Modeling and Optimization of an Enhanced Soft Sensor for the Fermentation Process of Pichia pastoris.

This paper proposes a novel soft sensor modeling approach, MIC-TCA-INGO-LSSVM, to address the decline in performance of soft sensor models during the fermentation process of Pichia pastoris, caused by changes in working conditions. Initially, the transfer component analysis (TCA) method is utilized to minimize the differences in data distribution across various working conditions. Subsequently, a least squares support vector machine (LSSVM) model is constructed using the dataset adapted by TCA, and strategies for improving the northern goshawk optimization (INGO) algorithm are proposed to optimize the parameters of the LSSVM model. Finally, to further enhance the model's generalization ability and prediction accuracy, considering the transfer of knowledge from multiple-source working conditions, a sub-model weighted ensemble scheme is proposed based on the maximum information coefficient (MIC) algorithm. The proposed soft sensor model is employed to predict cell and product concentrations during the fermentation process of Pichia pastoris. Simulation results indicate that the RMSE of the INGO-LSSVM model in predicting cell and product concentrations is reduced by 47.3% and 42.1%, respectively, compared to the NGO-LSSVM model. Additionally, TCA significantly enhances the model's adaptability when working conditions change. Moreover, the soft sensor model based on TCA and the MIC-weighted ensemble method achieves a reduction of 41.6% and 31.3% in the RMSE for predicting cell and product concentrations, respectively, compared to the single-source condition transfer model TCA-INGO-LSSVM. These results demonstrate the high reliability and predictive performance of the proposed soft sensor method under varying working conditions.

[Application of NGO-BP Neural Network in Battery Life Prediction of Portable Medical Devices].

The development of portable medical devices cannot be separated from safe and efficient batteries. Accurately predicting the remaining life of batteries can greatly improve the reliability of batteries, which is of great significance for portable medical devices. This article focuses on the high dependence of the BP neural network algorithm on initial weights and thresholds, as well as its tendency to fall into local minima. The Northern Goshawk Optimization (NGO) algorithm is used to optimize the BP neural network and to test the 18650 lithium battery data under different ambient temperatures (4, 24, 43°C) typical of medical equipment. The experimental results show that the NGO algorithm can significantly improve the prediction accuracy of the BP neural network under various temperature conditions, achieving accurate and effective prediction of the remaining battery life.

Tool Wear State Identification Based on SVM Optimized by the Improved Northern Goshawk Optimization.

Tool wear condition significantly influences equipment downtime and machining precision, necessitating the exploration of a more accurate tool wear state identification technique. In this paper, the wavelet packet thresholding denoising method is used to process the acquired multi-source signals and extract several signal features. The set of features most relevant to the tool wear state is screened out by the support vector machine recursive feature elimination (SVM-RFE). Utilizing these selected features, we propose a tool wear state identification model, which utilizes an improved northern goshawk optimization (INGO) algorithm to optimize the support vector machine (SVM), hereby referred to as INGO-SVM. The simulation tests reveal that INGO demonstrates superior convergence efficacy and stability. Furthermore, a milling wear experiment confirms that this approach outperforms five other methods in terms of recognition accuracy, achieving a remarkable accuracy rate of 97.9%.

Seasonal Dynamics of Testosterone and Corticosterone in Predatory Birds as Exemplified by the Northern Goshawk (Accipiter gentilis).

Testosterone and corticosterone are steroid hormones that regulate various aspects of bird behavior. The dynamics of blood level of these hormones depending on the stage of the life cycle have been studied in many species. It has been shown for both sexes that the levels of both hormones rise during the breeding season. We have studied changes in the level of these hormones in the northern goshawk (Accipiter gentilis) during a year. This has been the first study of this type on northern goshawk. We collected blood samples from 16 adult northern goshawks kept in pairs in aviaries in the VITASFERA Rare Bird Species Breeding Center. The testosterone level rises in males during the period of lekking and mating (March-June); however, there is no synchronous increase in females. The corticosterone level generally remains high throughout the year in both sexes. Since these are the only data on the northern goshawk, it cannot be concluded whether this is characteristic of the species as a whole or only for captive birds.

Food availability and predation risk, rather than intrinsic attributes, are the main factors shaping the reproductive decisions of a long-lived predator.

Deciphering the causes of variation in reproductive success is a fundamental issue in ecology, as the number of offspring produced is an important driver of individual fitness and population dynamics. Little is known, however, about how different factors interact to drive variation in reproduction, such as whether an individual's response to extrinsic conditions (e.g. food availability or predation) varies according to its intrinsic attributes (e.g. age, previous allocation of resources towards reproduction). We used 29 years of reproductive data from marked female tawny owls and natural variation in food availability (field vole) and predator abundance (northern goshawk) to quantify the extent to which extrinsic and intrinsic factors interact to influence owl reproductive traits (breeding propensity, clutch size and nest abandonment). Extrinsic and intrinsic factors appeared to interact to affect breeding propensity (which accounted for 83% of the variation in owl reproductive success). Breeding propensity increased with vole density, although increasing goshawk abundance reduced the strength of this relationship. Owls became slightly more likely to breed as they aged, although this was only apparent for individuals who had fledged chicks the year before. Owls laid larger clutches when food was more abundant. When owls were breeding in territories less exposed to goshawk predation, 99·5% of all breeding attempts reached the fledging stage. In contrast, the probability of breeding attempts reaching the fledging stage in territories more exposed to goshawk predation depended on the amount of resources an owl had already allocated towards reproduction (averaging 87·7% for owls with clutches of 1-2 eggs compared to 97·5% for owls with clutches of 4-6 eggs). Overall, our results suggested that changes in extrinsic conditions (predominantly food availability, but also predator abundance) had the greatest influence on owl reproduction. In response to deteriorating extrinsic conditions (fewer voles and more goshawks), owls appeared to breed more frequently, but allocated fewer resources per breeding attempt. However, intrinsic attributes also appeared to have a relatively small influence on how an individual responded to variation in extrinsic conditions, which indicates that owl reproductive decisions were shaped by a complex series of extrinsic and intrinsic trade-offs.

When hawks attack: animal-borne video studies of goshawk pursuit and prey-evasion strategies.

Video filmed by a camera mounted on the head of a Northern Goshawk (Accipiter gentilis) was used to study how the raptor used visual guidance to pursue prey and land on perches. A combination of novel image analysis methods and numerical simulations of mathematical pursuit models was used to determine the goshawk's pursuit strategy. The goshawk flew to intercept targets by fixing the prey at a constant visual angle, using classical pursuit for stationary prey, lures or perches, and usually using constant absolute target direction (CATD) for moving prey. Visual fixation was better maintained along the horizontal than vertical direction. In some cases, we observed oscillations in the visual fix on the prey, suggesting that the goshawk used finite-feedback steering. Video filmed from the ground gave similar results. In most cases, it showed goshawks intercepting prey using a trajectory consistent with CATD, then turning rapidly to attack by classical pursuit; in a few cases, it showed them using curving non-CATD trajectories. Analysis of the prey's evasive tactics indicated that only sharp sideways turns caused the goshawk to lose visual fixation on the prey, supporting a sensory basis for the surprising frequency and effectiveness of this tactic found by previous studies. The dynamics of the prey's looming image also suggested that the goshawk used a tau-based interception strategy. We interpret these results in the context of a concise review of pursuit-evasion in biology, and conjecture that some prey deimatic 'startle' displays may exploit tau-based interception.

Climatic conditions cause complex patterns of covariation between demographic traits in a long-lived raptor.

Environmental variation can induce life-history changes that can last over a large part of the lifetime of an organism. If multiple demographic traits are affected, expected changes in climate may influence environmental covariances among traits in a complex manner. Thus, examining the consequences of environmental fluctuations requires that individual information at multiple life stages is available, which is particularly challenging in long-lived species. Here, we analyse how variation in climatic conditions occurring in the year of hatching of female goshawks Accipiter gentilis (L.) affects age-specific variation in demographic traits and lifetime reproductive success (LRS). LRS decreased with increasing temperature in April in the year of hatching, due to lower breeding frequency and shorter reproductive life span. In contrast, the probability for a female to successfully breed was higher in years with a warm April, but lower LRS of the offspring in these years generated a negative covariance among fecundity rates among generations. The mechanism by which climatic conditions generated cohort effects was likely through influencing the quality of the breeding segment of the population in a given year, as the proportion of pigeons in the diet during the breeding period was positively related to annual and LRS, and the diet of adult females that hatched in warm years contained fewer pigeons. Climatic conditions experienced during different stages of individual life histories caused complex patterns of environmental covariance among demographic traits even across generations. Such environmental covariances may either buffer or amplify impacts of climate change on population growth, emphasizing the importance of considering demographic changes during the complete life history of individuals when predicting the effect of climatic change on population dynamics of long-lived species.

Age and sex-selective predation moderate the overall impact of predators.

Currently, there is no general agreement about the extent to which predators impact prey population dynamics and it is often poorly predicted by predation rates and species abundances. This could, in part be caused by variation in the type of selective predation occurring. Notably, if predation is selective on categories of individuals that contribute little to future generations, it may moderate the impact of predation on prey population dynamics. However, despite its prevalence, selective predation has seldom been studied in this context. Using recoveries of ringed tawny owls (Strix aluco) predated by 'superpredators', northern goshawks (Accipiter gentilis) as they colonized the area, we investigated the extent to which predation was sex and age-selective. Predation of juvenile owls was disproportionately high. Amongst adults, predation was strongly biased towards females and predation risk appeared to increase with age. This implies age-selective predation may shape the decline in survival with age, observed in tawny owls. To determine whether selective predation can modulate the overall impact of predation, age-based population matrix models were used to simulate the impact of five different patterns of age-selective predation, including the pattern actually observed in the study site. The overall impact on owl population size varied by up to 50%, depending on the pattern of selective predation. The simulation of the observed pattern of predation had a relatively small impact on population size, close to the least harmful scenario, predation on juveniles only. The actual changes in owl population size and structure observed during goshawk colonization were also analysed. Owl population size and immigration were unrelated to goshawk abundance. However, goshawk abundance appeared to interact with owl food availability to have a delayed effect on recruitment into the population. This study provides strong evidence to suggest that predation of other predators is both age and sex-selective and that selective predation of individuals with a low reproductive value may mitigate the overall impact of predators on prey population dynamics. Consequently, our results highlight how accounting for the type of selective predation occurring is likely to improve future predictions of the overall impact of predation.

Large increase in nest size linked to climate change: an indicator of life history, senescence and condition.

Many animals build extravagant nests that exceed the size required for successful reproduction. Large nests may signal the parenting ability of nest builders suggesting that nests may have a signaling function. In particular, many raptors build very large nests for their body size. We studied nest size in the goshawk Accipiter gentilis, which is a top predator throughout most of the Nearctic. Both males and females build nests, and males provision their females and offspring with food. Nest volume in the goshawk is almost three-fold larger than predicted from their body size. Nest size in the goshawk is highly variable and may reach more than 600 kg for a bird that weighs ca. 1 kg. While 8.5% of nests fell down, smaller nests fell down more often than large nests. There was a hump-shaped relationship between nest volume and female age, with a decline in nest volume late in life, as expected for senescence. Clutch size increased with nest volume. Nest volume increased during 1977-2014 in an accelerating fashion, linked to increasing spring temperature during April, when goshawks build and start reproduction. These findings are consistent with nest size being a reliable signal of parental ability, with large nest size signaling superior parenting ability and senescence, and also indicating climate warming.

Transformer fault diagnosis method based on SMOTE and NGO-GBDT.

In order to improve the accuracy of transformer fault diagnosis and improve the influence of unbalanced samples on the low accuracy of model identification caused by insufficient model training, this paper proposes a transformer fault diagnosis method based on SMOTE and NGO-GBDT. Firstly, the Synthetic Minority Over-sampling Technique (SMOTE) was used to expand the minority samples. Secondly, the non-coding ratio method was used to construct multi-dimensional feature parameters, and the Light Gradient Boosting Machine (LightGBM) feature optimization strategy was introduced to screen the optimal feature subset. Finally, Northern Goshawk Optimization (NGO) algorithm was used to optimize the parameters of Gradient Boosting Decision Tree (GBDT), and then the transformer fault diagnosis was realized. The results show that the proposed method can reduce the misjudgment of minority samples. Compared with other integrated models, the proposed method has high fault identification accuracy, low misjudgment rate and stable performance.

Gas engine CCHP system optimization: An energy, exergy, economic, and environment analysis and optimization based on developed northern goshawk optimization algorithm.

This paper aims to enhance the design and operation of a Combined Cooling, Heating, and Power (CCHP) system utilizing a gas engine as the primary energy source for a residential building in China. An Energy, Exergy, Economic, and Environment (4E) analysis is employed to assess the system's performance and impact based on energy, exergy, economic, and environmental criteria. The effectiveness of the DNGO algorithm is evaluated on a case study site and compared with Northern Goshawk Optimization (NGO) and Genetic Algorithm (GA). The findings demonstrate that the DNGO algorithm identifies the optimal gas engine size of 130 kW. The algorithm's search capabilities are greatly enhanced by this unique blend, surpassing what traditional methods can offer. The DNGO algorithm brings several advantages, including unparalleled energy efficiency, reduced exergy destruction, and a substantial decrease in C O 2 emissions. This not only supports environmental sustainability but also aligns with global standards. Economically, the algorithm enhances the performance of the CCHP system, evident through a reduced payback period and increased annual profit. Additionally, the algorithm's rapid convergence rate allows it to reach the optimal solution faster than its counterparts, making it advantageous for time-sensitive applications. Incorporating innovative methods like chaos theory, the DNGO algorithm effectively avoids local optima, enabling a broader search for the best solution. The utilization of Lévy flight further enhances the algorithm's ability to escape local optima and navigate the search space more efficiently. Additionally, swarm intelligence is employed to simulate the collective behavior of decentralized systems, aiding in problem-solving. This research represents a significant advancement in optimization techniques for CCHP systems and offers a fresh perspective to the field of swarm-based optimization algorithms.

Application of Improved Sparrow Search Algorithm to Path Planning of Mobile Robots.

Path planning is an important research direction in the field of robotics; however, with the advancement of modern science and technology, the study of efficient, stable, and safe path-planning technology has become a realistic need in the field of robotics research. This paper introduces an improved sparrow search algorithm (ISSA) with a fusion strategy to further improve the ability to solve challenging tasks. First, the sparrow population is initialized using circle chaotic mapping to enhance diversity. Second, the location update formula of the northern goshawk is used in the exploration phase to replace the sparrow search algorithm's location update formula in the security situation. This improves the discoverer model's search breadth in the solution space and optimizes the problem-solving efficiency. Third, the algorithm adopts the Lévy flight strategy to improve the global optimization ability, so that the sparrow jumps out of the local optimum in the later stage of iteration. Finally, the adaptive T-distribution mutation strategy enhances the local exploration ability in late iterations, thus improving the sparrow search algorithm's convergence speed. This was applied to the CEC2021 function set and compared with other standard intelligent optimization algorithms to test its performance. In addition, the ISSA was implemented in the path-planning problem of mobile robots. The comparative study shows that the proposed algorithm is superior to the SSA in terms of path length, running time, path optimality, and stability. The results show that the proposed method is more effective, robust, and feasible in mobile robot path planning.

Oral cancer diagnosis based on gated recurrent unit networks optimized by an improved version of Northern Goshawk optimization algorithm.

Oral cancer early diagnosis is a critical task in the field of medical science, and one of the most necessary things is to develop sound and effective strategies for early detection. The current research investigates a new strategy to diagnose an oral cancer based upon combination of effective learning and medical imaging. The current research investigates a new strategy to diagnose an oral cancer using Gated Recurrent Unit (GRU) networks optimized by an improved model of the NGO (Northern Goshawk Optimization) algorithm. The proposed approach has several advantages over existing methods, including its ability to analyze large and complex datasets, its high accuracy, as well as its capacity to detect oral cancer at the very beginning stage. The improved NGO algorithm is utilized to improve the GRU network that helps to improve the performance of the network and increase the accuracy of the diagnosis. The paper describes the proposed approach and evaluates its performance using a dataset of oral cancer patients. The findings of the study demonstrate the efficiency of the suggested approach in accurately diagnosing oral cancer.

Raptors bred in captivity: semen characteristics and assisted reproduction outcome in goshawk (Accipiter gentilis).

Three sexually mature goshawks reared in captivity and imprinted on humans to express reproductive behavior according to the cooperative method were studied for three consecutive breeding seasons to assess the quality of their sperm. The following parameters were analyzed: ejaculate volume and sperm concentration, motility, viability, and morphology. Ejaculate volume, sperm concentration and motility fluctuated along the reproductive season, revealing the greatest quality of the reproductive material at full springtime (i.e., April). Motility of the sperm collected in March strongly reduced with age, contrary to samples collected in April or May. Sperm viability was not influenced by either age or month of collection within each season. Ultrastructural investigations provided information on normal sperm morphology for the first time in this species. The morphological categories of sperm defects in fresh semen, present at low percentages, are also described. Functional analyses (perivitelline membrane assay and artificial inseminations) confirmed the good quality of the semen obtained using the cooperative method. The reported data provide the basis for further studies aimed at developing protocols to improve the outcome of artificial insemination and semen cryopreservation in the goshawk as well as other bird of prey species.

Face expression recognition based on NGO-BILSTM model.

Introduction: Facial expression recognition has always been a hot topic in computer vision and artificial intelligence. In recent years, deep learning models have achieved good results in accurately recognizing facial expressions. BILSTM network is such a model. However, the BILSTM network's performance depends largely on its hyperparameters, which is a challenge for optimization. Methods: In this paper, a Northern Goshawk optimization (NGO) algorithm is proposed to optimize the hyperparameters of BILSTM network for facial expression recognition. The proposed methods were evaluated and compared with other methods on the FER2013, FERplus and RAF-DB datasets, taking into account factors such as cultural background, race and gender. Results: The results show that the recognition accuracy of the model on FER2013 and FERPlus data sets is much higher than that of the traditional VGG16 network. The recognition accuracy is 89.72% on the RAF-DB dataset, which is 5.45, 9.63, 7.36, and 3.18% higher than that of the proposed facial expression recognition algorithms DLP-CNN, gACNN, pACNN, and LDL-ALSG in recent 2 years, respectively. Discussion: In conclusion, NGO algorithm effectively optimized the hyperparameters of BILSTM network, improved the performance of facial expression recognition, and provided a new method for the hyperparameter optimization of BILSTM network for facial expression recognition.

Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems.

The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is easy to fall into local optima during the exploration phase. Inspired by the different search fields of biological organisms with varying flight heights, this paper proposes a reptile search algorithm considering different flight heights. In the exploration phase, introducing the different flight altitude abilities of two animals, the northern goshawk and the African vulture, enables reptiles to have better search horizons, improve their global search ability, and reduce the probability of falling into local optima during the exploration phase. A novel dynamic factor (DF) is proposed in the exploitation phase to improve the algorithm's convergence speed and optimization accuracy. To verify the effectiveness of the proposed algorithm, the test results were compared with ten state-of-the-art (SOTA) algorithms on thirty-three famous test functions. The experimental results show that the proposed algorithm has good performance. In addition, the proposed algorithm and ten SOTA algorithms were applied to three micromachine practical engineering problems, and the experimental results show that the proposed algorithm has good problem-solving ability.

A novel model for runoff prediction based on the ICEEMDAN-NGO-LSTM coupling.

Prediction of runoff trends is a critical topic in hydrological forecasting. Accurate and reliable prediction models are important for the rational use of water resources. This paper proposes a new coupled model, ICEEMDAN-NGO-LSTM, for runoff prediction in the middle reaches of the Huai River. This model combines the excellent nonlinear processing capability of the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm, the perfect optimization strategy of the Northern Goshawk Optimization (NGO) algorithm, and the advantages of the Long Short-Term Memory (LSTM) algorithm in modeling time series data. The results show that the ICEEMDAN-NGO-LSTM model predicts the monthly runoff trend with higher accuracy compared to the actual data variation. The average relative error is 5.95% within 10%, and the Nash Sutcliffe (NS) is 0.9887. These results indicate that the ICEEMDAN-NGO-LSTM coupled model has superior prediction performance and provides a new method for short-term runoff forecasting.

The genome sequence of the northern goshawk, Accipiter gentilis (Linnaeus, 1758).

We present a genome assembly from an individual female Accipiter gentilis (the northern goshawk; Chordata; Aves; Accipitriformes; Accipitridae). The genome sequence is 1,398 megabases in span. The majority of the assembly (99.98%) is scaffolded into 40 chromosomal pseudomolecules, with the W and Z chromosomes assembled. The complete mitochondrial genome was also assembled and is 16.6 kilobases in length.

Feathers as an integrated measure of organohalogen contamination, its dietary sources and corticosterone in nestlings of a terrestrial bird of prey, the northern Goshawk (Accipiter gentilis).

In this study, we evaluated the suitability of body feathers, preen oil and plasma for estimation of organohalogen compound (OHC) exposure in northern goshawk Accipiter gentilis nestlings (n = 37; 14 nests). In addition, body feathers received further examination concerning their potential to provide an integrated assessment of (1) OHC exposure, (2) its dietary sources (carbon sources and trophic position) and (3) adrenal gland response (corticosterone). While tetrabromobisphenol A was not detected in any sample, the presence of polychlorinated biphenyls, organochlorine pesticides, polybrominated diphenyl ethers and hexabromocyclododecane in body feathers (median: 23, 19, 1.6 and 3.5 ng g-1 respectively), plasma (median: 7.5, 6.2, 0.50 and 1.0 ng g-1 ww, respectively) and preen oil (median: 750, 600, 18 and 9.57 ng g-1 ww, respectively) suggests analytical suitability for biomonitoring of major OHCs in the three matrices. Furthermore, strong and significant associations (0.20 ≤ R2 ≤ 0.98; all P < 0.05) among the OHC concentrations in all three tissues showed that body feathers and preen oil reliably reflect circulating plasma OHC levels. Of the dietary proxies, δ13C (carbon source) was the most suitable predictor for variation in feather OHCs concentrations, while no significant relationships between body feather OHCs and δ15N (trophic position) were found. Finally, body feather corticosterone concentrations were not related to variation in OHC concentrations. This is the first study to evaluate feathers of a terrestrial bird of prey as an integrated non-destructive tool to jointly assess nestling ecophysiology and ecotoxicology.

West Nile Virus Lineage 2 Spreads Westwards in Europe and Overwinters in North-Eastern Spain (2017-2020).

West Nile virus lineage 2 (WNV-L2) emerged in Europe in 2004; since then, it has spread across the continent, causing outbreaks in humans and animals. During 2017 and 2020, WNV-L2 was detected and isolated from four northern goshawks in two provinces of Catalonia (north-eastern Spain). In order to characterise the first Spanish WNV-L2 isolates and elucidate the potential overwintering of the virus in this Mediterranean region, complete genome sequencing, phylogenetic analyses, and a study of phenotypic characterisation were performed. Our results showed that these Spanish isolates belonged to the central-southern WNV-L2 clade. In more detail, they were related to the Lombardy cluster that emerged in Italy in 2013 and has been able to spread westwards, causing outbreaks in France (2018) and Spain (2017 and 2020). Phenotypic characterisation performed in vitro showed that these isolates presented characteristics corresponding to strains of moderate to high virulence. All these findings evidence that these WNV-L2 strains have been able to circulate and overwinter in the region, and are pathogenic, at least in northern goshawks, which seem to be very susceptible to WNV infection and may be good indicators of WNV-L2 circulation. Due to the increasing number of human and animal cases in Europe in the last years, this zoonotic flavivirus should be kept under extensive surveillance, following a One-Health approach.