Effect of wall-disruption on nutrient composition and in vitro digestion of camellia and lotus bee pollens

The nutrient digestion,absorption and biological activity of bee pollen may be limited due to the complex pollen wall.Here,the effect of superfine grinding technology on the release of nutrients from bee pollen were investigated,and their antioxidant activities and in vitro digestion were explored in this study.Results showed that the content of nutrients in bee pollen increased after wall disruption.Among them,fat content increased by 22.55%-8.31%,protein content increased by 0.54%-4.91%,starch content increased by 36.31%-48.64%,soluble sugar content increased by 20.57%-29.67%,total phenolic acid content increased by 11.73%-86.98%and total flavonoids content increased by 14.29%-24.79%.At the same time,the antioxidant activity increased by 14.84%-46.00%.Furthermore,the active components such as phenolic compounds in the wall-disruption bee pollen were more readily to be released during the in vitro digestion,and easier to be absorbed because of their higher bioaccessibility.Antioxidant activities during in vitro digestion were also improved in walldisruption bee pollen.These findings provide evidence that bee pollen wall disruption was suggested,thus,it is more conducive to exerting the value of bee pollen in functional foods.

Effect of different drying methods on the amino acids,α-dicarbonyls and volatile compounds of rape bee pollen

The significant demand for high quality food has motivated us to adopt appropriate processing methods to improve the food nutritional quality and flavors.In this study,the effects of five drying methods,namely,pulsed vacuum drying(PVD),freeze drying(FD),infrared drying(IRD),hot-air drying(HAD)and sun drying(SD)on free amino acids(FAAs),α-dicarbonyl compounds(α-DCs)and volatile compounds(VOCs)in rape bee pollen(RBP)were determined.The results showed that FD significantly released the essential amino acids(EAAs)compared with fresh samples while SD caused the highest loss.Glucosone was the dominantα-DCs in RBP and the highest loss was observed after PVD.Aldehydes were the dominant volatiles of RBP and SD samples contained more new volatile substances(especially aldehydes)than the other four drying methods.Comprehensively,FD and PVD would be potential methods to effectively reduce the quality deterioration of RBP in the drying process.

Comparative analyses of mitogenomes in the social bees with insights into evolution of long inverted repeats in the Meliponini

The insect mitogenome is typically a compact circular molecule with highly conserved gene contents.Nonetheless,mitogenome structural variations have been reported in specific taxa,and gene rearrangements,usually the tRNAs,occur in different lineages.Because synapomorphies of mitogenome organizations can provide information for phylogenetic inferences,comparative analyses of mitogenomes have been given increasing attention.However,most studies use a very few species to represent the whole genus,tribe,family,or even order,overlooking potential variations at lower taxonomic levels,which might lead to some incorrect inferences.To provide new insights into mitogenome organizations and their implications for phylogenetic inference,this study conducted comparative analyses for mitogenomes of three social bee tribes(Meliponini,Bombini,and Apini)based on the phylogenetic framework with denser taxonomic sampling at the species and population levels.Comparative analyses revealed that mitogenomes of Apini and Bombini are the typical type,while those of Meliponini show diverse variations in mitogenome sizes and organizations.Large inverted repeats(IRs)cause significant gene rearrangements of protein coding genes(PCGs)and rRNAs in Indo-Malay/Australian stingless bee species.Molecular evolution analyses showed that the lineage with IRs have lower dN/dS ratios for PCGs than lineages without IRs,indicating potential effects of IRs on the evolution of mitochondrial genes.The finding of IRs and different patterns of gene rearrangements suggested that Meliponini is a hotspot in mitogenome evolution.Unlike conserved PCGs and rRNAs whose rearrangements were found only in the mentioned lineages within Meliponini,tRNA rearrangements are common across all three tribes of social bees,and are significant even at the species level,indicating that comprehensive sampling is needed to fully understand the patterns of tRNA rearrangements,and their implications for phylogenetic inference.

Allergen degradation of bee pollen by lactic acid bacteria fermentation and its alleviatory effects on allergic reactions in BALB/c mice

Food allergy as a global health problem threatens food industry.Bee pollen(BP)is a typical food with allergenic potentials,although it performs various nutritional/pharmacological functions to humans.In this study,lactic acid bacteria(LAB)were used to ferment Brassica napus BP for alleviating its allergenicity.Four novel allergens(glutaredoxin,oleosin-B2,catalase and lipase)were identified with significant decreases in LAB-fermented BP(FBP)than natural BP by proteomics.Meanwhile,metabolomics analysis showed significant increases of 28 characteristic oligopeptides and amino acids in FBP versus BP,indicating the degradation of LAB on allergens.Moreover,FBP showed alleviatory effects in BALB/c mice,which relieved pathological symptoms and lowered production of allergic mediators.Microbial high-throughput sequencing analysis showed that FBP could regulate gut microbiota and metabolism to strengthen immunity,which were closely correlated with the alleviation of allergic reactivity.These findings could contribute to the development and utilization of hypoallergenic BP products.

中美英语词汇比赛模式的比较研究——以“词达人”和“Spelling Bee”为例

词汇比赛是考察学生词汇能力的有效方式,一直备受重视。通过比较我国“词达人”全国大学生英语词汇能力大赛和美国SpellingBee拼读比赛在组织模式、题型设置两方面的差异,可以梳理出当前以“词达人”为代表的国内词汇拼写类比赛可能存在的问题。研究者在此基础上为如何增加“词达人”比赛的观赏性以及扩大比赛影响力提出了可行的方案。

Effect of Apis mellifera on community composition of local pollinator bees and their pollination network in Qinling Mountains and surrounding areas

The Qinling Mountains, known for their rich vegetation and diverse pollinating insects, have seen a significant decline in bee species richness and abundance over recent decades, largely due to the introduction and spread of Apis mellifera. This decline has caused cascading effects on the region's community structure and ecosystem stability. To improve the protection of native bees in the natural and agricultural landscape of the Qinling Mountains and its surrounding areas, we investigated 33 sampling sites within three habitats: forest, forest-agriculture ecotones, and farmland. Using a generalized linear mixing model, t-test, and other data analysis methods, we explored the impact of Apis mellifera on local pollinator bee richness, abundance, and the pollination network in different habitats in these regional areas. The results show that(1)Apis mellifera significantly negatively affects the abundance and richness of wild pollinator bees,while Apis cerana abundance is also affected by beekeeping conditions.(2)There are significant negative effects of Apis mellifera on the community structure of pollinator bees in the Qinling Mountains and its surrounding areas: the Shannon-Wiener diversity index, Pielou evenness index, and Margalef richness index of bee communities at sites with Apis mellifera influence were significantly lower than those at sites without Apis mellifera influence.(3)The underlying driver of this effect is the monopolization of flowering resources by Apis mellifera. This species tends to visit flowering plants with large nectar sources, which constitute a significant portion of the local plant community. By maintaining a dominant role in the bee-plant pollination network, Apis mellifera competitively displaces native pollinator bees, reducing their access to floral resources. This ultimately leads to a reduction in local bee-plant interactions, decreasing the complexity and stability of the pollination network. These findings highlight the need for targeted conservation efforts to protect native pollinator species and maintain the ecological balance in the Qinling Mountains.

Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in Cloud Computing

Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment.Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios.In this work,the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm(HPSO-EABC)has been proposed,which hybrids our presented Evolutionary Artificial Bee Colony(EABC),and Hierarchical Particle Swarm Optimization(HPSO)algorithm.The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm.Comprehensive testing including evaluations of algorithm convergence speed,resource execution time,load balancing,and operational costs has been done.The results indicate that the EABC algorithm exhibits greater parallelism compared to the Artificial Bee Colony algorithm.Compared with the Particle Swarm Optimization algorithm,the HPSO algorithmnot only improves the global search capability but also effectively mitigates getting stuck in local optima.As a result,the hybrid HPSO-EABC algorithm demonstrates significant improvements in terms of stability and convergence speed.Moreover,it exhibits enhanced resource scheduling performance in both homogeneous and heterogeneous environments,effectively reducing execution time and cost,which also is verified by the ablation experimental.

Adaptive Network Sustainability and Defense Based on Artificial Bees Colony Optimization Algorithm for Nature Inspired Cyber Security

Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee Colony Algorithm

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are connected to the distribution network(DN),resulting in a decline in the stability of DN operation.It is urgent to find a method that can effectively connect multi-energy DG to DN.photovoltaic(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are considered in this paper.A multi-objective optimization model was established based on the life cycle cost(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of DN.Multi-objective artificial bee colony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and compared with the other three heuristic algorithms.Simulation tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,compared with that without DG configuration.In the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC configuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,compared with that without DG configuration,indicating that MOABC can reasonably plan the capacity and location of DG.Achieve the maximum trade-off between DG economy and DN operation stability.

Hepatic and renal effects of oral stingless bee honey in a streptozotocin-induced diabetic rat model

BACKGROUND Diabetes is known damage the liver and kidney,leading to hepatic dysfunction and kidney failure.Honey is believed to help in lowering the blood glucose levels of diabetic patients and reducing diabetic complications.However,the effect of stingless bee honey(SBH)administration in relieving liver and kidney damage in diabetes has not been well-studied.AIM To investigate the effect of SBH administration on the kidney and liver of streptozotocin-induced(STZ;55 mg/kg)diabetic Sprague Dawley rats.METHODS The rats were grouped as follows(n=6 per group):non-diabetic(ND),untreated diabetic(UNT),metformin-treated(MET),and SBH+metformin-treated(SBME)groups.After successful diabetic induction,ND and UNT rats were given normal saline,whereas the treatment groups received SBH(2.0 g/kg and/or metformin(250 mg/kg)for 12 d.Serum biochemical parameters and histological changes using hematoxylin and eosin(H&E)and periodic acid–Schiff(PAS)staining were evaluated.RESULTS On H&E and PAS staining,the ND group showed normal architecture and cellularity of Bowman’s capsule and tubules,whereas the UNT and MET groups had an increased glomerular cellularity and thickened basement membrane.The SBH-treated group showed a decrease in hydropic changes and mild cellularity of the glomerulus vs the ND group based on H&E staining,but the two were similar on PAS staining.Likewise,the SBME-treated group had an increase in cellularity of the glomerulus on H&E staining,but it was comparable to the SBH and ND groups on PAS staining.UNT diabetic rats had tubular hydropic tubules,which were smaller than other groups.Reduced fatty vacuole formation and dilated blood sinusoids in liver tissue were seen in the SBH group.Conversely,the UNT group had high glucose levels,which subsequently increased MDA levels,ultimately leading to liver damage.SBH treatment reduced this damage,as evidenced by having the lowest fasting glucose,serum alanine transaminase,aspartate transaminase,and alkaline phosphatase levels compared to other groups,although the levels of liver enzymes were not statistically significant.CONCLUSION The cellularity of the Bowman’s capsule,as well as histological alteration of kidney tubules,glomerular membranes,and liver tissues in diabetic rats after oral SBH resembled those of ND rats.Therefore,SBH exhibited a protective hepatorenal effect in a diabetic rat model.

Impact of Beekeeping on the Wild Bee Diversity in Northern Ivory Coast(West Africa)

In Ivory Coast,beekeeping takes an important place among the major economic activities.It contributes to improv-ing the population’s livelihoods thanks to its derived products which are honey,propolis,wax and royal jelly.How-ever,the installation of honey bee hives could put pressure on wild bee species,which often live solitary.However,these wild bees are excellent pollinators of cultivated and wild plants.The study aimed to assess the effect of honey bee hives on the diversity of wild bees.The methodology approach consisted of capturing bees in three different plots inside the forest fragment of the botanical garden located at the University Peleforo Gon Coulibaly.The first plot was chosen approximately from 10 m to an apiary containing ten hives.The two other plots were chosen to be 200 m and 400 m from the apiary,respectively.Bees were captured once a month for three months using pan traps(UV—blue,yellow and white).A total of 17 bee species belonging to three families(Apidae,Megachilidae and Halictidae)were identified.The furthest plot from the apiary was the most diverse(H’=2.49)and that near the apiary was the least diverse(H’=0.11).Only,two wild bee species,Hypotrigona sp.and Thrinchostoma petersi,persisted inside the plot nearby the apiary where honey bees were most abundant.The furthest plots from the apiary seem to have the highest diversity of wild bees.These findings are very relevant because they can be used for the policies of conservation of wild bees and the management of beekeeping activities.

The improved artificial bee colony algorithm for mixed additive and multiplicative random error model and the bootstrap method for its precision estimation

To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an improved artificial bee colony algorithm without derivative and the bootstrap method to estimate the parameters and evaluate the accuracy of MAM error model.The improved artificial bee colony algorithm can update individuals in multiple dimensions and improve the cooperation ability between individuals by constructing a new search equation based on the idea of quasi-affine transformation.The experimental results show that based on the weighted least squares criterion,the algorithm can get the results consistent with the weighted least squares method without multiple formula derivation.The parameter estimation and accuracy evaluation method based on the bootstrap method can get better parameter estimation and more reasonable accuracy information than existing methods,which provides a new idea for the theory of parameter estimation and accuracy evaluation of the MAM error model.

An Air Defense Weapon Target Assignment Method Based on Multi-Objective Artificial Bee Colony Algorithm

With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.

基于STM32和ZigBee的水产养殖水质监测系统设计

针对水产养殖水质监测操作复杂、监测周期长、监测参数单一等问题,设计了一套基于STM32和ZigBee的水产养殖水质参数监测系统。该系统主要由STM32F103微控系统、ZigBee无线通讯模块、多路传感器模块、信号调理模块、显示模块、蜂鸣器报警模块、按键模块和电源模块等组成,能够同时实现采集、传输,显示水体温度、酸碱度、溶解氧和氨氮,以及异常报警等功能。测试结果表明,该系统运行稳定、安全可靠,实用价值极高。

Efficacy of Bee Products(Anzer Honey,Pollen and Propolis)in Detection and Healing of Damage Induced by Antidiabetic Drug Vildagliptin/Metformin Hydrochloride in Healthy Human Pancreatic Cells:Cytotoxic,Genotoxic and Biochemical Studies

Background and Objective Although drugs are powerful therapeutic agents,they have a range of side effects.These side effects are sometimes cellular and not clinically noticeable.Vildagliptin/metformin hydrochloride is one of the most widely used oral antidiabetic drugs with two active ingredients.In this study,we investigated its harmful effects on the metabolic activation system in healthy human pancreatic cells“hTERT-HPNE”,and we aimed to improve these harmful effects by natural products.To benefit from the healing effect,we used the unique natural products produced by the bees of the Anzer Plateau in the Eastern Black Sea Region of Turkey.Methods Cytotoxic and genotoxic effects of the drug were investigated by different tests,such as MTT,flow cytometry-apoptosis and comet assays.Anzer honey,pollen and propolis were analyzed by gas chromatography/mass spectrometry(G/C-MS).A total of 19 compounds were detected,constituting 99.9%of the samples.Results The decrease in cell viability at all drug concentrations was statistically significant compared to the negative control(P<0.05).A statistically significant decrease was detected in the apoptosis caused by vildagliptin/metformin hydrochloride with the supplementation of Anzer honey,pollen and propolis in hTERT-HPNE cells(P<0.05).Conclusion This study can contribute to other studies testing the healing properties of natural products against the side effects of oral antidiabetics in human cells.In particular,Anzer honey,pollen and propolis can be used as additional foods to maintain cell viability and improve heal damage and can be evaluated against side effects in other drug studies.

A New S-Box Design System for Data Encryption Using Artificial Bee Colony Algorithm

Securing digital image data is a key concern in today’s information-driven society.Effective encryption techniques are required to protect sensitive image data,with the Substitution-box(S-box)often playing a pivotal role in many symmetric encryption systems.This study introduces an innovative approach to creating S-boxes for encryption algorithms.The proposed S-boxes are tested for validity and non-linearity by incorporating them into an image encryption scheme.The nonlinearity measure of the proposed S-boxes is 112.These qualities significantly enhance its resistance to common cryptographic attacks,ensuring high image data security.Furthermore,to assess the robustness of the S-boxes,an encryption system has also been proposed and the proposed S-boxes have been integrated into the designed encryption system.To validate the effectiveness of the proposed encryption system,a comprehensive security analysis including brute force attack and histogram analysis has been performed.In addition,to determine the level of security during the transmission and storage of digital content,the encryption system’s Number of Pixel Change Rate(NPCR),and Unified Averaged Changed Intensity(UACI)are calculated.The results indicate a 99.71%NPCR and 33.51%UACI.These results demonstrate that the proposed S-boxes offer a significant level of security for digital content throughout its transmission and storage.

Bee Colony Optimization Algorithm for Routing and Wavelength Assignment Based on Directional Guidance in Satellite Optical Networks

With the development of satellite communication,in order to solve the problems of shortage of on-board resources and refinement of delay requirements to improve the communication performance of satellite optical networks,this paper proposes a bee colony optimization algorithm for routing and wavelength assignment based on directional guidance(DBCO-RWA)in satellite optical networks.In D-BCORWA,directional guidance based on relative position and link load is defined,and then the link cost function in the path search stage is established based on the directional guidance factor.Finally,feasible solutions are expanded in the global optimization stage.The wavelength utilization,communication success probability,blocking rate,communication hops and convergence characteristic are simulated.The results show that the performance of the proposed algorithm is improved compared with existing algorithms.

Selective Harmonics Elimination Technique for Artificial Bee Colony Implementation

In this research,an Artificial Bee Colony(ABC)algorithm based Selective Harmonics Elimination(SHE)technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system.Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics.A high gain DC-DC-SEPIC converter keeps the photovoltaic(PV)panel’s output voltage constant.The Grey Wolf Optimization(GWO)filter removes far more Photovoltaic panel energy from the sunlight frame.To eliminate voltage harmonics,this unique inverter architecture employs a multi-carrier duty cycle,a high-frequency modulation approach.The proposed ABC harmonics elimination approach is compared to SHE strategies based on Particle Swarm Optimization(PSO)and Flower Pollination Algorithm(FPA).The suggested system’s performance is simulated and measured using the MATLAB simulation tool.The proposed ABC approach has a THD level of 4.86%,which is better than the PSO and FPA methods.

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these needs.The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)constraints.The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints.In this paper,we introduce an extension of our previous works on the Artificial Bee Colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search.The bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence rate.The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different runs.These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets.The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors.TheWilcoxon signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.

Artificial Bee Colony with Cuckoo Search for Solving Service Composition

In recent years,cloud computing has provided a Software As A Service(SaaS)platform where the software can be reused and applied to fulfill compli-cated user demands according to specific Quality of Services(QoS)constraints.The user requirements are formulated as a workflow consisting of a set of tasks.However,many services may satisfy the functionality of each task;thus,searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem.This work will introduce a hybrid Artificial Bee Colony(ABC)with a Cuckoo Search(CS)algorithm to untangle service composition problem.The ABC is a well-known metaheuristic algorithm that can be applied when dealing with different NP-hard problems with an outstanding record of performance.However,the ABC suffers from a slow convergence problem.Therefore,the CS is used to overcome the ABC’s limitations by allowing the abandoned bees to enhance their search and override the local optimum.The proposed hybrid algorithm has been tested on 19 datasets and then compared with two standard algorithms(ABC and CS)and three state-of-the-art swarm-based composition algorithms.In addition,extensive parameter study experiments were conducted to set up the proposed algorithm’s parameters.The results indicate that the proposed algorithm outperforms the standard algorithms in the three comparison criteria(bestfitness value,averagefitness value,and average execution time)overall datasets in 30 different runs.Furthermore,the proposed algorithm also exhibits better performance than the state–of–the–art algorithms in the three comparison criteria over 30 different runs.