This paper presents a novel blockchain-embedded cybersecurity framework for industrial solar power systems,integrating immutable machine learning(ML)with distributed ledger technology.Our contribution focused on three...This paper presents a novel blockchain-embedded cybersecurity framework for industrial solar power systems,integrating immutable machine learning(ML)with distributed ledger technology.Our contribution focused on three factors,Quantum-resistant feature engineering using theUNSW-NB15 dataset adapted for solar infrastructure anomalies.An enhanced Light Gradient Boosting Machine(LightGBM)classifier with blockchain-validated decision thresholds,and A cryptographic proof-of-threat(PoT)consensus mechanism for cyber attack verification.The proposed Immutable LightGBM model with majority voting and cryptographic feature encoding achieves 96.9% detection accuracy with 0.97 weighted average of precision,recall and F1-score,outperforming conventional intrusion detection systems(IDSs)by 12.7% in false positive reduction.The blockchain layer demonstrates a 2.4-s average block confirmation time with 256-bit SHA-3 hashing,enabling real-time threat logging in photovoltaic networks.Experimental results improve in attack traceability compared to centralized security systems,establishing new benchmarks for trustworthy anomaly detection in smart grid infrastructures.This study also compared traditional and hybrid ML based blockchian driven IDSs and attained better classification results.The proposed framework not only delivers a resilient,adaptable threat mitigation system(TMS)for Industry 4.0 solar powered infrastructure but also attains high explainability,scalability with tamper-proof logs,and remarkably exceptional ability of endurance to cyber attacks.展开更多
License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition M...License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition Method(DR2M)to address such a problem.This method operates on displaced features compared to the training input observed throughout definite time frames.The technique focuses on detecting features that remain relatively stable under haze,using a frame-based analysis to isolate edges minimally affected by visual noise.The edge detection failures are identified using a bilateral neural network through displaced feature training.The training converges bilaterally towards the minimum edges from the maximum region.Thus,the training input and detected edges are used to identify the displacement between observed image frames to extract and differentiate the license plate region from the other vehicle regions.The proposed method maps the similarity feature between the detected and identified vehicle regions.This aids in leveraging the plate recognition precision with a high F1 score.Thus,this technique achieves a 10.27%improvement in identification precision,a 10.57%increase in F1 score,and a 9.73%reduction in false positive rate compared to baseline methods under maximum displacement conditions caused by haze.The technique attains an identification precision of 95.68%,an F1 score of 94.68%,and a false positive rate of 4.32%,indicating robust performance under haze-affected settings.展开更多
Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and ...Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.展开更多
In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high d...In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate.We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations(SBSs)are deployed in the areas with high User Equipment(UE)density.Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs.For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication.By using tools from stochastic geometry,we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association.For UE clustering we considered Thomas cluster process and derive expressions for the association probability,coverage probability,area spectral efficiency,and energy efficiency.We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions.Furthermore,we analyze the impact of mmWave operating frequency,antenna gain,small cell biasing,and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets.Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.展开更多
Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless networks.It provides improved performance in terms of system throughput,spectral efficienc...Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless networks.It provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless channels.To combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)networks.In this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is presented.An in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold investigations.First,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA networks.Followed by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage probability.Moreover,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)method.The optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and maximum-ratio-transmission.Furthermore,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless networks.This work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA networks.This comparative analysis provides a solid foundation for the development of future IRS-enabled,energy-efficient wireless communication systems.展开更多
Flexible microelectronic devices have seen an increasing trend toward development of miniaturized,portable,and integrated devices as wearable electronics which have the requirement for being light weight,small in dime...Flexible microelectronic devices have seen an increasing trend toward development of miniaturized,portable,and integrated devices as wearable electronics which have the requirement for being light weight,small in dimension,and suppleness.Traditional three-dimensional(3D)and two-dimensional(2D)electronics gadgets fail to effectively comply with these necessities owing to their stiffness and large weights.Investigations have come up with a new family of one-dimensional(1D)flexible and fiber-based electronic devices(FBEDs)comprising power storage,energy-scavenging,implantable sensing,and flexible displays gadgets.However,development and manufacturing are still a challenge owing to their small radius,flexibility,low weight,weave ability and integration in textile electronics.This paper will provide a detailed review on the importance of substrates in electronic devices,intrinsic property requirements,fabrication classification and applications in energy harvesting,energy storage and other flexible electronic devices.Fiber-and textile-based electronic devices for bulk/scalable fabrications,encapsulation,and testing are reviewed and presented future research ideas to enhance the commercialization of these fiber-based electronics devices.展开更多
Objective:To evaluate the antiniicrobial polenlial of different extracts of the endophytic fungus Phoma sp.and the tentative identification of their active constituents.Methods:The extract and compounds were screened ...Objective:To evaluate the antiniicrobial polenlial of different extracts of the endophytic fungus Phoma sp.and the tentative identification of their active constituents.Methods:The extract and compounds were screened for antimicrobial activity using the Agar Well Diffusion Method.Four compounds were purified using column chromatography and tlieir structures were assigned using～1H and～(13)C NMR spectra,DEPT,2D COSY,HMQC and HMBC experiments.Results:The ethyl acetate fraction of Phoma sp.showed good antifungal,antibacterial,and algicidal properties.One new dihydrofuran derivative,named phomafuranol(1),together with tliree known compounds,phomalacton(2),(3R)-5-hydroxymellein(3)and emodin(4)were isolated from the ethyl acetate fraction of Phoma sp.Preliminary studies indicated that phomalacton(2)displayed strong antibacterial,good antifungal and antialgal activities.Similarly(3R)-5-hydroxymellein(3)and emodin(4)showed good antifungal,antibacterial and algicidal properties.Conclusions:Antimicrobial activities of the ethyl acetate fraction of the endophytic fungus Phoma sp.and isolated compounds clearly demonstrate that Phoma sp.and its active compounds represent a great potential for the food,cosmetic and pharmaceutical industries.展开更多
A feeding trial was conducted for 75 d to evaluate the nutritive value of a mixture of animal by-products （MAB） as a possible protein source in diets for juvenile mangrove red snapper, Lutjanus argentimaculatus （me...A feeding trial was conducted for 75 d to evaluate the nutritive value of a mixture of animal by-products （MAB） as a possible protein source in diets for juvenile mangrove red snapper, Lutjanus argentimaculatus （mean initial body weight, 30 g）. Fish were fed one of five isonitrogenous diets （40% crude protein） replacing 0, 25% （MAB25）, 50% （MAB50）, 75% （MAB75） and 100% （MAB100） of fish meal protein with similar percentages of MAB. The MAB consisted of 25% cow liver meal, 20% leather meal, 20% meat and bone meal, 15% blood meal, 10% APC （poultry feather meal）, 8% poultry manure dried, 1.5% choline and 0.5% chromic oxide. After 75 d of feeding, fish fed with diets MAB50, MAB75 and MABI00 exhibited significantly lower growth performance than that of fish fed with control and MAB25 diets. The optimum level of MAB was estimated to be 23%. Replacement of fish meal by MAB23% showed the following performance： maximum weight gain, 510%; SGR, 2.39% and FCE, 2.83%. The MAB substitution up to 75% of fish meal protein in diets did not show differences in apparent protein digestibility （83.6% for MAB25, 79.2% for MAB50, 78.7% for MAB75） compared with control （83.4%）, whereas in MABI00 group digestibility （65.3%） was significantly lower than in other groups. The apparent phosphorus absorption of test diet groups was significantly higher （37.1% for MAB25, 28.5% for MABS0, 55.6% for MAB75 and 54.5% for MABI00） than that of control （1 1.2%）. The levels of protein and ash in the whole body, carcass and viscera increased as MAB substitution in diets increased, whereas lipids and moisture remained consistent among all treatment groups. These results showed that approximately 23% of fish meal protein could be replaced by a mixture of animal by-products for juvenile snapper growing from 30 g to 167 g in 75 d without compromising growth performance and feed efficiency.展开更多
Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents,economically damaging traffic jams,hijacking,motivating to wrong routes,and financial losses for businesses and ...Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents,economically damaging traffic jams,hijacking,motivating to wrong routes,and financial losses for businesses and governments.Smart and autonomous vehicles are connected wirelessly,which are more attracted for attackers due to the open nature of wireless communication.One of the problems is the rogue attack,in which the attacker pretends to be a legitimate user or access point by utilizing fake identity.To figure out the problem of a rogue attack,we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state information of the communication link.We consider the communication link between vehicle-to-vehicle,and vehicle-to-infrastructure.We evaluate the performance of our proposed technique by measuring the rogue attack probability,false alarm rate(FAR),mis-detection rate(MDR),and utility function of a receiver based on the test threshold values of reinforcement learning algorithm.The results show that the FAR and MDR are decreased significantly by selecting an appropriate threshold value in order to improve the receiver’s utility.展开更多
Drought is one of the most prevalent abiotic stresses that adversely affect rice productivity(Petrozza et al, 2014). Rice is very sensitive to drought stress and drought can cause 50% reduction in rice production glob...Drought is one of the most prevalent abiotic stresses that adversely affect rice productivity(Petrozza et al, 2014). Rice is very sensitive to drought stress and drought can cause 50% reduction in rice production globally(Yang et al, 2008). To meet the food needs for global population, 63% more agricultural production will be required by the year 2050 than.展开更多
State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master an...State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master and slave systems. Second, it presents an elegant design procedure which requires a set of equations to be solved in order to compute the control gains of the bilateral loop. These design conditions are obtained by turning the master-slave error into an autonomous system and imposing the desired dynamic behavior of the teleoperation system. Resultantly, the convergence of master and slave states is achieved in a well-defined manner. The present study aims at achieving a similar convergence behavior offered by state convergence controller while reducing the number of variables sent across the communication channel. The proposal suggests transmitting composite master and slave variables instead of full master and slave states while keeping the operator's force channel intact. We show that,with these composite and force variables;it is indeed possible to achieve the convergence of states in a desired way by strictly following the method of state convergence. The proposal leads to a reduced complexity state convergence algorithm which is termed as composite state convergence controller. In order to validate the proposed scheme in the absence and presence of communication time delays, MATLAB simulations and semi-real time experiments are performed on a single degree-of-freedom teleoperation system.展开更多
Vehicular ad-hoc networks(VANETs)play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities.Direction-based greedy protocols pick the ne...Vehicular ad-hoc networks(VANETs)play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities.Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages(EMs)depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach.Nevertheless,such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously.Due to the high number of vehicles,it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions.A cluster-based EM transmitting technique is proposed in this paper.For urban VANETs,this paper pioneers the clustering of bi-directional road traffic for robust and efficient routing of EMs.In this regard,this paper introduces a routing protocol,namely,the bi-directional urban routing protocol(BURP).In addition to the paths and relative locations of vehicles,BURP takes account of the distance parameter by using the Hamming distance function to determine the direction ofmotion of vehicles and communicates EMs through the cluster head(CH).Amodified k-medoids algorithm is presented for the clustering of bi-directional road traffic.A median method is presented for selecting CH to ensure the longrunning of a cluster.Simulation results show that BURP provides enhanced throughput,a maximized packet delivery ratio,low energy consumption,and network delay relative to eminent routing protocols.展开更多
Cyber-physical wireless systems have surfaced as an important data communication and networking research area.It is an emerging discipline that allows effective monitoring and efficient real-time communication between...Cyber-physical wireless systems have surfaced as an important data communication and networking research area.It is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking technologies.Due to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and impersonation.Existing methods use physical layer authentication(PLA),themost promising solution to detect cyber-attacks.Still,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency target.These methods perform well but only in stationary scenarios.We have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile scenarios.The features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify data.The authentication of the received signal is considered a binary classification problem.The transmitted data is labeled as legitimate information,and spoofing data is illegitimate information.Therefore,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing attacks.It detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are mobile.The proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.展开更多
A new metabolite,named seimatoric acid（1）,representing a new oxobutanoic acid derivative has been isolated from Seimatosporium sp., in addition to four known compounds viz.,2-hydroxymethyl-4β,5α,6β-trihydroxycycl...A new metabolite,named seimatoric acid（1）,representing a new oxobutanoic acid derivative has been isolated from Seimatosporium sp., in addition to four known compounds viz.,2-hydroxymethyl-4β,5α,6β-trihydroxycyclohex-2-enone（2）,（-）-phyllostine（3）,（＋）-epiepoxydon（4） and（＋）-epoxydon monoacetate（5）.Similarly one new benzoic acid derivative,named colletonoic acid（6） was isolated from the ethyl acetate fraction of Colletotrichum sp.The structures of the new compounds were elucidated by detailed ^1 H NMR,^13C NMR,COSY,HMQC.HMBC spectroscopic analysis,and HR-E1-MS.Seimatoric acid（1）was also isolated from another taxonomical unidentified fungal strain 4295 in ourgroup.The structures of the known compounds were elucidated by their spectral data comparison to literature data.Preliminary studies showed that colletonoic acid（6） showed good antibacterial,antifungal,and antialgal activities.展开更多
Objective The current study was aimed to investigate the correlations between immobility time in the forced swimming test （FST, a behavioral indicator of stress level） and hippocampal monoamine levels （markers of d...Objective The current study was aimed to investigate the correlations between immobility time in the forced swimming test （FST, a behavioral indicator of stress level） and hippocampal monoamine levels （markers of depression）, plasma adrenalin level （a peripheral marker of stress） as well as fluoro-jade C staining （a marker of neurodegeneration）. Methods Male Sprague-Dawley rats were subjected to acute, sub-chronic （7 d） or chronic （14 d） FSTs and immobility time was recorded. Levels of noradrenalin, serotonin and dopamine in the hippocampus, and adrenalin level in the plasma were quantified by high-performance liquid chromatography with electrochemical detection. Brain sections from rats after chronic forced swimming or rotenone treatment （3 mg/kg subcutaneously for 4 d） were stained with fluoro-jade C. Results The rats subjected to swimming stress （acute, sub-chronic and chronic） showed long immobility times [（214 ± 5）, （220 ± 4） and （231 ± 7） s, respectively], indicating that the animals were under stress. However, the rats did not exhibit significant declines in hippocampal monoamine levels, and the plasma adrenalin level was not significantly increased compared to that in unstressed rats. The rats that underwent chronic swimming stress did not manifest fluoro-jade C staining in brain sections, while degenerating neurons were evident after rotenone treatment. Conclusion The immobility time in the FST does not correlate with markers of depression （monoamine levels） and internal stress （adrenalin levels and neurodegeneration）, hence this parameter may not be a true indicator of stress level.展开更多
Porcine reproductive and respiratory syndrome virus(PRRSV)GP4 protein was prokaryotically expressed,and used as an antigen to immunize six-week-old BALB/c female mice.With conventional cell fusion method,an anti-PRRSV...Porcine reproductive and respiratory syndrome virus(PRRSV)GP4 protein was prokaryotically expressed,and used as an antigen to immunize six-week-old BALB/c female mice.With conventional cell fusion method,an anti-PRRSV GP4 protein monoclonal antibody(Mab)5F12 was successfully prepared.It was identified as IgG2b subclass and had better stability and specificity,which not only responded with recombinant PRRSV GP4 protein,but also with PRRSV.Phage display technique had varieties of applications,in particular,the identification of key antigen epitopes for the development of therapeutic and diagnostic reagents and vaccines.In this study,Mab-5F12 was used as the target for biopanning a 12-mer phage random peptide library.After four rounds of biopanning,two phage-displayed peptides,named P-A and P-G(AKFEVCSPVVLG and GVNQENMLHFSF)were identified that recognized Mab-5F12 specifically.Sequence analysis showed that one or more of the peptides exhibited partial sequence similarity to the native GP4 protein sequence,which corresponded to 69-80 and 84-95 aa segments of the HP-PRRSV GP4 protein.Furthermore,real-time quantitative RT-PCR and indirect immunofluorescence assay indicated consistently the abilities of P-A and P-G to block viral infection in Marc-145 cells and they could function as antiviral agents for PRRSV.展开更多
In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only conside...In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.展开更多
Black phosphorus （BP） has received attention due to its own higher carrier mobility and layer dependent electronic properties, such as direct band gap. Interestingly, the single layer black phosphorus （SLBP） has h...Black phosphorus （BP） has received attention due to its own higher carrier mobility and layer dependent electronic properties, such as direct band gap. Interestingly, the single layer black phosphorus （SLBP） has had large popularity in applications related to thermoelectric, optoelectronic, and electronic devices. Here, we investigate the phonon spectrum, thermal conductivities, and stress strain effects. Robust anisotropy was mainly observed in the thermal conductivities together with the alongside zigzag （ZZ） direction value, compared to the armchair （AC） directions. We also investigated the attitude of stress that was anisotropic in both directions, and the stress effects were two times greater across the ZZ path than those in the AC direction at a low temperature. We obtained a ~oung＇s modulus of 63.77 and 20.74 GPa in the AC and ZZ directions, respectively, for a strain range of 0.01. These results had good agreement with first principle calculations. Our study here is useful and significant for the thermal tuning of phosphorus-based nanoelectronics and thermalelectric applications of phosphorus.展开更多
Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,1...Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.展开更多
文摘This paper presents a novel blockchain-embedded cybersecurity framework for industrial solar power systems,integrating immutable machine learning(ML)with distributed ledger technology.Our contribution focused on three factors,Quantum-resistant feature engineering using theUNSW-NB15 dataset adapted for solar infrastructure anomalies.An enhanced Light Gradient Boosting Machine(LightGBM)classifier with blockchain-validated decision thresholds,and A cryptographic proof-of-threat(PoT)consensus mechanism for cyber attack verification.The proposed Immutable LightGBM model with majority voting and cryptographic feature encoding achieves 96.9% detection accuracy with 0.97 weighted average of precision,recall and F1-score,outperforming conventional intrusion detection systems(IDSs)by 12.7% in false positive reduction.The blockchain layer demonstrates a 2.4-s average block confirmation time with 256-bit SHA-3 hashing,enabling real-time threat logging in photovoltaic networks.Experimental results improve in attack traceability compared to centralized security systems,establishing new benchmarks for trustworthy anomaly detection in smart grid infrastructures.This study also compared traditional and hybrid ML based blockchian driven IDSs and attained better classification results.The proposed framework not only delivers a resilient,adaptable threat mitigation system(TMS)for Industry 4.0 solar powered infrastructure but also attains high explainability,scalability with tamper-proof logs,and remarkably exceptional ability of endurance to cyber attacks.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R848)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiathe Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through the project number“NBU-FFR-2025-2932-09”.
文摘License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition Method(DR2M)to address such a problem.This method operates on displaced features compared to the training input observed throughout definite time frames.The technique focuses on detecting features that remain relatively stable under haze,using a frame-based analysis to isolate edges minimally affected by visual noise.The edge detection failures are identified using a bilateral neural network through displaced feature training.The training converges bilaterally towards the minimum edges from the maximum region.Thus,the training input and detected edges are used to identify the displacement between observed image frames to extract and differentiate the license plate region from the other vehicle regions.The proposed method maps the similarity feature between the detected and identified vehicle regions.This aids in leveraging the plate recognition precision with a high F1 score.Thus,this technique achieves a 10.27%improvement in identification precision,a 10.57%increase in F1 score,and a 9.73%reduction in false positive rate compared to baseline methods under maximum displacement conditions caused by haze.The technique attains an identification precision of 95.68%,an F1 score of 94.68%,and a false positive rate of 4.32%,indicating robust performance under haze-affected settings.
基金the Deanship of Scientific Research,Najran University,Kingdom of Saudi Arabia,for funding this work under the Research Groups Funding Program Grant Code Number(NU/RG/SERC/12/43).
文摘Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.
文摘In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate.We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations(SBSs)are deployed in the areas with high User Equipment(UE)density.Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs.For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication.By using tools from stochastic geometry,we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association.For UE clustering we considered Thomas cluster process and derive expressions for the association probability,coverage probability,area spectral efficiency,and energy efficiency.We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions.Furthermore,we analyze the impact of mmWave operating frequency,antenna gain,small cell biasing,and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets.Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.
基金supported by Higher Education Commission(HEC)of Pakistan through its National Research Program for Universities(NRPU)[Ref.No.20-14560/NRPU/R&D/HEC/2021]support provided by HEC。
文摘Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless networks.It provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless channels.To combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)networks.In this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is presented.An in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold investigations.First,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA networks.Followed by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage probability.Moreover,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)method.The optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and maximum-ratio-transmission.Furthermore,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless networks.This work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA networks.This comparative analysis provides a solid foundation for the development of future IRS-enabled,energy-efficient wireless communication systems.
基金National Funds through FCT–Portuguese Foundation for Science and Technology under the projects PTDC/CTM-CTM/1571/2020(All-Fi BRE),LA/P/0037/2020,UIDP/50025/2020 and UIDB/50025/2020(CENIMAT/I3N)by ERC-Co G-2014,CapTherPV,647596。
文摘Flexible microelectronic devices have seen an increasing trend toward development of miniaturized,portable,and integrated devices as wearable electronics which have the requirement for being light weight,small in dimension,and suppleness.Traditional three-dimensional(3D)and two-dimensional(2D)electronics gadgets fail to effectively comply with these necessities owing to their stiffness and large weights.Investigations have come up with a new family of one-dimensional(1D)flexible and fiber-based electronic devices(FBEDs)comprising power storage,energy-scavenging,implantable sensing,and flexible displays gadgets.However,development and manufacturing are still a challenge owing to their small radius,flexibility,low weight,weave ability and integration in textile electronics.This paper will provide a detailed review on the importance of substrates in electronic devices,intrinsic property requirements,fabrication classification and applications in energy harvesting,energy storage and other flexible electronic devices.Fiber-and textile-based electronic devices for bulk/scalable fabrications,encapsulation,and testing are reviewed and presented future research ideas to enhance the commercialization of these fiber-based electronics devices.
基金supported by the BMBF(Bundesministerium fr Bildung und Forschung,project no.03F0360A)
文摘Objective:To evaluate the antiniicrobial polenlial of different extracts of the endophytic fungus Phoma sp.and the tentative identification of their active constituents.Methods:The extract and compounds were screened for antimicrobial activity using the Agar Well Diffusion Method.Four compounds were purified using column chromatography and tlieir structures were assigned using～1H and～(13)C NMR spectra,DEPT,2D COSY,HMQC and HMBC experiments.Results:The ethyl acetate fraction of Phoma sp.showed good antifungal,antibacterial,and algicidal properties.One new dihydrofuran derivative,named phomafuranol(1),together with tliree known compounds,phomalacton(2),(3R)-5-hydroxymellein(3)and emodin(4)were isolated from the ethyl acetate fraction of Phoma sp.Preliminary studies indicated that phomalacton(2)displayed strong antibacterial,good antifungal and antialgal activities.Similarly(3R)-5-hydroxymellein(3)and emodin(4)showed good antifungal,antibacterial and algicidal properties.Conclusions:Antimicrobial activities of the ethyl acetate fraction of the endophytic fungus Phoma sp.and isolated compounds clearly demonstrate that Phoma sp.and its active compounds represent a great potential for the food,cosmetic and pharmaceutical industries.
文摘A feeding trial was conducted for 75 d to evaluate the nutritive value of a mixture of animal by-products （MAB） as a possible protein source in diets for juvenile mangrove red snapper, Lutjanus argentimaculatus （mean initial body weight, 30 g）. Fish were fed one of five isonitrogenous diets （40% crude protein） replacing 0, 25% （MAB25）, 50% （MAB50）, 75% （MAB75） and 100% （MAB100） of fish meal protein with similar percentages of MAB. The MAB consisted of 25% cow liver meal, 20% leather meal, 20% meat and bone meal, 15% blood meal, 10% APC （poultry feather meal）, 8% poultry manure dried, 1.5% choline and 0.5% chromic oxide. After 75 d of feeding, fish fed with diets MAB50, MAB75 and MABI00 exhibited significantly lower growth performance than that of fish fed with control and MAB25 diets. The optimum level of MAB was estimated to be 23%. Replacement of fish meal by MAB23% showed the following performance： maximum weight gain, 510%; SGR, 2.39% and FCE, 2.83%. The MAB substitution up to 75% of fish meal protein in diets did not show differences in apparent protein digestibility （83.6% for MAB25, 79.2% for MAB50, 78.7% for MAB75） compared with control （83.4%）, whereas in MABI00 group digestibility （65.3%） was significantly lower than in other groups. The apparent phosphorus absorption of test diet groups was significantly higher （37.1% for MAB25, 28.5% for MABS0, 55.6% for MAB75 and 54.5% for MABI00） than that of control （1 1.2%）. The levels of protein and ash in the whole body, carcass and viscera increased as MAB substitution in diets increased, whereas lipids and moisture remained consistent among all treatment groups. These results showed that approximately 23% of fish meal protein could be replaced by a mixture of animal by-products for juvenile snapper growing from 30 g to 167 g in 75 d without compromising growth performance and feed efficiency.
基金This work was partially supported by The China’s National Key R&D Program(No.2018YFB0803600)Natural Science Foundation of China(No.61801008)+2 种基金Beijing Natural Science Foundation National(No.L172049)Scientific Research Common Program of Beijing Municipal Commission of Education(No.KM201910005025)Defense Industrial Technology Development Program(No.JCKY2016204A102)sponsored this research in parts.
文摘Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents,economically damaging traffic jams,hijacking,motivating to wrong routes,and financial losses for businesses and governments.Smart and autonomous vehicles are connected wirelessly,which are more attracted for attackers due to the open nature of wireless communication.One of the problems is the rogue attack,in which the attacker pretends to be a legitimate user or access point by utilizing fake identity.To figure out the problem of a rogue attack,we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state information of the communication link.We consider the communication link between vehicle-to-vehicle,and vehicle-to-infrastructure.We evaluate the performance of our proposed technique by measuring the rogue attack probability,false alarm rate(FAR),mis-detection rate(MDR),and utility function of a receiver based on the test threshold values of reinforcement learning algorithm.The results show that the FAR and MDR are decreased significantly by selecting an appropriate threshold value in order to improve the receiver’s utility.
文摘Drought is one of the most prevalent abiotic stresses that adversely affect rice productivity(Petrozza et al, 2014). Rice is very sensitive to drought stress and drought can cause 50% reduction in rice production globally(Yang et al, 2008). To meet the food needs for global population, 63% more agricultural production will be required by the year 2050 than.
基金supported by the Natural Sciences and Engineering Research Council of Canada(NSERC)
文摘State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master and slave systems. Second, it presents an elegant design procedure which requires a set of equations to be solved in order to compute the control gains of the bilateral loop. These design conditions are obtained by turning the master-slave error into an autonomous system and imposing the desired dynamic behavior of the teleoperation system. Resultantly, the convergence of master and slave states is achieved in a well-defined manner. The present study aims at achieving a similar convergence behavior offered by state convergence controller while reducing the number of variables sent across the communication channel. The proposal suggests transmitting composite master and slave variables instead of full master and slave states while keeping the operator's force channel intact. We show that,with these composite and force variables;it is indeed possible to achieve the convergence of states in a desired way by strictly following the method of state convergence. The proposal leads to a reduced complexity state convergence algorithm which is termed as composite state convergence controller. In order to validate the proposed scheme in the absence and presence of communication time delays, MATLAB simulations and semi-real time experiments are performed on a single degree-of-freedom teleoperation system.
文摘Vehicular ad-hoc networks(VANETs)play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities.Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages(EMs)depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach.Nevertheless,such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously.Due to the high number of vehicles,it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions.A cluster-based EM transmitting technique is proposed in this paper.For urban VANETs,this paper pioneers the clustering of bi-directional road traffic for robust and efficient routing of EMs.In this regard,this paper introduces a routing protocol,namely,the bi-directional urban routing protocol(BURP).In addition to the paths and relative locations of vehicles,BURP takes account of the distance parameter by using the Hamming distance function to determine the direction ofmotion of vehicles and communicates EMs through the cluster head(CH).Amodified k-medoids algorithm is presented for the clustering of bi-directional road traffic.A median method is presented for selecting CH to ensure the longrunning of a cluster.Simulation results show that BURP provides enhanced throughput,a maximized packet delivery ratio,low energy consumption,and network delay relative to eminent routing protocols.
基金This work is supported in part by the Beijing Natural Science Foundation(No.4212015)Natural Science Foundation of China(No.61801008)+3 种基金China Ministry of Education-China Mobile Scientific Research Foundation(No.MCM20200102)China Postdoctoral Science Foundation(No.2020M670074)Beijing Municipal Commission of Education Foundation(No.KM201910005025)Beijing Postdoctoral Research Foundation(No.2021-ZZ-077,No.2020-YJ-006).
文摘Cyber-physical wireless systems have surfaced as an important data communication and networking research area.It is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking technologies.Due to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and impersonation.Existing methods use physical layer authentication(PLA),themost promising solution to detect cyber-attacks.Still,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency target.These methods perform well but only in stationary scenarios.We have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile scenarios.The features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify data.The authentication of the received signal is considered a binary classification problem.The transmitted data is labeled as legitimate information,and spoofing data is illegitimate information.Therefore,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing attacks.It detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are mobile.The proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.
基金BASF AG and the BMBF(Bundesministerium für Bildung und Forschung,No.03F0360A)
文摘A new metabolite,named seimatoric acid（1）,representing a new oxobutanoic acid derivative has been isolated from Seimatosporium sp., in addition to four known compounds viz.,2-hydroxymethyl-4β,5α,6β-trihydroxycyclohex-2-enone（2）,（-）-phyllostine（3）,（＋）-epiepoxydon（4） and（＋）-epoxydon monoacetate（5）.Similarly one new benzoic acid derivative,named colletonoic acid（6） was isolated from the ethyl acetate fraction of Colletotrichum sp.The structures of the new compounds were elucidated by detailed ^1 H NMR,^13C NMR,COSY,HMQC.HMBC spectroscopic analysis,and HR-E1-MS.Seimatoric acid（1）was also isolated from another taxonomical unidentified fungal strain 4295 in ourgroup.The structures of the known compounds were elucidated by their spectral data comparison to literature data.Preliminary studies showed that colletonoic acid（6） showed good antibacterial,antifungal,and antialgal activities.
文摘Objective The current study was aimed to investigate the correlations between immobility time in the forced swimming test （FST, a behavioral indicator of stress level） and hippocampal monoamine levels （markers of depression）, plasma adrenalin level （a peripheral marker of stress） as well as fluoro-jade C staining （a marker of neurodegeneration）. Methods Male Sprague-Dawley rats were subjected to acute, sub-chronic （7 d） or chronic （14 d） FSTs and immobility time was recorded. Levels of noradrenalin, serotonin and dopamine in the hippocampus, and adrenalin level in the plasma were quantified by high-performance liquid chromatography with electrochemical detection. Brain sections from rats after chronic forced swimming or rotenone treatment （3 mg/kg subcutaneously for 4 d） were stained with fluoro-jade C. Results The rats subjected to swimming stress （acute, sub-chronic and chronic） showed long immobility times [（214 ± 5）, （220 ± 4） and （231 ± 7） s, respectively], indicating that the animals were under stress. However, the rats did not exhibit significant declines in hippocampal monoamine levels, and the plasma adrenalin level was not significantly increased compared to that in unstressed rats. The rats that underwent chronic swimming stress did not manifest fluoro-jade C staining in brain sections, while degenerating neurons were evident after rotenone treatment. Conclusion The immobility time in the FST does not correlate with markers of depression （monoamine levels） and internal stress （adrenalin levels and neurodegeneration）, hence this parameter may not be a true indicator of stress level.
基金Supported by the National Natural Science Foundation of China(31372438,31200122)
文摘Porcine reproductive and respiratory syndrome virus(PRRSV)GP4 protein was prokaryotically expressed,and used as an antigen to immunize six-week-old BALB/c female mice.With conventional cell fusion method,an anti-PRRSV GP4 protein monoclonal antibody(Mab)5F12 was successfully prepared.It was identified as IgG2b subclass and had better stability and specificity,which not only responded with recombinant PRRSV GP4 protein,but also with PRRSV.Phage display technique had varieties of applications,in particular,the identification of key antigen epitopes for the development of therapeutic and diagnostic reagents and vaccines.In this study,Mab-5F12 was used as the target for biopanning a 12-mer phage random peptide library.After four rounds of biopanning,two phage-displayed peptides,named P-A and P-G(AKFEVCSPVVLG and GVNQENMLHFSF)were identified that recognized Mab-5F12 specifically.Sequence analysis showed that one or more of the peptides exhibited partial sequence similarity to the native GP4 protein sequence,which corresponded to 69-80 and 84-95 aa segments of the HP-PRRSV GP4 protein.Furthermore,real-time quantitative RT-PCR and indirect immunofluorescence assay indicated consistently the abilities of P-A and P-G to block viral infection in Marc-145 cells and they could function as antiviral agents for PRRSV.
基金National Research Foundation of Korea-Grant funded by the Korean Government(Ministry of Science and ICT)-NRF-2020R1AB5B02002478.
文摘In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.
文摘Black phosphorus （BP） has received attention due to its own higher carrier mobility and layer dependent electronic properties, such as direct band gap. Interestingly, the single layer black phosphorus （SLBP） has had large popularity in applications related to thermoelectric, optoelectronic, and electronic devices. Here, we investigate the phonon spectrum, thermal conductivities, and stress strain effects. Robust anisotropy was mainly observed in the thermal conductivities together with the alongside zigzag （ZZ） direction value, compared to the armchair （AC） directions. We also investigated the attitude of stress that was anisotropic in both directions, and the stress effects were two times greater across the ZZ path than those in the AC direction at a low temperature. We obtained a ~oung＇s modulus of 63.77 and 20.74 GPa in the AC and ZZ directions, respectively, for a strain range of 0.01. These results had good agreement with first principle calculations. Our study here is useful and significant for the thermal tuning of phosphorus-based nanoelectronics and thermalelectric applications of phosphorus.
基金the Researchers Supporting Project No.(RSP2023R410),King Saud University,Riyadh,Saudi Arabia.
文摘Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.
