Introducing Structures from Hexagonal Borophene to Nitrophene and Their Thermal Conductivity Investigation Using a Reactive Molecular Dynamics Simulation.

In the present work, the thermal conductivity (TC) of hexagonal structures of boron nitride and borophene was investigated by a reactive molecular dynamics (MD) simulation. Also, to figure out the effect of the boron and nitrogen in the hexagonal structure, five other hypothetical structures were created (in addition to the structure of boron nitride and borophene) and their structures were represented by the symbol BxNy, where x refers to the number of boron atoms and y refers to the number of nitrogen atoms. In this regard, B6N0 refers to borophene, B3N3 is boron nitride, and B0N6 is called nitrophene. The TC of B6N0 and B3N3 structures was calculated and compared with the literature values. Besides these two compounds, the five other structures have not been experimentally synthesized yet, so the TC of the five other hypothetical structures were predicted in the present work. The lowest TC belonged to B3N3, and the highest one was for B0N6. Based on the inherent potential of reactive MD simulation, during TC calculation, atoms' coordination and partial charges are changed and new bonds, rings, or even defects were automatically created on the surfaces. The coordination contour map showed that in B3N3, the atoms have collective movements like a large and single wave, while B0N6 and B6N0 have small group movements as vibrations. So, it became clear that the higher stability of structures caused more curved movements. In addition, the contour map of partial charges is calculated, and the results showed that the high differences in partial charge between atoms in the structure cause high TC, while small charge differences in the structure inhibit heat transfer and cause lower TC.

Effectiveness of Opioid Analgesic Medicines Prescribed in or at Discharge From Emergency Departments for Musculoskeletal Pain : A Systematic Review and Meta-analysis.

BACKGROUND: The comparative benefits and harms of opioids for musculoskeletal pain in the emergency department (ED) are uncertain. PURPOSE: To evaluate the comparative effectiveness and harms of opioids for musculoskeletal pain in the ED setting. DATA SOURCES: Electronic databases and registries from inception to 7 February 2022. STUDY SELECTION: Randomized controlled trials of any opioid analgesic compared with placebo or a nonopioid analgesic administered or prescribed to adults in or on discharge from the ED. DATA EXTRACTION: Pain and disability were rated on a scale of 0 to 100 and pooled using a random-effects model. Certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. DATA SYNTHESIS: Forty-two articles were included (n = 6128). In the ED, opioids were statistically but not clinically more effective in reducing pain in the short term (about 2 hours) than placebo and paracetamol (acetaminophen) but were not clinically or statistically more effective than nonsteroidal anti-inflammatory drugs (NSAIDs) or local or systemic anesthetics. Opioids may carry higher risk for harms than placebo, paracetamol, or NSAIDs, although evidence is very uncertain. There was no evidence of difference in harms associated with local or systemic anesthetics. LIMITATIONS: Low or very low GRADE ratings for some outcomes, unexplained heterogeneity, and little information on long-term outcomes. CONCLUSION: The risk-benefit balance of opioids versus placebo, paracetamol, NSAIDs, and local or systemic anesthetics is uncertain. Opioids may have equivalent pain outcomes compared with NSAIDs, but evidence on comparisons of harms is very uncertain and heterogeneous. Although factors such as route of administration or dosage may explain some heterogeneity, more work is needed to identify which subgroups will have a more favorable benefit-risk balance for one analgesic over another. Longer-term pain management once dose thresholds are reached is also uncertain. PRIMARY FUNDING SOURCE: None. (PROSPERO: CRD42021275293).

Preparation of dual-use GPTES@ZnO photocatalyst from waste warm filter cake and evaluation of its synergic photocatalytic degradation for air-water purification.

Organic pollutants are the most critical threats to the health of air and water resources. On this basis, fabricating a photocatalytic acrylic film with dual-use (i.e. removing benzene from air and MB/MO dyes from water) was aimed in this research. For this purpose, waste warm filter cake (WWFC) was used to extract zinc from it. Zinc element was separated from WWFC by a basic leaching method and acidified to prepare zinc oxide nanoparticles. In the following, a simple hydrothermal method was used to increase the surface functionality of the extracted ZnO nanoparticles in order to establish active reaction sites for reaction to silane coupling agent and increase in the holes that were prepared during photo-excitation. Thereafter, the nanoparticles were modified with 3-glycidoxypropyltriethoxysilane (GPTES) at different concentrations. The band gap of the modified nanoparticles decreased from 3.25 to 3.1 eV by surface modification. The photocatalytic performance of ZnO nanoparticles was assessed by degradation of MB and MO aqueous solution (50 ppm) under simulated UV/Visible irradiations. MB and MO were degraded 91 and 60% under UV light and 65 and 50% under visible light after 150 min of irradiation. The photo degradation rate increased after adding carboxy methyl cellulose (CMC) surfactant to methylene blue and adding cocamide-dea (CDE-G) surfactant to methyl orange. The results confirmed that the green surfactants improve the dispersion and surface interaction of the modified nanoparticles in the dyes solution and cause more electron charge transfer which creates effective photocatalytic sites. The prepared nanocomposite films were placed in a photo-reactor to remove gaseous benzene from air under UV/visible irradiation. Gas chromatography (GC) results showed that the modified nanoparticles removed up to 35.25 and 20.34% of benzene from air. Colorimetric analysis (ΔE*) showed that the acrylic film contained modified nanoparticles degraded 91 and 82% of MB, and 85 and 76% of MO under UV/visible lights, respectively. In the end, it can be said that these photocatalytic films are able to remove environmental pollution in air and water.

A Review of Synthesis Methods, Modifications, and Mechanisms of ZnO/TiO2-Based Photocatalysts for Photodegradation of Contaminants.

The environment being surrounded by accumulated durable waste organic compounds has become a critical crisis for human societies. Generally, organic effluents of industrial plants released into the water source and air are removed by some physical and chemical processes. Utilizing photocatalysts as cost-effective, accessible, thermally/mechanically stable, nontoxic, reusable, and powerful UV-absorber compounds creates a new gateway toward the removal of dissolved, suspended, and gaseous pollutants even in trace amounts. TiO2 and ZnO are two prevalent photocatalysts in the field of removing contaminants from wastewater and air. Structural modification of the photocatalysts with metals, nonmetals, metal ions, and other semiconductors reduces the band gap energy and agglomeration and increases the affinity toward organic compounds in the composite structures to expand their usability on an industrial scale. This increases the extent of light absorbance and improves the photocatalytic efficiency. Selecting a suitable synthesis method is necessary to prepare a target photocatalyst with distinct properties such as high specific surface area, numerous surface functional groups, and an appropriate crystalline phase. In this Review, significant parameters for the synthesis and modification of TiO2- and ZnO-based photocatalysts are discussed in detail. Several proposed mechanistic routes according to photocatalytic composite structures are provided. Some electrochemical analyses using charge carrier trapping agents and delayed recombination help to plot mechanistic routes according to the direction of photoexcited species (electron-hole pairs) and design more effective photocatalytic processes in terms of cost-effective photocatalysts, saving time and increasing productivity.

Silane modification of TiO2 nanoparticles and usage in acrylic film for effective photocatalytic degradation of methylene blue under visible light.

To fabricate a photocatalytic acrylic paint, TiO2 nanoparticles were surface modified by a bi-functional amino silane (i.e. bis-3-(aminopropyltriethoxysilane)) at different concentrations and applied at 1, 3 and 5 wt% to an acrylic latex. It was found that the surface modification of nano TiO2 enhanced its specific surface area about 42%. The tensile properties of the pristine and nanocomposite acrylic films were assessed. The photocatalytic degradation of aqueous solution and stain of methylene blue (MB) were evaluated (under solar, visible, and UV illuminations) by nanoparticles and nanocomposites, respectively. Results showed that incorporating 3 wt% of the pure and modified nano TiO2 to arylic film caused 62 and 144% increment in the tensile strength. The modified nanoparticles showed higher MB degradation contents under UV, visible and solar irradiation (82, 70, 48%, respectively). The addition of pure and modified nanoparticles to the acrylic film caused decrement in the water contact angle from 84 to 70 and 46°, respectively. It also caused considerable enhancement in the glass transition temperature (Tg) of acrylic film compared to the pristine and pure nanocomposite films (i.e. about 17 and 9 °C, respectively). Furthermore, it was found that the modified nanocomposite caused more color change of MB stain (65%).

Achieving outstanding mechanical/bonding performances by epoxy nanocomposite as concrete-steel rebar adhesive using silane modification of nano SiO2.

Anchoring steel rebar in concrete structures is a common method in the building and construction industry. This research focuses on improving the mechanical/bonding properties of the prepared epoxy nanocomposite adhesive using surface treatment of SiO2 nano fillers by glycidoxypropyltrimethoxysilane (GPTMS). For this purpose, the nano silica particles were silanized via a facile sol-gel method at silane concentrations of 1, 5, 10 and 20X (i.e. X is stoichiometric silane concentration). The nanoparticles were characterized carefully by FTIR, TGA, XRD and XPS techniques. It was found that the highest GPTMS grafting ratio was obtained at silane concentration of 10X. The pure and silanized nanoparticles were added to a two-pack epoxy resin and were compared for tensile and compressive properties. It was found that surface modification of nano silica caused improvement in the strength, modulus, compressive strength and compressive modulus by 56, 81, 200 and 66% compared to the pristine epoxy adhesive and also 70, 20, 17 and 21% compared to the pure nano silica containing adhesive. It also caused 40 and 25% improvement in the pullout strength, 33 and 18% enhancement in the pullout displacement and 130 and 50% in adhesion energy compared to the pristine and raw silica-containing adhesives, respectively.

Using a facile method to predict properties of recycled waste nitrile rubber (NBR) through devulcanization.

To prepare a reliable method for predicting the properties of devulcanized rubbers a nitrile rubber (NBR) compound was prepared and masticated before vulcanization for 0, 30 and 60 min under mechanical stress to prepare NBRs with different molecular weights. The masticated samples were vulcanized at different accelerator contents to prepare damples with different crosslink densities. The physical/mechanical/thermal properties (i.e. crosslink density, tensile strength, modulus, modulus at 100 and 300% elongation, elongation at break, hardness, curing behavior and molecular weight) of the samples were experimentally evaluated. In the next step, the prepared samples were assumed as devulcanized NBRs that underwent chains scission (masticated samples) or crosslinks breakage (vulcanized at different accelerator contents). On this basis, hypothetical devulcanization routes were considered between each sample that underwent chains scission or crosslinks breakage. Based on the results, numerical relationships between the number of chains scission or crosslinks breakage and decrease in the properties were obtained. Finally, the numerical reationships were used to calculate the properties of the samples that underwent both of chains scission and crosslinks breakage. It was found that the calculated contents of hardness, modulus at 100% and molecular weight (MZ) using the prepared method were very close to the evaluated ones.

Effects of functionalization and silane modification of hexagonal boron nitride on thermal/mechanical/morphological properties of silicon rubber nanocomposite.

Hexagonal boron nitride (h-BN) nanoparticles could induce interesting properties to silicone rubber (SR) but, the weak filler-matrix interfacial interaction causes agglomeration of the nanoparticles and declines the performance of the nanocomposite. In this work, h-BN nanoparticles were surface modified using vinyltrimethoxysilane (VTMS) at different concentrations. Before silane modification, h-BN nanoparticles were hydroxylated using 5 molar sodium hydroxide. The nanoparticles were characterized to assess success of silane grafting. The pure and modified h-BN nanoparticles were applied at 1, 3 and 5 wt% to HTV silicon rubber (SR). The curing, thermal, mechanical and morphological properties and hydrophobicity of the nanocomposites were evaluated. The morphology of the SR nanocomposites was characterized using AFM and FE-SEM analysis. It was found that silane grafting on the h-BN nanoparticles improves crosslink density but declines curing rate index (CRI) of the SR nanocomposite (at 5 wt% loading content) by 0.7 (dN m) and 3.5%, respectively. It also increased water contact angle of the nanocomposites from 97.5° to 107°. The improved nanoparticle-rubber interfacial interactions caused better dispersion of h-BN nanoparticles in SR matrix (at 5 wt%) that enhanced the elongation at break, modulus at 300% and Tg of the SR nanocomposites.

Investigating the use of titanium dioxide (TiO2) nanoparticles on the amount of protection against UV irradiation.

In this study, three samples of commercial titanium dioxide nanoparticles (TiO2) in different sizes were used to investigate their effect on the formulation of sunscreen creams. The aim was to evaluate their role in the performance of sunscreens (i.e. SPF, UVAPF, and critical wavelength). Then the particle size of these samples was determined by photon correlation spectroscopy methods. As a result, the size of primary particles was reduced by using milling and homogenization methods at different times. The results showed that the particle size of samples TA, TB, and TC in the ultrasonic homogenizer decreased from 966.4, 2745.8, and 2471.6 nm to 142.6, 254.8, and 262.8 nm, respectively. These particles were used in the pristine formulation. Then the functional characteristics of each formulation were determined by standard methods. TA had the best dispersion in cream compared to other samples due to its smaller size (i.e. 142.6 nm). For each formulation, two important parameters, including pH and TiO2 dosage, were investigated in different states. The results showed that the formulations prepared with TA had the lowest viscosity compared to formulations containing TB and TC. SPSS 17 statistical software analysis of variance showed that the performance of SPF, UVAPF and λc in formulations containing TA had the highest levels. Also, the sample containing TAU with the lowest particle size values had the highest protection against UV rays (SPF). According to the photocatalytic functionality of TiO2, the photodegradation of methylene blue in the presence of each nanoparticle of TiO2 was studied. The results showed that smaller nanoparticles (i.e. TA) had more photocatalytic activity under UV-Vis irradiation during 4 h (TA (22%) > TB (16%) > TC (15%)). The results showed that titanium dioxide can be used as a suitable filter against all types of UVA and UVB rays.

Cross-cultural adaptation, validity, and reliability of the pediatric constipation score-parent report in pediatric functional constipation in an Iranian population.

Aim: We evaluated the Persian version of the pediatric constipation score-parent report (PCS) validity and reliability. Background: Functional constipation in children results in physical and psychological problems. Therefore, it is necessary to utilize a questionnaire to assess the health-related quality of life in children with chronic constipation. Methods: First, our team translated the English version of the questionnaire into the Persian language. Second, the psychometric properties of the Persian version were collected in 149 children with functional constipation referred to a pediatrics hospital by an expert team. We assessed content validity (CV) through the CV index (CVI) and CV ratio (CVR). The construct validity was evaluated by exploratory factor analysis, and reproducibility was tested based on test-retest reliability using the intra-class correlation coefficient (ICC). Internal consistency was calculated using Cronbach's α. we also evaluated the ceiling or floor. Results: Results showed acceptable CVI in relevancy, clarity, and simplicity, acceptable CVR for all items, moderate internal consistency (Cronbach's alpha=0.548), and almost perfect reproducibility (ICC=0.93). No ceiling or floor effect was seen. Conclusion: The Persian version of PCS showed good validity and reliability in children with functional constipation in Iran. Therefore, we can use it in clinical and research domains in Persian-speaking countries.

Chemical/photochemical functionalization of polyethylene terephthalate fabric: effects on mechanical properties and bonding to nitrile rubber.

The aim of this work is to compare the effects of chemical and photochemical functionalization on the mechanical properties of PET fabric and its adhesion to nitrile rubber (NBR). The photochemical functionalization was performed by UV irradiation of PET fabric in the presence of glutaric acid peroxide at a temperature of 60 °C for different exposure times (i.e. 60, 90 and 120 min). The chemical functionalization (i.e. hydrolysis) of PET fabrics was performed by NaOH solution at a temperature of 60 °C for different times (i.e. 60, 120, 240 and 360 min). The tensile properties of the functionalized fibers were also evaluated. The functionalized PETs were evaluated for H-pull and T-peel adhesion to NBR. It was found that both treatment methods created functional groups on the PET surface. However, carboxylation of PET under GAP/UV irradiation generated much more OH groups on the PET surface (i.e. 4.5 times). The hydrolysis of PET in NaOH solution for more than 60 min caused a significant decrement in the tensile strength contrary to carboxylation under GAP/UV irradiation. It was also found that pullout and T-peel adhesions to NBR decreased in the case of hydrolysis of PET while they increased about 33 and 12% for GAP/UV irradiated PET, respectively.

Comparison of Open and Ultrasound-Guided Placement of Central Venous Catheter in Children Weighing Less Than Five Kilograms; A Randomized Clinical Trial.

OBJECTIVES: Ultrasound is currently utilized to locate the internal jugular vein (IJV), reduce the complications of catheter placement, and increase the likelihood of accessing IJV. Therefore, the aim of the present study was to evaluate the effectiveness of ultrasound in reducing complications during catheter placement in children weighing less than 5 kg. MATERIALS AND METHODS: The current randomized clinical trial was performed on 111 children weighing less than 5 kg who required a central venous catheter (CVC). Children were divided into two groups: in the first group (Seldinger group; n = 55), a CVC was inserted using the Seldinger wire method under ultrasound guidance, and in the second group (open surgical cutdown (OSC); n = 56), the catheter was inserted via the open method. Two weeks after catheter placement, patients were evaluated for thrombosis, catheter occlusion, catheter tip migration, infection, catheter removal, and catheter dysfunction. RESULTS: The success rate of catheter placement in the ultrasound-guided method was 85.5%. The incidence of thrombosis (3.6% vs. 5.4%), infection (1.8% vs. 7.4%), and bleeding (zero vs. 3.6%) was lower in the Seldinger group, but the difference was not significant (p ˃ 0.05). Hematoma (7.3% vs. 3.6%) occurred less frequently in the patients of the OSC group (p = 0.33). Hemothorax, pneumothorax, catheter migration, and occlusion did not occur in any of the patients. In the OSC group, two deaths (3.6%) occurred due to underlying diseases. CONCLUSION: When ultrasound is used to insert a CVC in children weighing less than 5 kg, the incidence of complications is not significantly different compared to when the open method is employed.

Personalized predictions of adverse side effects of the COVID-19 vaccines.

Background: Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was designed to generate personalized predictions of the most common adverse side effects following injection of six different COVID-19 vaccines based on personal and health-related characteristics. Methods: Prospective data of adverse side effects following COVID-19 vaccination in 19943 participants from Iran and Switzerland was utilized. Six vaccines were studied: The AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2, and the mRNA-1273 vaccine. The eight side effects were considered as the model output: fever, fatigue, headache, nausea, chills, joint pain, muscle pain, and injection site reactions. The total input parameters for the first and second dose predictions were 46 and 54 features, respectively, including age, gender, lifestyle variables, and medical history. The performances of multiple ML models were compared using Area Under the Receiver Operating Characteristic Curve (ROC-AUC). Results: The total number of people receiving the first dose of the AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2, and mRNA-1273 were 6022, 7290, 5279, 802, 277, and 273, respectively. For the second dose, the numbers were 2851, 5587, 3841, 599, 242 and 228. The Logistic Regression model for predicting different side effects of the first dose achieved ROC-AUCs of 0.620-0.686, 0.685-0.716, 0.632-0.727, 0.527-0.598, 0.548-0.655, 0.545-0.712 for the AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2 and mRNA-1273 vaccines, respectively. The second dose models yielded ROC-AUCs of 0.777-0.867, 0.795-0.848, 0.857-0.906, 0.788-0.875, 0.683-0.850, and 0.486-0.680, respectively. Conclusions: Using a large cohort of recipients vaccinated with COVID-19 vaccines, a novel and personalized strategy was established to predict the occurrence of the most common adverse side effects with high accuracy. This technique can serve as a tool to inform COVID-19 vaccine selection and generate personalized factsheets to curb concerns about adverse side effects.

Recycling NR/SBR waste using probe sonication as a new devulcanizing method; study on influencing parameters.

In this work, a vulcanized blend of natural rubber (NR) and styrene butadiene rubber (SBR) (i.e. at weight ratio of 50 : 50) as a model for tire rubber was devulcanized using probe sonication. The effect of processing parameters such as sonication media, power, temperature and time on sol/gel contents and devulcanization percent of rubbery samples was investigated. Moreover, the influence of pre-immersion of vulcanized NR/SBR samples in different liquids (i.e. water, oil and toluene) was assessed for different sonication times (i.e. 10 to 60 min) and powers (i.e. 30 to 60 W). It was found that pre-immersion of rubber particles in oil significantly increased the devulcanization percent. The optimum conditions for devulcanization of the NR/SBR blend via probe sonication were found to be 60 Watts, 20 min, oil and 24 h for sonication power, sonication time, pre-immersion/sonication media and pre-immersion time, respectively. The highest obtained devulcanization percent in this step was about 40%. The effects of two devulcanizing chemical agents (i.e. diphenyl disulfide and VitaX) on devulcanization performances of the samples were also studied. Results showed that higher devulcanization percent (i.e. about 52%) was obtained by using VitaX. It was also observed that VitaX significantly improved re-vulcanization speed (i.e. cure rate index) and decreased scorch time. It was also found that lower content of VitaX (i.e. 0.6 phr) caused better curing properties but lower mechanical properties compared to the higher content (i.e. 1.2 phr).

Synthesis of vinyl-based silica nanoparticles by sol-gel method and their influences on network microstructure and dynamic mechanical properties of nitrile rubber nanocomposites.

Non-agglomeration and dispersion of silica nanoparticles in polymers and their interfacial interactions to polymer matrix are the most important factors that influence nanocomposites performance. In this work, vinyltriethoxysilane (VTES) as a low VOC emission coupling agent was used for surface modification of silica nanoparticles to prepare better dispersion in nitrile rubber (NBR) and improve its interfacial interactions to silica nanoparticles. The results of X-ray photoelectron spectroscopy, thermogravimetric analysis and Fourier transform infra-red spectroscopy demonstrated successful attachment of VTES molecules on the surface of silica nanoparticles. Dispersion of the modified silica nanoparticles in NBR matrix was studied using field emission scanning electron microscopy and rubber process analysis. Results demonstrated that VTES significantly improved dispersion of nanoparticles in rubbery matrix. The bound rubber content showed that VTES effectively built a bridge between the silica nanoparticles and the rubber matrix that led to promising mechanical performances and strong interfacial interactions. Effect of nanoparticle content on the mechanical performances (static/dynamic) of the NBR was evaluated. It was found that higher modulus and reinforcement indices was obtained at 3 and 5 wt% of nanoparticles. Moreover, these composites had extremely low rolling resistance, the best wet skid resistance and the lowest Heat-Build up.

Laparoscopic and open surgery methods in managing surgical intussusceptions: A randomized clinical trial of postoperative complications.

PURPOSE: To compare postoperative complications of laparoscopic surgery (LS) with open surgery (OS) in surgical intussusception patients. METHODS: From March 2015 to February 2018, infants between 6 to 24 months old had the clinical and sono-graphical signs of intussusception enrolled in this double-blind, randomized clinical trial. We divided surgical intussusception patients into two groups. In the LS group, we evaluated patients by direct laparoscopic observation, on-table hydrostatic enema, and mechanical reduction of intussusception. In the OS group, we performed the conventional technique. These patients were followed for 2 years after procedures for comparison of postoperative complications between the two groups. RESULTS: We had 52 patients who needed surgical exploration (26 in each group). There were four (15%) and seven (27%) patients with self-reduced intussusception in LS and OS groups, respectively. The conversion rate was 31% (eight cases). Five cases (19%) in the LS group and four cases (15%) in the OS group needed bowel resections. Operating time was longer in the LS group (P ≤ 0.006), and the postoperative complication rate was higher in the OS group (P ≤ 0.021). DISCUSSION: Laparoscopy is a screening tool to determine the need for OS in surgical intussusception patients. Laparoscopy reduces the incidence of OS and its complications.

Improving the Mechanical/Anticorrosive Properties of a Nitrile Rubber-Based Adhesive Filled with Cerium Oxide Nanoparticles Using a Two-Step Surface Modification Method.

To prepare a nanocomposite adhesive based on nitrile rubber (NBR) with excellent mechanical/anticorrosion properties, cerium oxide (CeO2) nanoparticles were grafted with bis-[3-(triethoxysilyl)propyl]tetrasulfide silane (TESPT) at different concentrations (i.e., 1, 5, 10, and 20 times the stoichiometric content). The surface-modified nanoparticles were characterized by Fourier transform infrared spectroscopy (FTIR), ζ-potential, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), and field emission scanning electron microscopy (FE-SEM) techniques. The results showed that the steaming process resulted in an increase in the grafting ratio (R g) by 2.35 times. Pure and modified cerium oxide nanoparticles were added at 1.5, 4.5, and 7.5 wt % to a mixture of a phenolic resin and NBR compound to prepare adhesive samples. The prepared adhesives were evaluated for curing behavior and thermomechanical properties. The morphology of the adhesives was also characterized using SEM analysis. The bonding of adhesives to steel plates was measured by a cathodic disbonding test. The adhesive-coated steel plates were evaluated for anticorrosion performances using a salt spray test. It was found that surface-modified hydrothermally steamed CeO2 nanoparticles that had the highest silane grafting ratio enhanced the anticorrosion properties and cathodic disbonding of NBR-based adhesives. The curing rate index (CRI) and crosslinking of the NBR compound were enhanced using the modified and steamed nanoparticles. This also improved the interfacial interactions between rubber chains and nanoparticle surface, resulting in a 6 °C increase in the glass-transition temperature (T g) of NBR compared to the pristine rubber.

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU.

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies. Objectives: Early prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission. Methods: We retrospectively studied 797 patients diagnosed with COVID-19 in Iran and the United Kingdom (U.K.). To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Several machine learning algorithms, including Random Forest (RF), logistic regression, gradient boosting classifier, support vector machine classifier, and artificial neural network algorithms were utilized to build classification models. The impact of each marker on the RF model predictions was studied by implementing the local interpretable model-agnostic explanation technique (LIME-SP). Results: Among 66 documented parameters, 15 factors with the highest predictive values were identified as follows: gender, age, blood urea nitrogen (BUN), creatinine, international normalized ratio (INR), albumin, mean corpuscular volume (MCV), white blood cell count, segmented neutrophil count, lymphocyte count, red cell distribution width (RDW), and mean cell hemoglobin (MCH) along with a history of neurological, cardiovascular, and respiratory disorders. Our RF model can predict patient outcomes with a sensitivity of 70% and a specificity of 75%. The performance of the models was confirmed by blindly testing the models in an external dataset. Conclusions: Using two independent patient datasets, we designed a machine-learning-based model that could predict the risk of mortality from severe COVID-19 with high accuracy. The most decisive variables in our model were increased levels of BUN, lowered albumin levels, increased creatinine, INR, and RDW, along with gender and age. Considering the importance of early triage decisions, this model can be a useful tool in COVID-19 ICU decision-making.

Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning.

Background: Early prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation strategies, and thus reduce the prevalence of the disease. Such publicly accessible prediction models are lacking, however. Methods: Based on a comprehensive evaluation of existing machine learning (ML) methods, we created two models based solely on the age, gender, and medical histories of 23,749 hospital-confirmed COVID-19 patients from February to September 2020: a symptom prediction model (SPM) and a mortality prediction model (MPM). The SPM predicts 12 symptom groups for each patient: respiratory distress, consciousness disorders, chest pain, paresis or paralysis, cough, fever or chill, gastrointestinal symptoms, sore throat, headache, vertigo, loss of smell or taste, and muscular pain or fatigue. The MPM predicts the death of COVID-19-positive individuals. Results: The SPM yielded ROC-AUCs of 0.53-0.78 for symptoms. The most accurate prediction was for consciousness disorders at a sensitivity of 74% and a specificity of 70%. 2,440 deaths were observed in the study population. MPM had a ROC-AUC of 0.79 and could predict mortality with a sensitivity of 75% and a specificity of 70%. About 90% of deaths occurred in the top 21 percentile of risk groups. To allow patients and clinicians to use these models easily, we created a freely accessible online interface at www.aicovid.net. Conclusion: The ML models predict COVID-19-related symptoms and mortality using information that is readily available to patients as well as clinicians. Thus, both can rapidly estimate the severity of the disease, allowing shared and better healthcare decisions with regard to hospitalization, self-isolation strategy, and COVID-19 vaccine prioritization in the coming months.

Sol-gel synthesis of carbon-doped TiO2 nanoparticles based on microcrystalline cellulose for efficient photocatalytic degradation of methylene blue under visible light.

Carbon-doped titanium dioxide photocatalyst with improved performance in visible light was prepared via the typical sol-gel method. Microcrystalline cellulose (MCC) was used as carbon elements source. The prepared pure and carbon-doped TiO2 samples were calcined at 400-650°C in air and the effect of annealing temperature on the stability of carbon ions was investigated. EDX analysis showed the presence of 5.66 wt.% carbon atoms in TiO2 nanoparticles formed on MCC, which was attributed to the doping of carbon atoms in TiO2 lattice. Carbon doping was also confirmed by Raman spectroscopy. According to the UV-VIS DRS analysis, the band gap of TiO2 particles decreased from 2.96 to 2.71 eV in pure and carbon-doped TiO2, respectively. Therefore the visible light absorbance increased to 15.05% compared to 0% absorbance in pure TiO2. The heat treatment of carbon-doped TiO2 nanostructures showed that carbon element could escape from the O-Ti-O lattice at temperatures higher than 600°C. According to the SEM images, synthesis of TiO2 in presence of MCC also limited the growth of TiO2 nanoparticles and controlled the morphology and aggregation of nanoparticles. Carbon doping improved the photocatalytic performance of TiO2 photocatalyst compared to the pure nanoparticles in degradation of methylene blue in the aqueous phase. Carbon-doped TiO2 attained the efficiency of 56.25%, 51.18% and 62.95% under UV, visible and solar lights, respectively, compared to 28.43%, 6.36% and 33.65% related to the pure TiO2.