Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy

Background Global prevalence of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. Methods In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. Results From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from −11.7 to −10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0. 39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Conclusion Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.
Structure-Based Evaluation of Hybrid Lipid–Polymer Nanoparticles: The Role of the Polymeric Guest

The combination of phospholipids and block-copolymers yields advanced hybrid nanoparticles through the self-assembly process in an aqueous environment. The physicochemical features of the lipid/polymer components, like the lipid–polymer molar ratio, the macromolecular architecture of the block copolymer, the main transition temperature of the phospholipid, as well as the formulation and preparation protocol parameters, are some of the most crucial parameters for the formation of hybrid lipid/polymer vesicles and for the differentiation of their morphology. The morphology, along with other physicochemical nanoparticle characteristics are strictly correlated with the nanoparticle’s later biological behavior after being administered, affecting interactions with cells, biodistribution, uptake, toxicity, drug release, etc. In the present study, a structural evaluation of hybrid lipid–polymer nanoparticles based on cryo-TEM studies was undertaken. Different kinds of hybrid lipid–polymer nanoparticles were designed and developed using phospholipids and block copolymers with different preparation protocols. The structures obtained ranged from spherical vesicles to rod-shaped structures, worm-like micelles, and irregular morphologies. The obtained morphologies were correlated with the formulation and preparation parameters and especially the type of lipid, the polymeric guest, and their ratio.
Microprudential Indicators of Financial System Stability: An AHP Approach

In general there are two indicators of financial system stability, namely microprudential and macroprudential. Among macroprudential indicators are economic growth, balance of payments, inflation rate, interest and exchange rates, crisis contagion effect, and many others. Different from the previous researches concerning financial system stability measurement, this research will use the financial and banking practitioners' perspective regarding the leading indicator in measuring financial system stability so that we can presumably determine the real leading financial stability indicator for the current situation using Analytic Hierarchy Process (AHP) method. This study will look at the indicator of financial system stability from a microprudential perspective in Indonesia. The results show that based on the results of interviews with experts/banking practitioners, the 3 (three) most important aspects are Capital & Asset (0.187), Profitability (0.186) and Asset Quality (0.177). Important indicators of financial system stability from the next microprudential aspect are Liquidity (0.176), Market-based Indicators (0.139) and finally Risk Sensitivity (0.136). The Macroprudential Policy and microprudentials issued by Bank Indonesia as the central bank that has full authority, play an important role in maintaining Financial System Stability (SSK) in Indonesia.
Analysis of signal-in-space range error for users of pseudolite system

Aiming at the problem that the existing GNSS signal-in-space range error (SISRE) contribution factor is not applicable to the SISRE assessment of pseudolite systems, in order to assess the system-side performance of pseudolite systems, the contribution factor of the SISRE of pseudolites under different altitude conditions is given based on the definition of the SISRE, and the results of this paper show that unlike the GNSS system, the radial error of pseudolite has a smaller impact on the SISRE, and the tangent-plane error has a larger impact on the SISRE. Moreover, the error decomposition and calculation of the SISRE are carried out in this paper.
A Quantitative Re-Assessment of Microencapsulation in (Pre-Treated) Yeast

Most hydrophobes easily diffuse into yeast cells, where they experience reduced evaporation and protection from oxidation, thus allowing inherently biocompatible encapsulation processes. Despite a long-standing industrial interest, the effect of parameters such as how is yeast pre-treated (extraction with ethanol, plasmolysis with hypertonic NaCl, depletion to cell walls), the polarity of the hydrophobes and the process conditions are still not fully understood. Here, we have developed thorough analytical protocols to assess how the effects of the above on S. cerevisiae’s morphology, permeability, and encapsulation efficiency, using three differently polar hydrophobes (linalool, 1,6-dihydrocarvone, limonene) and three separate processes (hydrophobes as pure ‘oils’, water dispersions, or acetone solutions). The harsher the pre-treatment (depleted > plasmolyzed/extracted > untreated cells), the easier the diffusion into yeast became, and the lower both encapsulation efficiency and protection from evaporation, possibly due to denaturation/removal of lipid-associated (membrane) proteins. More hydrophobic terpenes performed worst in encapsulation as pure ‘oils’ or in water dispersion, but much less of a difference existed in acetone. This indicates the specific advantage of solvents/dispersants for ‘difficult’ compounds, which was confirmed by principal component analysis; furthering this concept, we have used combinations of hydrophobes (e.g., linalool and α-tocopherol), with one acting as solvent/enhancer for the other. Our results thus indicate advantages in using untreated yeast and—if necessary—processes based on solvents/secondary hydrophobes.
Novel Magnesium Nanocomposite for Wire-Arc Directed Energy Deposition

Magnesium alloys play an essential role in metallic lightweight construction for modern mobility applications due to their low density, excellent specific strength, and very good castability. For some years now, degradable implants have also been made from magnesium alloys, which, thanks to this special functionality, save patients a second surgery for explantation. New additive manufacturing processes, which are divided into powder-based and wire-based processes depending on the feedstock used, can be utilized for these applications. Therefore, magnesium alloys should also be used here, but this is hardly ever implemented, and few literature reports exist on this subject. This is attributable to the high affinity of magnesium to oxygen, which makes the use of powders difficult. Therefore, magnesium wires are likely to be used. In this paper, a magnesium-based nanocomposite wire is made from an AM60 (Mg-6Al-0.4Mn) (reinforced with 1 wt% AlN nanoparticles and containing calcium to reduce flammability), using a high-shear process and then extruded into wires. These wires are then used as feedstock to build up samples by wire-arc directed energy deposition, and their mechanical properties and microstructure are examined. Our results show that although the ductility is reduced by adding calcium and nanoparticles, the yield strength in the welding direction and perpendicular to it is increased to 131 MPa.
Effects of Nitrogen Availability on Plant Biomass Along a Barrier Island Dune Chronosequence

Many researchers stress the importance of nutrient limitation on barrier island plant communities. The accreting north end of Hog Island, part of the Virginia Coast ReserveLong Term Ecological Research site, provided an opportunity to quantify amounts of plant biomass along a natural dune chronosequence (24, 36, 120+ yr-old dunes) and biomass response to experimental additions of nitrogen. In a one-year study, nitrogen addition increased plant biomass, with greater allocation to shoots than roots. In response to nitrogen fertilization, soil nitrogen increases were greatest on the oldest site while biomass increases were smallest. Naturally occurring NO2- + NO3- availability increased with age across the chronosequence. Aboveground biomass was inversely proportional to nitrogen availability and decreased from younger dunes to the oldest. Nitrogen does not appear to be the major limiting factor along the chronosequence. Groundwater hydrographs suggest the oldest dune may be moisture limited.
Emerging Multiscale Biofabrication Approaches for Bacteriotherapy

Bacteriotherapy is emerging as a strategic and effective approach to treat infections by providing putatively harmless bacteria (i.e., probiotics) as antagonists to pathogens. Proper delivery of probiotics or their metabolites (i.e., post-biotics) can facilitate their availing of biomaterial encapsulation via innovative manufacturing technologies. This review paper aims to provide the most recent biomaterial-assisted strategies proposed to treat infections or dysbiosis using bacteriotherapy. We revised the encapsulation processes across multiscale biomaterial approaches, which could be ideal for targeting different tissues and suit diverse therapeutic opportunities. Hydrogels, and specifically polysaccharides, are the focus of this review, as they have been reported to better sustain the vitality of the live cells incorporated. Specifically, the approaches used for fabricating hydrogel-based devices with increasing dimensionality (D)—namely, 0D (i.e., particles), 1D (i.e., fibers), 2D (i.e., fiber meshes), and 3D (i.e., scaffolds)—endowed with probiotics, were detailed by describing their advantages and challenges, along with a future overlook in the field. Electrospinning, electrospray, and 3D bioprinting were investigated as new biofabrication methods for probiotic encapsulation within multidimensional matrices. Finally, examples of biomaterial-based systems for cell and possibly post-biotic release were reported.
Empowering Healthcare with Deep Learning for Oral Cancer Prevention

Oral cancer early detection and prediction are of paramount importance due to the profound impact they have on patient outcomes, healthcare systems, and public health. First and foremost, early detection significantly improves the chances of survival. When oral cancer is diagnosed in its initial stages, treatment options are more effective, less aggressive, and less debilitating. This translates into higher survival rates and a better quality of life for patients. Moreover, early detection reduces healthcare costs. Treating advanced-stage oral cancer requires more resources, including extensive surgeries, radiation therapy, and chemotherapy. Identifying the disease early minimizes the need for such intensive interventions, thereby decreasing the financial burden on healthcare systems and patients. Therefore, in this paper, we have made an attempt to detect and predict oral cancer at an early stage using Deep Learning techniques such as Convolutional Neural Networks with different activation functions and transfer learning methods such as ResNet50, VGG16, VGG19, and AlexNet. It can be seen that the proposed Customized CNN model outperforms by giving an accuracy of 87.6%.
REMOVAL OF KEROSENE FROM WASTE WATER USING IRAQI BENTONITE

The aim of the present research is to study the potentiality of Iraqi bentonite as adsorbent for removing of kerosene from wastewater. Also the capacity of bentonite for kerosene removal was compared to the activated carbon capacity. The sorption of kerosene onto bentonite and AC. were described by two well – known adsorption isotherm models namely Langmuir and Freundlich models. It was found that the Freundlich model can fit very well the equilibrium isotherm adsorption of kerosene onto bentonite and AC. Batch experiments were carried out to study the effect of adsorption of kerosene onto bentonite using various conditions such as initial concentrations of kerosene ( 100-500 ) mg/L, agitation speeds (125, 250, 500, 800) RPM, and weights of bentonite ( 0.05, 0.5,1.1 ) gm, particle sizes (0.5- 0.6) mm, and temperature 303 k . It was found that the best results for removing kerosene onto bentonite were obtained at Co=500 mg/L, RPM =800. Activated carbon was used as powder and granular of particle sizes ranged (1-1.18) mm and (0.5-0.6) mm. The results indicated that the activated carbon was more active than bentonite for removing of kerosene from wastewater
Ultralong Nanowires of Cadmium Phosphate Hydroxide Synthesized Using a Cadmium Oleate Precursor Hydrothermal Method and Sulfidation Conversion to Ultralong CdS Nanowires

Ultralong nanowires with ultrahigh aspect ratios exhibit high flexibility, and they are promising for applications in various fields. Herein, a cadmium oleate precursor hydrothermal method is developed for the synthesis of ultralong nanowires of cadmium phosphate hydroxide. In this method, water-soluble cadmium salt is used as the cadmium source, water-soluble phosphate is used as the phosphorus source, and sodium oleate is adopted as a reactant to form cadmium oleate precursor and as a structure-directing agent. By using this method, ultralong nanowires of cadmium phosphate hydroxide are successfully synthesized using CdCl2, sodium oleate, and NaH2PO4 as reactants in an aqueous solution by hydrothermal treatment at 180 °C for 24 h. In addition, a new type of flexible fire-resistant inorganic paper with good electrical insulation performance is fabricated using ultralong nanowires of cadmium phosphate hydroxide. As an example of the extended application of this synthetic method, ultralong nanowires of cadmium phosphate hydroxide can be converted to ultralong CdS nanowires through a convenient sulfidation reaction. In this way, ultralong CdS nanowires are successfully synthesized by simple sulfidation of ultralong nanowires of cadmium phosphate hydroxide under mild conditions. The as-prepared ultralong nanowires of cadmium phosphate hydroxide are promising for applications as the precursors and templates for synthesizing other inorganic ultralong nanowires and have wide applications in various fields.
The Role of Automated Infrared Pupillometry in Traumatic Brain Injury: A Narrative Review

Pupillometry, an integral component of neurological examination, serves to evaluate both pupil size and reactivity. The conventional manual assessment exhibits inherent limitations, thereby necessitating the development of portable automated infrared pupillometers (PAIPs). Leveraging infrared technology, these devices provide an objective assessment, proving valuable in the context of brain injury for the detection of neuro-worsening and the facilitation of patient monitoring. In cases of mild brain trauma particularly, traditional methods face constraints. Conversely, in severe brain trauma scenarios, PAIPs contribute to neuro-prognostication and non-invasive neuromonitoring. Parameters derived from PAIPs exhibit correlations with changes in intracranial pressure. It is important to acknowledge, however, that PAIPs cannot replace invasive intracranial pressure monitoring while their widespread adoption awaits robust support from clinical studies. Ongoing research endeavors delve into the role of PAIPs in managing critical neuro-worsening in brain trauma patients, underscoring the non-invasive monitoring advantages while emphasizing the imperative for further clinical validation. Future advancements in this domain encompass sophisticated pupillary assessment tools and the integration of smartphone applications, emblematic of a continually evolving landscape.
A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning

Worldwide, heart attacks, also called myocardial infarctions, are a leading cause of death. Early detection and accurate prediction of heart attacks are crucial for effective medical intervention and patient care. In recent years, machine learning techniques have shown great promise in aiding the diagnosis and prediction of heart attacks. The Organization for World Health (WHO) reports that around 17 million individuals worldwide pass away from cardiovascular diseases (CVD), notably heart attacks and strokes, each year. In this study, 1026 patients, both men and women, are almost equally affected by CVDs. While heart attacks and strokes remain among the leading causes of mortality worldwide, the use of machine learning for predicting heart disease could potentially prevent premature deaths. A comparative study evaluated the performance of five well-known two-class classification algorithms: two-class boosted decision trees, two-class decision forests, two-class locally deep SVMs, two-class neural networks, and two-class logistic regression. Among these algorithms, the Two-Class Boosted Decision Tree method demonstrated outstanding prediction ability, achieving a 100% accuracy rating. Its exceptional recall and precision rates highlight its effectiveness in handling challenging classifications. To facilitate the development and deployment of machine learning models, Azure Machine Learning offers a range of tools and services. By leveraging Azure Machine Learning's capabilities, researchers and healthcare professionals can analyze large datasets containing patient information and medical records to identify patterns and risk factors associated with heart attacks.
Compensation of deteriorated CSI allocation due to fast fading and feedback delay based on turbo decision direct for MUDiv/OFDMA

In a wireless propagation channel, the channel for each user is independent. By using this characteristic, in orthogonal frequency division multiple access (OFDMA) systems, the multiuser diversity (MUDiv) gain is obtained. However, at high Doppler frequency, since channel state information (CSI) is changed between the head and latter of packets due to the fast fading channel, the system performance is degraded. Moreover, in this case, when the feedback delay is occurred, CSI is more changed and the system performance is more degraded. To solve these problems, in this paper, we propose the compensation of the deteriorated CSI allocation due to the fast fading channel and the feedback delay based on the turbo decision direct for MUDiv/OFDMA systems.
Machine Learning Models Based Crop Recommendation and Plant Disease Identification for Real Time Application

The production of crops contributes significantly to the economic health of every country. One of the most crucial elements of maintaining a country with a developed agricultural sector is plant disease identification. An agricultural sector that is healthy and productive and that doesn't waste money or other resources requires the quick and effective diagnosis of plant diseases. Various useful technologies to solve global challenges have been developed with the aid of machine learning. The use of several ML algorithms can help solve the agriculture problem. The creation of a website that incorporates both a crop recommendation system and a plant disease identification system is one of the two goals of this essay. The datasets might be accessed by anyone online. The dataset is trained once the characteristics required for Task 1 are retrieved using five distinct algorithms: logistic regression, decision tree, support vector machine (SVM), multilayer perceptron, and random forest. In suggested machine learning models, random forest exceeds all other techniques, achieving an accuracy rate of 99.92%.
Sea nomads’ mobile dwellings and settlements and their ideas of place and space

This chapter deals with the Orang Suku Laut or 'Sea Tribe People' of the Indonesian Riau Archipelago, one of several small communities of 'sea nomads' found throughout large areas of Southeast Asia. It focuses on the simple and ephemeral Orang Suku Laut dwellings and the constantly changing structure of their moorages and settlements. The chapter reviews the main groups of Southeast Asian sea nomads and the present way of life of the Orang Suku Laut in a region undergoing a process of modernization. It describes the construction and materials of Orang Suku Laut houseboats, temporary huts and more permanent pile-buildings as well as the structure of their moorages and coastal settlements. Finally, the chapter discusses the persistence and change with which the Orang Suku Laut choose and create places to live, specifically with regard to resettlement sites on land in permanent houses recently given to them by the government. Keywords: Orang Suku Laut dwellings; Orang Suku Laut's settlements; permanent pile-buildings; Southeast Asian sea nomads; temporary huts
A 64-Element Antenna Array With a Low Wind Load for 5G Base Station Applications

In this work, a 64-element antenna array with a low wind load is proposed for sub-6 GHz base stations. The proposed array element consists of a radiating layer with regular cross-dipoles, a defected ground layer to improve isolation between input ports, a metal mesh reflector to reduce the size of the windward side and maintain electromagnetic performance, and the metal support structure to keep the physical structure stable and provide enough space for installing the radome. A prototype of the proposed 64-element array formed by using the above-mentioned antenna element is fabricated and measured. The results show that the -10-dB impedance bandwidth is 3.4–3.6 GHz, the realized gain is 24.2 ± 0.4 dBi and the front-to-back ratio is larger than 16 dB, which proves that the proposed structure is suitable for 5G sub-6 GHz base stations.