) formation, malondialdehyde (MDA) production, depletion of glutathione (GSH), mitochondrial membrane potential (MMP) and lysosomal membrane integrity were studied. We found that pretreatment with vanillic acid significantly increased the survival of mice up to 57%, delay in death time (30%) and prevented weight changes after exposure to ENU. In addition, it was found that vanillic acid protected ROS formation, lipid peroxidation mitochondrial dysfunction, and lysosomal membrane destabilization in isolated lymphocytes. These data suggest that vanillic acid exhibited significant protection against ENU-induced toxicity and carcinogenicity, which might be related to the protection of the mitochondria and lysosomes and the reduction of ROS formation and oxidative stress.

Clinical genomic profiling of cell-free nucleic acids (e.g. cell-free DNA or cfDNA) from blood and other body fluids has ushered in a new era in non-invasive diagnostics and treatment monitoring strategies for health conditions and diseases such as cancer. Genomic analysis of cfDNAs not only identifies disease-associated mutations, but emerging findings suggest that structural, topological, and fragmentation characteristics of cfDNAs reveal crucial information about the location of source tissues, their epigenomes, and other clinically relevant characteristics, leading to the burgeoning field of fragmentomics. The field has seen rapid developments in computational and genomics methodologies for conducting large-scale studies on health conditions and diseases – that have led to fundamental, mechanistic discoveries as well as translational applications. Several recent studies have shown the clinical utilities of the cfDNA fragmentomics technique which has the potential to be effective for early disease diagnosis, determining treatment outcomes, and risk-free continuous patient monitoring in a non-invasive manner. In this article, we outline recent developments in computational genomic methodologies and analysis strategies, as well as the emerging insights from cfNA fragmentomics. We conclude by highlighting the current challenges and opportunities.

This study focuses on the comprehensive exploration of Swat soapstone, employing a range of analytical techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and X-ray fluorescence (XRF) spectroscopy. XRD was used to identify the phase and lattice parameters of the soapstone. SEM further scrutinizes the dispersed soapstone particles, revealing different structural characteristics such as a slightly elongated, cubic-like structure, a straight rod-like formation, and a rough, textured surface. EDX spectroscopy was utilized for studying the elemental composition of the soapstone. The analysis identifies talc as the primary mineral in Swat soapstone, with iron, an element, also contributing notably to its composition. This underscores the complexity of Swat soapstone’s internal structure. XRF analysis further contributes to the elemental characterization, revealing a dominant composition of silicon (Si) at 48.567 wt% and a notable contribution from iron (Fe) at 16.108 wt%. FTIR analysis confirmed the absorption of infrared radiation at the non-bridging oxygen (Si–O–) within the silicate network and the Si–O–Si bending vibration. This work investigates the chemical and morphological details of the Swat soapstone.

This study explores factors influencing entrepreneurial development among women microentrepreneurs in Malaysia. Using self-administered questionnaires distributed to 50 participants, the research examined four key factors: family support, business prospects, sociocultural factors, and government support, with entrepreneurial development as the dependent variable and perception of success as a mediator. The data was analyzed using SmartPLS software. Results indicated that most variables had reliable Cronbach Alpha values, though issues with discriminant validity were found. The structural model showed substantial explanatory power, and most path coefficients indicated positive relationships, except for the link between government support and entrepreneurial development. However, only one hypothesis was accepted, revealing that socio-cultural factors significantly influence entrepreneurial development through the perception of success. The study suggests that future research should focus on specific sectors within microenterprises and include a larger sample size for a broader understanding of women’s economic contributions. This research provides valuable insights for policymakers aiming to enhance support for women microentrepreneurs in Malaysia.

Key Clinical Message In cases of primary hyperaldosteronism, the aldosterone renin ratio (ARR) is crucial for determining the need for adrenal vein sampling (AVS). Our case highlights the importance of utilizing ARR with AVS, contextual interpretation of plasma renin and aldosterone levels, and stresses that sole reliance on imaging without AVS may result in unnecessary or contralateral adrenalectomy.

This paper examines the environmental impacts of Li-NMC batteries throughout their life cycle using life cycle assessment with OpenLCA software V1.11.0 and data from the Ecoinvent database and manufacturers. Results show that the most significant environmental impact occurs during battery mining and production phase (76.93 %), followed by battery use phase (17.13 %), and battery pyrometallurgical recycling (2.32 %). The battery mining and production phase is also the most energy-intensive (67.76 %), followed by battery pyrometallurgical recycling (23.27 %) and hydrometallurgical processes (8.023 %). The battery carbon footprint is calculated at 189.357 kg CO2-eq/kWh, with manufacturing and mining phases dominating energy consumption (67.76 %). The battery estimated cost payback period is approximately 5.7 years when the calculations were done using the banks' tariff and about 9 years when the hotel's tariff was applied, while for household usage, the cost payback period was estimated to be 17.5 years.

Islamic liberation theology emphasizes the importance of man's role as a caliph, who is God's representation on earth. This research seeks to understand the paradigm of human responsibility as a caliph in Islamic liberation. The method used in this research is a literature study. Data collection techniques used in this research were obtained from books, academic journals, the Qur'an and other articles relevant to the research problem. The data analysis technique used is the analysis and interpretation of the data obtained. The results of the study explain that the responsibility of human 'Khalifah' in liberation is very large; as a representation of God who is given the ability to think, humans are explained to be emancipatory entities over the chaotic condition of the earth. Realizing liberation in Islam is explained as a form of unity with God; divine affairs are not only matters of transcendental worship but also relate to harmony of human relations with other humans and also nature, and ultimately with liberation as a form of implementing God's orders. Islam explains the importance of liberation with the presence of the Qur'an, which is taught to liberate man from his condition.

Kegiatan pertanian di Kelurahan Bukit Tunggal menghasilkan sisa sayur dan buah yang belum dimanfaatkan secara optimal. Biasanya sisa-sisa tersebut hanya dibiarkan membusuk ditumpuk di suatu tempat. Tim memandang permasalahan ini harus diselesaikan, supaya tidak menambah dampak buruk pada lingkungan dengan adanya gas metana. Oleh sebab itu, tim memberikan pelatihan dan pendampingan kelompok tani dalam mengolah limbah pertanian menjadi ekoenzim. Metode yang tim gunakan dalam pelaksanaan kegiatan PkM mengacu pada 4 tahapan yaitu persiapan, sosialisasi program, pelatihan dan pendampingan, serta evaluasi. Hasil kegiatan pelatihan dan pendampingan menunjukkan antusiasme 35 peserta yang berasal dari seluruh kelompok tani di kelurahan Jekan Raya. Kegiatan ini dipandang berhasil dengan tolak ukur pre test dan post tes yang tim lakukan. Hanya terdapat 25% peserta pelatihan yang mengetahui ekoenzim pada saat prestes, namun setelah kegiatan pelatihan pemahaman peserta meningkat menjadi 90% terhadap pembuatan ekoenzim.

In solid-state welding, the basis of joining is the combination of materials in the weld area using the tool. The tool pin is a key parameter that can facilitate tool penetration into the parts and result in better material mixing. On the other hand, the presence of the end cavity of the process can be a factor in reducing the mechanical properties of the weld. To address these two conflicting issues, this study examined the effect of pin thickness on the mechanical and metallurgical properties of aluminum 6061 and 5052 plates. The variable parameters included pin diameters (4 mm, 8 mm, and no pin) and three tool penetration depths (0.5 mm, 1.5 mm, and 2.5 mm). The impact of changing the arrangement of the plates on each other was also investigated regarding the properties and quality. Experimental results showed that decreasing the pin diameter and increasing the tool penetration depth improved the weld breakage force. The failure modes of all welds were button pull-out and ductile failure. Using a pinless tool increased microhardness in the weld nugget area and led to more uniform microhardness variations. Placing the aluminum 6061 alloy on top of the arrangement improved shear tensile strength and microhardness of the joints. The microstructure in the heat-affected zone showed an increase in grain size, which was accompanied by a decrease in microhardness. The microstructure in the stirred zone was dense and compacted, and with increasing tool penetration depth and decreasing pin diameter, the grain size became finer.

Through an analysis of Islamic jurisprudence, ethics, and theological frameworks, the research identifies key considerations and implications for Islamic broadcasters engaging with social media platforms. The study employed a qualitative approach, drawing upon Islamic texts, scholarly literature, and interviews with Islamic broadcasters. Analysis focused on identifying theological principles relevant to social media engagement and examining strategies used by broadcasters to navigate digital communication landscapes. One significant finding is the tension between the imperative to disseminate Islamic teachings widely and the need to maintain theological integrity in online interactions. The study highlights the nuanced approaches taken by Islamic broadcasters to navigate this tension, emphasizing the importance of upholding Islamic values such as tawhid (monotheism) and adab (etiquette) while leveraging the reach and accessibility of social media. Overall, the findings underscore the necessity for a theological re-evaluation of Islamic broadcasting practices in the digital age. By synthesizing traditional Islamic teachings, which refer to the principles, beliefs, and practices that have been passed down in Islam since the time of the Prophet Muhammad SAW and his companions, with contemporary digital realities, this research advocates for an approach that balances the imperative of outreach with the necessity of maintaining theological integrity. It concludes by emphasizing the importance of aligning digital practices with core Islamic values to ensure ethical and responsible engagement with social media platforms.

This work investigated the effect of hybridization of flax fabric (FF) with carbon/Kevlar fabric (CK) on the flexural, dynamic mechanical analysis and high velocity impact. Hand lay-up technique was used to fabricated different ratio of flax to carbon/Kevlar hybrid composites, which were hot-pressed and then cured. It was revealed that increase in ratio of CK has improved the flexural properties, storage modulus, loss modulus, energy absorption and ballistic limit of the composites. Interestingly, hybrid composite with ratio 25:75(FF:CK) has highest flexural properties, storage modulus and loss modulus among the other composites. The cole-cole plot and damping factor reveals that hybrid composite with ratio 25:75(FF:CK) has the strongest fibre/matrix adhesion. The hybrid composite with ratio 25:75 (FF:CK) displayed the highest Tg. Based on high velocity impact test, it was shown that there is not much different in energy absorption and ballistic of the hybrid composites compared to plain CK composite. FF/CK hybrid composites have the potential to be used in high performance application such as ballistic helmet.

The purpose of this study is to investigate the chemical treatment impact on Washingtonia filifera (WF) fibers using sodium bicarbonate (10% NaHCO3) for varying durations (24, 48, 72, 120, and 168 h) on the physical and mechanical characteristics of polylactic acid (PLA)/WF-biochar/biomass hybrid biocomposites. Differential scanning calorimetry, thermogravimetric analysis, and Fourier transform infrared spectroscopy were employed to examine the temperature effect on the mineralogical composition of treated and raw WF fibers and monitor their thermal behavior. The produced biocomposites' tensile, impact, flexural, and morphological characteristics were evaluated. The results demonstrate that chemical treatments improve matrix-fiber adhesion and remove impurities from the fiber surface. Hybrid biocomposites of PLA biopolymers manufactured from biochar and WF fibers given a sodium bicarbonate treatment for 72 h exhibit improved mechanical properties, such as elasticity modulus and strength under tensile and flexural forces. Consequently, these new hybrid biocomposites can be used in various structural and non-structural products, such as car interiors, new 3D printer filament, biomedical equipment and materials, sports equipment, food packaging.