Effect of Gum Arabic from Acacia senegal var. kerensis as an Improver on the Rheological Properties of Wheat Flour Dough

Dough improvers are substances with functional characteristics used in baking industry to enhance dough properties. Currently, the baking industry is faced with increasing demand for natural ingredients owing to increasing consumer awareness, thus contributing to the rising demand for natural hydrocolloids. Gum Arabic from Acacia senegal var. kerensis is a natural gum exhibiting excellent water binding and emulsification capacity. However, very little is reported on how it affects the rheological properties of wheat dough. The aim of this study was therefore, to determine the rheological properties of wheat dough with partial additions of gum Arabic as an improver. Six treatments were analyzed comprising of: flour-gum blends prepared by adding gum Arabic to wheat flour at different levels (1%, 2% and 3%), plain wheat flour (negative control), commercial bread flour and commercial chapati flour (positive controls). The rheological properties were determined using Brabender Farinograph, Brabender Extensograph and Brabender Viscograph. Results showed that addition of gum Arabic significantly (p chapati. These findings support the need to utilize gum Arabic from Acacia senegal var. kerensis as a dough improver.

Poly-Acrylic Acid Derivatives as Diesel Flow Improver for Paraffin-Based Daqing Diesel

Since the diesel products from paraffin-based Daqing crude oil showed low sensitivity to certain commercial diesel pour point depressant （PPDs） that resulted from the high content of paraffin, certain poly-acrylic acid derivatives （PADE） with-COOR, -COOH,-CONHR, and -COO-NH3^＋R groups by molecular design on the mechanics of diesel; PPDs were synthesized and evaluated as cold flow improver for Daqing 0^# diesel in this paper. The pure PADE was superior to the commercial PPDs and displayed a substantial ability of wax crystals dispersion. There was a synergistic effect among the PADE and T1804 and secondary amine. The synergism clearly improved the low temperature performance of Daqing diesel products and could reduce the cold filter plugging point of 0^# diesel by 6-7 ℃.

A new alternating copolymerized derivative as a cold flow improver for diesel fuel

Synthesis of a cold flow improver （MAVA-a） for diesel fuel and its effect on solidifying point （SP） and cold filter plugging point （CFPP） of diesel fuels were investigated, The cold flow improver was prepared by using maleic anhydride （MA） and vinyl acetate （VA） as raw materials, toluene as solvent, dibenzoyl peroxide （BPO） as initiator, through alternating polymerization under nitrogen to obtain a binary-polymer and then through aminolysis by using a higher carbon amine as aminating agent at a temperature of 80 ℃. A cold flow improver was designed and prepared for No. 0 diesel fuel from Zhang Jia-Gang Petrochemical Company according to the contents of n-paraffin and its carbon number distribution in the No. 0 diesel fuel. It was also used together with two kinds of ethene-vinyl acetate copolymer improvers （EVA） separately. The test result showed that the CFPP of the No. 0 diesel fuel could be lowered by 3-5 ℃ when the improver MAVA-a was used. The CFPP was lowered by 8℃ when the improver MAVA-a was used together with EVA-2.

Chloroaluminate ionic liquid catalyzed isomerization of n-pentane in the presence of product distribution improver

The ionic liquid Et3NHC1-2AIC13 can catalyze the isomerization of n-pentane. This paper investigates the ionic liquid catalyzed isomerization performance of n-pentane with several product distribution improvers in an autoclave. The product distribution of n-pentane isomerization could be improved by such improvers as benzene, cyelohexane, and methyl cyclohexane at the expense of conversion of n-pentane. The optimal product distribution improver was determined to be cyclohexane. The yield of isomerate and the selectivity of liquid isoalkanes increased, whereas the conversion of n-pentane decreased, with increasing cyclohexane amount. At the same conversion of n-pentane, the research octane number （RON） of liquid product, with cyclohexane amount of 0.5 wt%, was about 1.3 higher than that without cyclohexane. At the same reaction conditions, the presence of cyclohexane enhanced the yield of isomerate, the selectivity of liquid isoalkanes, and the RON of the liquid product, but reduced the conversion of n-pentane.

How Polymers Behave as Viscosity Index Improvers in Lubricating Oils

One of the requirements of engine lubricating oil is that it must have a low enough viscosity at low temperatures to assist in cold starting and a high enough viscosity at high temperatures to maintain its load-bearing characteristics. Viscosity Index (VI) is one approach used widely in the lubricating field to assess the variation of viscosity with temperature. The VI of both mineral and synthetic base oils can be improved by the addition of polymeric viscosity modifiers (VMs). VI improvement by VMs is widely attributed to the polymer coil size expanding with increasing temperature. However, there is very little physical data supporting this generally accepted mechanism. To address this issue, intrinsic viscosity measurements and Small-Angle Neutron Scattering (SANS) have been used to study the variation of polymer coil size with changing temperature and concentration in a selection of solvents. The results will show that coil size expansion with temperature is not necessary to achieve significant elevation of viscosity index.

Co-adsorption behaviors of asphaltenes and different flow improvers and their impacts on the interfacial viscoelasticity

Commonly used flow improvers in oilfields,such as ethylene–vinyl acetate copolymer(EVA),poly(octadecyl acrylate)(POA),and polymethylsilsesquioxane(PMSQ)are proven to be effective to enhance the flowability of crude oil.However,the addition of these flow improvers may change the stability of the emulsion and make the crude oil treatment process challenging.In this research,the impacts of different flow improvers on the interfacial properties of the emulsions containing asphaltenes are systematically investigated.The co-adsorption behaviors of the flow improvers and asphaltenes are analyzed through dynamic interfacial tension(DIFT).The rheological properties of the interfacial layer after the adsorption are explored via dilational viscoelasticity.Significant difference is observed in the structural properties of the interface adsorbed by different flow improvers,which is attributed to different interactions between the flow improvers and asphaltenes.To investigate these interactions,conductivity,asphaltenes precipitation,dynamic light scattering(DLS),and contact angle experiments are conducted systematically.Results show that EVA and POA can alter the interfacial properties by changing the asphaltene dispersion state.The interaction between EVA and asphaltenes is stronger than that between POA and asphaltenes due to the difference in molecular structures.Unlike EVA and POA,the change of interfacial property with the addition of PMSQ is attributed to the partial adsorption of asphaltenes on PMSQ.

Aminated Copolymers as Flow Improvers for Super-viscous Crude Oils

The new flow improvers for super-viscous crude oils were developed via esterification of polybasic high carbon alcohol with methacrylate and copolymerizafion of monomers followed by amination of copolymers. The structure of the synthesized polymer flow improver additive was confirmed by IR spectroscopy and the crystal structure of the flow improver additives were determined by X-ray diffrac- tion analysis. The structure of wax crystals was also studied at the same time. The results showed that the wax crystal structure was closely related with the crystal structure of the flow improver, which could change the pour point depression and viscosity reduction behavior of the crude oil. When the wax crystal structure matched well with that of the additive, the wax crystals were dispersed satisfactorily, resulting in favorable effects in terms of pour point depression and viscosity reduction. The new synthe- sized aminated polymer flow improver additive was most efficient for treating super-viscous crude oils. The super-viscous crude oil had a high content of resins and asphaltenes, which might aggregate onto the surface of wax crystals to form blocks to limit the crude oil fluidity. However, amination of copolymers having similar structure with the resins and asphaltenes contained in crude oil could dissolve the huge polar groups to make the deposit formation difficult.

Synthesis and Properties of Dendritic Long-Chain Esters as Crude Oil Flow Improver Additives

The efficiencies of 6 kinds of macromolecules with dendritic structure in improving the flow properties of crude oil were investigated. The dendritic additives were synthesized using low-generation dendritic poly(amidoamine) and alkyl longchain acrylic esters as starting materials, and their structures were characterized by the Fourier transform infrared spectroscopy, 1H-nuclear magnetic resonance and elemental analysis. The effects on the pour point and rheological properties of crude oil samples were studied. Efficiencies of dendritic long-chain esters were not only influenced by the alky chain length, but also by the generation of dendrimer. The longer the alkyl chain of dendritic long-chain ester was, the better the effect in the reduction of pour point and apparent viscosity was. Efficiencies of 1.5 generation dendritic long-chain ester with 8 branched chains for the reduction of pour point and apparent viscosity were superior to those of 0.5 generation dendritic long-chain ester with 4 branched chains. Under the same conditions, efficiencies of 1.5 generation dendritic eighteen ester were superior to those of other 1.5 generation dendritic long-chain esters for the reduction of pour point and viscosity of crude oil.

Effects of Soil Improver on Wheat in Saline-Alkali Lands in the Yellow River Delta

Field experiment carried out to test the effects of soil improver on wheat yield and soil physical-chemical properties. The results indicated that soil improver could optimize soil aggregates structure, decrease soil bulk density, soil pH and soil salt content, increase soil organic matter and 1 000-grain weight, thereby enhancing wheat yield. With the increase of soil improver application amount, soil physical-chemical properties became better and wheat yield increased. However, there was no significant difference in the treatments with the application amounts of 3%, 4% and 5%. In addition, the treatment of reducing nitrogen showed no superiority in soil physical-chemical properties and wheat yield, indicating that sufficient nitrogen was essential for the growth of wheat.

Effects of Cereal Malts Used as Improver on Physico-Chemical, Nutritional and Sensory Characteristics of Wheat and Millet Composites Breads

The aim of this study was to optimize composite breads of wheat and whole millet flour by the use of natural improvers. Three types of local malted cereals were used as natural improvers. The millet flour was fermented with EPSs producing LAB strain prior to use. The technological characteristics of the composite flours were determined using an alveograph. The physico-chemical and nutritional characteristics of the composite breads were determined using standard methods and their sensory profiles were evaluated by a panel of 35 consumers. The alveograph results showed an increase in dough resistance, deformation and a decrease in extensibility and elasticity with the level of incorporation of millet flour. From the results of physico-chemical analyses of composite breads, no significant difference (p > 0.05) was observed in the use of the three types of local cereal malts except for the incorporation of 50% of the millet flour. The control sample presented the lowest acidity and dry matter value, the highest water content and pH value. No significant difference (p > 0.05) was observed in the use of the three types of cereal malts for the macronutrient contents of the composite bread samples. However, differences were observed according to the levels of incorporation. Macronutrients results showed an increase in protein content (11.17% ± 0.28% - 14.01% ± 0.10%/DM);crude fat content (1.86% ± 0.05% - 2.48% ± 0.20%/DM) and a decrease in carbohydrates content (85.36% ± 0.54% - 81.06% ± 0.36%/ DM). Regarding the content of mineral elements, significant differences (p < 0.05) were observed in the use of the three types of cereal malts for the incorporation of 15% (Mg and Fe content), 30% (Fe, Zn and K) and 50% (content of Zn, K, Na and Mg) of millet flour. The free amino acid profile revealed three essential amino acids such as valine, isoleucine and lysine. Breads incorporated with 30% of whole millet flour were the most appreciated by consumers.

An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor accuracy.Therefore,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection algorithm.To improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone network.The Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference capabilities.The Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the algorithm.The experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the YOLOv7.The feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Rheological Study of Polymers Used as Viscosity Index Improvers for Automotive Lubricant Oils

In this work, a rheological study of automotive lubricant oils, neutral light paraffinic (NLP) and neutral medium paraffinic (NMP), additivated with two commercial viscosity index improvers-VIIs, based on hydrogenated poly (isoprene-co-styrene), at different concentrations, was carried out. The study included the determination of the kinematic viscosity of the mixtures, the calculation of the viscosity indexes and their behavior when subjected to various rheometric experiments, including stress sweep, steady state flow, creep and recovery, and temperature ramp oscillatory tests. The obtained results showed the efficacy of the additives as viscosity index improvers, enabling a significant increase in the viscosity index of the pure oils at relatively low concentrations. The determination of the storage (G’) and of the loss (G”) moduli for the mixtures oil/VII additives showed a large predominance of the viscous effect over the elastic one. Except when under low shear stress, the mixtures showed a pseudoplastic behavior, with the flow curves being adjusted to fit the Ostwald-de-Waele model (Power Law), with negative flow behavior indexes.

Mechanism of La2O3 as combustion improver in blast furnace coal injection

La2O3 is a combustion improver suitable for burning pulverized coal in blast furnace. La2O3 forms the active species La3＋（CO-）3 that weakens the bridge adhesion of carbon structural units and alters the lattice structures, thus reducing the activation energy of the pulverized coal and accelerating the burning process. Research shows that La2O3 can form the active species La3＋（CO-）3, which weakens the bridge adhesion of carbon structural units and alters the lattice structures of the fixed carbon, hence decreasing the activation energy of the pulverized coal and accelerating the burning process.

Nitrogen, Phosphorus, and Potassium Interactive Effects for Improving Drought Resistance on Mung Bean Varieties

The planting areas of mung bean are mostly arid and semi-arid areas, and lack of irrigation conditions. Many studies have reported that fertilization can increase drought resistance. In our previous research, optimized nitrogen (N), phosphorus (P) and potassium (K) combined fertilization model was established in mung bean. In the present study, the optimal fertilization was conducted in pot trails, and mung bean varieties Bailv9 and Bailv11 were used as materials, while the four water regimes, and three fertilization ratios of F120 (optimal fertilization), F100 (conventional fertilization), F50 (half of conventional fertilization) treatments were set, to compare each fertilization ratio effects and non-fertilization condition under each water regimes respectively. Under different water conditions, the investigation of N, P, and K effects of optimal fertilization showed that the yield of Bailv9 was not sensitive to water stress and had strong drought resistance;their water sensitivity index and drought resistance coefficient were BaiLv9 as Di = 0.89 and DC = 0.79. The yield of Bailv11 was sensitive to water stress, and their drought resistance was weak;their water sensitivity index and drought resistance coefficient were BL11 Di = 1.76 DC = 0.59, and under different water treatment conditions, Bailv9 and Bailv11 all had the best yield and other related traits increase in the F120 fertilization mode compared with other fertilization and non-fertilization conditions, and the average yield increases were 31.56% and 28.08%, respectively. The pot trails conduct the drought stress treatments in mung bean varieties Bailv9, Bailv11, Bailv935 and Bailv985 to determine the function of NPK optimized fertilization for improving plants growth in drought stress condition. Compared with the mung bean varieties treated with F50, F100, and F120, the yield of Bailv9 increased by 56.20%, 81.27%, and 107.22%, respectively;compared with that of F0, the yield of Bailv11 increased by 10.18%, 19.42%, and 45.88%, respectively;Bailv935 increased by 26.52%, 61.90%, 74.16% respectively, and Bailv985 increased by 23.78%, 56.92%, 87.62% respectively. The significant performances of optimized fertilization were also verified in 20 mung bean varieties in our filed trails. The research establishes a theoretical basis for introducing the model into production practice in the next step.

IGED:Towards Intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly vital.We propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data volume.Then the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization capabilities.Experimental results show that the proposed method can efficiently distinguish normal traffic from DDoS traffic.Compared with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

Value of improved nursing measures and enhanced nursing management to reduce the occurrence of adverse events in pediatric infusion

BACKGROUND Intravenous infusion is a common method of drug administration in clinical practice.Errors in any aspect of the infusion process,from the verification of medical orders,preparation of the drug solution,to infusion by nursing staff,may cause adverse infusion events.AIM To analyzed the value of improving nursing measures and enhancing nursing management to reduce the occurrence of adverse events in pediatric infusion.METHODS The clinical data of 130 children who received an infusion in the pediatric department of our hospital from May 2020 to May 2021 were analyzed and divided into two groups according to the differences in nursing measures and nursing management:65 patients in the control group received conventional nursing and nursing management interventions,while 65 patients in the observation group received improved nursing measure interventions and enhanced nursing management.The occurrence of adverse events,compliance of children,satisfaction of children’s families,and complaints regarding the transfusion treatment were recorded in both groups.RESULTS The incidence of fluid extravasation and infusion set dislodgement in the observation group were 3.08%and 1.54%,respectively,which were significantly lower than 12.31%and 13.85%in the control group(P<0.05),while repeated punctures and medication addition errors in the observation group were 3.08%and 0.00%,respectively,which were lower than 9.23%and 3.08%in the control group,but there was no significant difference(P>0.05).The compliance rate of children in the observation group was 98.46%(64/65),which was significantly higher than 87.69%(57/65)in the control group,and the satisfaction rate of children’s families was 96.92%(63/65),which was significantly higher than 86.15%(56/65)in the control group(P<0.05).The observation group did not receive any complaints from the child’s family,whereas the control group received four complaints,two of which were due to the crying of the child caused by repeated punctures,one due to the poor attitude of the nurse,and one due to medication addition errors,with a cumulative complaint rate of 6.15%.The cumulative complaint rate of the observation group was significantly lower than that of the control group(P<0.05).CONCLUSION Improving nursing measures and enhancing nursing management can reduce the incidence of fluid extravasation and infusion set dislodgement in pediatric patients,improve children’s compliance and satisfaction of their families,and reduce family complaints.

Approaches to Improving Selectivity During Photoelectrochemical Transformation of Small Molecules

Photoelectrochemical (PEC) small-molecule oxidation can selectively transform substrates into high-value-added fine chemicals and increase the rate of cathode hydrogen evolution. Nevertheless, achieving high-selectivity PEC oxidation of small molecules to produce specific products is a very challenging task. In general, selectivity can be improved by changing the surface catalyticsites of the photoanode and modulating the interfacial environments of the reactions. Herein, recent advances in approaches to improving selective PEC oxidation of small molecules are introduced. We first briefly discuss the basic concept and fundamentals of small-molecule PEC oxidation. The reported approaches to improving the performance of selective PEC oxidation of small molecules are highlighted from two aspects: (1) changing the surface properties of photoanodes by selecting suitable materials or modifying the photoanodes and (2) mediating the oxidation reactions using redox mediators. The PEC oxidation mechanism of these studies is emphasized. We also discuss the challenges in this research direction and offer a perspective on the further development of selective PEC-based small-molecule transformation.

Anti-aging performance improvement and enhanced combustion efficiency of boron via the coating of PDA

Boron is an ambitious fuel in energetic materials since its high heat release values,but its application is prohibited by low combustion efficiency and oxidization during storage.The polydopamine(PDA)was introduced into boron particles,investigating the impact of PDA content on the energetic behavior of boron.The results indicated that the PDA coating formed a fishing net structure on the surface of boron particles.The heat release results showed that the combustion calorific value of B@PDA was higher than that of the raw boron.Specifically,the actual combustion heat of boron powder in B@10%PDA increased by 38.08%.Meanwhile,the DSC peak temperature decreased by 100.65℃under similar oxidation rate compared to raw boron.Simultaneously,the B@PDA@AP and B@AP composites were prepared,and their combustion properties were evaluated.It was demonstrated that B@10%PDA@AP exhibited superior performance in terms of peak pressure and burning time,respectively.The peak pressure is 12.43 kPa more than B@AP and burning time is 2.22 times higher than B@AP.Therefore,the coating of PDA effectively inhibits the oxidization of boron during storage and enhances the energetic behavior of boron and corresponding composites.

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.