Performance Comparison of Hyper-V and KVM for Cryptographic Tasks in Cloud Computing

As the extensive use of cloud computing raises questions about the security of any personal data stored there,cryptography is being used more frequently as a security tool to protect data confidentiality and privacy in the cloud environment.A hypervisor is a virtualization software used in cloud hosting to divide and allocate resources on various pieces of hardware.The choice of hypervisor can significantly impact the performance of cryptographic operations in the cloud environment.An important issue that must be carefully examined is that no hypervisor is completely superior in terms of performance;Each hypervisor should be examined to meet specific needs.The main objective of this study is to provide accurate results to compare the performance of Hyper-V and Kernel-based Virtual Machine(KVM)while implementing different cryptographic algorithms to guide cloud service providers and end users in choosing the most suitable hypervisor for their cryptographic needs.This study evaluated the efficiency of two hypervisors,Hyper-V and KVM,in implementing six cryptographic algorithms:Rivest,Shamir,Adleman(RSA),Advanced Encryption Standard(AES),Triple Data Encryption Standard(TripleDES),Carlisle Adams and Stafford Tavares(CAST-128),BLOWFISH,and TwoFish.The study’s findings show that KVM outperforms Hyper-V,with 12.2%less Central Processing Unit(CPU)use and 12.95%less time overall for encryption and decryption operations with various file sizes.The study’s findings emphasize how crucial it is to pick a hypervisor that is appropriate for cryptographic needs in a cloud environment,which could assist both cloud service providers and end users.Future research may focus more on how various hypervisors perform while handling cryptographic workloads.

Single-cell and spatial heterogeneity landscapes of mature epicardial cells

Tbx18,Wt1,and Tcf21 have been identified as epicardial markers during the early embryonic stage.However,the gene markers of mature epicardial cells remain unclear.Single-cell transcriptomic analysis was performed with the Seurat,Monocle,and CellphoneDB packages in R software with standard procedures.Spatial transcriptomics was performed on chilled Visium Tissue Optimization Slides(10x Genomics)and Visium Spatial Gene Expression Slides(10x Genomics).Spatial transcriptomics analysis was performed with Space Ranger software and R software.Immunofluorescence,whole-mount RNA in situ hybridization and X-gal staining were performed to validate the analysis results.Spatial transcriptomics analysis revealed distinct transcriptional profiles and functions between epicardial tissue and non-epicardial tissue.Several gene markers specific to postnatal epicardial tissue were identified,including Msln,C3,Efemp1,and Upk3b.Single-cell transcriptomic analysis revealed that cardiac cells from wildtype mouse hearts(from embryonic day 9.5 to postnatal day 9)could be categorized into six major cell types,which included epicardial cells.Throughout epicardial development,Wt1,Tbx18,and Upk3b were consistently expressed,whereas genes including Msln,C3,and Efemp1 exhibited increased expression during the mature stages of development.Pseudotime analysis further revealed two epicardial cell fates during maturation.Moreover,Upk3b,Msln,Efemp1,and C3 positive epicardial cells were enriched in extracellular matrix signaling.Our results suggested Upk3b,Efemp1,Msln,C3,and other genes were mature epicardium markers.Extracellular matrix signaling was found to play a critical role in the mature epicardium,thus suggesting potential therapeutic targets for heart regeneration in future clinical practice.

Decision Analysis on IoV Routing Transmission and Energy Efficiency Optimization Algorithm with AmBC

The improvement of the quality and efficiency of vehicle wireless network data transmission is always a key concern in the Internet of Vehicles(IoV).Routing transmission solved the limitation of transmission distance to a certain extent.Traditional routing algorithm cannot adapt to complex traffic environment,resulting in low transmission efficiency.In order to improve the transmission success rate and quality of vehicle network routing transmission,make the routing algorithm more suitable for complex traffic environment,and reduce transmission power consumption to improve energy efficiency,a comprehensive optimized routing transmission algorithm is proposed.Based on the routing transmission algorithm,an optimization algorithmbased on road condition,vehicle status and network performance is proposed to improve the success rate of routing transmission in the IoV.Relative distance difference and density are used as decision-making indicators to measure Road Side Unit(RSU)assisted transmission.And the Ambient backscatter communication(AmBC)technology and energy collection are used to reduce the energy consumption of routing relay transmission.An energy collection optimization algorithm is proposed to optimize the energy efficiency of AmBC and improve the energy efficiency of transmission.Simulation results show that the proposed routing optimization algorithm can effectively improve the success rate of packet transmission in vehicular ad hoc networks(VANETs),and theAmBC optimization algorithmcan effectively reduce energy consumption in the transmission process.The proposed optimization algorithm achieves comprehensive optimization of routing transmission performance and energy efficiency.

Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between learners.Integrating the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students learn.Nevertheless,learning data is very sensitive and must be protected when transmitted over the network or stored in data centers.Moreover,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of attacks.However,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure communication.In addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being used.In this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university network.It allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user re-authentication.The proposed architecture was tested using a simulation tool,and measured to evaluate its performance.The simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication mechanisms.In addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the university network.

Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection

The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized.While it is a multi-objective problem,current methods tend to treat feature selection as a single-objective optimization task.This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase(LMuMOGWO)for tackling feature selection problems.The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer(MOGWO):a Lévy flight and a mutation operator.The Lévy flight,a type of random walk with jump size determined by the Lévy distribution,enhances the global search capability of MOGWO,with the objective of maximizing classification accuracy while minimizing the number of selected features.The mutation operator is integrated to add more informative features that can assist in enhancing classification accuracy.As feature selection is a binary problem,the continuous search space is converted into a binary space using the sigmoid function.To evaluate the classification performance of the selected feature subset,the proposed approach employs a wrapper-based Artificial Neural Network(ANN).The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO,BMOGWO-S(based sigmoid),BMOGWO-V(based tanh)as well as Non-dominated Sorting Genetic Algorithm II(NSGA-II)and Multi-objective Particle Swarm Optimization(BMOPSO).The results demonstrate that the proposed LMuMOGWO approach is capable of successfully evolving and improving a set of randomly generated solutions for a given optimization problem.Moreover,the proposed approach outperforms existing approaches in most cases in terms of classification error rate,feature reduction,and computational cost.

Depositional Environment of Sediments in Tonle Sap Sedimentary Basin, Western Part of Cambodia: Insights from Field and Geochemical Studies

Tonle Sap sedimentary basin was considered a favorable geological condition for hydrocarbon accumulation in the onshore Cambodia. Two exposure outcrops in Battambang province, called Somlout and Takream, were selected to represent sediments in this basin. The sedimentology and geochemistry studies provide insights into the depositional environment of sediments using field investigation, lithological, sedimentological, paleontological, and geochemical analysis. The redox condition, water column, and depositional setting were analyzed by plotting the ratio of V vs. Cr, Uauthigenic vs. V/Cr, Sr vs. Ba, Ca vs. (Fe + Ca), and Fe2O3/TiO2 vs. Al2O3/(Al2O3 + Fe2O3) diagram. Moreover, these diagrams can be used to predict depositional conditions as well. Based on the results, Somlout and Takream comprise calcareous shale and limestone facies. The geochemical analysis showed that Somlout calcareous shale samples were deposited in the dysoxic freshwater of the lake setting during the regression, while Somlout limestones and Takream were deposited in high salinity seawater, oxic condition of shallow-marine water. In addition, Somlout limestones consist of fragmental fusulinid foraminifera, bivalve shelve, and bryozoan, which suggest a barrier environment. Meanwhile, Teakream consists of fine-grained calcareous shale, and lime-mudstone, which are presented to form in the quiet marine setting of the lagoon environment. Therefore, the Tonle Sap basin sediments were deposited in the Somlout area’s barrier and lake environment, and the lagoon environment for Takream.

Numerical Study on Hydraulic Characteristics and Discharge Capacity of Modified Piano Key Weir with Various Inlet/Outlet Width Ratio

A modified piano key weir with a rounded nose and a parapet wall (MPKW) can improve the discharge capacity significantly compared to a standard piano key weir. However, the optimum of the inlet/outlet width ratio (Wi/Wo) on the discharge efficiency of MPKW is still not investigated numerically. The present work utilized the numerical modeling to investigate and analyze the effects of the inlet/outlet key width ratios on the hydraulic characteristics and discharge capacity of the MPKW. To validate the numerical model with the experimental data, the results indicate that the average relative error is 2.96%, which confirms that the numerical model is fairly well to predictthe specifications of flow over on the MPKW. Numerical simulation results indicated that the discharge capacity of the MPKW can be improved up to 8.5% by optimizing the Wi/Wo ratio ranging from 1.53 to 1.67 even if the other parameters of the MPKW keep unchanged. A big Wi/Wo ratio generally leads to an increase in discharge capacity at low heads and a little effect on the discharge efficiency at high heads. The discharge efficiency of the inlet and outlet crests increases up to 9.6% for high heads, while discharge efficiency of the lateral crest decreases up to 23.5% compared with the reference model. The findings of the study revealed that the intrinsic influencing mechanism of the Wi/Wo ratio on the discharge performance of MPKWs.

Characterization of Sandstone Reservoir at Bokor Formation, Kampot Province, Kampong Som Basin, Onshore Cambodia

Kampong Som Basin is a Paleozoic-Mesozoic sedimentary basin located in southern Cambodia. While the sandstone of the Bokor Formation is expected to be the reservoir for hydrocarbon accumulation. Hence, this study aims to define the properties, quality, and factors that control reservoir rock quality. Sandstones of the Bokor Formation are sampled and analyzed using a helium porosimeter, nitrogen permeameter, polarized light microscope, and scanning electron microscope (SEM) to check the porosity, permeability, minerals, pore geometry, and clay minerals that influence the reservoir quality. According to the result of petrography analysis described by thin section, the sandstone samples from Bokor formation are classified as quartz arenite that composes mainly of quartz, rock fragment, mica-flake, and sericite with connected and unconnected pores of 50 μm to 500 μm with interparticle pore type. Sandstones in this formation have porosity values ranging from 6.55% to 13.19%, and permeability values ranging from 10 mD to 60 mD. The statistics of porosity and permeability of sandstone reservoirs indicate low porosity and permeability that are suggested to be fair reservoir rock for hydrocarbon accumulation. SEM results indicate that there are three types of authigenic clay minerals involving such as kaolinite, illite, and chlorite. In addition, the pore geometry, quartz overgrowth, dissolution of quartz and felspar grain filling in pore space, compaction, replacement diagenesis processes, and cementation presence of clay minerals are the main controlling factors of the sandstone reservoir from the Bokor Formation. Furthermore, this area exhibits sedimentary structures such as planar cross-bedding, cross-bedding, parallel lamination, normal grading, massive, wavy, and reverse graded bedding, which indicates these lithofacies may be deposited in shallow marine environments.

The Milestone of Cambodian First Oil Production in the Khmer Basin, Gulf of Thailand

As an ASEAN member country, Cambodia is the eighth country to produce oil from its maritime water in late 2020. The first oil was produced from Cambodian Block A (CBA) which covers most of the Khmer basin, located in the east and in the north of producing oil and gas Pattani and Malay basin respectively, in the Gulf of Thailand (GoT). Before being an oil-producing country, Cambodia has been involved in a long history of exploration activities since the 1970s with international companies including Elf-Erap, Marine Associate, Enterprise, Campex, Premier, etc. The first phase of petroleum development was initiated by Chevron Texaco in 2010 when this US company submitted the Petroleum Permit Application (PPA) to the government of Cambodia. The company failed to reach an agreement with the government on revenue sharing, then KrisEnergy bought out the working interest in 2014 and became the only operator of CBA. A justified Mini Phase 1A was operated by KrisEnergy to flow the oil from six production wells in the Apsara area where there is still a high risk of geological information and time constrain. Apsara area which covers the most prospective petroleum exploration geological trend in Cambodian water was built a minimal facility platform and used the production barge, Ingenium II, to separate the reservoir fluids. As long as the accumulative oil production reached about 300,000 bbl for about five months, the operator of CBA went into the liquidation. In the primary plan, this initial phase was expected to produce 7500 bopd at the peak, however it actually produced the oil less than double in the end. This situation indicated the underperformance of Mini Phase 1A, which resulted in a huge declination of each well capacity. This underperformance of Mini Phase 1A seemed express clearly the results of the uncertainties of petroleum formation, the complexities of the particular reservoir properties in the CBA and the inappropriate method of Mini Phase 1A. This paper synthesizes the existing literature, and the technical reports to reassess the geology, basin evolution, and reservoir characteristics of the CBA, especially the Apsara oil field. This review could be a help to disseminate of the update the CBA for the petroleum business companies and for academic in the purpose of researches.

Outage Analysis of Optimal UAV Cooperation with IRS via Energy Harvesting Enhancement Assisted Computational Offloading

The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of employing intelligent reflective surfaces(IRS)andUAVs as relay nodes to efficiently offload user computing tasks to theMEC server system model.Specifically,the user node accesses the primary user spectrum,while adhering to the constraint of satisfying the primary user peak interference power.Furthermore,the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes,namely time switching(TS)and power splitting(PS).The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio.Subsequently,the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed.The study investigates the impact of various system parameters,including the number of UAVs,peak interference power,TS,and PS factors,on the system’s outage performance through simulation.The proposed system is also compared to two conventional benchmark schemes:the optimal UAV link transmission and the IRS link transmission.The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes.

Anti-Jamming Null Space Projection Beamforming Based on Symbiotic Radio

With the development of information technology,more and more devices are connected to the Internet through wireless communication to complete data interconnection.Due to the broadcast characteristics ofwireless channels,wireless networks have suffered more and more malicious attacks.Physical layer security has received extensive attention from industry and academia.MIMO is considered to be one of the most important technologies related to physical layer security.Through beamforming technology,messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR by legitimate users.Combining the symbiotic radio(SR)technology,this paper considers a symbiotic radio antijamming MIMO system equipped with a multi-antenna system at the main base station.In order to avoid the interference signal and improve the SINR of the signal received by the user.The base station is equipped with a uniform rectangular antenna array,and using Null Space Projection(NSP)Beamforming,Intelligent Reflecting Surface(IRS)can assist in changing the beam’s angle.The simulation results show that NSP Beamforming could make a better use of the null space of interference,which can effectively improve the received SINR of users under directional interference,and improve the utilization efficiency of signal energy.

Dysbiosis promotes recurrence of adenomatous polyps in the distal colorectum

BACKGROUND Colorectal polyps,which are characterized by a high recurrence rate,represent preneoplastic conditions of the intestine.Due to unclear mechanisms of pathogenesis,first-line therapies for non-hereditary recurrent colorectal polyps are limited to endoscopic resection.Although recent studies suggest a mechanistic link between intestinal dysbiosis and polyps,the exact compositions and roles of bacteria in the mucosa around the lesions,rather than feces,remain unsettled.AIM To clarify the composition and diversity of bacteria in the mucosa surrounding or 10 cm distal to recurrent intestinal polyps.METHODS Mucosal samples were collected from four patients consistently with adenomatous polyps(Ade),seven consistently with non-Ade(Pol),ten with current Pol but previous Ade,and six healthy individuals,and bacterial patterns were evaluated by 16S rDNA sequencing.Linear discriminant analysis and Student’s t-tests were used to identify the genus-level bacteria differences between groups with different colorectal polyp phenotypes.Pearson’s correlation coefficients were used to evaluate the correlation between intestinal bacteria at the genus level and clinical indicators.RESULTS The results confirmed a decreased level of probiotics and an enrichment of pathogenic bacteria in patients with all types of polyps compared to healthy individuals.These changes were not restricted to the mucosa within 0.5 cm adjacent to the polyps,but also existed in histologically normal tissue 10 cm distal from the lesions.Significant differences in bacterial diversity were observed in the mucosa from individuals with normal conditions,Pol,and Ade.Increased abundance of Gram-negative bacteria,including Klebsiella,Plesiomonas,and Cronobacter,was observed in Pol group and Ade group,suggesting that resistance to antibiotics may be one risk factor for bacterium-related harmful environment.Meanwhile,age and gender were linked to bacteria changes,indicating the potential involvement of sex hormones.CONCLUSION These preliminary results support intestinal dysbiosis as an important risk factor for recurrent polyps,especially adenoma.Targeting specific pathogenic bacteria may attenuate the recurrence of polyps.

Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization problems.The past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer simulations.Moreover,it is hard to traverse the huge search space within reasonable resource as problem dimension increases.Traditional evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory results.To reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent years.Yet there lacks a thorough review of the state of the art in this specific and important area.This paper provides a comprehensive survey of these evolutionary algorithms for HEPs.We start with a brief introduction to the research status and the basic concepts of HEPs.Then,we present surrogate-assisted evolutionary algorithms for HEPs from four main aspects.We also give comparative results of some representative algorithms and application examples.Finally,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over Internet.It plays a key role in modern industry since it connects physical and cyber worlds.In order to meet ever-changing industrial requirements,its structures and functions are constantly improved.Meanwhile,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and practitioners.This paper presents a survey of state-of-the-art results of cyber attacks on cyber physical systems.First,as typical system models are employed to study these systems,time-driven and event-driven systems are reviewed.Then,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are discussed.In particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and defenders.Namely,both attack and defense strategies are discussed based on different system models.Some challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

Nanocrystalline and nanocomposite permanent magnets by melt spinning technique

The melt-spinning technique offers an opportunity for tailoring magnetic properties by controlling the structures and microstructures in both single-phase and composite magnets.This review first broadly discusses the principle of cooling control,amorphization,crystallization,annealing,and consolidation of the melt-spun ribbons.The phase,microstructure,and magnetic properties of popular single-phase nanocrystalline magnets are reviewed,followed by the nanocomposite magnets consisting of magnetically hard and soft phases.The precipitation-hardened magnetic materials prepared by melt spinning are also discussed.Finally,the role of intergrain exchange coupling,thermal fluctuation,and reversible/irreversible magnetization processes are discussed and correlated to the magnetic phenomena in both single-phase and nanocomposite magnets.

Accuracy and responses of genomic selection on key traits in apple breeding

The application of genomic selection in fruit tree crops is expected to enhance breeding eficiency by increasing prediction accuracy,increasing selection intensity and decreasing generation interval.The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits.The training population comprised 977 individuals derived from 20 pedigreed fllsib families.Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an llumina 20K SNP array.From these data,a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application fllsib families.The application families had genotypes at 364 SNPs from a dedicated 512 SNP array,and these genotypic data were extended to the high-density level by imputation.These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values.Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19.The accuracies were strongly affected by the phenotypic distribution and heritability of traits.In the largest family,significant selection response was observed for traits with high heritability and symmetric phenotypic distribution.Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability.Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population.The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.

Magnetohydrodynamic flow and heat transfer impact on ZnO-SAE50 nanolubricant flow over an inclined rotating disk

The present article has been fine-tuned with the investigation of mixed convection Darcy-Forchheimer flow of ZnO-SAE50 oil nanolubricant over an inclined rotating disk under the influence of uniform applied magnetic field applied to various industries.The current study has been enriched with additional consideration of slip flow,thermal radiation,viscous dissipation,Joulian dissipation and internal heating.In view of augmentation of thermal conductivity of nanolubricant,a new micro-nano-convection model namely Patel model has been invoked.The specialty of this model involves the effects of specific surface area and nano-convection due to Brownian motion of nanoparticles,kinetic theory based micro-convection,liquid layering and particle concentration.Suitably transformed governing equations have been solved numerically by using Runge-Kutta-Fehlberg scheme.An analysis of the present study has shown that applied magnetic field,porosity of the medium,velocity slip and inertia coefficient account for the slowing down of radial as well as tangential flow of ZnO-SAE50 oil nanolubricant,thereby leading to an improvement in velocity and thermal boundary layers.

Antibacterial activity of Bixa orellana L.(achiote) against Streptococcus mutans and Streptococcus sanguinis

Objective: To evaluate the cytotoxic and antibacterial effect of Bixa orellana L.(B. orellana)(achiote) methanol extract against Streptococcus mutans(ATCC 25175)(S. mutans) and Streptococcus sanguinis(ATCC 10556)(S. sanguinis).Methods: Two methanol extracts of B. orellana were prepared in vitro, from the seeds and leaves. The antibacterial activity of extracts against S. mutans and S. sanguinis was evaluated using the cup-plate agar diffusion method. The minimum inhibitory concentration(MIC) was determined using the microdilution method and the cytotoxic activity was determinated by using the cell line MDCK.Results: A stronger antibacterial effect was observed with the leaves methanolic extract with an inhibition zone of(19.97 ± 1.31) mm against S. mutans and(19.97 ± 1.26) mm against S. sanguinis. The methanolic extract of the seeds had an activity of(15.11 ± 1.03)mm and(16.15 ± 2.15) mm against S. mutans and S. sanguinis, respectively. The MIC of the leaf and the seed extracts against S. sanguinis was 62.5 and 125 mg/m L, respectively,and the MIC of the leaf extract against S. mutans was 62.5 mg/m L, and for the seed extract it was 31.25 mg/m L. The 50% cytotoxic concentration was 366.45 and 325.05 mg/m L for the leaves and seeds extracts, respectively.Conclusions: The experimental findings demonstrated the antibacterial effect of the methanolic extract of B. orellana(achiote) on S. mutans and S. sanguinis. The extract of this plant is cytotoxic at high concentrations.

An integrated approach for increasing breeding efficiency in apple and peach in Europe

Despite the availability of whole genome sequences of apple and peach,there has been a considerable gap between genomics and breeding.To bridge the gap,the European Union funded the FruitBreedomics project(March 2011 to August 2015)involving 28 research institutes and private companies.Three complementary approaches were pursued:(i)tool and software development,(ii)deciphering genetic control of main horticultural traits taking into account allelic diversity and(iii)developing plant materials,tools and methodologies for breeders.Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding,development of new,dense SNP arrays in apple and peach,new phenotypic methods for some complex traits,software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis(PBA).This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies(GWAS)on several European genebank collections.FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities.Through FruitBreedomics,significant progresses were made in the field of apple and peach breeding,genetics,genomics and bioinformatics of which advantage will be made by breeders,germplasm curators and scientists.A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public.This review covers the scientific discoveries made in this major endeavour,and perspective in the apple and peach breeding and genomics in Europe and beyond.

A real-world data collection framework for a fused dataset creation for joint human and remotely operated vehicle monitoring and anomalous command detection

Unmanned Remotely Operated Vehicles(ROVs)are widely used in safety-critical missions,spanning across monitoring,surveillance,and search and rescue missions.In most cases,the human operator controls the ROV under stressful conditions and in harsh environments.The physical and mental states of the operator are vital as they may cause involuntary movements,issuing unintentional commands due to fatigue or stress.Consequently,a joint monitoring mechanism that will assess the operator's commands can be beneficial in preventing potentially catastrophic events,such as accidents.To this end,in this study,we propose a data collection framework for creating a fused dataset,consisting of data obtained from both the human operator and the ROV,and we integrate stress induction to stimulate stress and fatigue that may affect operators during missions.We optimise the dataset,which includes the operator's physiological signals and inertial measurement unit(IMU)sensor data from the ROV,using data fusion approaches and feature extraction.We evaluate the dataset through the statistical analysis,illustrating a statistical difference between data characterising normal and involuntary commands.Finally,we evaluate the optimised and original datasets over a variety of classifiers,demonstrating an accuracy of 94%and 95%,respectively.