Order Rate Research Articles

Novel method for synthesizing high S-bearing hybrid sorbent for efficient silver binding – Characterization, testing, and application to metal recovery from X-ray films

The reaction of thiocarbazide with pentaerythritol tetrakis(3-mercaptopropionate) in the presence of mesoporous silica beads allows producing a composite sorbent (PTMF-SiO2) with high affinity for silver. The high density of both N- and S-based reactive groups (about 5 mmol g−1) explains sorption capacities as high as 3 mmol Ag g−1 at pH 6. The sorption mechanisms are correlated to the pH effect, and to FTIR and XPS spectroscopic analyses. The sorption is endothermic and spontaneous, and the sorption isotherms are successfully modeled using the Temkin equation. Uptake kinetics are fitted by the pseudo-first order rate equation: the equilibrium is reached in 20–30 min. Ultrasonic treatment allows slightly increasing both kinetics (apparent rate coefficient k1 is almost doubled) and sorption capacities (by less than 7 %). Silver (being a soft acid) preferentially reacts with soft bases; this may explain the selective removal of Ag(I) by PTMF-SiO2 against base metals and alkali or alkaline earth metals (in multicomponent equimolar solutions). The sorbent shows remarkable recycling stability (for at least 5 cycles): complete desorption is achieved in ≈20 min with 0.3 M HNO3 solution and the loss in sorption does not exceed 2.5 % at the fifth recycling. Finally, the sorbent is successfully applied to silver recovery from acidic leachates of spent X-ray films (from different hospitals from Hengyang, China), as a case study. Silver is selectively recovered with high efficiency (>96 %) (together with Cu(II), to a lesser extent).

Tipping in a low-dimensional model of a tropical cyclone

A presumed impact of global climate change is the increase in frequency and intensity of tropical cyclones. Due to the possible destruction that occurs when tropical cyclones make landfall, understanding their formation should be of mass interest. In 2017, Kerry Emanuel modeled tropical cyclone formation by developing a low-dimensional dynamical system which couples tangential wind speed of the eye-wall with the inner-core moisture. For physically relevant parameters, this dynamical system always contains three fixed points: a stable fixed point at the origin corresponding to a non-storm state, an additional asymptotically stable fixed point corresponding to a stable storm state, and a saddle corresponding to an unstable storm state. The goal of this work is to provide insight into the underlying mechanisms that govern the formation and suppression of tropical cyclones through both analytical arguments and numerical experiments. We present a case study of both rate and noise-induced tipping between the stable states, relating to the destabilization or formation of a tropical cyclone. While the stochastic system exhibits transitions both to and from the non-storm state, noise-induced tipping is more likely to form a storm, whereas rate-induced tipping is more likely to cause the storm to destabilize. In fact, rate-induced tipping can never lead to the formation of a storm when acting alone. When rate-induced tipping causes the storm to destabilize, a striking result is that both wind shear and maximal potential velocity have to increase at a substantial rate in order to affect tipping away from the active hurricane state. For storm formation through noise-induced tipping, we identify a specific direction along which the non-storm state is most likely to get activated.

Resuscitation of people with a do-not-resuscitate order: When does it happen and what are the outcomes?

BackgroundDo-not-resuscitate (DNR) orders allow competent individuals to state their wishes to not receive resuscitation. Despite the existence of a DNR order, resuscitative efforts may still occur. MethodsThe statewide out-of-hospital cardiac arrest (OHCA) registry in Victoria, Australia (population 6.5 million) identified rates of DNR orders and resuscitative efforts in ≥60-year-olds from 2006-2021. ResultsOf 47,322 patients ≥60 years old with OHCA, 2,688 (5.7%) had a DNR order. DNR order was communicated to emergency call-takers in only 332 (12.4%) cases. Bystander resuscitation was commenced in 1,074 (40.0%) patients, with EMS terminating efforts in 346 (32.2%) patients on arrival but commencing resuscitation in 189 others. Strongest predictors of bystander resuscitation were shockable rhythm (OR 7.75, 95% CI 5.04–11.9) and OHCA in public location (OR 4.8, 95% CI 2.0–11.3). Predictors of EMS terminating resuscitation efforts were OHCA in residential aged care facility (OR 1.93, 95% CI 1.47–2.5) and older age (OR 1.02, 95% CI 1.00–1.04). Transfer to hospital was undertaken in 107 patients, with strongest predictors being return of spontaneous circulation (OR 91.1, 95% CI 51.7–160.7) and witnessed OHCA (OR 7.5, 95% CI 3.9–14.5). Only 7 (0.3%) transported patients survived to discharge, with 5 deceased at 12-month follow-up. ConclusionApproximately 5% of EMS-attended OHCAs in ≥60-year-olds involve a patient with a DNR order, with low rates of awareness of DNR orders. Resuscitation is commenced in 47% of patients, and 4% are transported to hospital with very poor outcomes. Strategies to communicate DNR status and respect patients’ autonomy are extremely important.

Statistical rules for safety monitoring in clinical trials.

Protecting patient safety is an essential component of the conduct of clinical trials. Rigorous safety monitoring schemes are implemented for these studies to guard against excess toxicity risk from study therapies. They often include protocol-specified stopping rules dictating that an excessive number of safety events will trigger a halt of the study. Statistical methods are useful for constructing rules that protect patients from exposure to excessive toxicity while also maintaining the chance of a false safety signal at a low level. Several statistical techniques have been proposed for this purpose, but the current literature lacks a rigorous comparison to determine which method may be best suitable for a given trial design. The aims of this article are (1) to describe a general framework for repeated monitoring of safety events in clinical trials; (2) to survey common statistical techniques for creating safety stopping criteria; and (3) to provide investigators with a software tool for constructing and assessing these stopping rules. The properties and operating characteristics of stopping rules produced by Pocock and O'Brien-Fleming tests, Bayesian Beta-Binomial models, and sequential probability ratio tests (SPRTs) are studied and compared for common scenarios that may arise in phase II and III trials. We developed the R package "stoppingrule" for constructing and evaluating stopping rules from these methods. Its usage is demonstrated through a redesign of a stopping rule for BMT CTN 0601 (registered at Clinicaltrials.gov as NCT00745420), a phase II, single-arm clinical trial that evaluated outcomes in pediatric sickle cell disease patients treated by bone marrow transplant. Methods with aggressive stopping criteria early in the trial, such as the Pocock test and Bayesian Beta-Binomial models with weak priors, have permissive stopping criteria at late stages. This results in a trade-off where rules with aggressive early monitoring generally will have a smaller number of expected toxicities but also lower power than rules with more conservative early stopping, such as the O-Brien-Fleming test and Beta-Binomial models with strong priors. The modified SPRT method is sensitive to the choice of alternative toxicity rate. The maximized SPRT generally has a higher number of expected toxicities and/or worse power than other methods. Because the goal is to minimize the number of patients exposed to and experiencing toxicities from an unsafe therapy, we recommend using the Pocock or Beta-Binomial, weak prior methods for constructing safety stopping rules. At the design stage, the operating characteristics of candidate rules should be evaluated under various possible toxicity rates in order to guide the choice of rule(s) for a given trial; our R package facilitates this evaluation.

МИНЕРАЛЬНОЕ ПИТАНИЕ ЯРОВОЙ ПШЕНИЦЫ ПРИ РАЗЛИЧНЫХ НОРМАХ ВЫСЕВА НА СЕРЫХ ЛЕСНЫХ ПОЧВАХ ПРЕДКАМЬЯ РЕСПУБЛИКИ ТАТАРСТАН

The article summarizes the results of experiments on the study and development of methods for optimizing mineral nutrition for spring wheat on the soils of the Kama region of the Republic of Tatarstan at different seeding rates in order to increase the yield and quality of grain. Field research was carried out in 2022 on the territory of Agrobiotechnopark LLC of Kazan State Agrarian University, located in the Pre-Kama zone of the Republic of Tatarstan. The object of the study was spring wheat of the Yoldyz variety, cultivated in conditions of gray forest soil. For the experiment, a soil of gray forest heavy loam was selected, containing 3.0 (according to Tyurin) units of humus, 176 mg of mobile phosphorus, 109 mg/kg of exchangeable potassium (according to Kirsanov) and 27.3 bases per 100 g of soil in a layer of 0-20 cm. The saturation of the bases was 87.7%, and the pH of the salt extract solution was 5.6. For the experiment, a series of four seeding rates was applied - 4, 5, 6, and 7 million seeds per hectare for each nutrient background. Several plots with different nutrient backgrounds and consistent seeding rates were randomly located. The total area of the plots was 60 m2, and the accounting area was 50 m2. Scheme of the experiment: I background - without fertilizers (control); II background - calculated background for the planned grain yield of 3 tons / ha; III background - calculated background for the planned grain yield of 4 tons/ha. The optimal seeding rate was 5 million/ha for the fertilized variety and 4 million/ha for the natural variety and led to an increase in yield by 1060-1200 kg per hectare compared to the control. With a seeding rate of 6 million/ha on the II and III nutrient background, the gluten content increased by 1.8% compared to the natural background.

Analysis of the Relationship between Interest Rate, Exchange Rate and Economic Growth in Nigeria

This study analyses the relationship between interest rate, exchange rate and economic growth in Nigeria spanning from 1980-2022. Data for the study were obtained from World Development Indicators. The study undertook unit root test using the Augmented Dickey Fuller (ADF) method. Consequently, based on the outcome of the ADF result, the research used Auto-regressive Distributive Lag (ARDL) model to determine the existence of a long-run interactive relationship between interest rate, exchange rate, and economic growth in Nigeria. The Auto-regressive distributive Lag (ARDL) bound test result of the long-run interactive relationship between the variables reported the existence of long-run relationship. The study further revealed that the interaction between real interest rate and exchange rate on growth of gross domestic product is negative, but statistically significant both in the long-run and previous period of the short-run. Similarly, the interaction between lending interest rate and exchange rate is negatively related with growth of gross domestic in the long-run. However, deposit interest rate and exchange rate recounted a positive but insignificant interactive relationship. It has been suggested, among other recommendations, that the Central Bank of Nigeria (CBN), should raise deposit interest rate in order to incentivize individuals to save a greater portion of their income. This will enable financial institutions to enhance their capacity to allocate more cash towards investment, thereby fostering economic growth.

Interest Rate and Volatility of Share Prices of Firms Listed at the Nairobi Securities Exchange, Kenya

Purpose: The study sought to establish the effect of interest rate on volatility of share prices of companies listed at the NSE. The study was anchored the loanable funds theory.
 Methodology: The study employed a descriptive research design. The population of the study was the 20 companies listed at the NSE that forms the NSE share index as of December 2022. The study applied census where all the accessible population of all the 20 NSE share index was used. Data was gathered from secondary sources by the aid of a secondary data collection sheet. Data was obtained from financial and statistical reports released by the CBK. Data was analyzed using descriptive and inferential statistics. The descriptive statistical tools included frequencies, percentages, means, variances and standard deviations. Inferential statistic tools included Pearson’s Product Moment correlation and the multiple regression analysis.
 Findings: The findings indicated that interest rate (β3=0.52939, P=003) have significant positive effect on share price volatility. The study recommended that the monetary committee at CBK should maintain stable interest rates in order to encourage borrowing as it would foster investment in the NSE and other sectors.
 Unique Contribution to Theory, Practice and Policy: The recommendation is in line with the Loanable Funds Theory, as it seeks to establish a reliable and advantageous climate for borrowing. This approach allows businesses and investors to make more effective investment plans, as they can predict the cost of borrowing over time. Additionally, the monetary committee at the Central Bank of Kenya (CBK), responsible for setting the policy rate, should take into account how their decisions influence short-term interest rates in the economy. This consideration is important for the well-being of businesses, investors and the Nairobi Securities Exchange (NSE).

Removal of polymethyl methacrylate nanoplastics and silver nanoparticles by a novel ferrofluid-COF-aminated natural cotton-based hydrogel nanosorbent

In this work, an innovative nanosorbent is assembled based on the combination of Fe2VO6 ferrofluid, silane covalent organic frameworks (COFs) and gelatin/aminated natural cotton/chitosan hydrogel (FF-SiCOF@Gel-ANC@Ch.Hgel). The developed nanomaterial was fully identified using several characterization techniques such as FTIR, electron microscopy, XRD and XPS; and was then studied as an effective nanosorbent for removal of organic nanopollutants such as polymethyl methacrylate nanoplastics (PMMA) and inorganic nanopollutants such as silver nanoparticles from water. Optimization of experimental parameters such as reaction duration, nanosorbent mass, nanopollutant concentration, solution pH, temperature and medium ionic strength revealed promising removal efficiencies towards both nanopollutants with 98.3% and 99.2% recovery for Ag and PMMA nanopollutants, respectively. Kinetic studies confirmed that the adsorptive removal of both nanosorbent followed via a pseudo-second order chemisorption process. Thermodynamic investigations highlighted that spontaneity of the chemisorption process in terms of negative ΔG° values. Industrial scale applicability was confirmed with interestingly high removal efficiencies toward both nanopollutants (99.45% and 96.80% for Ag and PMMA, respectively) in industrial wastewater. Furthermore, proposed nanosorbent showed appreciable recyclability with little decrease in removal efficiencies (from 95.30% to 91.00% and from 97.20% to 93.00% for Ag and PMMA respectively) after 5 adsorption/regeneration cycles. Considering nanosorbent comparatively high adsorption capacities, together with its industrial applicability and reusability, it was proposed as a promising candidate for wastewater treatment applications. The green aspects in this study were investigated in terms of reusing the recovered Ag@FF-SiCOF@Gel-ANC@Ch.Hgel as a potential nanocatalyst in reductive degradation of sulfasalazine drug, a potentially hazardous pollutant. High degradation rates were deduced at optimal conditions providing 2.3 min−1pseudo-first order rate constant with only 3.18% drop in the catalytic activity after 5 successive reduction/regeneration cycles. This accounts for the promising potential of recycled Ag@FF-SiCOF@Gel-ANC@Ch.Hgel as reductive degradation catalyst for targeted water treatment applications.

Constructing a Model of Poplus spp. Growth Rate Based on the Model Fusion and Analysis of Its Growth Rate Differences and Distribution Characteristics under Different Classes of Environmental Indicators

Poplar (Poplus spp.) is an important forest species widely distributed in China of great significance in identifying factors that clearly influence its growth rate in order to achieve effective control of poplar growth. In this study, we selected 16 factors, including tree size, competition, climate, location, topography, and soil characteristics, to construct linear regression (LR), multilayer perceptron (MLP), k-nearest neighbor regression (KNN), gradient boosting decision tree (GBDT), extreme gradient boosting (XGB), random forest (RF), and deep neural network (DNN) models based on the poplar growth rate. Using model fusion methods, the fitting accuracy and estimation capability were improved. The relative importance of each variable in estimating the poplar growth rate was analyzed using the permutation importance evaluation. The results showed the following: (1) the model fusion approach significantly improved the estimation accuracy of the poplar growth rate model with an R2 of 0.893; (2) the temperature and precipitation exhibited the highest importance in poplar growth; (3) the forest stand density, precipitation, elevation, and temperature had significant variations in growth rates among different-sized poplar trees within different ranges; (4) low-forest stand density, high-precipitation, low-elevation, and high-temperature environments significantly increased the poplar growth rate and had a larger proportion of large-sized individuals with high growth rates. In conclusion, environmental factors significantly influence poplar growth, and corresponding planting and protection measures should be tailored to different growth environments to effectively enhance the growth of poplar plantations.

Cu doped ZnO nanoparticles: Correlations between tuneable optoelectronic, antioxidant and photocatalytic activities

Microstructural, optical and electronic properties of Cu doped ZnO nanoparticles with a general formula Zn1-xCuxO (x = 0.0, 0.1 and 0.2) prepared via wet chemical co-precipitation method were investigated thoroughly. Both the free radicals scavenging properties and photocatalytic activities of synthesized nanoparticles were explored. Formation of pure hexagonal wurtzite crystal structure of entire samples were identified by recorded x-ray diffraction patterns. For determining both the mean crystallite size and intrinsic microstrain of all the samples, several standard methods were utilized and a comparative study was introduced. Average size, morphology and shape regularity of synthesized samples were examined using HRTEM images. Optical direct band gap estimated from Tauc plots was noted to reduce with increasing Cu concentration in ZnO nanoparticles. Collected FTIR spectra at 300 K also validated the incorporation of Cu ions and their complete dissolution in the host ZnO crystal structure. It is also found that the hopping of electrons is the fundamental charge conduction process for all the samples in presence of ac electric field. FDTD simulation clearly predicts increase in electric field intensity with increased doping of Cu. There could be a plasmonic coupling between particles at the hotspot region that increases the electric field intensities. BET study revealed that the 10 % Cu doped ZnO sample has highest specific surface area which implies it contains more active sites for taking part in rapid photodegradation of toxic dyes compared to other samples. It was observed that the 10 % Cu doped ZnO nanoparticles were more efficient in degrading toxic dyes and the degradation pathway of all the samples obeyed first order rate kinetics model. Based on estimated bandgap of nanoparticles, a possible mechanism for the Rhodamine B (RhB) and Methylene blue (MB) dye degradation is suggested. All the prepared samples also exhibited notable antioxidant properties. Consequently, this study clearly shows that the Cu doped ZnO nanoparticles are the effective nanomaterial for photocatalytic and antioxidant applications.

Mixer Design and Flow Rate as Critical Variables in Flow Chemistry Affecting the Outcome of a Chemical Reaction: A Review

Flow chemistry offers several advantages for performing chemical reactions and has become an important area of research. It may seem that sufficient knowledge has already been acquired on this topic to understand how to choose the design of microreactor/micromixer and flow rate in order to achieve the desired outcome of a reaction. However, some experimental data are difficult to explain based on commonly accepted concepts of chemical reactivity and performance of microfluidic systems. In this mini review, we attempt to identify such data and offer a rational explanation of unusual results based on the supramer approach. We demonstrate that variation in flow regime (determined by mixer design and flow rate) can either improve or worsen the reactivity and lead to completely different products, including stereoisomers. It is not necessary to mix the reagents with maximum efficiency. The real challenge is to mix reagents the right way since at a too high or too low flow rate (in the particular mixer), the molecules of reagents are incorrectly presented on the surface of supramers, leading to altered stereoselectivity, or form tight supramers, in which most of the molecules are located inside the supramer core and are inaccessible for attack, leading to low yields.

Lessons learnt on the impact of an unprecedented soil decontamination program in Fukushima on contaminant fluxes

In the context of elevated concerns related to nuclear accidents and warfare, the lessons learnt from the Fukushima Daiichi Nuclear Power Plant accident in 2011 are important. In particular, Japanese authorities implemented an ambitious decontamination program to reduce the air dose rate in order to facilitate the return of the local inhabitants to previously evacuated areas. This approach contrasts the strategy adopted in Chernobyl, where the most contaminated areas remain off limits. Nonetheless, the effectiveness of the Japanese decontamination strategy on the dispersion of radioactive contaminant fluxes across mountainous landscapes exposed to typhoons has not been quantified. Based on the unique combination of river monitoring and modeling in a catchment representative of the most impacted area in Japan, we demonstrate that decontamination of 16% of the catchment area resulted in a decrease of 17% of sediment-bound radioactive fluxes in rivers. Decontamination operations were therefore relatively effective, although they could only be conducted in a small part of the area due to the dominance of steep forested slopes. In fact, 67% of the initial radiocesium contamination was calculated to remain stored in forested landscapes, which may contribute to future downstream radiocesium dispersion during erosive events. Given that only a limited proportion of the initial population had returned in 2019 (~30%), it raises the question as to whether decontaminating a small percentage of the contaminated area was worth the effort, the price, and the amount of waste generated?

Analysis of the Operational and Safety Features of the In-Core Bubbling System of the Molten Salt Fast Reactor

A foreseen feature of the Molten Salt Fast Reactor is the adoption of a bubbling system for the removal of gaseous and metallic fission products (FPs). This mechanism injects helium bubbles into the core to remove FPs from the salt through floating and mass transfer mechanisms for metallic and gaseous FPs, respectively. The present work is aimed at analyzing this helium bubbling system, focusing on gaseous FPs. We investigate both operational and safety-related features in order to get information useful for the design and to assess the convenience of its adoption. Accordingly, our investigations split into two strands: (1) analyzing the characteristics of the bubbling system itself and (2) assessing the safety features of the reactor in its presence. In order to perform the above analyses, we add the capability to simulate production, transport, and mass transfer of an arbitrary number of gaseous FPs to a preexisting multiphysics solver, built with the OpenFOAM suite. In terms of operational characterization, our analyses quantify the removal efficiency through a characteristic removal time and estimate the poisoning effect of gaseous FPs. In addition, we evaluate the activity and decay heat of the removed gas, which is an aspect crucial for the design of the off-gas unit, and the effect of the bubbling system on the power versus the fuel mass flow rate curve, which is a possible control mechanism. Among our safety-related studies, we first evaluate the void coefficient, determining upper bounds on the helium flow rate in order to avoid prompt supercriticality in case of prompt loss of helium injection. The latter accidental scenario is also analyzed considering the thermal-hydraulic dynamics of the system. We also discuss another accident: complete loss of helium removal.

Transformation of 2-Line Ferrihydrite to Goethite at Alkaline pH.

The transformation of 2-line ferrihydrite to goethite from supersaturated solutions at alkaline pH ≥ 13.0 was studied using a combination of benchtop and advanced synchrotron techniques such as X-ray diffraction, thermogravimetric analysis, and X-ray absorption spectroscopy. In comparison to the transformation rates at acidic to mildly alkaline environments, the half-life, t1/2, of 2-line ferrihydrite reduces from several months at pH = 2.0, and approximately 15 days at pH = 10.0, to just under 5 h at pH = 14.0. The calculated-first order rate constants of transformation, k, increase exponentially with respect to the pH and follow the progression log10 k = log10 k0 + a·pH3. Simultaneous monitoring of the aqueous Fe(III) concentration via inductively coupled plasma optical emission spectroscopy demonstrates that (i) goethite likely precipitates from solution and (ii) its formation is rate-limited by the comparatively slow redissolution of 2-line ferrihydrite. The analysis presented can be used to estimate the transformation rate of naturally occurring 2-line ferrihydrite in aqueous electrolytes characteristic to mine and radioactive waste tailings as well as the formation of corrosion products in cementitious pore solutions.

Fluid shear stress stimulates ATP release without regulating purinergic gene expression in the renal inner medullary collecting duct.

In the kidney, the flow rate of the pro-urine through the renal tubules is highly variable. The tubular epithelial cells sense these variations in pro-urinary flow rate in order to regulate various physiological processes, including electrolyte reabsorption. One of the mechanosensitive pathways activated by flow is the release of ATP, which can then act as a autocrine or paracrine factor. Increased ATP release is observed in various kidney diseases, among others autosomal dominant polycystic kidney disease (ADPKD). However, the mechanisms underlying flow-induced ATP release in the collecting duct, especially in the inner medullary collecting duct, remain understudied. Using inner medullary collecting duct 3 (IMCD3) cells in a microfluidic setup, we show here that administration of a high flow rate for 1 min results in an increased ATP release compared to a lower flow rate. Although the ATP release channel pannexin-1 contributed to flow-induced ATP release in Pkd1-/- IMCD3 cells, it did not in wildtype IMCD3 cells. In addition, flow application increased the expression of the putative ATP release channel connexin-30.3 (CX30.3) in wildtype and Pkd1-/- IMCD3 cells. However, CX30.3 knockout IMCD3 cells exhibited a similar flow-induced ATP release as wildtype IMCD3 cells, suggesting that CX30.3 does not drive flow-induced ATP release in wildtype IMDC3 cells. Collectively, our results show differential mechanisms underlying flow-induced ATP release in wildtype and Pkd1-/- IMCD3 cells and further strengthen the link between ADPKD and pannexin-1-dependent ATP release.

An efficient compact difference-proper orthogonal decomposition algorithm for fractional viscoelastic plate vibration model

In this article, we aim to prove the solvability for the fractional viscoelastic plate vibration model through the Galerkin argument in Sobolev spaces as a compensation for the absence of its mathematical theory, then propose an efficient compact difference-proper orthogonal decomposition (CD-POD) algorithm. Rigorous numerical analyses are conducted to show that the CD-POD algorithm inherits the merits of the compact difference and the proper orthogonal decomposition technique, that is, it is unconditionally stable, possesses the spatial and temporal convergence rates of fourth order and second order, respectively, and reduces greatly the storage and computing cost, and thus may adapts for long time simulation for the plate vibration model. As a bridge for the plate vibration model and the CD-POD algorithm, a compact difference scheme is also proposed and analyzed previously. Numerical experiments, one of which is for resonance case, indicate that the CPU time of the CD-POD algorithm is at least 20 times less than that of the compact difference scheme, for resonance case or for non-resonance case, and thus verifies again that the CD-POD algorithm is a reasonable computation candidate for long time simulation of the viscoelastic plate vibration model.

Nickel sulfate solution fluoride separation with hydrous zirconium oxide

AbstractFluoride is an impurity in nickel sulfate production, which is required for electric vehicle batteries. Hydrous zirconium oxide (HZO) was evaluated for removing fluoride from nickel sulfate solution. Maximum fluoride removal occurred at pH value 4 and optimal pH value is 4–5, considering Zr solubility. Fluoride availability decreases with pH due to hydrogen fluoride and zirconium fluoride aqueous species. Fluoride removal is initially rapid, with 50 wt.% removal in 7 min, followed by slow removal up to 68 wt.% after 72 h and follows second order rate kinetics. Fluoride removal was dominated by an ion exchange mechanism and resulting Zr–F bonds were observed using Fourier-transform infrared spectroscopy. The presence of nickel sulfate decreased loading capacity compared to a salt-free solution. HZO maintained adsorption capacity through five cycles of loading and regeneration.

Safety, immunogenicity and efficacy of Relcovax®, a dual receptor binding domain (RBD) and nucleocapsid (N) subunit protein vaccine candidate against SARS-CoV-2 virus

SARS-CoV-2, severe acute respiratory syndrome coronavirus-2, causes coronavirus disease- 2019 (COVID-19). Mostly, COVID-19 causes respiratory symptoms that can resemble those of a cold, the flu, or pneumonia. COVID-19 may harm more than just lungs and respiratory systems. It may also have an impact on other parts of the body and debilitating effects on humans, necessitating the development of vaccines at an unprecedented rate in order to protect humans from infections. In response to SARS-CoV-2 infection, mRNA, viral vector-based carrier and inactivated virus-based vaccines, as well as subunit vaccines, have recently been developed. We developed Relcovax®, a dual antigen (Receptor binding domain (RBD) and Nucleocapsid (N) proteins) subunit protein vaccine candidate. Preliminary mouse preclinical studies revealed that Relcovax® stimulates cell-mediated immunity and provides broader protection against two SARS-CoV-2 variants, including the delta strain. Before conducting human studies, detailed preclinical safety assessments are required, so Relcovax® was tested for safety, and immunogenicity in 28-day repeated dose toxicity studies in rats and rabbits. In the toxicity studies, there were no mortality or morbidity, abnormal clinical signs, abnormalities in a battery of neurobehavioral observations, abnormalities in detailed clinical and ophthalmological examinations, or changes in body weights or feed consumption. In any of the studies, no abnormal changes in organ weights, haematology, clinical chemistry, urinalysis parameters, or pathological findings were observed. Immunogenicity tests on rats and rabbits revealed 100 % seroconversion. Relcovax® was therefore found to be safe in animals, with a No Observed Adverse Effect Level (NOAEL) of 20 µg/protein in rats and rabbits. In efficacy studies, Relcovax® immunised hamsters demonstrated dose-dependent protection against SARS-CoV-2 infection, with a high dose (20 µg/protein) being the most protective, while in cynomolgus macaque monkey study, lowest dose 5 µg/protein had the highest efficacy. In conclusion, Relcovax® was found to be safe, immunogenic, and efficacious in in vivo studies.

Do Trust based Social Recommendation Algorithms Work as Intended?

Recommender systems are powerful tools that filter and recommend content/information relevant to a given user. Collaborative filtering is the most popular technique used in building recommender systems and it has been successfully incorporated in many applications. These conventional recommendation systems require a minimum number of users, items, and ratings in order to provide effective recommendations. This results in the infamous cold-start problem where the system is not able to produce effective recommendations for new users. Recently, there has been an escalation in the popularity and usage of social networks, which persuades people to share their experiences in the form of reviews and ratings on social media. The components of social media such as the influence of friends, interests, and enjoyment create the opportunities to develop solutions for sparsity and cold start problems of recommendation systems. This paper aims to observe these patterns and analyze three of the existing social recommendation systems, SocialMF, SocialFD, and GraphRec. SocialMF and SocialFD algorithms are based on matrix factorization and distance metric learning respectively whereas GraphRec is an attention based deep learning model. Through extensive experimentation with the datasets that these algorithms were tested on and one new dataset, we compared the results based on evaluation metrics including Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). To investigate how trust impacts the performance of these models, we evaluated them by modifying the trust and social component. Experimental results show that there is no conclusive evidence that trust propagation plays a major part in these models. Moreover, these models show a slightly improved performance in the absence of trust statements.

SAT170 Paraneoplastic Hypoglycemia Secondary To Hepatocellular Carcinoma

Abstract Disclosure: S. Dejhansathit: None. N. Sheung: None. A. Akofu: None. A. Uddin: None. F. marium: None. N.G. Akabogu: None. W. Salam, MD: None. Introduction: Hypoglycemia is a known but rare Paraneoplastic manifestation of hepatocellular carcinoma and can lead to significant morbidity and mortality. Even though HCC-related hypoglycemia is a known entity, knowledge about prevention and treatment is limited. Case Description: We report a 36-year-old male with no significant past medical history presenting initially to emergency room for abdominal pain and distension for 2 months. He reported associated 10 pounds unintentional weight loss, fatigue, night sweat and loss of appetite in the past 3 months. The patient noted to have hypoglycemia with blood glucose of 20 mg/dl on admission. He was given 2 ampoules of 50% dextrose and started on 5% dextrose solution intravenously. A CT abdomen and pelvis showed enlarged heterogenous liver with numerous hepatic lesions, concerning for multifocal hepatocellular carcinoma. A liver biopsy was done and confirmed hepatocellular carcinoma. Labs showed alpha fetoprotein level over 60500 ng/mL (0-8.3 ng/mL). Hepatitis B surface antigen was reactive with positive hepatitis B DNA, confirming the diagnosis of chronic hepatitis B infection. Gastroenterology, Oncology and Surgical Oncology were consulted. Patient was felt not to be a good surgical or transarterial chemo-embolization. Endocrinology was consulted when patient develops scrotal and legs swelling after receiving high rate of dextrose fluid since admission to maintain blood glucose. Prednisone 20 mg twice a day was initiated and later increased to 30 mg twice day after 2 days without significant improvement. Prednisone was then switched to dexamethasone 4 mg four times a day for longer half-life. 10% dextrose was slowly decreased from 200cc/hr to100cc/hr but resulted in rebound hypoglycemia. Somatropin 4 mg daily was also added with a goal to further decrease fluid rate in order to help with his discomfort from swelling. 10% dextrose was eventually decreased to 75 cc/hr. Patient subsequently opted for hospice care and passed away within 24 hours. Discussion: The paraneoplastic hypoglycemia associated with HCC can be classified into two categories. Type A hypoglycemia is usually found in the late-stage HCC when tumor burden is high. Type B hypoglycemia is caused by an increase in pro-IGF-2 level that is incompletely processed by the tumor cells, stimulating insulin receptors. It is likely our patient had type A hypoglycemia due to the extensive tumor burden. Overall, paraneoplastic hypoglycemia associated with HCC has very poor prognosis and high mortality rate. There is no single effective management and combination of steroids and Somatropin may provide palliative improvement as seen in our patient. Presentation: Saturday, June 17, 2023