Colony Hybridization Research Articles

A Neglected Design Style: Colonial Era Hybrid Architecture, Furniture and Interior Decoration in Aotearoa New Zealand

Colonial hybrid design has been a neglected style in Aotearoa New Zealand’s and design history. However, an overview of the corpus, its quantity and plurality, with both Māori and Pākehā makers working into the early twentieth century, indicates that a reappraisal is required. The case study of one Pākehā maker, J.H. Menzies, shows a combination of respect and ignorance of toi Māori (Māori art).[i] Despite the negative connotations of cultural appropriation, a kernel of genuine creative exchange is at the heart of this colonial phenomenon, as exemplified in his work. [i] I use this term generically to include all forms of art customarily practised by Māori, including (but not limited to) hoahoanga (architecture), toi whakairo (the art of carving) and kōwhaiwahi (painted patterns).

Optimization of Sewing Equipment Based on Improved Genetic-ant Colony Hybrid Algorithm

The optimization of the cutting path of the sample can effectively reduce the cutting time, thereby improving the production efficiency of numerical control processing. This paper comprehensively considers the impact of the cutting order and the position of the knife entry point on the cutting path, converts the cutting path problem into a type of traveling salesman problem (TSP), and proposes an improved genetic-particle swarm optimization algorithm. The selection mechanism of the algorithm combines the elitist retention strategy and roulette wheel selection method to accelerate the search for the optimal solution; the mutation strategy designs a linear decreasing mutation rate, which enhances the global search ability; at the same time, introduces the ant colony optimization algorithm to process the fitness function, adjusts the population evolution difference, and speeds up the optimization process. Through this hybrid algorithm, the cutting order of the sample can be quickly optimized, and the nearest neighbor algorithm is used to determine the position of the knife entry point. Tests are conducted on clothing patterning charts and standard examples. Compared with several commonly used algorithms, experimental results verify the feasibility and effectiveness of this algorithm

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

AbstractNature‐inspired algorithms revolve around the intersection of nature‐inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature‐inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, and the efficacy of nature‐inspired algorithms in IoT‐based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature‐inspired algorithms in IoT‐based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature‐inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37.9% of cases, showcasing a prevalent choice among researchers. Our evaluation emphasizes adaptability as the paramount parameter, accounting for 18.4% of considerations. By shedding light on attributes, limitations, and potential directions for future research and development, this review aims to contribute to a comprehensive understanding of nature‐inspired algorithms in the dynamic landscape of IoT‐based healthcare services.

An Analysis of the Identity Structures Built Up by the Characters in Zadie Smith's Novel White Teeth

This paper has been prepared in order to analyze the construction of an identity of both Bangladeshi migrants (Samad Iqbal) as well as English men (Archies Jones) who emigrated from other countries. Those are close friends. Lived in the multicultural city of London in Britain. In the novel White Teeth, the author explores the problems resulting from immigrants from various countries living in Britain, especially those who have left behind physical artifacts (cultural properties) and intangible attributes relating to their ethnic group inherited from the past of the immigrants, who lived in Britain from the first generation to the second generation. The novel of the Smiths is interconnected with their past and also deals with their dissatisfaction with their lives in a society in which they live today. According to Smith, his work is sensitively concerned with the second generation immigrants and their beliefs, which are transmitted from ultra-modern societies via their bringing up, living standards, values, taboos, thinking processes, and the likes. The purpose of this paper is to evaluate the way in which the construction of identity of different characters in the novel White Teeth is explored through the lenses of different theories of social scholars, such as Colonial theory, hybridity theory, and post-modern era theories of identity in the social system. This paper also explores how characters existing in the novel construct identity of themselves and how different cultural interact on their identity formation in White Teeth

Revisiting Colonial Encounters in Maitreyi Devi’s It Does Not Die: A Romance: A Postcolonial Perspective

The Indian novelist, Maitreyi Devi’s account of her love story with Romanian novelist, Mircea Eliade came out in 1974 as Na Hanyate in the Bengali language and its English version was titled It Does Not Die in 1976 by the author herself. Following Nirmala Menon’s critical insights on Bhabha’s (post)colonial hybridity discourse, this study aims to reinterpret the novel as an illustrative text of postcolonial “interrogative hybridity.” Devi employs hybridity in such a way that it unsettles a linear narrative with constant shifts in focus and style. It is upheld that her ingenious hybridity originates from her position as an off-center postcolonial female writer who critiques colonial stereotypes and mimicry by revisiting/challenging colonial discourse constructed against the colonized by the colonizers. Hence, the study explores how her novel is a postcolonial hybrid counter-narrative text to colonial fantasies. To conclude, postcolonial hybridity can only problematize colonial individuations and representations, if it reverses the seemingly sound effects of colonial discourse in such a way that “other ‘denied’ knowledges” enter upon the dominant discourse and estrange the basis of its authority—its rules of recognition.

Increasing the Accuracy of Writer Identification Based on Bee Colony Optimization Algorithm and Hybrid Deep Learning Method

Increasing the Accuracy of Writer Identification Based on Bee Colony Optimization Algorithm and Hybrid Deep Learning Method

Artificial Bee Colony Algorithm-based Feature Selection and Hybrid ML Framework for Efficient Rice Yield Prediction

India's economy predominantly depends on monsoon and agricultural output. Agribusiness products contribute to nearly a quarter of its gross domestic product and 58% of its population depends on agriculture for their livelihood. Certain crops, like rice, are vital to its food security being the most widely grown crop and accounting for one-third production of foodgrains in India. Understanding and enhancing its production is critical in ensuring food availability and promoting sustainable agricultural practices. Rice yield prediction has been a most researched area in the agriculture domain. Machine Learning (ML) frameworks have been found to perform well in patches with large, complex datasets as insufficient feature engineering and temporal dependencies plague efficacy. In this paper, we propose a swam-based meta-heuristic artificial bee colony (ABC) algorithm for feature selection from the dataset sourced from the Agricultural Production and Statistical Division of the Department of Agriculture Cooperation and Farmers Welfare, Government of India. The feature engineering is further optimized by a hybrid model comprising a convolutional neural network (CNN) for learning hierarchical representations and identifying relevant attributes from the complex dataset and long short-term memory (LSTM) for temporal aspects. Finally, a random forest (RF) regressor provides the benefits of ensemble learning, which merges multiple decision trees to remove bias, and variance and improve prediction accuracy. From the results, it is observed that the proposed hybrid model outperforms existing state-of-the-art standalone and hybrid models with the highest coefficient of determination (R2) and lowest mean square error (MSE) of 0.989 and 13613 respectively. The reliable and efficient hybrid model can aid farmers and policymakers in making informed decisions related to rice yield prediction leading to sustainable agricultural practices.

Campylobacter fetus isolates from both human patients and healthy cattle carry three distinct cytolethal distending toxin (cdt) gene clusters.

Campylobacter fetus is a zoonotic pathogen. Although the precise virulence mechanisms have not yet been fully elucidated, cytolethal distending toxin (CDT) is considered as one of the well-characterized virulence factors in Campylobacter. In silico analysis of the genome of C. fetus type strain of ATCC27374T indicates that there are three cdt gene clusters, Cfcdt-I, Cfcdt-II and Cfcdt-III. However, it is not clear whether these clusters are ubiquitously present in C. fetus and their association with diseases in humans and animals. In this study, we have analyzed the distribution and nucleotide sequences of these cdt gene clusters in 137 C. fetus strains isolated from human patients and healthy cattle. MLST and PFGE were also applied to determine clonal relationship between C. fetus strains isolated from patients and cattle. We found all C. fetus strains carry three Cfcdt gene clusters by colony hybridization assay and the strains belonged to 38 different pulsotypes. Whole genome sequencing of 38 C. fetus strains was carried out to determine the entire cdt gene cluster sequences and their sequence type (ST). Among 38 strains, six STs were identified, and each cdt gene cluster showed high similarity (>99%). Interestingly, some of these Cfcdt genes are more similar to the cdt genes of other Campylobacter species than other Cfcdt gene types. Altogether, the results suggest that three Cfcdt gene clusters are highly conserved in C. fetus and the strains belonging to ST-6 may be more pathogenic to human.

Addressing Current Challenges in Poultry Meat Safety: Development of a Cultivation and Colony Hybridization Approach to Recover Enterotoxigenic Clostridium perfringens from Broiler Chicken Carcasses.

Enterotoxigenic Clostridium perfringens is one of the main causes of foodborne illness in Canada. The use of a conventional bacterial culture approach to isolate enterotoxigenic C. perfringens from poultry meat is common. This approach is based on the phenotype attributable to a double hemolysis phenomenon, whereas few enterotoxigenic strains of C. perfringens produce it, which further complicates the study of the reservoirs of this important pathogen. The objectives of the current study were to validate the ability of a digoxigenin-labeled probe to detect the C. perfringens cpe gene and to validate the use of either a filtration or a direct plating approach, combined with colony hybridization to detect enterotoxigenic C. perfringens. Pure DNA and pure colonies of enterotoxigenic C. perfringens and broiler chicken carcass rinsate samples were subjected to colony hybridization. The results showed that the synthesized DNA probe can detect the cpe gene from both DNA and pure colonies of enterotoxigenic C. perfringens, and from colonies grown from carcass rinsates artificially contaminated with enterotoxigenic C. perfringens. Our study suggests that this isolation method is a promising tool for a better understanding of the epidemiology of this zoonotic pathogen.

Retracted: Design of College Scheduling Algorithm Based on Improved Genetic Ant Colony Hybrid Optimization

Retracted: Design of College Scheduling Algorithm Based on Improved Genetic Ant Colony Hybrid Optimization

High-Dimensional Feature Selection Based on Improved Binary Ant Colony Optimization Combined with Hybrid Rice Optimization Algorithm

In the realm of high-dimensional data analysis, numerous fields stand to benefit from its applications, including the biological and medical sectors that are crucial for computer-aided disease diagnosis and prediction systems. However, the presence of a significant number of redundant or irrelevant features can adversely affect system accuracy and real-time diagnosis efficiency. To mitigate this issue, this paper proposes two innovative wrapper feature selection (FS) methods that integrate the ant colony optimization (ACO) algorithm and hybrid rice optimization (HRO). HRO is a recently developed metaheuristic that mimics the breeding process of the three-line hybrid rice, which is yet to be thoroughly explored in the context of solving high-dimensional FS problems. In the first hybridization, ACO is embedded as an evolutionary operator within HRO and updated alternately with it. In the second form of hybridization, two subpopulations evolve independently, sharing the local search results to assist individual updating. In the initial stage preceding hybridization, a problem-oriented heuristic factor assignment strategy based on the importance of the knee point feature is introduced to enhance the global search capability of ACO in identifying the smallest and most representative features. The performance of the proposed algorithms is evaluated on fourteen high-dimensional biomedical datasets and compared with other recently advanced FS methods. Experimental results suggest that the proposed methods are efficient and computationally robust, exhibiting superior performance compared to the other algorithms involved in this study.

Modelling of Subject Scheduling Systems Using Hybrid Artificial Bee Colony Algorithm

A common schedule problem found in colleges is the positioning of courses in a certain space and time. This placement process often encounters barriers that must be met so that there is no imbalance in the school schedule. One of the problems that often arise is the placement of class capacity that does not match the course requirements. In this study, the researchers used the Artificial Bee Colony Hybrid Algorithm (HABC) to construct course schedules efficiently at the college. The objective of the research was to develop a course scheduling system using the HABC algorithm by combining the Engineering of Artificial Bee Colony (ABC) and genetic algoritms, especially on the crossover process to better address the schedule problems. The research procedure used is to design and implement a course scheduling system using the Hybrid ABC algorithm. The results of the research demonstrate that the Hybrid ABC algorithm is effective in generating optimal course schedule schedules, in line with time limits, room needs, and lecturer requirements and can automate course schedule processes, saving time and resources, while ensuring optimal schedules.

Environmental Factors Influencing Occurrence of Vibrio parahaemolyticus and Vibrio vulnificus.

Incidence of vibriosis is rising globally, with evidence that changing climatic conditions are influencing environmental factors that enhance growth of pathogenic Vibrio spp. in aquatic ecosystems. To determine the impact of environmental factors on occurrence of pathogenic Vibrio spp., samples were collected in the Chesapeake Bay, Maryland, during 2009 to 2012 and 2019 to 2022. Genetic markers for Vibrio vulnificus (vvhA) and Vibrio parahaemolyticus (tlh, tdh, and trh) were enumerated by direct plating and DNA colony hybridization. Results confirmed seasonality and environmental parameters as predictors. Water temperature showed a linear correlation with vvhA and tlh, and two critical thresholds were observed, an initial increase in detectable numbers (>15°C) and a second increase when maximum counts were recorded (>25°C). Temperature and pathogenic V. parahaemolyticus (tdh and trh) were not strongly correlated; however, the evidence showed that these organisms persist in oyster and sediment at colder temperatures. Salinity (10 to 15 ppt), total chlorophyll a (5 to 25 μg/L), dissolved oxygen (5 to 10 mg/L), and pH (8) were associated with increased abundance of vvhA and tlh. Importantly, a long-term increase in Vibrio spp. numbers was observed in water samples between the two collection periods, specifically at Tangier Sound (lower bay), with the evidence suggesting an extended seasonality for these bacteria in the area. Notably, tlh showed a mean positive increase that was ca. 3-fold overall, with the most significant increase observed during the fall. In conclusion, vibriosis continues to be a risk in the Chesapeake Bay region. A predictive intelligence system to assist decision makers, with respect to climate and human health, is warranted. IMPORTANCE The genus Vibrio includes pathogenic species that are naturally occurring in marine and estuarine environments globally. Routine monitoring for Vibrio species and environmental parameters influencing their incidence is critical to provide a warning system for the public when the risk of infection is high. In this study, occurrence of Vibrio parahaemolyticus and Vibrio vulnificus, both potential human pathogens, in Chesapeake Bay water, oysters, and sediment samples collected over a 13-year period was analyzed. The results provide a confirmation of environmental predictors for these bacteria, notably temperature, salinity, and total chlorophyll a, and their seasonality of occurrence. New findings refine environmental parameter thresholds of culturable Vibrio species and document a long-term increase in Vibrio populations in the Chesapeake Bay. This study provides a valuable foundation for development of predicative risk intelligence models for Vibrio incidence during climate change.

Medical emergency supplies dispatching vehicle path optimization based on demand urgency

Abstract In recent years, the frequency of disasters, natural disasters, and other emergencies has been increasing worldwide. When an emergency occurs, effective rescue measures must be taken promptly to minimize the loss of life and property. In the process of rescuing casualties, a large amount of medical emergency supplies are urgently needed. Therefore, it is of great practical significance to study the vehicle path problem in medical emergency supplies dispatching. In this paper, we take the vehicle path optimization problem of medical emergency supplies dispatching considering the demand urgency as the research object, design the improved cuckoo-ant colony hybrid algorithm to solve the model based on the urgency analysis, and compare it with the ant colony algorithm and cuckoo algorithm to verify the efficiency of the designed algorithm. The results show that compared with the vehicle path scheme without considering the demand urgency, the path optimization scheme considering the demand urgency is more expensive and requires a small increase in time, but improves the efficiency and rationality of medical emergency supplies dispatching. The study of the emergency vehicle path problem can improve the weaknesses in the current emergency rescue decision-making, so that the emergency rescue work can be done quickly, economically, and reasonably, and provide a theoretical basis and suggestions for the emergency management department when making decisions.

Research on Ship Thrust Distribution Based on Adaptive Particle Swarm Bee Colony Hybrid Algorithm

Aiming at the thrust distribution problem of nonlinear constraint in ship dynamic positioning system, an adaptive hybrid particle swarm optimization and bee colony algorithm was proposed, which was based on particle swarm optimization and bee colony algorithm, and introduced by the adaptive idea and bidirectional stochastic optimization mechanism. The optimization objective function with the minimum energy consumption and the minimum error of the thruster system was established by fully considering the thrust feasible region, the change rate of thrust and rudder angle and other constraints. Simulation results show that this algorithm can solve the thrust distribution problem reasonably and efficiently.

Evaluation of Alternative Colony Hybridization Methods for Pathogenic Vibrios

Vibrios, such as Vibrio parahaemolyticus, are naturally occurring halophilic bacteria that are a major cause of foodborne illness. Because of their autochthonous nature, managing vibrio levels in marine and estuarine environments is impossible. Instead, it is crucial to reliably enumerate their abundance to minimize human exposure. One method of achieving this is the direct plating/colony hybridization (DP/CH) method, which has been used to efficiently quantify pathogenic vibrios in oysters and other seafood products. Although successful, the method relies on proprietary resources. We examined alternative approaches, assessed the influence of the reagent suppliers' source on enumeration accuracy, and made experimental adjustments that maximized efficiency, sensitivity, and specificity. We report here that in-house conjugation via Cell Mosaic is a viable alternative to the previously available sole-source distributor of the alkaline phosphatase-conjugated probes used to enumerate vibrios in oysters. We also report that milk was a viable alternative as a blocking reagent, pH must be eight, an orbital shaker was a viable alternative to a water bath, and narrow polypropylene containers were a viable alternative to Whirl-Pak bags. These modifications will be crucial to scientists enumerating vibrios and other pathogens in food products.

An improved genetic algorithm for solving the helicopter routing problem with time window in post-disaster rescue.

The vehicle routing problem (VRP) is a highly significant and extensively studied issue in post-disaster rescue. In recent years, there has been widespread utilization of helicopters for post-disaster rescue. However, efficiently dispatching helicopters to reach rescue sites in post-disaster rescue is a challenge. To address this issue, this study models the issue of dispatching helicopters as a specific variant of the VRP with time window (VRPTW). Considering that the VRPTW is an NP-hard problem, the genetic algorithm (GA) as one of the prominent evolutionary algorithms with robust optimization capabilities, is a good candidate to deal with this issue. In this study, an improved GA with a local search strategy and global search strategy is proposed. To begin, a cooperative initialization strategy is proposed to generate an initial population with high quality and diversity. Subsequently, a local search strategy is presented to improve the exploitation ability. Additionally, a global search strategy is embedded to enhance the global search performance. Finally, 56 instances extended from Solomon instances are utilized for conducting simulation tests. The simulation results indicate that the average relative percentage increase (RPI) of the distance travelled by helicopters as obtained by the proposed algorithm is 0.178, 0.027, 0.075 and 0.041 times smaller than the average RPIs obtained by the tabu search algorithm, ant colony optimization algorithm, hybrid GA and simulated annealing algorithm, respectively. Simulation results reveal that the proposed algorithm is more efficient and effective for solving the VRPTW to reduce the driving distance of the helicopters in post-disaster rescue.

English teaching resources recommendation based on improved Ant colony optimization algorithms

To achieve the goal of exploiting all the advantages and avoiding the disadvantages, this paper presents a genetic algorithm-based development to integrate the spider colony algorithm for teaching optimization of English data recommendation methods. This algorithm first takes advantage of the genetic algorithm to extract the pheromone required by the ant colony algorithm, and then obtains a good solution through the fast and comprehensive integration mechanism of the global optimization of the ant colony algorithm. Therefore, combining the two algorithms can increase the processing time and efficiency. According to the experimental results, compared to using the genetic algorithm or the ant colony algorithm, the violation of the soft parameters of the training data based on the genetic ant hybrid algorithm is reduced to a minimum, and the feasibility and quality of the training data are good. alone. The power of our algorithm is directly proportional to the number of assignments. The security of the algorithm seems to be stable when the number of scales reaches one. For the same scale, the power of the hybrid genetic colony algorithm is the highest, the ant colony algorithm is the second, and the genetic algorithm is the last. When the class setting is 500, when the motor reaches 300, the algorithm stops working and the test is repeated 10 times. The genetic ant colony hybrid algorithm needs the shortest time to reach the fitness value. Conclusion: this algorithm is much better than genetic algorithm or spider colony algorithm.

Writing Back to the Imperial Canon : Hybridity and Resistance in Aimé Césaire’s A Tempest

Négritude, as the social movement initiated by Francophone colonial writers and intellectuals in the 1930s, sought to debunk the longstanding myth of ‘blackness’ that had been invented and propagated in order to justify the histories of slave trade and colonial rule. Though Léopold Sédar Senghor and Aimé Césaire, the co-founders of Négritude, shared the agenda of decolonizing the mind and rebuilding black consciousness, their means to achieve it were not identical. While one had nostalgia for a ‘pure’ and ‘authentic’ African culture of the pre-colonial past, the other accepted the given condition of colonial hybridity as a point of departure for anticolonial resistance. This essay examines how Césaire put his political theory of Négritude into literary practice in A Tempest, an adaptation of William Shakespeare’s colonial romance The Tempest. For Césaire, Shakespeare was not simply the Bard of English literature but also an icon of Western cultural hegemony that served to rationalize the unequal power relations between colonizer and colonized. Césaire’s writing back to the representative Western canon from an Afro-Caribbean perspective had both aesthetic and ideological purpose. By making ‘the imperial canon’ a site of intercultural dialogue, by using the English text and the French language in the non-European context, Césaire suggested that appropriation as well as rejection can be a means of cultural resistance. Further, Césaire’s challenging experiment in A Tempest provided a viable model of cultural hybridity for his succeeding postcolonial critics like Frants Fanon, Edward Said, and Homi Bhabha.

Development of Recombinase Polymerase Amplification Combined with Lateral Flow Dipstick Assay To Detect Hemolysin Gene of Vibrio vulnificus in Oysters

Vibrio vulnificus inhabits estuarine waters around the world and can cause severe infections in people who eat contaminated raw or undercooked oysters. Although current detection methods are sensitive and specific, there are continuous demands for the development of rapid and accurate methods without a trained operator and equipment in the field conditions. Herein, we developed a simple and rapid method by detecting the hemolysin (vvh) gene of V. vulnificus by using recombinase polymerase amplification (RPA) combined with a lateral flow dipstick (LFD). The RPA-LFD could detect 100 fg of DNA (P < 0.05) and 20 CFU of V. vulnificus per reaction within 30 min (P < 0.01) and showed the result with incubation temperature ranges from 30 to 45°C (P < 0.001). The test was specific only to V. vulnificus and was not responsive to 10 other closely related Vibrio species and 18 foodborne pathogenic bacteria. Compared with PCR, quantitative PCR, and colony hybridization assays by using naturally contaminated oyster samples, our RPA-LFD showed the same detection ability as quantitative PCR assay. Therefore, the current RPA-LFD would be a valuable tool to detect V. vulnificus in oysters, especially in field conditions.