Control Factors Research Articles

Study on the Destruction Law and Main Controlling Factors of Corrosion Product Film in H2S-CO2 Coexistence System

Abstract The failure law and main controlling factors of corrosion product film in this corrosion environment were studied according to the characteristics of H2S-CO2 coexistence in a gas field pipeline, so as to provide guidance for corrosion prevention and control of gas field pipeline. Sediment effects of sand particles in the pipeline on corrosion, the influence of flow rate, dissolved oxygen and sediment on corrosion products were analyzed by conducting corrosion experiments at 0.5m/s, 1m/s and 2m/s, corrosion experiments without oxygen and aerobic conditions. The destruction law of corrosion product film in pipeline and the main controlling factors of corrosion product film in single well pipeline and gathering and transportation line were determined. The results show that high flow rate will cause local damage of corrosion product film and promote pitting corrosion, dissolved oxygen will destroy the integrity of corrosion product film, and sediment is one of the factors causing local corrosion and perforation of pipeline inner wall. The corrosion product film structure of the gas field pipeline will be destroyed and pitting corrosion under the condition of high flow rate, oxygen and sand deposition. Meanwhile, the main control factor affecting the corrosion product film destruction of the gas field single well pipeline is dissolved oxygen, and the main control factor affecting the corrosion product film destruction of the gas field gathering and transportation main line is sediment.

An empirical study of ISAC channel characteristics with human target impact at 105 GHz

AbstractLeveraging the ultra‐wideband advantages of the terahertz band, Integrated sensing and communication (ISAC) facilitates high‐precision sensing demands in human smart home applications. ISAC channel characteristics are the basis for ISAC system design. Currently, the ISAC channel is divided into target and background channels. Existing researches primarily focus on the attributes of human target itself, e.g. radar cross‐section and micro‐Doppler effect. However, the impact of human target on neither the pathloss characteristic of background channel nor the multipath propagation characteristic of target channel is considered. To address the gap, we conduct indoor channel measurements at 105 GHz to investigate the ISAC channel characteristics with the impact of human target. Firstly, by analysing the power angular delay profiles with and without human target, the changes in quantity and power of multipath components (MPCs) are observed. Then, a parameter called power control factor is proposed to evaluate the human target impact on pathloss, thereby modifying the existing pathloss model of background channel. Eventually, the MPCs belonging to target channel are extracted within target‐oriented power delay profile to count the power proportion of each bounce MPCs of the target‐Rx link, which supports the necessity of multi‐bounce (indirect) paths modelling in target channel.

Multifactorial influences on land surface temperature within local climate zones of typical global cities

The land surface temperature (LST) of most cities is rising steadily due to both human activities and global climate change, affecting the thermal comfort of cities and threatening the physical health of their inhabitants. Investigating surface temperature features and their affecting elements is therefore essential to improve the thermal environment of cities. Due to differences in surface temperature characteristics in different climatic belts. However, there is still a lack of research on how the local climate zones (LCZs) of different climate belts are affected by natural and social causes. According to the Koppen-Geiger climate classification system, we selected three representative cities from each of the four macroclimatic belts and adopted multiple linear stepwise regression and boosted regression trees (BRT) to systematically explore the linear relationships, relative impacts and marginal effects of normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), population density, and road nuclear density within urban LCZs on LST. The results indicate that (1) LCZs with significant differences in LST among the four global climatic belts account for more than 95 % (P < 0.05), demonstrating that LCZs can effectively differentiate LST based on different land surface cover types. This study can delve into the relationships between the four influencing factors and LST based on LCZs. (2) Primary control factors regulating LST differ in different climate belts. The relative effects of NDVI and MNDWI on LST are greater in the arid and temperate belts, with each 0.1 increase in NDVI and MNDWI producing a cooling effect of more than 0.40 °C and 0.92 °C, respectively. Ventilation corridors created by increased road core density produced a cooling effect of 1 °C or more in the cold belt, with the most pronounced cooling effect. (3) When natural factors are higher and social factors are lower, LST cannot be minimized. It was found that LST was minimized when NDVI, MNDWI, population density and road nuclear density were controlled above 0.4, 0.1–0.2, 10,000–50,000 and 1500–2000 respectively. Our study will provide targeted measures for LCZ-based mitigation of urban thermal environments in various macroclimatic belts.

Offline reinforcement learning based feeding strategy of ethylene cracking furnace

The feeding process of the ethylene cracking furnace necessitates the synchronized adjustment of multiple controlled factors. The process mainly relies on operators to do it manually, which is burdensome and may lead to significant variations in coil out temperature (COT) due to the differing expertise of operators. This paper proposes a method for learning the feeding strategy of the ethylene cracking furnace using offline reinforcement learning. The agent learns and optimizes the operating strategy directly from datasets, eliminating the need for sophisticated process simulator modeling. In addition, the advantage function is incorporated into the Twin Delayed Deep Deterministic Behavioral Cloning (TD3BC) algorithm, which enables the agent to acquire more effective operational experience. The proposed method is initially evaluated using benchmark datasets. Further, the proposed method is validated through comparative experiments on a feeding process validation model, demonstrating superior rewards and outperforming manual operating experience as well as other offline reinforcement learning methods.

Machine learning based prognostics and statistical optimization of the performance of biogas-biodiesel blends powered engine

In this study, waste biomass-derived biogas was employed as the main fuel while the biodiesel-diesel blend was used as pilot fuel. This paper describes the development of a Decision Tree and Response Surface methodology-based statistical framework for prediction modeling and optimization. The compression ratio, fuel injection time, fuel injection pressure, and biogas flow rate were employed as controllable inputs, and brake thermal efficiency, peak combustion pressure, and exhaust emission were selected as responses. The experimental data for model development was gathered for the development of prediction models and optimization. The decision tree-based models were robust with almost negligible mean squared errors and R2 values of more than 0.9487 for all models. Response surface methodology-based optimized engine parameters were validated with the following results compression ratio was 17.9, fuel injection pressure was 225 bar, fuel injection timing was 26.3-degree crank angle after top dead center, and the biogas flow rate was 0.85 kg/h. Validation results were within 5 % of the model-optimized results. The prognostic models for all control factors were developed with decision tree-based machine learning with high predictive efficiency and low errors.

Grey-Taguchi and ANN optimization in CI Engines using acetylene &amp; biodiesel blends for Low Emissions and Better Performance

This study aimed to reduce smoke and NOx emissions in a diesel engine fuelled with a 20% blend of Calophyllum inophyllum and Prosopis juliflora biodiesel (B20) with neat diesel, supplemented with acetylene at flow rates of 1, 2, and 3 liters per minute (lpm) in dual-fuel mode. Using the Grey-Taguchi method and an L9 (3^3) orthogonal array, the effects of compression ratio, fuel type, and acetylene flow rate were examined. Regression models were developed to predict brake thermal efficiency, smoke, and NOx emissions based on these controllable factors. The study found that the optimal individual values for NOx, brake thermal efficiency, and smoke were 2353 ppm, 31.52%, and 48.7 ppm, respectively. The best-combined results were achieved with a compression ratio of 17.5 and an acetylene flow rate of 3 lpm using the CI20 blend. The findings demonstrated significant improvements in output response factors when the optimal combination was applied, as validated by experimental and artificial neural network (ANN) simulations. The Grey-Taguchi approach proved effective in reducing emissions while enhancing engine performance.

The Application of Converter Sludge and Slag to Produce Ecological Cement Mortars.

The paper presents an analysis of the effective use of a mixture of steel sludge (S1) and slag (S2) from the converter process of steel production for the production of cement mortars. Metallurgical waste used in the research, which is currently deposited in waste landfills and heaps near plants, posing a threat to groundwater (possibility of leaching metal ions present in the waste), was used as a substitute for natural sand in the range of 0-20% by weight of cement (each). The obtained test results and their numerical analysis made it possible to determine the conditions for replacing part of the sand in cement mortars with a mixture of sludge and slag from a basic oxygen furnace (BOF) and to determine the effects of such modification. For the numerical analysis, a full quadratic Response Surface Model (RSM) was utilized for two controlled factors. This model was subsequently optimized through backward stepwise regression, ensuring the inclusion of only statistically significant components and verifying the consistency of residual distribution with the normal distribution (tested via Ryan-Joiner's test, p > 0.1). The designated material models are helpful in designing ecological cement mortars using difficult-to-recycle waste (i.e., sludge and converter slag), which is important for a circular economy. Mortars modified with a mixture of metallurgical waste (up to 20% each) are characterized by a slightly lower consistency, compressive and flexural strength, and water absorption. However, they show a lower decrease in mechanical strength after the freezing-thawing process (frost resistance) compared to control mortars. Mortars modified with metallurgical waste do not have a negative impact on the environment in terms of leaching heavy metal ions. The use of a mixture of sludge and steel slag in the amount of 40% (slag/sludge in a 20/20 ratio) allows you to save 200 kg of sand when producing 1 m3 of cement mortar (cost reduction by approx. EUR 5.1/Mg) and will also reduce the costs of the environmental fee for depositing waste.

Hybrid adaptive moment estimation based performance measure approach for complex reliability-based design optimization

The complexity of engineering problems often poses challenges, especially in reliability-based design optimization, where the nonlinearity of the performance function is not known in advance. The substantial costs and oscillating results significantly impede the engineering application for highly nonlinear problems. To address this issue, a hybrid adaptive moment estimation (HAME) method is proposed in this work. Given that the performance measure approach is heavily influenced by the gradient of performance function, this method employs the statistical moment information of the gradient, thereby accelerating the search for the minimum performance target point. By combining gradient mean and modified chaos control as new search directions, oscillation phenomena are resolved. To filter the aggregated gradient calculations, the gradient variance and state variable are introduced to approximate the gradients for weakly nonlinear performance functions or in later iterations by the dynamic identification of the nonlinearity of the performance function. The proposed method eliminates the limitation of taking the upper bound for the chaos control factor and addresses the balance issue between efficiency and robustness. The advantages of the proposed method are demonstrated through inverse reliability analysis problems, several highly nonlinear classic RBDO examples, and engineering applications of the crank rod mechanism of an engine.

Determining priority control factors for heavy metal management in urban road dust based on source-oriented probabilistic ecological-health risk assessment: A study in Xi'an during peak pollution season

Urban road dust (URD) is essential for transporting heavy metals (HMs), which can be a major danger to both the environment and human health. Moreover, URD has the potential to be carried into bodies of water, leading to contamination of the aquatic ecosystem. A study was conducted in Xi'an, a city in northwestern China known for high air pollution levels, during January 2024 - a period characterized by peak pollution due to frequent low wind speeds and temperature inversions. The research investigated the presence of 10 types of HMs (Cu, Zn, Cd, Cr, Pb, As, Ni, Hg, Co, and Mn) in URD. Findings revealed elevated levels of Cu, Zn, Cd, Cr, Pb, As, and Hg in URD compared to background levels. Hg showed the most significant contamination (moderate to heavy), followed by moderate contamination of Cd, and lower levels of As, Zn, and Cu. The main sources of HMs were traffic (58.2%), mixed natural and industrial (30.3%), and industrial (11.5%). The ecological risk in the area was deemed to be very high, primarily because of Hg and Cd. Based on probabilistic health risk assessments, it was determined that non-carcinogenic risks were deemed acceptable for all groups. Nevertheless, the possibility of carcinogenic risks should not be disregarded. Strategies for controlling ecological-health risks prioritize mixed natural and industrial sources, with a focus on Hg, Cd, and As in URD. The results offer a foundation for policymakers to create specific control strategies.

The impact of policy and technology infrastructure on telehealth utilization.

The COVID-19 outbreak resulted in an unprecedented surge in telehealth utilization. However, the effects of policy enactment on utilization remain understudied in the literature. Our research examines the impact of policy mandates relating to federal incentive programs on telehealth utilization across states during the pandemic by considering technology infrastructure, such as broadband penetration and equipment possession. This study also considers the impact of political orientation and control factors, including income attributes, on telehealth utilization. Considering telehealth utilization in the Medicare program as a test case, this study employed the partial least square and structural equation model to analyze data from the Centers for Medicare & Medicaid Services, the American Community Survey, and the Microsoft Airband Project to draw inferences. Our study finds that telehealth legislation, broadband penetration, political orientation, and control factors have a direct significant impact on telehealth utilization, whereas incentive programs and equipment possession have an indirect impact through broadband penetration.

Degradation of Aniline and Antimony in Printing and Dyeing Wastewater by Micro-Oxygenated Hydrolytic Acidification and Their Removal Effects on Chemical Oxygen Demand and Ammonia Nitrogen

The degradation characteristics of aniline and antimony in printing and dyeing wastewater during the micro-oxygenated hydrolytic acidification process and its effect on COD and ammonia nitrogen removal were investigated in this experiment. Firstly, the effects of control factors such as pH, dissolved oxygen (DO), and sludge concentration on COD and ammonia nitrogen removal in the hydrolysis acidification section were optimized. It was recommended that the pH value should be maintained at 6.5; low DO (0–0.5 mg/L) could assist in the conversion of nitrogen for subsequent treatment; the optimum treatment temperature was 25 °C; finally, it was recommended that the sludge concentration should be controlled at 4 mg/L during the operation. Secondly, the effects of aniline and antimony on COD and nitrogen removal were investigated. It was found that when the concentration of aniline was increased from 0.4 mg/L to 5.4 mg/L, the COD concentration in the effluent increased by 96.5%, which indicated that aniline was toxic to anaerobic sludge and obviously inhibited the degradation of COD. When the concentration of antimony was increased from 0.05 mg/L to 2.05 mg/L, the COD removal rate was only 2.9%, which was much lower than that of the water samples with no antimony added. The anaerobic sludge concentration decreased from 5.58 g/L to 3.44 g/L, which indicated that aniline and antimony had a strong inhibitory effect on the activity of anaerobic bacteria and inversely affected COD removal.

Determination of contamination, source, and risk of potentially toxic metals in fine road dust in a karst region of Southwest China.

Understanding the pollution situation of potentially toxic metals (PTMs) in fine road dust (FRD) in emerging industrialized cities and identifying priority control factors is crucial for urban environmental management, resident health protection, and pollution control. This study conducted a comprehensive investigation on PTMs pollution in FRD in Zunyi, a representative emerging industrialized city in the karst region of southwestern China. The average contents of Ni, Cr, Mn, Cu, Zn, Ba, Pb, V, and Co in the FRD were 43.2, 127.0, 1232.1, 134.4, 506.6, 597.8, 76.1, 86.8, and 16.2mgkg-1, respectively, which were obviously higher than the corresponding background levels of the local soil except for V and Co. The comprehensive pollution level of the determined PTMs in the FRD was very high, primarily caused by Zn and Cu. The sources of PTMs in Zunyi FRD were traffic, industrial, construction, and natural sources, accounting for 38.0, 23.7, 21.9, and 16.4% of the total PTMs content, respectively. The PTMs in Zunyi FRD exhibited a low to moderate overall ecological risk level, mainly contributed by Cu and traffic source. The cancer risks of PTMs in Zunyi FRD were high for all populations. The non-carcinogenic risk of PTMs in Zunyi FRD was acceptable for adults, but cannot be ignored for children. According to the source-specific probabilistic health risk estimation results, the priority control source is industrial source and the priority control PTM is Cr. Local governments need to give more attention to the carcinogenic risks and health hazards posed by PTMs in the FRD.

Characteristics and Control Factors of a High-Quality Deeply Buried Calcareous Sandstone Reservoir, the Fourth Member of the Upper Xujiahe Formation in the Western Sichuan Basin, China

A special type of sandstone in which carbonate rock fragments (CRFs) dominate the composition developed in the Upper Triassic Xujiahe Formation’s fourth member (Xu4) in the western Sichuan Basin, known as calcareous sandstone. Calcareous sandstones are widely distributed in the western Sichuan and is the main production target of tight sandstone gas in the Sichuan Basin. In this study, thin sections, porosity–permeability testing, scanning electron microscopy, and X-ray diffraction are applied to examine the characteristics and control factors for high-quality reservoirs in the calcareous sandstones, with a view to providing guidance for natural gas exploration and development in calcareous sandstones. The results show that the calcareous sandstone belongs to litharenite, with an average framework grain composition of 30% quartz, 1% feldspar, and 69% rock fragments, while the Xu4 sandstone has a high quartz content (average content of 71%). Primary intergranular pores are the main storage space, and the reservoir quality is quite poor. Under the influence of different parent rock properties of sandstones, there are obvious differences in the composition of framework grains between the calcareous sandstone and the ordinary Xu4 sandstone, which in turn affects the reservoir storage space, diagenesis, and reservoir quality. High-energy depositional conditions, low content of late cements, and the development of fractures are the main controlling factors for the formation of high-quality reservoirs in Xu 4 calcareous sandstones.

Regulation of cholesterol biosynthesis by CTCF and H3K27 methylation is critical for cell migration

CTCF is a key factor in three-dimensional chromatin folding and transcriptional control that was found to affect cancer cell migration by a mechanism that is still poorly understood. To identify this mechanism, we used mouse melanoma cells with a partial loss of function (pLoF) of CTCF. We found that CTCF pLoF inhibits cell migration rate while leading to an increase in the expression of multiple enzymes in the cholesterol biosynthesis pathway along with an elevation in the cellular cholesterol level. In agreement with the cholesterol change we detected altered membrane dynamics in CTCF pLoF cells as measured by reduced formation of migrasomes, extracellular vesicles formed at the rear side of migrating cells. Inhibition of cholesterol synthesis in CTCF pLoF cells restored the cellular migration rate and migrasome formation, suggesting that CTCF supports cell migration by suppressing cholesterol synthesis. Detailed analysis of the promoter of Hmgcs1, an early enzyme in the cholesterol synthesis pathway, revealed that CTCF prevents formation of a loop between that promoter and another promoter 200 kb away. CTCF also supports PRC2 recruitment to the promoter and deposition of H3K27me3. H3K27me3 at the promoter of Hmgcs1 prevents SREBP2 binding and activation of transcription. By this mechanism, CTCF fine-tunes cholesterol levels to support cell migration. Notably, genome wide association studies suggest a link between CTCF and cholesterol-associated diseases, thus CTCF emerges as a new regulator of cholesterol biosynthesis.

Optimizing ketogenic diet therapy for childhood epilepsy: Identifying key factors for seizure control and psychomotor enhancement.

To identify key factors influencing the therapeutic efficacy of the ketogenic diet (KD) for children with drug-resistant epilepsy and elucidate their interconnected relationships to optimize clinical practice. Participants were selected from children receiving KD treatment at West Second University Hospital of Sichuan University from September 2015 to October 2023. Clinical factors pre-KD and post-KD (at the third month) were analyzed systematically using an analytical framework. Descriptive analyses, univariate analyses, and multivariate regression analyses were performed for the entire cohort and subgroups of genetic and non-genetic (i.e., structural and unknown) etiologies. Thereby, the most significant predictors were identified for each relevant dependent variable. Path analysis diagrams were used for visual representation. Of 156 patients, genetic etiology was prevalent (38.5%). In the genetic subgroup, channelopathies predicted lower baseline seizure frequency and increased chance of seizure freedom with KD. Frequent seizures and complex history of anti-seizure medications (ASMs) predicted severe baseline psychomotor abnormalities. Younger age at KD initiation benefited psychomotor improvement. In the non-genetic subgroup, lower baseline seizure frequency increased the likelihood of seizure freedom post-KD. Concurrent use of multiple ASMs helped achieve ≥50% seizure reduction. Boys were more likely to experience psychomotor improvement. A significant correlation was found between ≥50% seizure reduction and psychomotor improvement in both subgroups. Delayed KD initiation (longer epilepsy duration at KD start) was related to a greater number of ASMs used, infrequent seizures, and older age at epilepsy onset. In addition, patients with channelopathies had delayed initiation of KD. Children with genetic epilepsy display more pronounced characteristics of epileptic encephalopathy. Early KD intervention is crucial for channelopathies, notably SCN1A variants. For other drug-resistant epilepsy cases, KD alongside diverse ASMs may improve seizure control and developmental outcomes. However, the patient population benefiting most from early KD tends to start the treatment later, urging a re-evaluation of KD decision-making paradigms.

Exploring Factors Influencing Stroke Risk: Insights From a Predictive Analysis.

Introduction Stroke is a serious medical condition characterized by the sudden interruption of blood flow to the brain, resulting in the death of brain cells. It is a leading cause of long-term disability and mortality worldwide. Stroke has some associated risk factors, both modifiable and non-modifiable ones.As for non-modifiable risk factors, these are age, gender (men are more vulnerable), and family history of stroke.The controllable or adjustable risk factors include hypertension (high blood pressure), diabetes, smoking, high cholesterol levels, obesity, and insulin resistance. Methods In our study, we collected data from 229 patients which were originally collected for clinical purposes and were retrospectively analyzed. These data contain features such assex and age, the presence of ischemic heart disease (IHD) or stroke history, and different blood sugar readings. These measurements include fasting blood sugar (FBS), postprandial blood sugar (PPBS), HbA1c%, and insulin levels (fasting and postprandial).Furthermore, cholesterol was also tested, such as total cholesterol, triglycerides (TGL), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL). Surprisingly, stroke was observed in 24of the 205 patients. This contrast permits us to be concerned with the chance of the association between stroke and insulin levels. Given the imbalanced nature of our outcome variable (stroke occurrence), the primary analytical method will be logistic regression. Results In this cross-sectional study, we investigated the association between high insulin levels (both fasting and postprandial) and the occurrence of stroke within a dataset of 229 patients. Out of the 229 included cases, 102 individuals were female (44.5%) and 127 individuals were male (55.5%). Twenty-four cases have ischemic heart disease (10.5%). Among the analyzed cases, 24 individuals have a history of stroke. The average age of the sample is approximately 57 years ± 14.87. There was no significant difference between the males and females in most of the descriptive statistics. However, females experienced significantly higher levels of postprandial glucose level and significantly lower levels of postprandial insulin. According to our predictive model, we found that an increase in fasting insulin levels was linked to a lower risk of stroke occurrence. On the other hand, increasing insulin postprandial levels and age were associated with an increased risk of stroke. Conclusion Our study identified age, fasting insulin, and postprandial insulin as key factors influencing stroke risk. Higher fasting insulin levels were associated with reduced risk, while increased postprandial insulin and age were linked to higher risk. Blood glucose, cholesterol, and triglycerides had minor effects. Notably, higher total cholesterol and triglyceride levels were slightly associated with lower stroke occurrence. Further research with larger samples is needed for validation.

Predicting and understanding photocatalytic CO2 reduction reaction with IR spectroscopy-based interpretable machine learning framework.

The highly selective conversion of carbon dioxide into value-added products is extremely valuable. However, even with the aid of in situ characterization techniques, it remains challenging to directly correlate extensive spectral data carrying microscopic information with macroscopic performance. Herein, we adopted advanced machine learning (ML) approaches to establish an accurate and interpretable relationship between vibrational spectral signals and catalytic performances to uncover hidden physical insights. Focusing on photocatalytic CO2 reduction, our model is shown to effectively and accurately predict the CO production activity and selectivity based solely on the infrared (IR) spectral signals, the generalizability of which is additionally demonstrated with a new Bi5O7I photocatalytic system. More importantly, further model analysis has revealed a novel strategy to steer CO selectivity, the physical sanity of which is verified by a detailed reaction mechanism analysis. This work demonstrates the tremendous potential of machine-learned spectroscopy to efficiently identify reaction control factors, which can further lay the foundation for targeted optimization and reverse design.

Uranium mobility and enrichment during hydrocarbon generation and accumulation processes: A review

Black shale serve as a new uranium sources and provide reducing agents for uranium deposits through hydrocarbon generation. However, the systematically interplay between the black shale and the formation of uranium deposits is not obscure. This paper provides a comprehensive summary and critical assessment of the depositional control factors of uranium in black shales, the extent of uranium migration during hydrocarbon generation, the enrichment of uranium in oil/gas reservoirs, and the relationship between crude oil-natural gas leakage and uranium. The study show that U-riched constituents within black shale persist through mechanisms of adsorption, reduction, complexation, and absorption within matrices rich in phosphates, iron, carbonate minerals, and organic matter. The U in black shale originates from continental weathering, volcanic eruptions, and seabed hydrothermal activities. The average U concentration in black shale is determined by the U content in atmosphere, while its relative content is controlled by the degree of anoxia during the geological historical periods.. Black shale prior to the Late Neoproterozoic period exhibits minimal migration with hydrocarbon substances, whereas black shale post the Late Neoproterozoic period demonstrates migration, with a migration rate ranging approximately between 55 and 75 %. However, the migrated uranium does not accumulate in (ancient) reservoirs. The correlation between hydrocarbon substances and sandstone-type uranium deposit is attributed to the oxygen uptake by hydrocarbons or the thermochemical sulfate reduction (TSR). The study has fundamental significance for further understand the interaction mechanisms between uranium and hydrocarbon substances.

A single institution retrospective study of efficacy and complications perspective of Gamma Knife Radiosurgery for benign skull base meningioma: A 12-year follow-up

Background and Objectives: Gamma knife radiosurgery (GKRS) has established its role as an effective treatment modality for inaccessible, recurrent, and residual benign skull base meningioma. Therefore, it is necessary to study the outcome in the long term. The current retrospective study aims to analyze and report the clinical and radiological outcomes after long-term follow-up of GKRS for skull base meningiomas &gt;= 12 years. Patients and methods: The present study was conducted on 106 consecutive patients harboring benign skull base meningiomas treated by GKRS at our IMC center between 2005 and 2012 and was followed till the end of 2023. Results: After a median follow-up of 13 years (3.6-18 years), a tumor control rate was reported in 88.7% of patients (n 94/106). Recurrences and tumor progression occurred in 11.3% (n 12/106) at a median follow-up period of 5.4 years (3–10.3 years). The 3, 5-, 10-, 12-and 15-year actuarial tumor control rate was 100%, 95.3%, 89.7%, 88.7%, and 78.1% respectively. Conclusions: The current retrospective study provides a long-term 12-year follow-up and comprises one of the longest follow-up studies of GKRS-treated benign skull base meningiomas. The current series documents a persistent long-term high local tumor control and an acceptable low incidence of neurological deficits. Benign skull base meningioma volume variant at the time of GKRS is a statistically significance predictor factor for tumor control at long-term outcomes.

Low concentration of serum vitamin B12 may be a strong predictor of large-artery atherosclerosis stroke: A case-control study

IntroductionIdentifying controllable risk factors for large-artery atherosclerosis (LAA) stroke is crucial due to its significant role as a leading cause of ischemic stroke. We aimed to validate the correlation of serum vitamin B12 with LAA stroke. MethodsInpatients with LAA stroke and healthy controls were retrospectively collected for a case-control study from January 2020 to May 2022. Serum vitamin B12 concentration and other blood indicators, demographic, lifestyle factors and comorbidities were investigated. Logistic regression analysis was used to identify the correlation of serum vitamin B12 concentrations with LAA stroke, meanwhile adjusted for confounding factors. ResultsPatients with LAA stroke had significantly lower serum vitamin B12 concentrations in comparison to those of controls. In the fully adjusted model, vitamin B12 (per 1 interquartile range increase, odds ratio [OR] = 0.84, 95 % confidence interval [CI]: 0.77–0.91), vitamin B12 < 200 pg/mL (OR=7.70, 95 %CI: 2.19–27.03) and vitamin B12 < 300 pg/mL (OR=4.19, 95 %CI: 1.82–9.66) were independently factors for LAA stroke. Furthermore, the optimal cut-off values for vitamin B12 to predict LAA stroke were 305.25 pg/mL (area under the curve [AUC] = 0.71) when unadjusted and 308.25 pg/mL when adjusted for age and sex (AUC=0.68). Lower vitamin B12 concentrations were significantly associated with male sex, smoking, older age, higher neutrophil count, higher creatinine, lower folate and higher total homocysteine. ConclusionResults indicate that low concentration of serum vitamin B12 may be a strong predictor for the risk of LAA stroke.