The gut microbiota significantly influences host physiology and provides essential ecosystem services.While diet can affect the composition of the gut microbiota,the gut microbiota can also help the host adapt to spec...The gut microbiota significantly influences host physiology and provides essential ecosystem services.While diet can affect the composition of the gut microbiota,the gut microbiota can also help the host adapt to specific dietary habits.The carrion crow(Corvus corone),an urban facultative scavenger bird,hosts an abundance of pathogens due to its scavenging behavior.Despite this,carrion crows infrequently exhibit illness,a phenomenon related to their unique physiological adaptability.At present,however,the role of the gut microbiota remains incompletely understood.In this study,we performed a comparative analysis using 16S rRNA amplicon sequencing technology to assess colonic content in carrion crows and 16 other bird species with different diets in Beijing,China.Our findings revealed that the dominant gut microbiota in carrion crows was primarily composed of Proteobacteria(75.51%)and Firmicutes(22.37%).Significant differences were observed in the relative abundance of Enterococcus faecalis among groups,highlighting its potential as a biomarker of facultative scavenging behavior in carrion crows.Subsequently,E.faecalis isolated from carrion crows was transplanted into model mice to explore the protective effects of this bacterial community against Salmonella enterica infection.Results showed that E.faecalis down-regulated the expression of pro-inflammatory cytokines tumor necrosis factor alpha(TNF-α),interferon gamma(IFN-γ),and interleukin 6(IL-6),prevented S.enterica colonization,and regulated the composition of gut microbiota in mice,thereby modulating the host’s immune regulatory capacity.Therefore,E.faecalis exerts immunoregulatory and anti-pathogenic functions in carrion crows engaged in scavenging behavior,offering a representative case of how the gut microbiota contributes to the protection of hosts with specialized diets.展开更多
In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on ...In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper.This method can effectively utilize downhole parameters collected in real-time during drilling,to identify lithology in real-time and provide a reference for optimization of drilling parameters.Given the imbalance of lithology samples,the synthetic minority over-sampling technique(SMOTE)and Tomek link were used to balance the sample number of five lithologies.Meanwhile,this paper introduces Tent map,random opposition-based learning and dynamic perceived probability to the original crow search algorithm(CSA),and establishes an improved crow search algorithm(ICSA).In this paper,ICSA is used to optimize the hyperparameter combination of random forest(RF),extremely random trees(ET),extreme gradient boosting(XGB),and light gradient boosting machine(LGBM)models.In addition,this study combines the recognition advantages of the four models.The accuracy of lithology identification by the weighted average probability model reaches 0.877.The study of this paper realizes high-precision real-time lithology identification method,which can provide lithology reference for the drilling process.展开更多
Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images fr...Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images from the database.This CBIR system helps a physician to give better treatment.Local features must be described with the input images to retrieve similar images.Exist-ing methods are inefficient and inaccurate by failing in local features analysis.Hence,efficient digital mammography image retrieval needs to be implemented.This paper proposed reliable recovery of the mammographic image from the data-base,which requires the removal of noise using Kalman filter and scale-invariant feature transform(SIFT)for feature extraction with Crow Search Optimization-based the deep belief network(CSO-DBN).This proposed technique decreases the complexity,cost,energy,and time consumption.Training the proposed model using a deep belief network and validation is performed.Finally,the testing pro-cess gives better performance compared to existing techniques.The accuracy rate of the proposed work CSO-DBN is 0.9344,whereas the support vector machine(SVM)(0.5434),naïve Bayes(NB)(0.7014),Butterfly Optimization Algorithm(BOA)(0.8156),and Cat Swarm Optimization(CSO)(0.8852).展开更多
Drainage divides along a southern Laramie Range crest area and in the nearby southeast Wyoming Gangplank area (as observed on detailed topographic maps) suggest present-day drainage routes in the Cheyenne Tablelands r...Drainage divides along a southern Laramie Range crest area and in the nearby southeast Wyoming Gangplank area (as observed on detailed topographic maps) suggest present-day drainage routes in the Cheyenne Tablelands region originated as headward erosion of south-oriented valleys (now the downstream Lodgepole, Crow, and Lone Tree Creek valleys) from an actively eroding northeast-oriented South Platte River valley captured flood flow in the south half of a large east-oriented anastomosing channel complex while headward erosion of a north-oriented valley (now the downstream Horse Creek valley) from the southeast-oriented North Platte River valley captured the north half of the same large anastomosing channel complex. The Gangplank, which today serves as a low gradient ramp of Tertiary Ogallala Formation sediments leading from the Great Plains to the Laramie Range erosion surface, is located along the Crow Creek-Lone Tree Creek drainage divide and low points along that divide (referred to here as divide crossings) suggest, prior to headward erosion of what is now its south-oriented downstream Lone Tree Creek valley, upstream east-oriented Lone Tree Creek drainage routes were intertwined with east-oriented Crow Creek drainage routes, which today flow much further in an east direction (than east-oriented upstream Lone Tree Creek drainage routes) before also turning in a south direction to reach the South Platte River. The ability of the commonly accepted regional geomorphology paradigm to explain this topographic map evidence is then compared with a fundamentally different and new regional geomorphology paradigm’s ability to explain the same evidence. While both paradigms offer possible explanations the new paradigm, which requires headward erosion of the valleys to have occurred as massive continental ice sheet melt water floods crossed the region, explains much more of the drainage system evidence and also permits much more detailed explanations.展开更多
Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images fro...Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images from the database.This CBIR system helps a physician to give better treatment.Local features must be described with the input images to retrieve similar images.Exist-ing methods are inefficient and inaccurate by failing in local features analysis.Hence,efficient digital mammography image retrieval needs to be implemented.This paper proposed reliable recovery of the mammographic image from the data-base,which requires the removal of noise using Kalmanfilter and scale-invariant feature transform(SIFT)for feature extraction with Crow Search Optimization-based the deep belief network(CSO-DBN).This proposed technique decreases the complexity,cost,energy,and time consumption.Training the proposed model using a deep belief network and validation is performed.Finally,the testing pro-cess gives better performance compared to existing techniques.The accuracy rate of the proposed work CSO-DBN is 0.9344,whereas the support vector machine(SVM)(0.5434),naïve Bayes(NB)(0.7014),Butterfly Optimization Algorithm(BOA)(0.8156),and Cat Swarm Optimization(CSO)(0.8852).展开更多
The next step in mobile communication technology,known as 5G,is set to go live in a number of countries in the near future.New wireless applica-tions have high data rates and mobility requirements,which have posed a c...The next step in mobile communication technology,known as 5G,is set to go live in a number of countries in the near future.New wireless applica-tions have high data rates and mobility requirements,which have posed a chal-lenge to mobile communication technology researchers and designers.5G systems could benefit from the Universal Filtered Multicarrier(UFMC).UFMC is an alternate waveform to orthogonal frequency-division multiplexing(OFDM),infiltering process is performed for a sub-band of subcarriers rather than the entire band of subcarriers Inter Carrier Interference(ICI)between neighbouring users is reduced via the sub-bandfiltering process,which reduces out-of-band emissions.However,the UFMC system has a high Peak-to-Average Power Ratio(PAPR),which limits its capabilities.Metaheuristic optimization based Selective mapping(SLM)is used in this paper to optimise the UFMC-PAPR.Based on the cognitive behaviour of crows,the research study suggests an innovative metaheuristic opti-mization known as Crow Search Algorithm(CSA)for SLM optimization.Com-pared to the standard UFMC,SLM-UFMC system,and SLM-UFMC with conventional metaheuristic optimization techniques,the suggested technique sig-nificantly reduces PAPR.For the UFMC system,the suggested approach has a very low Bit Error Rate(BER).展开更多
The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated fr...The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.展开更多
Chi Zijian’s novel White Snow Crow is about the pestis in Northeast China from the autumn and winter of 1910 to the spring of 1911,focusing on the living conditions of people in Fujiadian,Harbin,under the shadow of t...Chi Zijian’s novel White Snow Crow is about the pestis in Northeast China from the autumn and winter of 1910 to the spring of 1911,focusing on the living conditions of people in Fujiadian,Harbin,under the shadow of the pestis,and thus connects the vicissitudes of Harbin in the development of modern Chinese history.Re-reading this novel in the context of the post-epidemic era not only allows us to immerse ourselves in the specific temporal and spatial fields described in the text with an immersive reading mindset,feel the heavy impact that the disaster has brought to the people of Northeast China,but also provide us with a different perspective to observe the current social reality.In particular,the social problems shown by the novel through the pestis and the description of ordinary people’s life experience under the plague still deserve further discussion.展开更多
Introduction: The use of growth factors and cytokines in skin rejuvenation and reversal of photo ageing is a novel anti-ageing treatment. These factors provide a microenvironment that seems to favor tissue repair and ...Introduction: The use of growth factors and cytokines in skin rejuvenation and reversal of photo ageing is a novel anti-ageing treatment. These factors provide a microenvironment that seems to favor tissue repair and regeneration. Methods: An open label, monocentric, single arm study to evaluate anti-ageing efficacy of conditioned medium obtained from adult human bone-marrow derived allogenic mesenchymal stromal cells (BMMSC) along with excipients formulated into a cosmetic serum, was conducted in 40 Indian female population aged 35 to 60 years, belonging to skin type IV - VI of Norwood Scale for a duration of 90 days. Parameters—fine lines, wrinkles, crow’s feet, evenness of skin tone, skin firmness/laxity, hydration of skin, homogeneity of age spots, and visible pores were used to evaluate the anti-ageing and rejuvenating properties of the test product. Results and Discussion: Improvement was seen in majority of parameters starting from 15 - 30 days. Product was safe and well tolerated as per the dermatologist and subjects’ self-assessment.展开更多
This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distributio...This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distribution system (EDS). Egypt has an excellent wind regime with wind speeds of about 10 m/s at many areas. The disadvantage of wind energy is its seasonal variations. So, if wind power is to supply a significant portion of the demand, either backup power or electrical energy storage (EES) system is needed to ensure that loads will be supplied in reliable way. So, the hybrid WE/PEMFC system is designed to completely supply a part of the Egyptian distribution system, in attempt to isolate it from the grid. However, the optimal allocation of the hybrid units is obtained, in order to enhance their benefits in the distribution networks. The critical buses that are necessary to install the hybrid WE/ PEMFC system, are chosen using sensitivity analysis. Then, the binary Crow search algorithm (BCSA), discrete Jaya algorithm (DJA) and binary particle swarm optimization (BPSO) techniques are proposed to determine the optimal operation of power systems using single and multi-objective functions (SOF/MOF). Then, the results of the three optimization techniques are compared with each other. Three sensitivity factors are employed in this paper, which are voltage sensitivity factor (VSF), active losses sensitivity factor (ALSF) and reactive losses sensitivity factor (RLSF). The effects of the sensitivity factors (SFs) on the SOF/MOF are studied. The improvement of voltage profile and minimizing active and reactive power losses of the EDS are considered as objective functions. Backward/forward sweep (BFS) method is used for the load flow calculations. The system load demand is predicted up to year 2022 for Mersi-Matrouh City as a part of Egyptian distribution network, and the design of the hybrid WE/PEMFC system is applied. The PEMFC system is designed considering simplified mathematical expressions. The economics of operat展开更多
基金supported by the National Key Research and Development Program of China(2022YFC2601602)Major Program of National Natural Science Foundation of China(32090023)Beijing Wildlife Rescue Center,China。
文摘The gut microbiota significantly influences host physiology and provides essential ecosystem services.While diet can affect the composition of the gut microbiota,the gut microbiota can also help the host adapt to specific dietary habits.The carrion crow(Corvus corone),an urban facultative scavenger bird,hosts an abundance of pathogens due to its scavenging behavior.Despite this,carrion crows infrequently exhibit illness,a phenomenon related to their unique physiological adaptability.At present,however,the role of the gut microbiota remains incompletely understood.In this study,we performed a comparative analysis using 16S rRNA amplicon sequencing technology to assess colonic content in carrion crows and 16 other bird species with different diets in Beijing,China.Our findings revealed that the dominant gut microbiota in carrion crows was primarily composed of Proteobacteria(75.51%)and Firmicutes(22.37%).Significant differences were observed in the relative abundance of Enterococcus faecalis among groups,highlighting its potential as a biomarker of facultative scavenging behavior in carrion crows.Subsequently,E.faecalis isolated from carrion crows was transplanted into model mice to explore the protective effects of this bacterial community against Salmonella enterica infection.Results showed that E.faecalis down-regulated the expression of pro-inflammatory cytokines tumor necrosis factor alpha(TNF-α),interferon gamma(IFN-γ),and interleukin 6(IL-6),prevented S.enterica colonization,and regulated the composition of gut microbiota in mice,thereby modulating the host’s immune regulatory capacity.Therefore,E.faecalis exerts immunoregulatory and anti-pathogenic functions in carrion crows engaged in scavenging behavior,offering a representative case of how the gut microbiota contributes to the protection of hosts with specialized diets.
基金supported by CNPC-CZU Innovation Alliancesupported by the Program of Polar Drilling Environmental Protection and Waste Treatment Technology (2022YFC2806403)。
文摘In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper.This method can effectively utilize downhole parameters collected in real-time during drilling,to identify lithology in real-time and provide a reference for optimization of drilling parameters.Given the imbalance of lithology samples,the synthetic minority over-sampling technique(SMOTE)and Tomek link were used to balance the sample number of five lithologies.Meanwhile,this paper introduces Tent map,random opposition-based learning and dynamic perceived probability to the original crow search algorithm(CSA),and establishes an improved crow search algorithm(ICSA).In this paper,ICSA is used to optimize the hyperparameter combination of random forest(RF),extremely random trees(ET),extreme gradient boosting(XGB),and light gradient boosting machine(LGBM)models.In addition,this study combines the recognition advantages of the four models.The accuracy of lithology identification by the weighted average probability model reaches 0.877.The study of this paper realizes high-precision real-time lithology identification method,which can provide lithology reference for the drilling process.
文摘Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images from the database.This CBIR system helps a physician to give better treatment.Local features must be described with the input images to retrieve similar images.Exist-ing methods are inefficient and inaccurate by failing in local features analysis.Hence,efficient digital mammography image retrieval needs to be implemented.This paper proposed reliable recovery of the mammographic image from the data-base,which requires the removal of noise using Kalman filter and scale-invariant feature transform(SIFT)for feature extraction with Crow Search Optimization-based the deep belief network(CSO-DBN).This proposed technique decreases the complexity,cost,energy,and time consumption.Training the proposed model using a deep belief network and validation is performed.Finally,the testing pro-cess gives better performance compared to existing techniques.The accuracy rate of the proposed work CSO-DBN is 0.9344,whereas the support vector machine(SVM)(0.5434),naïve Bayes(NB)(0.7014),Butterfly Optimization Algorithm(BOA)(0.8156),and Cat Swarm Optimization(CSO)(0.8852).
文摘Drainage divides along a southern Laramie Range crest area and in the nearby southeast Wyoming Gangplank area (as observed on detailed topographic maps) suggest present-day drainage routes in the Cheyenne Tablelands region originated as headward erosion of south-oriented valleys (now the downstream Lodgepole, Crow, and Lone Tree Creek valleys) from an actively eroding northeast-oriented South Platte River valley captured flood flow in the south half of a large east-oriented anastomosing channel complex while headward erosion of a north-oriented valley (now the downstream Horse Creek valley) from the southeast-oriented North Platte River valley captured the north half of the same large anastomosing channel complex. The Gangplank, which today serves as a low gradient ramp of Tertiary Ogallala Formation sediments leading from the Great Plains to the Laramie Range erosion surface, is located along the Crow Creek-Lone Tree Creek drainage divide and low points along that divide (referred to here as divide crossings) suggest, prior to headward erosion of what is now its south-oriented downstream Lone Tree Creek valley, upstream east-oriented Lone Tree Creek drainage routes were intertwined with east-oriented Crow Creek drainage routes, which today flow much further in an east direction (than east-oriented upstream Lone Tree Creek drainage routes) before also turning in a south direction to reach the South Platte River. The ability of the commonly accepted regional geomorphology paradigm to explain this topographic map evidence is then compared with a fundamentally different and new regional geomorphology paradigm’s ability to explain the same evidence. While both paradigms offer possible explanations the new paradigm, which requires headward erosion of the valleys to have occurred as massive continental ice sheet melt water floods crossed the region, explains much more of the drainage system evidence and also permits much more detailed explanations.
文摘Mammography is considered a significant image for accurate breast cancer detection.Content-based image retrieval(CBIR)contributes to classifying the query mammography image and retrieves similar mammographic images from the database.This CBIR system helps a physician to give better treatment.Local features must be described with the input images to retrieve similar images.Exist-ing methods are inefficient and inaccurate by failing in local features analysis.Hence,efficient digital mammography image retrieval needs to be implemented.This paper proposed reliable recovery of the mammographic image from the data-base,which requires the removal of noise using Kalmanfilter and scale-invariant feature transform(SIFT)for feature extraction with Crow Search Optimization-based the deep belief network(CSO-DBN).This proposed technique decreases the complexity,cost,energy,and time consumption.Training the proposed model using a deep belief network and validation is performed.Finally,the testing pro-cess gives better performance compared to existing techniques.The accuracy rate of the proposed work CSO-DBN is 0.9344,whereas the support vector machine(SVM)(0.5434),naïve Bayes(NB)(0.7014),Butterfly Optimization Algorithm(BOA)(0.8156),and Cat Swarm Optimization(CSO)(0.8852).
文摘The next step in mobile communication technology,known as 5G,is set to go live in a number of countries in the near future.New wireless applica-tions have high data rates and mobility requirements,which have posed a chal-lenge to mobile communication technology researchers and designers.5G systems could benefit from the Universal Filtered Multicarrier(UFMC).UFMC is an alternate waveform to orthogonal frequency-division multiplexing(OFDM),infiltering process is performed for a sub-band of subcarriers rather than the entire band of subcarriers Inter Carrier Interference(ICI)between neighbouring users is reduced via the sub-bandfiltering process,which reduces out-of-band emissions.However,the UFMC system has a high Peak-to-Average Power Ratio(PAPR),which limits its capabilities.Metaheuristic optimization based Selective mapping(SLM)is used in this paper to optimise the UFMC-PAPR.Based on the cognitive behaviour of crows,the research study suggests an innovative metaheuristic opti-mization known as Crow Search Algorithm(CSA)for SLM optimization.Com-pared to the standard UFMC,SLM-UFMC system,and SLM-UFMC with conventional metaheuristic optimization techniques,the suggested technique sig-nificantly reduces PAPR.For the UFMC system,the suggested approach has a very low Bit Error Rate(BER).
文摘The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.
文摘Chi Zijian’s novel White Snow Crow is about the pestis in Northeast China from the autumn and winter of 1910 to the spring of 1911,focusing on the living conditions of people in Fujiadian,Harbin,under the shadow of the pestis,and thus connects the vicissitudes of Harbin in the development of modern Chinese history.Re-reading this novel in the context of the post-epidemic era not only allows us to immerse ourselves in the specific temporal and spatial fields described in the text with an immersive reading mindset,feel the heavy impact that the disaster has brought to the people of Northeast China,but also provide us with a different perspective to observe the current social reality.In particular,the social problems shown by the novel through the pestis and the description of ordinary people’s life experience under the plague still deserve further discussion.
文摘Introduction: The use of growth factors and cytokines in skin rejuvenation and reversal of photo ageing is a novel anti-ageing treatment. These factors provide a microenvironment that seems to favor tissue repair and regeneration. Methods: An open label, monocentric, single arm study to evaluate anti-ageing efficacy of conditioned medium obtained from adult human bone-marrow derived allogenic mesenchymal stromal cells (BMMSC) along with excipients formulated into a cosmetic serum, was conducted in 40 Indian female population aged 35 to 60 years, belonging to skin type IV - VI of Norwood Scale for a duration of 90 days. Parameters—fine lines, wrinkles, crow’s feet, evenness of skin tone, skin firmness/laxity, hydration of skin, homogeneity of age spots, and visible pores were used to evaluate the anti-ageing and rejuvenating properties of the test product. Results and Discussion: Improvement was seen in majority of parameters starting from 15 - 30 days. Product was safe and well tolerated as per the dermatologist and subjects’ self-assessment.
文摘This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distribution system (EDS). Egypt has an excellent wind regime with wind speeds of about 10 m/s at many areas. The disadvantage of wind energy is its seasonal variations. So, if wind power is to supply a significant portion of the demand, either backup power or electrical energy storage (EES) system is needed to ensure that loads will be supplied in reliable way. So, the hybrid WE/PEMFC system is designed to completely supply a part of the Egyptian distribution system, in attempt to isolate it from the grid. However, the optimal allocation of the hybrid units is obtained, in order to enhance their benefits in the distribution networks. The critical buses that are necessary to install the hybrid WE/ PEMFC system, are chosen using sensitivity analysis. Then, the binary Crow search algorithm (BCSA), discrete Jaya algorithm (DJA) and binary particle swarm optimization (BPSO) techniques are proposed to determine the optimal operation of power systems using single and multi-objective functions (SOF/MOF). Then, the results of the three optimization techniques are compared with each other. Three sensitivity factors are employed in this paper, which are voltage sensitivity factor (VSF), active losses sensitivity factor (ALSF) and reactive losses sensitivity factor (RLSF). The effects of the sensitivity factors (SFs) on the SOF/MOF are studied. The improvement of voltage profile and minimizing active and reactive power losses of the EDS are considered as objective functions. Backward/forward sweep (BFS) method is used for the load flow calculations. The system load demand is predicted up to year 2022 for Mersi-Matrouh City as a part of Egyptian distribution network, and the design of the hybrid WE/PEMFC system is applied. The PEMFC system is designed considering simplified mathematical expressions. The economics of operat
