Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel PolyPropylene–Sargassum Particles Composites: Evaluation of Thermal and Thermomechanical Properties

Sargassum is a type of marine algae that has caused environmental problems in Mexico because it arrives in high quantities along the Mexican coast, especially in the Mexican Caribbean. This situation has become an environmental and economic problem, impacting tourism and other activities. As a result, it is reasonable to try to find an application for these algae. Recently, some applications in civil construction, cosmetics, and the food industry, among others, have been reported. The present work evaluates the thermal and structural properties of new polypropylene (PP)–Sargassum-based composites. Also, the effect of adding calcium stearate (CS) to increase the interaction between PP and Sargassum particles was investigated. PP–Sargassum particle composites were prepared by a melt mixing process, and the properties of these composites were evaluated using thermal techniques such as dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and infrared spectroscopy (FTIR). The DMA results showed that composites with low concentrations of Sargassum particles perform better than those with higher concentrations. When CS was added to composites, there was a significant improvement in storage modulus compared with composites without CS. This was attributed to the good adhesion of the particles to the matrix because the mobility of macromolecules increased in the presence of CS. The thermal stability of PP–Sargassum particle composites decreases when the amount of particles increases, and the addition of CS does not positively affect the thermal behavior of composites. The findings open the possibility of using Sargassum particles in new applications of these algae as a polymer additive to generate sustainable materials.
Investigation of structural properties and antibacterial activity of AgO nanoparticle extract from Solanum nigrum/Mentha leaf extracts by green synthesis method

Abstract Solanum nigrum and Mentha leaf extracts were used as reducing and stabilizing reagents in the green synthesis of silver oxide nanoparticles (AgO NPs), and their antibacterial efficacy was subsequently evaluated. The structure and morphology of AgO NPs were evaluated using X-ray diffraction and filed emission scanning electron microscope. High-resolution transmission electron microscopy images were used to analyze the characteristics of certain particles with clearly discernible atomic structures. The functional group and elemental composition of AgO NPs were investigated using fourier transform infrared spectroscopy and energy dispersive X-ray spectroscopy. Ultraviolet–visible spectroscopy was used to determine the energy band gap (E g) of the sample. The dielectric constant of both samples was found to be inversely proportional to frequency, whereas the dielectric loss was found to be directly proportional to temperature but directly proportional to frequency. This suggests that the space charge has an effect on the mechanism of charge transfer as well as polarizability. AC conductivity rises and is inversely proportional to temperature increases. AgO NPs had a size range of around 56 nm and were mostly spherical. The antibacterial potential of the synthesized AgO NPs using both extracts was compared by the well-diffusion method. AgO NPs at 50–100 µg·mL−1 concentration significantly inhibited the bacterial growth of Bacillus cereus, Staphylococcus aureus, Escherichia coli, and Klebsiella pneumonia.
Analisis Sentimen Respons Twitter terhadap Persyaratan Badan Penyelenggara Jaminan Sosial (BPJS) di Kantor Pertanahan

The Indonesian government has issued a policy regarding applications for registration services for the transfer of land rights or ownership rights to apartment units because buying and selling must be accompanied by a photocopy of the BPJS Health participant card. This policy has given rise to various kinds of public opinion, including that of internet residents (netizens) on Twitter and social media. This research aims to determine netizens' responses to this policy. This research uses quantitative methods. Crawling and data analysis use the Python programming language or lexicon-based method with the program execution time before August 19, 2023. The research results show that as many as 57.7% of Twitter users' opinions responded positively to BPJS requirements for service activities at land offices, compared to opinions that responded negatively by as much as 33.1% and neutrally by as much as 9.2%. Based on the source, tweets from government accounts tend to give positive responses, while personal accounts give negative responses. Sentiment analysis can provide valuable insight for the government and related agencies to evaluate and improve public services quickly and practically by examining the views, concerns, and hopes of the community regarding the policies that have been established. Pemerintah Indonesia mengeluarkan kebijakan pada permohonan pelayanan pendaftaran peralihan hak atas tanah atau hak milik atas satuan rumah susun karena jual beli harus dilengkapi dengan fotokopi kartu peserta BPJS Kesehatan. Kebijakan tersebut menimbulkan berbagai macam opini masyarakat, termasuk warga internet (netizen) di media sosial twitter. Penelitian ini bertujuan untuk mengetahui tanggapan netizen terhadap kebijakan tersebut. Penelitian ini menggunakan metode kuantitatif. Crawling dan analisis datanya menggunakan bahasa pemrograman python atau metode lexicon-based dengan waktu execute program sebelum tanggal 19 Agustus 2023. Hasil penelitian menunjukkan sebanyak 57,7% opini pengguna twitter memberikan tanggapan positif terhadap persyaratan BPJS pada kegiatan pelayanan di kantor pertanahan, opini yang menanggapi negatif sebanyak 33,1%, dan netral sebanyak 9,2%. Berdasarkan sumbernya, tweet dari yang berasal dari akun milik pemerintah cenderung memberikan tanggapan positif, sedangkan akun personal memberikan tanggapan negatif. Analisis sentimen dapat memberikan wawasan yang berharga bagi pemerintah dan instansi terkait untuk mengevaluasi serta meningkatkan pelayanan publik secara cepat dan praktis dengan mengkaji pandangan, kekhawatiran, dan harapan masyarakat atas kebijakan yang telah ditetapkan.
Indications and Effectiveness of ICD for Primary and Secondary Prevention in Patients Admitted in Ahvaz Imam Khomeini Hospital since 2017

Background: Implantable cardioverter-defibrillators (ICDs) have been established for primary and secondary prevention of fatal arrhythmias and effectively reduce the rate of sudden cardiac death (SCD). This study aims to evaluate the indications and effectiveness of ICD for primary and secondary prevention of SCD. Materials and Methods: This retrospective study was conducted on 229 patients (136 for primary and 93 for secondary prevention) with ICD implantations in Imam Khomeini Hospital, Ahvaz, between 2017 and 2020. The incidence of arrhythmic events after implantation of ICDs was saved in electrograms, and the performed treatments (antitachycardia pacing (ATP)/shock) were recorded from the device memory. Results: The indications for ICD implantation in primary and secondary prevention were different (P < 0.0001). The most common cause of ICD implantation for primary prevention was ischemic cardiomyopathy (ICMP, 90.4%) and for secondary prevention was ICMP (58.1%) followed by dilated cardiomyopathy (31.2%). During ICD implantation, 54 patients (39.7%) with ICD implantation for primary prevention and 50 patients (53.8%) for secondary prevention had arrhythmia (P = 0.043). The rate of appropriate therapies in patients with secondary prevention was higher than the primary prevention (57.9% vs. 42.1%), while the rate of inappropriate treatments in patients with primary prevention indication was more than the secondary prevention (63% vs. 37%) (P = 0.060). Conclusions: ICMP was the main cause of ICD implantation for the prevention of SCD in both groups. At follow-up, the high prevalence of appropriate ICD therapy was observed in both groups, and this risk was slightly higher in the secondary prevention group.
Tingkatkan Kesadaran Stroke, UPN Veteran Jakarta Lakukan Penyuluhan dan Lokakarya Pembuatan Biskuit dari Jamur Merang

Stroke adalah penyakit yang menyebabkan angka kematian dan angka kesakitan yang tinggi. Selain itu stroke juga menyebabkan angka ketergantungan hidup yang tinggi. Penyakit stroke ini merupakan penyakit yang secara statistik berhubungan dengan faktor resiko. Faktor resiko yang menyebabkan stroke terbagi menjadi faktor resiko yang bisa dimodifikasi dan yang tidak bisa dimodifikasi. Beberapa faktor resiko yang dapat dimodifikasi atau dicegah diantaranya adalah hipertensi, penyakit jantung, kegemukan, diabetes mellitus yang merupakan faktor resiko stroke. Faktor resiko yang merupakan focus pengabdian ini adalah diet. PKM ini mencoba memberikan solusi nutrisi antioksidan untuk penyakit stroke dan penyuluhan yang akan mengubah tingkat pengetahuan mengenai factor resiko stroke. Metode PKM. Melakukan screening factor resiko hipertensi dan kegemukan, penyuluhan dan lokakarya pembuatan biscuit jamur merang. Hasil. Sebanyak 18 orang sebelumnya dengan tingkat pengetahuan yang rendah, dan berubah menjadi tingkat pengetahuan baik setelah penyuluhan. Perspesi tentang biscuit jamur merang sangat baik dan mengerti bahwa jamur merang adalah sumber nutrisi yang baik. Kesimpulan. PKM ini berhasil mengubah tingkat pengetahuan tentang factor resiko stroke dan persepsi jamur merang sebagai sumber energi dengan antioksidan tinggi.
Benefits of contrast enhanced ultrasound in intervention

For evaluating unclear tumorous lesions, CEUS is an important imaging modality besides contrast-enhanced computed tomography (CECT) and magnetic resonance imaging (MRI) and may provide valuable insights into the microvascularization of tumors by its dynamic examination. In interventional procedures, CEUS can make a valuable contribution in pre-, periand post-interventional settings, reduce radiation exposure and, under certain circumstances, the number of interventions for the patient.
Few-shot Learning for Plastic Bearing Fault Diagnosis – An Integrated Image Processing and NLP Approach

Plastic bearings have a wide range of industrial applications due to their many desirable properties such as lightweight, low friction coefficient, chemical resistance, and ability to operate without lubrication. Timely bearing fault diagnosis can prevent equipment failure and costly downtime. In recent years, developing machine learning based bearing fault diagnosis with few labelled data has attracted a lot of attentions as datasets with fault labels are rare in many industrial applications. One effective approach to meet the challenge is few-shot learning. Among many approaches, utilizing a good pre-trained deep learning model to achieve few-shot learning is an effective and efficient alternative. In this paper, a pre-trained deep learning model called CLIP that combines image processing and natural language processing (NLP) is adopted to few-shot learning for plastic bearing fault diagnosis. We explore the feasibility of leveraging CLIP model in the realm of bearing fault diagnosis via few-shot learning. Specifically, we tackle the challenges posed by CLIP's creation of requisite text prompt embeddings for the diagnosis of mechanical faults, within a few-shot learning framework. Our investigation illuminates the remarkable capability of CLIP to adapt to new tasks with minimal examples, a feature we exploit to devise a solution for plastic bearing fault diagnosis. The effectiveness of the few-shot learning method with CLIP is demonstrated using vibration data collected from plastic bearing seeded fault tests in the laboratory.
Mapping choice in the NHS: Analysis of routine data

New policies in the National Health Service in England seek to extend the choice of provider of care for patients on waiting lists for elective surgery. We try to identify where in the country there are likely to be most constraints on choice for patients waiting over 6 months for elective care. The available supply and demand for hsoptial care, based on a 60 minute travel time from individual location, is estimated using routinely collected information. We show that for most of the population there is already a significant potential choice of hospital. The number of available and unoccupied beds within 60 minutes travel time is lowest in the Scottish Borders, North Yorkshire, and parts of East Anglia, Lincolnshire, Devon and Cornwall. Adding in private facilities does not alter this pattern. Putting together demand with this supply, the number waiting over 6 months per bed within 60 minutes travel time is highest in the South East (except London), parts of the South West (Cornwall, Bristol), East Anglia and the Welsh Borders. We conlcude that people in the South East outside London, East Anglia, and parts of the South West are likely to have to travel further to exercise meaningful choice.
Network–Polymer–Modified Superparamagnetic Magnetic Silica Nanoparticles for the Adsorption and Regeneration of Heavy Metal Ions

Superparamagnetic magnetic nanoparticles (MNPs, Fe3O4) were first synthesized based on a chemical co–precipitation method, and the core–shell magnetic silica nanoparticles (MSNPs, Fe3O4@SiO2) were obtained via hydrolysis and the condensation of tetraethyl orthosilicate onto Fe3O4 seed using a sol–gel process. Following that, MSNPs were immobilized using a three–step grafting strategy, where 8-hloroacetyl–aminoquinoline (CAAQ) was employed as a metal ion affinity ligand for trapping specific heavy metal ions, and a macromolecular polymer (polyethylenimine (PEI)) was selected as a bridge between the surface hydroxyl group and CAAQ to fabricate a network of organic networks onto the MSNPs’ surface. The as–synthesized MSNPs–CAAQ nanocomposites possessed abundant active functional groups and thus contained excellent removal features for heavy metal ions. Specifically, the maximum adsorption capacities at room temperature and without adjusting pH were 324.7, 306.8, and 293.3 mg/g for Fe3+, Cu2+, and Cr3+ ions, respectively, according to Langmuir linear fitting. The adsorption–desorption experiment results indicated that Na2EDTA proved to be more suitable as a desorbing agent for Cr3+ desorption on the MSNPs–CAAQ surface than HCl and HNO3. MSNPs–CAAQ exhibited a satisfactory adsorption capacity toward Cr3+ ions even after six consecutive adsorption–desorption cycles; the adsorption efficiency for Cr3+ ions was still 88.8% with 0.1 mol/L Na2EDTA as the desorbing agent. Furthermore, the MSNPs–CAAQ nanosorbent displayed a strong magnetic response with a saturated magnetization of 24.0 emu/g, and they could be easily separated from the aqueous medium under the attraction of a magnet, which could facilitate the sustainable removal of Cr3+ ions in practical applications.
Quantitative Morphometric analysis of a Semi Urban Watershed, Trans Yamuna, draining at Allahabad using Cartosat (DEM) data and GIS

In the present paper, an attempt has been made to study the Morphometric characteristic of a Semi Urban watershed, trans Yamuna at Allahabad, Uttar Pradesh, India. For detail study Survey of India toposheets at 1:50,000 scale and CartoSAT-1 DEM data with 30m spatial resolutions has been used. Watershed boundary, flow accumulation, stream number, stream ordering, stream length have been prepared using ArcGIS 9.3, Hydrotool. It has been found that the total length of all stream segments under stream order I to VIII is 266.38,88.15,39.17,17.17,10.62,4.0,4.7,0.2 Km respectively. The total length of Streams for the entire watershed has thus been found to be 430.39 Kms representing a dense drainage network. More than ten morphometric parameters of all aspects have been analysis. This study is very useful for planning rain water harvesting and watershed management.
Does False Lumen Thrombosis Lead to Better Outcomes in Patients with Aortic Dissection: A Meta-Analysis and Systematic Review.

OBJECTIVES For a long time, the association of the false lumen status and the outcomes of patients suffering from aortic dissection has been unclear, so this review article aims to study whether the unobstructed of the false lumen is related to the outcome of patients suffering from aortic dissection. METHODS We performed this systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta Analyzes Protocols (PRISMA) statement 2009 and registered with PROSPERO (CRD42022381869). We searched PubMed, the Cochrane library, Web of Science and Embase to collect potential studies. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. The main outcome is long-term survival. Data included in the study were summarized using the risk ratio or mean difference and 95% confidence interval. RESULTS There were 16 trials, 2829 patients in total, with a mean age of 62.1 years. Compared with completely thrombosed false lumen, patent group has better long-term survival (risk ratio (RR), 0.88; 95% CI, 0.79 to 0.97; p = 0.01; I2 = 58%) and smaller yearly aortic growth rate (mean difference (MD), 1.03; 95% CI, 0.23 to 1.82; p = 0.01; I2 = 98%). In addition, patients with a patent false lumen had a lower risk of aortic event (RR, 0.81; 95% CI, 0.68 to 0.97; p = 0.02; I2 = 37%), but higher risk of aortic rupture (RR, 7.02; 95% CI, 2.55 to 19.3; p = 0.0002; I2 = 0) and hospital death (RR, 2.72; 95% CI, 1.45 to 5.08; p = 0.002; I2 = 0). CONCLUSION Completely thrombosed of the false lumen is more beneficial to the long-term survival of patients with aortic dissection. And the risk of aortic rupture and hospital death in patients with patent false lumen is 7 times and 3 times that of patients with complete thrombosed false lumen. It is expected to provide individualized medical care for different types of patients according to different false lumen status to minimize death and related complications.
An IoT-based Smart Plug Energy Monitoring System

—Over the years, considerable efforts have been made to maintain electricity. However, there is still a significant need to explore new technologies and solutions conserve and enhance electricity supply. This project discusses research studies and applications conducted in the field of energy control, including a comparison of these applications undertaken in order to highlight constraints that need to be further addressed. This can be considered as the first step in developing a system that helps building owners to control their electricity consumption using Internet of Things (IoT) technologies. The main phases of the proposed system are data collection, data analysis and mobile application development. The project utilizes Wi-Fi smart plugs to collect active power consumption data, of which analysis is conducted on the cloud. The mobile application allows the building owner to manage buildings, and to obtain active and accumulated consumption data of plugged-in devices. This paper involves the architecture design of the proposed system, and the experimentation, testing, and implementation. The application was tested and the active and accumulative consumption per device and per building were reported. To confirm the accuracy of the active power consumption measurements from the smart plugs, a comparison is performed between these values and the active power consumptions measured by the company and shown on the labels. The results showed that using IoT-based smart plugs gives accurate readings.
Cross-network Embeddings Transfer for Traffic Analysis

—Artiﬁcial Intelligence (AI) approaches have emerged as powerful tools to improve trafﬁc analysis for network monitoring and management. However, the lack of large labeled datasets and the ever-changing networking scenarios make a fundamental difference compared to other domains where AI is thriving. We believe the ability to transfer the speciﬁc knowledge acquired in one network (or dataset) to a different network (or dataset) would be fundamental to speed up the adoption of AI-based solutions for trafﬁc analysis and other networking applications (e.g., cybersecurity). We here propose and evaluate different options to transfer the knowledge built from a provider network, owning data and labels, to a customer network that desires to label its trafﬁc but lacks labels. We formulate this problem as a domain adaptation problem that we solve with embedding alignment techniques and canonical transfer learning approaches. We present a thorough experimental analysis to assess the performance considering both supervised (e.g., classiﬁcation) and unsupervised (e.g., novelty detection) downstream tasks related to darknet and honeypot trafﬁc. Our experiments show the proper transfer techniques to use the models obtained from a network in a different network. We believe our contribution opens new opportunities and business models where network providers can successfully share their knowledge and AI models with customers.
A Markov Regime-Switching Framework Application for Describing El Niño Southern Oscillation (ENSO) Patterns

The El Nino-Southern Oscillation (ENSO) is an ocean – atmosphere phenomenon that involves sustained sea surface temperature fluctuations in the Pacific Ocean. This causes disruption in the behavior of the ocean and the atmosphere having important consequences on the global weather. This paper develops a stochastic model to describe El Nino-Southern Oscillation patterns. A Markov Switching Autoregressive model (MS-AR) was implemented to fit the Southern Oscillation Index (SOI), a variable that explains the phenomenon. The model consists of two autoregressive processes describing the time evolution of SOI, each of which associated with a specific phase of ENSO (El Nino and la Nina). The switching between these two models is governed by a discrete time Markov chain. We study the advantages of incorporating time-varying transition probabilities between them and show that the fitted model provides an adequate description of the time series, and demonstrate its utility in analysis and evaluation of the phenomenon
Migrant penalty in the European labor markets: the interplay between individual characteristics and the regional context

This study aims to verify if and how migrant penalty in the labor market is associated with sub-national characteristics, exploring the relevance of the regional occupational structure. We expect that a greater relevance of the share of low-status jobs at the regional level reduces the migrant penalty in terms of the probability of being employed, but increases the gap with natives in terms of job quality. We investigate this trade-off by estimating a set of hierarchical models on the EU-LFS data (2009–2015) for 19 countries and 189 regions. Results suggest a pattern consistent with the trade-off hypothesis, nuanced by heterogeneity at the individual level: in regions where the share of low-status jobs is higher, mid-high educated immigrants from less developed countries are less (or not) penalized compared to natives in terms of employment, while they face a stronger penalty in terms of job quality. What is more, the trade-off is not observed when considering low-educated migrants or those from high-income countries.