Miracle-dz/UniFAR-FTUs huggingface dataset:
An analysis of intrinsically disordered proteins using hidden Markov models and experimental design of stochastic kinetic models

An intrinsically disordered protein (IDP) is a protein without a stable secondary or tertiary structure and just over one third of human proteins can be described as IDPs. There has been shown to be a link between neurodegenerative diseases, cancer and protein misfolding, with many of these misfolded proteins being intrinsically disordered. These IDPs may be cytotoxic by interacting and contributing to the aggregation process, which is why cells need to regulate these proteins carefully. Research has shown that hydrophobicity and charge may be important in determining if the amino acid sequence has unstructured areas. We study the sequence structure by first recoding amino acid sequences according to their hydrophobicity and charge and then fitting a hidden Markov model using Markov chain Monte Carlo methods to analyse the sequence structure and use a power posterior analysis to determine the number of distinct transition structures. The results show there to be distinct segment types within the amino acid sequences of the FET proteins which may have biological importance. The location of these segments can be used to guide laboratory work which tests the biological significance of these segment types within cells. One particular segment found in the FET proteins has been linked to oncogenic fusion proteins and experimental analysis has shown a link between this segment and oncogenic activity. When conducting an experiment, an experimenter needs to determine when and under what conditions they should take measurements. Often the choice of optimal design is made with respect to some statistical criteria. The aim of this work is to determine, for a stochastic kinetic model, the optimal location of the timepoints at which observations are taken. Commonly the statistical criteria involves maximising a utility function over the prior predictive distribution of possible experimental outcomes. Current methodologies for experimental design for models with intractable likelihoods are very computationally expensive as, within the iterative search for the optimal design, the calculation of the utility function requires the determination of the parameter posterior distribution at each iteration. We show how to use delta methods and a Gaussian process as an emulator for the utility to reduce the computational cost and illustrate their application for the simple death process and the Lotka–Volterra model.
Looking for Nano- and Microplastics in Meiofauna Using Advanced Methodologies

Meiofauna (body size within 30–1000 µm) are the community of microscopic invertebrates that live at the bottom of marine and freshwater ecosystems and play a key role in the food webs of these environments. Several studies have addressed the adverse effects of anthropic stressors on meiofauna; however, data on the presence and impact of plastic debris in wild meiofaunal organisms are scant. Since the amount of microplastic waste in sediments may surge rapidly, ascertaining the ingestion of these xenobiotics by the abundant micrometazoan community is necessary to understand their potential accumulation in aquatic food webs and their hazard to the health of the ecosystem. The absence of documentation in this regard may be due to the difficulty in detecting the small size of the plastic fragments meiofauna may potentially ingest. To overcome this difficulty, we developed an integrated approach based on different microscopic/spectroscopic techniques suitable for detecting plastic particles of sizes down to 200 nm.
Prospects and Advances in Adoptive Natural Killer Cell Therapy for Unmet Therapeutic Needs in Pediatric Bone Sarcomas

Malignant bone tumors are aggressive tumors, with a high tendency to metastasize, that are observed most frequently in adolescents during rapid growth spurts. Pediatric patients with malignant bone sarcomas, Ewing sarcoma and osteosarcoma, who present with progressive disease have dire survival rates despite aggressive therapy. These therapies can have long-term effects on bone growth, such as decreased bone mineral density and reduced longitudinal growth. New therapeutic approaches are therefore urgently needed for targeting pediatric malignant bone tumors. Harnessing the power of the immune system against cancer has improved the survival rates dramatically in certain cancer types. Natural killer (NK) cells are a heterogeneous group of innate effector cells that possess numerous antitumor effects, such as cytolysis and cytokine production. Pediatric sarcoma cells have been shown to be especially susceptible to NK-cell-mediated killing. NK-cell adoptive therapy confers numerous advantages over T-cell adoptive therapy, including a good safety profile and a lack of major histocompatibility complex restriction. NK-cell immunotherapy has the potential to be a new therapy for pediatric malignant bone tumors. In this manuscript, we review the general characteristics of osteosarcoma and Ewing sarcoma, discuss the long-term effects of sarcoma treatment on bones, and the barriers to effective immunotherapy in bone sarcomas. We then present the laboratory and clinical studies on NK-cell immunotherapy for pediatric malignant bone tumors. We discuss the various donor sources and NK-cell types, the engineering of NK cells and combinatorial treatment approaches that are being studied to overcome the current challenges in adoptive NK-cell therapy, while suggesting approaches for future studies on NK-cell immunotherapy in pediatric bone tumors.
Sensitivity and Mechanism Study of Single-Event Burnout in 4H-SiC Devices With FLRs Termination

The 4H-silicon carbide (SiC) junction barrier Schottky with field limiting rings (FLRs-JBS) termination was fabricated and analyzed to evaluate its radiation tolerance of the single-event burnout (SEB). Experimental and simulation results show that the SiC/SiO2/metal intersection is the most sensitive position in the FLRs-JBS. This work proposes that there are different mechanisms between the active and the terminal regions under heavy-ion irradiation for the first time. The simulation results show that the FLRs terminal area is more likely to burn out under single-event irradiation than the active area due to the serious current crowding effect. This work redefines the sensitive volume of the conventional FLRs-JBS under single-event irradiation, including the transition ring of the terminal zone, the part of the active area near the terminal zone, and the p+ island spacing of the active area.
In vitro antibacterial-antibiofilm effect of Hypericum atomarium Boiss and chemical composition

Treatment with plant is considered an effective option against increased antibiotic resistance. In this study antibiofilm activity of methanol (CH 3 OH), chloroform (CHCl 3 ), ethyl acetate (EtOAc) and water (H 2 O) extracts of Hypericum atomarium Boiss. which is member of Hypericum genus was evaluated in Pseudomonas aeruginosa PAO1 and antibacterial performance against Gram (+) and Gram (-) strains and also bioactive compounds of extract were analysed using by HPLC and GC-MS. According to antibacterial activity test results the extracts were effective all Gram (+) bacteria and Gram (-) Chromobacterium violaceum (MICs ranging from 0.42 µg/ ml to 4.3 mg). Inhibition effect of biofilm formation was found to be different rate in extracts (methanol-63%, chloroform-52%). The major flavonoids were detected (−)-epicatechin (2388.93 µg/ml) and (+)-catechin (788.94 µg/ml). The main phenolic acids were appeared as caffeic acid 277.34 µg/ml and chlorogenic acid 261.79 µg/ml. And according to GC results α-pinene was found main compound for three solvent extracts methanol, chloroform and ethyl acetate 67.05, 62.69, 49.28% rate respectively.
Field‐gradient partitioning for fracture and frictional contact in the material point method

Contact and fracture in the material point method require grid‐scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. A new method is presented in which a kernel‐based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. This approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3‐D fracture with crack branching and coalescence. A straightforward extension of this approach permits frictional ‘self‐contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach. Copyright © 2016 John Wiley & Sons, Ltd.
Natural Convection Flow of Radiative Casson Fluid Past a Stretching Cylindrical Surface in a Porous Medium with Applied Magnetic Field and Joule Heating

This study is based on the exploration of MHD Casson fluid flow past a stretching cylinder in the presence of non-uniform heat generation, thermal radiation and Joule heating. Boussinesq approximation is also put into consideration due to density difference in the fluid. The governing equations and their corresponding boundary conditions are changed into system of ordinary differential equations with the aid of appropriate similarity variables. The obtained ordinary differential equations are solved numerically using Runge-Kutta Fehlberg method alongside shooting technique. The flow and thermal fields are investigated in the presence of emerging parameters, namely Grashof number, Prandtl number, radiation parameter, curvature parameter, Eckert number, Casson parameter, permeability parameter, magnetic number, space and temperature dependent heat generation parameter. In this study, enhancement in velocity distributions is noticed as values of Grashof number grow but velocity profiles are depreciated by permeability parameter and curvature parameter.
On the variable circular plot method of estimating animal density

The development by ornithologists of the variable circular plot method of estimating bird densities from observer-to-bird distances has led to estimation problems similar to those of line transect sampling. However, to apply line transect methods without modification requires that the distance data be transformed to areas by squaring. The implications of this transformation on the assumed shapes for the detection curve have not been investigated in the literature. This paper illustrates that application of line transect models to area data may lead to poor model performance and erroneous conclusions. Developments based on distance data are discussed briefly, and binomial models are derived for the special case in which birds are categorised simply according to whether they are within or beyond a specified distance.
Influence of essential oil: cyclodextrin ratio and stirring rate on physicochemical characteristics of orange essential oil: β-cyclodextrin microparticles

ABSTRACT Some encapsulation process and formulation parameters influence on several physicochemical properties of the encapsulated products. In this study, the influence of the OEO:β-CD ratio and stirring speed on the total oil, surface oil, oil retention, entrapment efficiency, yield, size distribution (d10, d32, and d43), span value, bounding rectangle aspect ratio (BRAR), Feret’s aspect ratio (FAR), circularity, smoothness, and opacity of microparticles were examined. The superior entrapment efficiency (95.18%), highest oil retention (79.13%), and lowest surface oil content (10.02 mg oil/g powder microparticles) were achieved at an OEO:β-CD ratio of 0.15 (w/w) and stirring speed of 700 rpm. Likewise, all microparticles showed irregular and elongated shapes, in which the opacity distribution was more influenced. Finally, the obtained FTIR spectra contained OEO bands hidden inside β-CD peaks, indicating the occurrence of a complexation reaction after encapsulation.
Shark Fin Occlusive Myocardial Infarction ECG Pattern Post-cardiac Arrest Misinterpreted As Ventricular Tachycardia

In addition to the well-known convex ST-segment elevation myocardial infarction (STEMI) pattern associated with acute occlusive myocardial infarction (OMI), there are other cases that are recognized as OMI without fulfilling the established characteristic STEMI criteria. Over one-fourth of the patients initially classified as having non-STEMI can be re-classified as having OMI by recognizing other STEMI equivalent patterns. We report a case of a 79-year-old man with multiple comorbidities who was brought to the ED by paramedics with a two-hour history of ongoing chest pain. During transport, the patient suffered a cardiac arrest associated with ventricular fibrillation (VF) that required electric defibrillation and active cardiopulmonary resuscitation. Upon ED arrival, the patient was unresponsive, with a heart rate of 150 beats/min and ECG evidence of wide-QRS tachycardia that was misinterpreted as ventricular tachycardia (VT). He was further managed with intravenous amiodarone, mechanical ventilation, sedation, and unsuccessful defibrillation therapy. Upon persistence of the wide-QRS tachycardia and clinical instability, the cardiology team was emergently consulted for bedside assistance. On further review of the ECG, a shark fin (SF) OMI pattern was identified, indicative of an extensive anterolateral OMI. A bedside echocardiogram revealed a severe left ventricular systolic dysfunction with marked anterolateral and apical akinesia. The patient underwent a successful percutaneous coronary intervention (PCI) to an ostial left anterior descending (LAD) culprit occlusion with hemodynamic support but ultimately died due to multiorgan failure and refractory ventricular arrhythmias. This case illustrates an infrequent OMI presentation (<1.5%) formed by the fusion of the QRS, ST-segment elevation, and T-wave resulting in a wide triangular waveform, giving the appearance of an SF that can also potentially lead to ECG misinterpretation as VT. It also highlights the importance of recognizing STEMI-equivalent ECG patterns to avoid delays in reperfusion therapy. The SF OMI pattern has also been associated with a large amount of ischemic myocardium (such as with left main or proximal LAD occlusion) with a higher mortality risk from cardiogenic shock and/or VF. This high-risk OMI pattern should lead to a more definite reperfusion treatment, such as primary PCI and the possible need for backup hemodynamic support.
Analyzing Effects of Institutional Quality on Banking Stability: Evidence from Asean Countries

Purpose: The aim of this study is to examine the effect of institutional quality on bank stability using bank-level data from 2010 to 2020. Theoretical framework: The study considers institutions from the perspective of governance institutions. Accordingly, the concept of government institutions is related to the country's organizational foundation in terms of governance, implying institutional quality. Design/methodology/approach: The study uses GMM method and also choose the Zscore as the primary variable for bank stability. Findings: The results show that institutional quality increases the stability of banks. Moreover, with the threshold model, the results show that countries with institutional quality above the threshold will increase the stability of banks. In addition, macroeconomic and banking characteristics variables such as total assets, income diversification, quality of control, inflation, and GDP growth rate have a high significance in the model. Research, Practical & Social implications: The study shows The study's empirical results have specific policy implications for the Government in implementing policies related to institutional quality to improve bank stability. Originality/value: there are not many researches done to investigate institutional quality to improve bank stability. Moreover, from economic crisis, the matter of banking stability is among main concerns of many researches. Second, previous researches just focus on the aspect of corruption and ignore other aspects or other factors. That’s why authors conduct this research.
Optimality of the auxiliary particle filter

In this article we study asymptotic properties of weighted samples produced by the auxiliary particle filter (APF) proposed by Pitt and Shephard [17]. Besides establishing a central limit theorem (CLT) for smoothed particle estimates, we also derive bounds on the Lp error and bias of the same for a finite particle sample size. By examining the recursive formula for the asymptotic variance of the CLT we identify first- stage importance weights for which the increase of asymptotic variance at a single iteration of the algorithm is minimal. In the light of these findings, we discuss and demonstrate on several examples how the APF algorithm can be improved.
Application of Deep Learning in Healthcare: A Survey on Brain Tumor Detection

Brain tumors are one of the most dangerous diseases that continue to be threatened worldwide.As a result, the diagnosis and treatment in the early stages are very important in this case. As a result, the diagnosis and treatment in the early stages are very important in this case. Furthermore, the determination of the correct nature of the tumor is a sensitive process in patient treatment . In recent years, with the advancement of deep learning solutions in computer vision, such as image segmentation, image classification, and object detection, promising results have been achieved in the accuracy of medical diagnosis.In this paper, we propose the most famous deep learning model and architecture used to predict the existence of brain tumors from an MR image dataset.
Salmonella Type III Secretion Effector SrfJ: A Glucosylceramidase Affecting the Lipidome and the Transcriptome of Mammalian Host Cells

Type III secretion systems are found in many Gram-negative pathogens and symbionts of animals and plants. Salmonella enterica has two type III secretion systems associated with virulence, one involved in the invasion of host cells and another involved in maintaining an appropriate intracellular niche. SrfJ is an effector of the second type III secretion system. In this study, we explored the biochemical function of SrfJ and the consequences for mammalian host cells of the expression of this S. enterica effector. Our experiments suggest that SrfJ is a glucosylceramidase that alters the lipidome and the transcriptome of host cells, both when expressed alone in epithelial cells and when translocated into macrophages in the context of Salmonella infection. We were able to identify seventeen lipids with higher levels and six lipids with lower levels in the presence of SrfJ. Analysis of the forty-five genes, the expression of which is significantly altered by SrfJ with a fold-change threshold of two, suggests that this effector may be involved in protecting Salmonella from host immune defenses.
Multi-sensory Olfactory Quadruped Robot for Odor Source Localization*

With the rapid development of industrialization, hazardous chemical gas leakage accidents not only cause huge losses to people and economy, but also cause great damage to the environment. Research into how to efficiently, safely and accurately search for and locate sources of toxic, hazardous, explosive, flammable and other dangerous chemical gas leaks has become an urgent and realistic need. In this work, we focused on promoting the application scenarios of mobile robot-based odor source localization technology and proposed an olfactory quadruped robot capable of odor source localization tasks in complex environments. Compared to traditional wheeled robots, olfactory quadruped robot are more adaptive and eco-friendly. The robot is equipped with a variety of sensors and has a rich perception of complex environments, enabling it to complete complex tasks such as mapping, navigation and odor source localization in unstructured terrain.
Regulation of Nod-like receptor expression in the liver of ewes
during early pregnancy

pregnancy-ABSTRACT. Multiple factors are involved in the regulation of maternal-foetal tolerance, and nucleotide-binding and oligomerisation domain (NOD)-like receptors (NLRs) were shown to play roles in innate immune signalling pathways. The objective of this study was to investigate the effects of early pregnancy on the expression of NLRs in the liver of ewes. Livers from ewes were collected on day 16 of the oestrous cycle, and days 13, 16 and 25 of gestation (n = 6 for each group). Real-time quantitative PCR, Western blot and immunohistochemical analysis were used to analyse mRNA and protein expression of NLRs, including NOD1, NOD2, major histocompatibility complex class II transactivator (CIITA), neuronal apoptosis inhibitor protein (NAIP), NLR family, pyrin domain-containing 1 (NLRP1), NLRP3 and NACHT, LRR and PYD domains-containing protein 7 (NLRP7). The data showed that NOD1, CIITA, NLRP1, NLRP3 and NLRP7 were upregulated in maternal liver on days 13 to 25 of pregnancy, and NOD2 expression was upregulated on days 13 and 16 of pregnancy, but downregulated on day 25 of pregnancy. In addition, NOD2 and NLRP7 proteins were located in the endothelial cells of the proper hepatic arteries and portal veins, and in hepatocytes. NAIP expression was the highest at day 16 of pregnancy. In conclusion, this study reported for the first time that early pregnancy modulated the expression of NLRs, suggesting that NLRs were involved in the regulation of maternal hepatic immune functions during early pregnancy in sheep.
CNN-based real-time prediction of growth stage in soybeans cultivated in hydroponic set-ups

The purpose of this research is to create a deep learning model capable of predicting the day of harvest for soybeans growing in hydroponic conditions. The algorithm uses feature extraction to calculate the day of growth for each annotated picture fed into the model. The recorded photos in this study were tagged using the Computer Vision Annotation Tool (CVAT), which was then used to train a five-layer Convolutional Neural Network (CNN) to predict the range of cultivation days. This pre-trained model was then deployed on the backend using Flask, and for each picture provided as input to the model, a Graphical User Interface (GUI) was created to accept a taken image as input and estimate the day of cultivation for real-time application.
Artificial Intelligence and Its Theranostic Applications in Dentistry

As new technologies emerge, they continue to have an impact on our daily lives, and artificial intelligence (AI) covers a wide range of applications. Because of the advancements in AI, it is now possible to analyse large amounts of data, which results in more accurate data and more effective decision-making. This article explains the fundamentals of AI and examines its development and present use. AI technology has had an impact on the healthcare sector as a result of the need for accurate diagnosis and improved patient care. An overview of the existing AI applications in clinical dentistry was provided. Comprehensive care involving artificial intelligence aims to provide cutting-edge research and innovations, as well as high-quality patient care, by enabling sophisticated decision support tools. The cornerstone of AI advancement in dentistry is creative inter-professional coordination among medical professionals, scientists, and engineers. Artificial intelligence will continue to be associated with dentistry from a wide angle despite potential misconceptions and worries about patient privacy. This is because precise treatment methods and quick data sharing are both essential in dentistry. Additionally, these developments will make it possible for patients, academicians, and healthcare professionals to exchange large data on health as well as provide insights that enhance patient care.