Miracle-dz/UniFAR-FTUs huggingface dataset:
MOLECULAR ENVIRONMENT OF THE SUPERNOVA REMNANT IC 443: DISCOVERY OF THE MOLECULAR SHELLS SURROUNDING THE REMNANT

We have carried out 12CO, 13CO, and C18O observations toward the mixed morphology supernova remnant (SNR) IC 443. The observations cover a 1. °5 × 1. °5 area and allow us to investigate the overall molecular environment of the remnant. Some northern and northeastern partial shell structure of CO gas is around the remnant. One of the partial shells, about 5′ extending beyond the northeastern border of the remnant's bright radio shell, seems to just confine the faint radio halo. On the other hand, some faint CO clumps can be discerned along the eastern boundary of the faint remnant's radio halo. Connecting the eastern CO clumps, the northeastern partial shell structures, and the northern CO partial shell, we can see that a half molecular ring structure appears to surround the remnant. The LSR velocity of the half-ring structure is in the range of −5 km s−1 to −2 km s−1, which is consistent with that of the −4 km s−1 molecular clouds. We suggest that the half-ring structure of the CO emission at VLSR ∼ −4 km s−1 is associated with the SNR. The structures are possibly swept up by the stellar winds of SNR IC 443's massive progenitor. Based on the Wide-field Infrared Survey Explorer and the Two Micron All Sky Survey near-IR database, 62 young stellar object (YSO) candidates are selected within the radio halo of the remnant. These YSO candidates concentrated along the boundary of the remnant's bright radio shell are likely to be triggered by the stellar winds from the massive progenitor of SNR IC 443.
Comparative Study of Friction and Wear Performance of PEK, PEEK and PEKK Binders in Tribological Coatings

Tribological coatings are widely used in industry, particularly when the conventional oil lubrication of sliding surfaces has to be replaced by maintenance-free contacts. This work studies the tribological performance of waterborne tribological coatings based on three binders of the polyaryletherketone (PAEK) family: polyetherketone (PEK), PEEK, and polyetherketoneketone (PEKK). Even though PEEK is a well-known commercial solution for this type of tribological coatings, PEK and PEKK have never been studied in such a context. PTFE particles were added to all coatings as a solid lubricant. High thermal resistance of the binder materials was confirmed, with decomposition starting above 550 °C, under either N2 or O2 atmosphere. XRD analysis showed that PEK and PEEK are semi-crystalline after being subjected to the coating curing conditions, while PEKK is amorphous. The coatings were successfully applied with thicknesses of 20–30 µm. Tribological measurements showed that the PEK-based coating possesses a coefficient of friction (COF) of 0.08 under high load and pressure conditions (hertzian point contact), which is lower than the reference PEEK-based coating (around 0.11). The PEKK-based coating showed an impressive wear resistance with almost no wear measured compared to the 105 µm wear obtained for PEEK-based coating, while showing a similar COF. These results suggest that PEK and PEKK seem to be interesting alternatives to PEEK and should be further studied for use in tribological coatings.
Protein Acetylation Going Viral: Implications in Antiviral Immunity and Viral Infection

During viral infection, both host and viral proteins undergo post-translational modifications (PTMs), including phosphorylation, ubiquitination, methylation, and acetylation, which play critical roles in viral replication, pathogenesis, and host antiviral responses. Protein acetylation is one of the most important PTMs and is catalyzed by a series of acetyltransferases that divert acetyl groups from acetylated molecules to specific amino acid residues of substrates, affecting chromatin structure, transcription, and signal transduction, thereby participating in the cell cycle as well as in metabolic and other cellular processes. Acetylation of host and viral proteins has emerging roles in the processes of virus adsorption, invasion, synthesis, assembly, and release as well as in host antiviral responses. Methods to study protein acetylation have been gradually optimized in recent decades, providing new opportunities to investigate acetylation during viral infection. This review summarizes the classification of protein acetylation and the standard methods used to map this modification, with an emphasis on viral and host protein acetylation during viral infection.
Stability and performances synthesis of a class of Takagi–Sugeno systems with unmeasured premises: restricted-model-based approach

This paper presents the design of a robust Restricted-Model-Based control providing tools for both stability and performance analysis of a class of Single-Input-Single-Output (SISO) Takagi–Sugeno (T–S) systems. The proposed method is evaluated in terms of induced -gain (or so-called norm) to be robust to disturbances, sensor noises and uncertainties on the premise variables. Unlike the common approaches reported in the literature that consider exact premise variables, this work deals with the problem of unmeasured premises. The main results of this paper illustrate that stability and performance conditions can be evaluated by examining the feasibility of parametrised sets of linear matrix inequalities (LMIs). The proof of stability is based on the non-linear sector approach of the closed loop under Lyapunov conditions, norm and system transformations. The result is a control structure with only one parameter tuned via simple conditions. The performance and applicability of the proposed approach are illustrated through numerical simulations of an academic example.
Geodetic observation of strain accumulation in the Banda Arc region

Abstract The Banda Arc region has produced several large destructive earthquakes, some of which have been followed by tsunamis. To better understand the earthquake potential in this area, we performed a comparison between geodetic and seismic moment rates. Data were collected from 110 continuous and campaign GPS stations observed for approximately ten years. The results show that the derived velocity field indicates that the Banda Arc deformation is characterized mainly by crustal shortening caused by the interaction of the Australian, Pacific, and Philippine Sea plates. Meanwhile, the contraction strain pattern dominates the Banda Arc area except around Papuan Bird’s Head. Areas with high strain rates have a history of significant seismicity, such as the Flores-Wetar Back Arc, the area around Ambon, and the Papuan Bird’s Head. The ratio of the geodetic moment rate to the seismic moment rate in the Banda, Bird’s Head, South Sulawesi, and Sumba zones are ∼1.5–7.0, indicating a moment deficit rate. The moment deficit rate provides an equivalent earthquake potential of Mw 7.7–8.1. This potential may be related to an aseismic deformation or stress accumulation, the under-sampling of long-term earthquake rates within the seismic catalogs, or a composite of these factors.
Interactions of Cavitation Bubbles Observed by High‐Speed Imaging in Shock Wave Lithotripsy

A multi‐frame high‐speed photography was used to investigate the dynamics of cavitation bubbles induced by a passage of a lithotripter shock wave in a water tank. Solitary bubbles in the free field each radiated a shock wave upon collapse, and typically emitted a micro‐jet on the rebound following initial collapse. For bubbles in clouds, emitted jets were directed toward neighboring bubbles and could break the spherical symmetry of the neighboring bubbles before they in turn collapsed. Bubbles at the periphery of a cluster underwent collapse before the bubbles at the center. Observations with high‐speed imaging confirm previous predictions that bubbles in a cavitation cloud do not cycle independently of one another but instead interact as a dynamic bubble cluster.
Systematic Review and Meta-Analysis on Human African Trypanocide Resistance

Background Human African trypanocide resistance (HATr) is a challenge for the eradication of Human African Trypansomiaisis (HAT) following the widespread emergence of increased monotherapy drug treatment failures against Trypanosoma brucei gambiense and T. b. rhodesiense that are associated with changes in pathogen receptors. Methods: Electronic searches of 12 databases and 3 Google search websites for human African trypanocide resistance were performed using a keyword search criterion applied to both laboratory and clinical studies. Fifty-one publications were identified and included in this study using the PRISMA checklist. Data were analyzed using RevMan and random effect sizes were computed for the statistics at the 95% confidence interval. Results: Pentamidine/melarsoprol/nifurtimox cross-resistance is associated with loss of the T. brucei adenosine transporter 1/purine 2 gene (TbAT1/P2), aquaglyceroporins (TbAQP) 2 and 3, followed by the high affinity pentamidine melarsoprol transporter (HAPT) 1. In addition, the loss of the amino acid transporter (AAT) 6 is associated with eflornithine resistance. Nifurtimox/eflornithine combination therapy resistance is associated with AAT6 and nitroreductase loss, and high resistance and parasite regrowth is responsible for treatment relapse. In clinical studies, the TbAT1 proportion of total random effects was 68% (95% CI: 38.0–91.6); I2 = 96.99% (95% CI: 94.6–98.3). Treatment failure rates were highest with melarsoprol followed by eflornithine at 41.49% (95% CI: 24.94–59.09) and 6.56% (3.06–11.25) respectively. HATr-resistant phenotypes used in most laboratory experiments demonstrated significantly higher pentamidine resistance than other trypanocides. Conclusion: The emergence of drug resistance across the spectrum of trypanocidal agents that are used to treat HAT is a major threat to the global WHO target to eliminate HAT by 2030. T. brucei strains were largely resistant to diamidines and the use of high trypanocide concentrations in clinical studies have proved fatal in humans. Studies to develop novel chemotherapeutical agents and identify alternative protein targets could help to reduce the emergence and spread of HATr.
Biogenic Synthesis of Copper-Based Nanomaterials Using Plant Extracts and Their Applications: Current and Future Directions

Plants have been used for multiple purposes over thousands of years in various applications such as traditional Chinese medicine and Ayurveda. More recently, the special properties of phytochemicals within plant extracts have spurred researchers to pursue interdisciplinary studies uniting nanotechnology and biotechnology. Plant-mediated green synthesis of nanomaterials utilises the phytochemicals in plant extracts to produce nanomaterials. Previous publications have demonstrated that diverse types of nanomaterials can be produced from extracts of numerous plant components. This review aims to cover in detail the use of plant extracts to produce copper (Cu)-based nanomaterials, along with their robust applications. The working principles of plant-mediated Cu-based nanomaterials in biomedical and environmental applications are also addressed. In addition, it discusses potential biotechnological solutions and new applications and research directions concerning plant-mediated Cu-based nanomaterials that are yet to be discovered so as to realise the full potential of the plant-mediated green synthesis of nanomaterials in industrial-scale production and wider applications. This review provides readers with comprehensive information, guidance, and future research directions concerning: (1) plant extraction, (2) plant-mediated synthesis of Cu-based nanomaterials, (3) the applications of plant-mediated Cu-based nanomaterials in biomedical and environmental remediation, and (4) future research directions in this area.
An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI

Diabetes is a chronic disease that continues to be a primary and worldwide health concern since the health of the entire population has been affected by it. Over the years, many academics have attempted to develop a reliable diabetes prediction model using machine learning (ML) algorithms. However, these research investigations have had a minimal impact on clinical practice as the current studies focus mainly on improving the performance of complicated ML models while ignoring their explainability to clinical situations. Therefore, the physicians find it difficult to understand these models and rarely trust them for clinical use. In this study, a carefully constructed, efficient, and interpretable diabetes detection method using an explainable AI has been proposed. The Pima Indian diabetes dataset was used, containing a total of 768 instances where 268 are diabetic, and 500 cases are non-diabetic with several diabetic attributes. Here, six machine learning algorithms (artificial neural network (ANN), random forest (RF), support vector machine (SVM), logistic regression (LR), AdaBoost, XGBoost) have been used along with an ensemble classifier to diagnose the diabetes disease. For each machine learning model, global and local explanations have been produced using the Shapley additive explanations (SHAP), which are represented in different types of graphs to help physicians in understanding the model predictions. The balanced accuracy of the developed weighted ensemble model was 90% with a F1 score of 89% using a five-fold cross-validation (CV). The median values were used for the imputation of the missing values and the synthetic minority oversampling technique (SMOTETomek) was used to balance the classes of the dataset. The proposed approach can improve the clinical understanding of a diabetes diagnosis and help in taking necessary action at the very early stages of the disease.
COLLOIDAL SOLUTIONS OF CdS/L-CYSTEIN NANOPARTICLES: FEATURES, SYNTHESIS AND PROPERTIES

The article presents materials of the review of international and domestic scientific papers devoted to the technology of synthesis and research of properties of nanosized particles based on semiconductor material CdS, and particles of cadmium sulfide stabilized by biocompatible amino acid L-cysteine. The article mainly focuses on the results of research that reflect different methods of synthesis of nanoparticles of semiconductor materials, the main stages of their formation and maturation, the dependence of shape, size, morphology, and properties of particles on synthesis conditions, concentration, and the ratio of starting reagents in the reaction medium, the additive effect of components on studied properties of CdS / L-Cysteine nanoparticles. The goal of the paper is to establish physicochemical regularities of processes of synthesis of low-dimensional CdS-based structures with the formation of colloidal solutions of CdS/L-Cys nanocrystals with predicted properties, elucidation of correlation between thermodynamic conditions of colloidal systems formation and morphology of nanoparticles, their size, and optical properties.
Transmission and Control of SARS-CoV-2 in the Food Production Sector: A Rapid Narrative Review of the Literature

This review aimed to provide an overview of the literature assessing the extent of COVID-19 transmission in the food processing sector along with the risk factors associated with COVID-19 infection/mortality rates in this setting, and the preventive measures used to reduce transmission. An electronic search was conducted using scientific databases, including Web of Science, OVID, PubMed and MedRxiv. The search strategy identified 26 papers that met the inclusion criteria. Six of these studies were based in the UK and the country with the most papers was the USA, with a total of nine papers. Findings showed some evidence of a high transmission level of SARS-CoV-2 within some areas of the food production sector. Risk factors associated with the spread included ethnicity, poor ventilation, lack of social distancing and lack of sick pay. The preventative measures included/recommended were social distancing, testing, adequate ventilation, cleaning regimes and access to PPE. Additional research focusing on the food production sector could show the potential variations in transmission and risk between each sub-sector. Future research focusing on the application of various preventative measures and their efficacy by sub-sector would be beneficial, while further qualitative research could help provide in-depth information regarding knowledge gaps.
Physics-Based Simulation of Soft-Body Deformation Using RGB-D Data

Providing real-time interaction in an immersive environment has drawn considerable attention in the virtual training fields. Physics-based simulations are suitable for such environments; however, they require the definition and adjustment of coefficients that determine material properties, making the methods more complex and time-consuming. In this paper, we introduce a novel approach to simulating the soft-body deformation of an observed object. Using an off-the-shelf RGB-D sensor, the proposed approach tracks an object’s movement and simulates its deformation in an iterative manner. Polygonal models with different resolutions are used to improve the simulation speed and visual quality. During the simulation process, a low-resolution model is used for surface deformation using neighboring feature points detected from the sensor, and a volumetric model is added for internal force estimation. To visualize the observed model in detail, the deformed and low-resolution model is mapped to a high-resolution model using mean value coordinate interpolation. To handle topological deformations, such as cutting or tearing, a part intersected by a cutting tool is recognized by the sensor and responds to external forces. As shown in the experimental results, our approach generates convincing deformations of observed objects in real time.
Fuzzy Logic-Based Energy Management Strategy of Hybrid Electric Propulsion System for Fixed-Wing VTOL Aircraft

An energy management strategy for a series hybrid electric propulsion system designed for a fixed-wing vertical take-off and landing (VTOL) aircraft is presented in this paper. The proposed method combines an ideal operating line (IOL) and fuzzy logic. Fuzzy logic is used to dynamically and optimally allocate the output power of the generator and the battery pack according to the power requirement of the aircraft and the SOC of the battery pack. The IOL controller is used to optimize the internal combustion engine (ICE) operating point to improve the fuel economy of the system. The detailed aircraft model and energy system model are established. The flight process of a 100 kg scale VTOL aircraft under a typical mission profile is simulated. The simulation results show that running the ICE based on IOL can greatly improve its efficiency The introduction of fuzzy logic to optimize the power allocation of the generator and battery pack improves the overall efficiency of the system. The feasibility and effectiveness of the energy management strategy proposed in this paper are verified, and the design ideas and analysis methods are provided for the energy management of a hybrid electric aircraft.
Methyl Jasmonate Induces Genes Involved in Linalool Accumulation and Increases the Content of Phenolics in Two Iranian Coriander (Coriandrum sativum L.) Ecotypes

The medicinal herb coriander (Coriandrum sativum L.), with a high linalool (LIN) content, is widely recognized for its therapeutic benefits. As a novel report, the goals of this study were to determine how methyl jasmonate (MeJA) affects total phenolic content (TPC), LIN content, flavonoid content (TFC), and changes in gene expression involved in the linalool biosynthesis pathway (CsγTRPS and CsLINS). Our findings showed that, in comparison to the control samples, MeJA treatment substantially enhanced the TPC, LIN, and TFC content in both ecotypes. Additionally, for both Iranian coriander ecotypes, treatment-induced increases in CsγTRPS and CsLINS expression were connected to LIN accumulation in all treatments. A 24 h treatment with 150 µM MeJA substantially increased the LIN content in the Mashhad and Zanjan ecotypes, which was between 1.48 and 1.69 times greater than that in untreated plants, according to gas chromatography–mass spectrometry (GC-MS) analysis. Our findings demonstrated that MeJA significantly affects the accumulation of LIN, TPC, and TFC in Iranian C. sativum treated with MeJA, which is likely the consequence of gene activation from the monoterpene biosynthesis pathway. Our discoveries have improved the understanding of the molecular mechanisms behind LIN synthesis in coriander plants.
Osteopenia and Sarcopenia as Potential Risk Factors for Surgical Site Infection after Posterior Lumbar Fusion: A Retrospective Study

Surgical site infection (SSI) is a feared complication in spinal surgery, that leads to lower outcomes and increased healthcare costs. Among its risk factors, sarcopenia and osteopenia have recently attracted particular interest. The purpose of this article is to evaluate the influence of sarcopenia and osteopenia on the postoperative infection rate in patients treated with posterior fusion for degenerative diseases of the lumbar spine. This retrospective study included data from 308 patients. Charts were reviewed and central sarcopenia and osteopenia were evaluated through magnetic resonance images (MRI), measuring the psoas to lumbar vertebral index (PLVI) and the M score. Multivariate linear regression was performed to identify independent risk factors for infection. The postoperative SSI rate was 8.4%. Patients with low PLVI scores were not more likely to experience postoperative SSI (p = 0.68), while low M-score patients were at higher risk of developing SSI (p = 0.04). However, they did not generally show low PLVI values (p = 0.5) and were homogeneously distributed between low and high PLVI (p = 0.6). Multivariate analysis confirmed a low M score to be an independent risk factor for SSI (p = 0.01). Our results suggest that osteopenia could have significant impact on spinal surgery, and prospective studies are needed to better investigate its role.
Bayesian Inference for Thermal Model of Synchronous Generator Part—II: State Estimation

This paper is the Part II of the series on parameter and state estimation using the Bayesian inference for a thermal model of a synchronous generator. Part I is about Parameter Estimation. In this paper, state estimation of rotor copper and air-gap temperatures of the synchronous generator are performed using Bayesian inference. Estimators such as Unscented Kalman Filter (UKF), Ensemble Kalman Filter (EnKF), and Particle Filters (PFs) with different sampling algorithms, are compared based on the estimation accuracy and computational time. The inferences are drawn for the posterior distributions of the state, dispersion of particles, error convergence and particle realizations of the state estimator, choice, and the computational effort of the estimators. Results show that UKF has fair estimation accuracy with the fastest computational time as compared to other estimators.