Greater Effect Research Articles

Text‐based corn futures price forecasting using improved neural basis expansion network

AbstractThe accurate forecasting of agricultural futures prices is critical for ensuring national food security. Therefore, this study proposes a text‐based deep learning forecasting model. This model first uses the ChineseBERT + a text convolution neural network to classify Weibo text and obtain a raw sentiment index. Then, complete ensemble empirical mode decomposition with adaptive noise, variational mode decomposition, correlation coefficient, and sample entropy are combined to decompose and reconstruct the raw sentiment index and obtain a denoised sentiment index. Subsequently, the neural basis expansion analysis with exogenous variables is improved by designing a weight coefficient and Optuna is used to optimize the designed weight coefficient and the hyperparameters. Finally, the SHapley Additive exPlanations value is used to increase the interpretability of prediction results. Corn futures prices for the Dalian Exchange are used in forecasting to validate the accuracy and stability of the proposed model. Experimental results show that the proposed denoising sentiment index contributes more to the improvement of predictive model performance than the raw sentiment index. The proposed text‐based deep predictive model demonstrates strong predictive ability for prediction horizons of 30 and 60 days. SHapley Additive exPlanations value analysis shows that the three features with greater effects on corn futures prices are as follows: “Corn Spot Price of Zhengzhou market,” “CBOT_corn_futures_price,” and “Pork futures price.”

Application of ANN in Construction: Comprehensive Study on Identifying Optimal Modifier and Dosage for Stabilizing Marine Clay of Qingdao Coastal Region of China

Nowadays, the use of new compound chemical stabilizers to treat marine clay has gained significant attention. However, the complex non-linear relationship between the influencing factors and the unconfined compressive strength of chemically treated marine clay is not clear. In order to study the influence of various factors (dosage, type of stabilizer, curing age) on the unconfined compressive strength of solidified soil during chemical treatment, experiments were performed to determine the unconfined compressive strength of soft marine clay modified with various types of stabilizers. Further, an artificial neural network (ANN) model was used to establish a prediction model based on the unconfined compressive strength test data and to verify the performance. Sensitivity and optimization analyses were further conducted to explore the relative significance of parameters as well as the optimal dosage amount. Research has found that when the content of aluminate cement is 89.5% and the content of curing agent is 30%, the unconfined compressive strength significantly increases after 28 days of solidification, and the change in quicklime content has the greatest effect on the improvement in the unconfined compressive strength. The influence of modifiers on the unconfined compressive strength is in the order: potassium hydroxide > kingsilica > quick lime > bassanite. The values of each factor were obtained when the unconfined compressive strength was the maximum, which provided support for the optimization of the treatment scheme. The analysis of chemical treatment is no longer limited to the linear relationship according to the test results, which proves the feasibility of non-linear relationship analysis based on the artificial neural network.

Variation in Phenolic Content, Antioxidant Activity and Alpha-amylase and Acetylcholinesterase Inhibitory Capacities of Different Extracts from Tunisian Satureja barceloi (Willk) L.

The antioxidant activity and the anti-α-amylase and anti-acetylcholinesterase capacities of secondary metabolites from different organs (roots, stems, leaves and flowers) of Tunisian Satureja barceloi were determined. The variation in the distribution of phenolic metabolites among roots, stems, leaves and flowers extracts of S. barceloi with various solvent systems (methanol, ethyl acetate, hexane and distilled water) has not been characterized before. Significant variation of phenolic compounds was observed according to organs rather than to extracting solvents. The analyzed organs show a high level of phenolic compounds although the stems contains the highest total polyphenols (132.53±0.48 mg AGE/g Ex), flavonoids (48.99±0.65 mg RE/g Ex) and flavonols (34.93±0.29 mg QE/g Ex) contents. The phenolic fraction was dominated by sagerinic acid, caffeic acid glucoside and epigallocatechin, detected using HPLC-PDA/ESI-MS. The antioxidant activity of all extracts, evaluated by four in vitro tests, was high and varied significantly according to the type of solvent used and the plant organ. The aqueous extracts of leaves exhibited the greatest inhibitory effect on alpha-amylase while the methanolic extract of leaves and stems revealed the most important acetylcholinesterase inhibitory effect. Hence, S. barceloi extracts could be used as a source of various bioactive molecules in pharmaceutical industry.

Cardiorespiratory effects of indoor ozone exposure during sleep and the influencing factors: A prospective study among adults in China

Ambient ozone (O3) is recognized as a significant air pollutant with implications for cardiorespiratory health, yet the effects of indoor O3 exposure have received less consideration. Furthermore, while sleep occupies one-third of life, research on the health consequences of O3 exposure during this crucial period is scarce. This study aimed to investigate associations of indoor O3 during sleep with cardiorespiratory function and potential predisposing factors. A prospective study among 81 adults was conducted in Beijing, China. Repeated measurements of cardiorespiratory indices reflecting lung function, airway inflammation, cardiac autonomic function, blood pressure, systemic inflammation, platelet and glucose were performed on each subject. Real-time concentrations of indoor O3 during sleep were monitored. Associations of O3 with cardiorespiratory indices were evaluated using linear mixed-effect model. Effect modification by baseline lifestyles (diet, physical activity, sleep-related factors) and psychological status (stress and depression) were investigated through interaction analysis. The average indoor O3 concentration during sleep was 20.3 μg/m3, which was well below current Chinese indoor air quality standard of 160 μg/m3. O3 was associated with most respiratory indicators of decreased airway function except airway inflammation; whereas the cardiovascular effects were only manifested in autonomic dysfunction and not in others. An interquartile range increases in O3 at 6-h average was associated with changes of −3.60 % (95 % CI: −6.19 %, −0.93 %) and −9.60 % (95 % CI: −14.53 %, −4.39 %) in FVC and FEF25–75, respectively. Further, stronger effects were noted among participants with specific dietary patterns, poorer sleep and higher level of depression. This study provides the first general population-based evidence that low-level exposure to indoor O3 during sleep has greater effects on the respiratory system than on the cardiovascular system. Our findings identify the respiratory system as an important target for indoor O3 exposure, and particularly highlight the need for greater awareness of indoor air quality, especially during sleep.

Climate Change Paradox: The Least Responsible for It Encounters the Most of Its Implications

Carbon dioxide (CO2) emissions are a major cause of climate change. However, CO2 emissions data for 178 countries from 1960 to 2018 revealed inequality in global CO2 emissions. For example, we found that 50% of the world’s population (ca. 3.75 billion people) was responsible for just 8.9% of the global cumulative carbon emissions. These people are concentrated in low- and middle-income countries. Conversely, 10% of the world’s population (ca. 757 million people), concentrated in high-income countries, were responsible for 46.8% of the global emissions. Furthermore, the literature review disclosed evolution of CO2 emission inequalities within countries. A significant (p < 0.001) negative (r2 = −0.52) correlation was detected between carbon emissions and climate change impacts on national incomes. Such correlation indicated that countries most likely to experience the greatest effects of climate change are also those who make the smallest contributions to its underlying causes. Similar disparities were observed within countries where low-income groups who make the smallest contributions to climate change are subjected to its worst implications. Evaluations of the data from the literature showed that migration could be the result of climate change, though such migration does not happen in isolation. In other words, this kind of migration is frequently linked to other issues such as the fragility and lack of adaptability of the communities. Furthermore, reviews showed that climate change catalyzes instability and conflict. On the other hand, conflict damages the environment and climate in multiple ways. Therefore, it is necessary to collaborate to resolve these two issues concurrently.

Joint effects of heat-humidity compound events on drowning mortality in Southern China

BackgroundSeveral previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality.MethodsThe drowning mortality data and...

The effects of feeding frequency on jaw loading in two lemur species.

Studies on oral processing are often snapshots of behaviors that examine feeding through individual bouts. In this study, we expand on our previous work comparing bite/chew variables per feeding bout to summed daily biting, chewing, and food intake to interpret loading that could have potential morphological effects. We observed sympatric Lemur catta and Propithecus verreauxi over two field seasons in the dry forest of Bezà Mahafaly Special Reserve in southwestern Madagascar. Bite and chew rates determined from videos filmed during observations were multiplied with time spent feeding on specific foods during focal follows to calculate daily values for each feeding bout. Food mechanical properties (FMPs) were tested on dietary items with a portable tester. We contrasted daily bite/chew numbers and intake with FMPs, species, season, and food shape. Daily bite and chew numbers increased with maximum, but not average, food toughness. Daily intake decreased with average and maximum toughness. Season had a strong effect on daily bites and chews, but not on intake. Food shape influenced intake and total bite and chew numbers. The lemur species did not differ in our models. Maximum food toughness impacted feeding behaviors and intake, which is consistent with higher loads having a greater effect on morphology. In contrast to feeding per bout, cumulative biting and chewing did not differ between species; taking feeding frequency into consideration affects interpretation of jaw loading. Finally, biting, as much as chewing, may generate strains that impact morphology.

Ecological intensification: multifunctional flower strips support beneficial arthropods in an organic apple orchard

Flower strips are a fundamental part of agri-environment schemes in the Common Agricultural Policy (CAP). Although vegetation is central for many arthropod groups, a few studies have evaluated the effects of flower strip structural and functional attributes on arthropod communities. In this study, we explored the relationship between flower strip attributes and the abundance of different arthropod functional groups in annual flower strips located in an organic apple orchard. We surveyed plant and arthropod communities in 30 1 m × 6 m plots. In each plot, we collected data on species composition and vegetation structure (e.g., total cover, density, number of floral displays). For each plant species, we also retrieved data on leaf palatability and nutritional value. Arthropods were collected using sweep netting technique. Structural and functional attributes of the flower strip revealed a crucial role in regulating arthropod abundance, which however depended on the specific arthropod functional group. We identified three main attributes (plant species richness, composition, and vegetation density) of flower strips that should be considered when implementing multifunctional flower strips. Specifically, plant species richness to ensure complementarity of resources and niches, plant species composition to ensure complementary floral resources, and vegetation density to ensure sheltering microhabitats and suitable microclimatic conditions and to increase the density of floral resources. Our results suggest that by considering structural and functional attributes of flower strips, it is possible to design multifunctional flower strips with greater effectiveness as measures for ecological intensification.

Global stability design of concrete-filled corrugated steel tubular columns

In recent years, various types of concrete-filled steel tubular (CFST) columns were proposed and they have been widely used in engineering practice. Considering the great confinement effect of corrugated steel plate on the concrete, a novel type of CFST column called concrete-filled corrugated steel tubular (CFCST) column was proposed. The CFCST column consists of horizontally corrugated steel plates, corner steel bars and infilled concrete. In this paper, the stability performance of CFCST columns is studied. Firstly, a finite element (FE) model was developed for numerical simulation. The ultimate resistances, load-displacement curves and failure modes obtained from the FE models were compared with previous test results to verify the validity of the FE model. Subsequently, seven sets of numerical examples were analyzed to investigate the impact of key parameters on the global stability performance of CFCST columns. These examples involved variations in geometric dimensions, corrugation shapes and material strengths. Finally, the stability coefficients φ of CFCST columns obtained from FE numerical simulation were compared to several existing stability curves. On this basis, a new stability curve was proposed for predicting the global stability resistance of CFCST columns with good accuracy and reasonable redundancy.

Alpha effect-driven enhancement of CO2 capture kinetics and size-controlled NaHCO3 crystals: Promoter-added NaOH absorbent study

In this study, the kinetics of the transition of Na2CO3 to NaHCO3 were enhanced based on the alpha effect by adding rate promoters to NaOH-based absorbents. Because the α-effect shows strong correlation with the electronegativity of the α-atom, to analyze their kinetic improvement, H2O2, NaOCl, and H3BO3 were selected as rate promoters. The promoters were chosen based on compounds with an O− or OH– group that can act as a Lewis base when CO2 acts as a Lewis acid or a structure that is easily accessible to CO2 molecules. Each promoter was added at different concentrations (0.05, 0.1, and 0.2 M), and the reaction rates of the absorbent solutions were experimentally evaluated. Among selected promoters, H2O2 exhibits the greatest effect, achieved the highest conversion efficiency, which showed an approximately 45-fold increase in reaction rate compared to the promoter-free NaOH solution. Furthermore, the enhancement in reaction rate allows the particle size to be controlled and precipitated with different crystalline structure. Therefore, the introduction of a promoter based on the α-effect not only significantly improves the reaction rate leading to NaHCO3 formation but also allows control of the crystal size and shape. This breakthrough can be a promising solution to address the limitations of conventional NaOH absorbents.

Do Workplace Fish Tanks Influence Employee Wellbeing and Cognitive Performance? An Embedded Mixed-Methods Study

ABSTRACT Evidence from “pet-friendly” workplaces highlights potential benefits associated with taking companion animals to work, including reduced stress among employees. Ornamental fishes carry a much lower risk than other companion animals and may be a suitable alternative in situations where other animals would introduce too great a risk (e.g., allergy, accidental injury). The aim of this study was to investigate whether watching an aquarium during the working day influenced employee wellbeing through the reduction of stress and improvements in stress-related outcomes. An embedded mixed-methods study was conducted, comprising two within-subjects trials (Trials A and B) and a qualitative follow-up. Participants were university employees and research students who participated during their working day. In Trial A (n = 30), the immediate effects of watching live fishes on mood, physiological stress, and cognitive performance were compared with the effects of watching a fish video or resting quietly. Although some outcomes improved from pre- to post-activity, there was no evidence that watching fishes (live or video) had greater effects than resting quietly. In Trial B (n = 27), the effects of repeatedly engaging in the same three activities over several weeks were examined. Watching fish videos was associated with improvements in “high pleasure-low arousal” and overall job-related affective wellbeing, but no further effects of condition were found. Qualitative follow-up data collected from a subset of participants from the experimental trials (n = 13) indicated that all three activities may be beneficial as leaving their desks provided detachment from work for a short period. Qualitative data suggested that live fishes were perceived as more engaging, but this did not translate to quantitative findings. Locating fish aquaria within offices (rather than a separate workplace location) may promote wellbeing by encouraging “microbreaks”; further research is needed to investigate this hypothesis.

The National Nutrition Improvement Program and the equity of educational opportunities: evidence from rural China

ABSTRACT The Children’s Nutrition and Health Poverty Alleviation Project is a vital initiative of the Chinese government to boost education, narrow urban-rural educational gaps, and ensure equal educational opportunities. Based on the 2015 China Health and Nutrition Survey (CHNS) data, this paper empirically evaluates the impact of the National Nutrition Improvement Program on the equity of rural educational opportunities using Differences-in-Differences (DID) method of the cross-sectional data. Findings indicate that Nutrition Improvement Program (NIP), by providing free nutritious lunches for children, reduced the opportunity cost of children going to school, and significantly promoted the improvement of children’s education level. The implementation of the one-semester policy increased children’s educational years by an average of 0.14, which is attributed to the fact that the NIP has contributed to children’s access to higher levels of education, because we found that the NIP had no significant impact on children’s primary and junior high school enrolment, but significantly increased senior high school and university enrolment by 5.8 and 4.2% points. Heterogeneity analysis reveals a stronger impact on children with less-educated, poorer fathers and a greater effect on boys than girls. Additionally, central pilot counties experience a more significant policy effect than local pilot counties.

66 Effect of copper oxide wire particles on parasitism and growth in Katahdin lambs divergently selected for fecal egg count estimated breeding value

Abstract Internal parasites are one of the greatest threats to small ruminant production across the United States and parasitic resistance to anthelmintics continues to increase. Genetic selection and copper oxide wire particles (COWP) are two tools that could help reduce effects of parasites in small ruminants. The objective of this project was to determine the effects and interactions of COWP and genetic selection based on fecal egg count (FEC) estimated breeding value (EBV) on gastrointestinal nematode (GIN) infection and performance in naturally infected Katahdin lambs. Spring-born Katahdin ram lambs (n = 52) selected for extremely high FEC EBV (HighFEC, PFEC EBV = +100%) or low FEC EBV (LowFEC, PFEC EBV = -81%) were managed on a fescue-based pasture at the Southwest Virginia Agricultural Research and Extension Center (Glade Spring, VA). At weaning (June 29), lambs were dewormed with a three-combination treatment and rested for 21 d. At the start of the project (July 18), a random subset of lambs (HighFEC, n = 11; LowFEC, n = 15) were given a 2 g copper oxide wire particle bolus, while an equal number of remaining lambs were managed as controls without a copper bolus. All lambs were managed as one contemporary group. Fecal egg counts, FAMACHA scores, body weights, and packed cell volume (PCV) were measured bi-weekly for 10 weeks. Statistical analysis was performed using PROC Mixed Procedure of SAS (SAS Institute, Cary, NC) and FEC data were log transformed for normality. There were no effects of COWP treatment on FEC (P = 0.18). However, LowFEC-selected lambs had less FEC than HighFEC-selected lambs (230 vs. 565 eggs/g, respectively; P < 0.01). There was no interaction of COWP treatment and FEC genotype (P = 0.37). Copper oxide wire particle treatment had no effect on lamb body weight (P = 0.21), PCV (P = 0.69), FAMACHA score (P = 0.41), or overall ADG (P = 0.12). Lamb FEC genotype did not affect FAMACHA score or overall ADG (P = 0.10 and P = 0.22, respectively). LowFEC-selected lambs had lighter body weights (27.7 vs. 30.6 kg, respectively) and PCV (29.2% vs. 30.4%, respectively) than the HighFEC-selected lambs (P < 0.05). None of the 52 lambs met the requirement for deworming (FAMACHA ≥ 3) during the study. These results indicate that lamb FEC genotype may have a greater effect on parasitism than COWP treatment when given once during the post-weaning period. Even so, multiple tools should be considered, in addition to selection, for an integrated parasite management plan.

Higher percentage of CD34+ stem cells and elevated efficacy in androgenetic alopecia treatment observed in CGF prepared from 640 nm laser-pretreated blood: A preliminary study.

Concentrated growth factor (CGF) injection has proven effective in treating androgenetic alopecia (AGA). The primary mechanism of CGF in treating AGA is thought to be the CD34+ stem cells and platelets-associated growth factors being injected into the scalp. CGF efficacy in treating AGA may rely on the activation level of these stem cells and platelets. The 640 nm laser is a United States Food and Drug Administration approved AGA treatment that activates follicle stem cells. Therefore, we hypothesize that pretreating CGF with a 640 nm laser may further activate CD34+ stem cells and platelets, thereby improving the efficacy of CGF in treating AGA. This study aims to investigate whether 640 nm laser pretreated CGF (640CGF) has a greater effect in treating AGA than 640 nm laser non-pretreated CGF (N640CGF) and evaluate whether 640 nm laser pretreatment changed CD34+ cell percentage. This study enrolled 10 patients (8 male, 2 female) with AGA aged 18-60 years who received CGF injections. The 640CGF group was pretreated with a 640 nm laser at an energy density of 4 J/cm2, with a 30 cm irradiation distance for 30 min. Half of the scalp was treated with 640CGF, whereas the other half was treated with N640CGF. The injection was prepared by a doctor who did not know which blood tube had been pretreated. The treatment efficacy was evaluated using a trichoscope 1 month after injection. All 10 (100%) patients participated in the follow-up visit, and a higher quantity of new hairs was observed on the side injected with 640CGF than N640CGF (p = 0.019). Additionally, fewer malnourished hairs were observed on the 640CGF pretreated side (p = 0.015). No serious adverse events were reported. A higher percentage of CD34+ stem cells and improved efficacy in AGA treatment could be observed with CGF prepared from 640 nm laser-pretreated blood.

Continuous Gesture Control of a Robot Arm: Performance Is Robust to a Variety of Hand-to-Robot Maps.

Despite advances in human-machine-interface design, we lack the ability to give people precise and fast control over high degree of freedom (DOF) systems, like robotic limbs. Attempts to improve control often focus on the static map that links user input to device commands; hypothesizing that the user's skill acquisition can be improved by finding an intuitive map. Here we investigate what map features affect skill acquisition. Each of our 36 participants used one of three maps that translated their 19-dimensional finger movement into the 5 robot joints and used the robot to pick up and move objects. The maps were each constructed to maximize a different control principle to reveal what features are most critical for user performance. 1) Principal Components Analysis to maximize the linear capture of finger variance, 2) our novel Egalitarian Principal Components Analysis to maximize the equality of variance captured by each component and 3) a Nonlinear Autoencoder to achieve both high variance capture and less biased variance allocation across latent dimensions Results: Despite large differences in the mapping structures there were no significant differences in group performance. Participants' natural aptitude had a far greater effect on performance than the map. Robot-user interfaces are becoming increasingly common and require new designs to make them easier to operate. Here we show that optimizing the map may not be the appropriate target to improve operator skill. Therefore, further efforts should focus on other aspects of the robot-user-interface such as feedback or learning environment.

Explainable ensemble learning predictive model for thermal conductivity of cement-based foam

Cement-based foam has emerged as a strong contender in sustainable construction owing to its superior thermal and sound insulation properties, fire resistance, and cost-effectiveness. To effectively use cement-based foam as a thermal insulation material, it is important to accurately predict its thermal conductivity. The current study aims at coining an accurate methodology for predicting the thermal conductivity of cement-based foam using state-of-the-art machine learning techniques. A comprehensive experimental dataset of 504 data points was developed and used for training ensemble learning models including XGBoost, CatBoost, LightGBM and Random Forest. The independent variables of this dataset affecting the thermal conductivity are the cast density, percentage of pozzolan, porosity, percentage of moisture, and duration of hydration in days. Using the Isolation Forest algorithm proved effective in detecting and eliminating outliers in the dataset. All the ensemble learning techniques explored in this study achieved superior predictive accuracy with a coefficient of determination greater than 0.98 on the test dataset. The influence of the input features on the thermal conductivity was visualized using the SHapley Additive exPlanations (SHAP) approach and individual conditional expectation (ICE) plots. The cast density had the greatest effect on thermal conductivity. The explainable machine learning models demonstrated superior accuracy, efficiency, and reliability in estimating the thermal insulation of cement-based foam, opening the door for wider acceptance of this material in sustainable energy efficient construction.

The Potential of Pop-Up Artworks for Visual Communication in Digital Media

The pop-up mechanism or paper engineering is often referred to as a physical card or book, which can show 3D objects when it is opened. In fact, pop-up artworks can also be found in digital media such as movies, animation, video games, video advertisement, and music video. There are many interesting differences between physical pop-up and digital pop-up that can be analyzed to maximize its potential and create great visual effects, especially in digital media. This research uses a qualitative descriptive method by collecting data through observation of digital pop-up artworks and literature studies. Various examples will be analyzed to find out the strengths, weaknesses, and potential of pop-up artworks for visual communication in digital media.

Curcumin activates the JNK signaling pathway to promote ferroptosis in colon cancer cells.

Recent evidence has proved that curcumin as a natural polyphenol have a great anticancer and anti-proliferative effects in cancer cells. Ferroptosis, a new form of regulated cell death, plays a vital role in the pathogenesis and therapy of cancers. In this study, we aimed to examine the effects of curcumin in ferroptosis of human colorectal cancer cells and its underlying molecular mechanisms. SW-480 colorectal cancer cells were treated by curcumin with different concentrations. Cell viability was determined by using MTT assay. The concentrations of reactive oxygen species (ROS) and intracellular iron were measured using specific related kits. Real-time PCR and Western blot analysis were used to determine the expression of ferroptosis-related proteins including ACSL4, GPx4 and FTH1 and activation of JNK protein. Curcumin suppressed SW-480 cancer cells viability in dose-dependent manner. Cell treatment with curcumin led to accumulation of ROS and iron within cells and increase in the intracellular levels of lipid peroxidation. In addition, curcumin modulated the mRNA and protein expression levels of ferroptosis-related proteins including ACSL4, GPx4 and FTH1 and suppression of JNK signaling. Curcumin may exhibit its anticancer effect on colorectal cancer by downregulating JNK signaling to induce ferroptosis in SW-480 cells.

Исследование нефтеемкости природных опоков Астраханской области

The article deals with the issues of studying the absorption capacity of oil and petroleum products (oil capacity) by a natural sorbent- the flask of the Central Kamennoyarsk field of the Astrakhan region. The study of oil capacity makes it possible to determine the possibility of using natural flakes as oil sorbents to collect oil and more viscous petroleum products from the surface of soils and hard coatings. In this work, the influence of the granulometric composition of the sorbent, the sorption temperature and the viscosity characteristics of oil and petroleum products on the oil capacity of the sorbent is studied. The regularities of the absorption capacity of natural flakes in the presence of oil, fuel oil, oil, gasoline and diesel fractions at temperature range from –5 to 40°C have been established. To determine the oil capacity, a static research method was used, in which the sorbent was not subjected to mechanical mixing during contact with the petroleum product. Thus, when testing sorbent fractions with particle sizes less than 1 and 2.5 mm it was stated that high oil capacity results (0.79-0.88 g/g) were achieved at temperature range from –5 and 20ºC in the presence of fuel oil and oil. The greatest sorption effect is achieved due to the influence of external adsorption and the adhesive action of high-viscosity petroleum products. A further increase in temperature to 40ºC reduces the viscosity of petroleum products and prevents the formation of a stable mixture with the sorbent. Relatively low values of the sorption capacity were obtained in the presence of watered oil. Regardless of the temperature, the oil capacity does not exceed 0.75 g/g. The collection of gasoline and diesel fuel is ineffective due to their low viscosity and high volatility.

Impact of digitization on carbon productivity: an empirical analysis of 136 countries

Enhancing carbon productivity (CP) is key to achieving carbon reduction goals while maintaining economic growth. Digital technology plays a significant role in improving CP. Based on panel data from 136 countries worldwide from 2000 to 2020, this study empirically examines the impact of digitalization on CP and its mechanisms using fixed-effects and mediation models. The conclusions are as follows: (1) Overall, digitalization significantly enhances CP. (2) In terms of the mechanism, digitalization primarily improves CP through technological innovation and mitigating income inequality. (3) In terms of the quantile regression results, as the quantile level of CP increases, the promoting effect of digitalization on CP gradually strengthens. (4) From the perspective of heterogeneity among regions, income levels and human capital levels, digitalization has the greatest promotion effect on carbon productivity in European countries, high-income countries and high human capital countries. This study provides a reference for policymakers worldwide to use digital technology in achieving carbon emission reduction targets.