Development Of Control Strategies Research Articles

Dynamic Response Control Strategy for Parallel Hybrid Ships Based on PMP-HMPC

With increasingly stringent emission regulations, various clean fuel engines, electric propulsion systems, and renewable energy sources have been demonstratively applied in marine power systems. The development of control strategies that can effectively and efficiently coordinate the operation of multiple energy sources has become a key research focus. This study uses a modular modeling method to establish a system simulation model for a parallel hybrid ship with a natural gas engine (NGE) as the prime mover, and designs an energy management control strategy that can run in real time. The strategy is based on Pontryagin’s minimum principle (PMP) for power allocation, and is supplemented by a hybrid model predictive control (HMPC) method for speed-tracking control of the power system. Finally, the designed strategy is evaluated. Through simulation and hardware-in-the-loop (HIL) experimental validation, results compared with the Rule-based strategy indicate that under the given conditions, the SOC final value deviation from the initial value is reduced from 11.5% (in the reference strategy) to 0.39%. The system speed error integral is significantly lower at 39.06, compared to 2264.67 in the reference strategy. While gas consumption increased slightly by 2.4%, emissions were reduced by 3.2%.

Exploring the genomic basis of Mpox virus-host transmission and pathogenesis.

Mpox disease, caused by the monkeypox virus (MPXV), was recently classified as a public health emergency of international concern due to its high lethality and pandemic potential. MPXV is a zoonotic disease that emerged and is primarily spread by small rodents. Historically, it was considered mainly zoonotic and not likely to sustain human-to-human transmission. However, the worldwide outbreak of Clade IIb MPXV from 2020 to 2022 and ongoing Clade I MPXV epidemics in the Democratic Republic of the Congo and surrounding areas are a warning that human-adapted MPXVs will continually arise. Understanding the viral genetic determinants of host range, pathogenesis, and immune evasion is imperative for developing control strategies and predicting the future of Mpox. Here, we delve into the MPXV genome to detail genes involved in host immune evasion strategies for this zoonotic rodent-borne and human-circulating virus. We compare MPXV gene content to related Orthopoxviruses, which have narrow host ranges, to identify potential genes involved in species-specific pathogenesis and host tropism. In addition, we cover the key virulence factor differences that distinguish the MPXV clade lineages. Finally, we dissect how genomic reduction of Orthopoxviruses, through various molecular mechanisms, is contributing to the generation of novel MPXV lineages with increased human adaptation. This review aims to highlight gene content that defines the MPXV species, MPXV clades, and novel MPXV lineages that have culminated in this virus being elevated to a public health emergency of national concern.

Using ecological niches to determine potential habitat suitability for Psacothea hilaris (Coleoptera: Cerambycidae) and its natural enemies in China under future climates.

Climate change impacts the distribution of pests and its natural enemies, prompting this study to investigate the dynamics and shifts in distribution under current and future climate conditions. The spatial pattern of Psacothea hilaris (Pascoe) (Coleoptera: Cerambycidae) in China was analyzed, and the MaxEnt model was optimized to predict the potential geographic distribution of P. hilaris and its two natural enemies (Dastarcus helophoroides (Fairmaire) (Coleoptera: Bothrideridae) and Dendrocopos major (Linnaeus) (Piciformes: Picidae)) in China, to further analyze the key environmental factors affecting the survival of P. hilaris and its natural enemies, and to determine the potential of using D. helophoroides and D. major as natural enemies to control P. hilaris. The results showed that the suitable ranges of P. hilaris and natural enemies are expanding under the influence of climate change, and both have migrated to higher latitudes. The potential ranges of D. helophoroides, D. major, and P. hilaris are highly similar. It is noteworthy that the potential range of D. helophoroides completely covers the potential range of P. hilaris. This indicates that D. helophoroides and D. major can be employed as biological control agents to manage P. hilaris populations. This study provides a theoretical framework and empirical evidence for the development of early warning and green control strategies for P. hilaris.

The Application of PID Control in DC Motor Control Systems

Abstract. The application of Proportional-Integral-Derivative (PID) control in direct current (DC) motor control systems is essential for achieving high levels of precision and reliability in both industrial and robotic applications. As DC motors are widely utilized in environments requiring accurate speed and torque control, this study seeks to address common challenges such as overshoot, instability, and sluggish response times that can compromise performance. The research is centered on the development and implementation of a PID-based control strategy using MATLAB/Simulink as the primary tool for simulation and testing. The study involves detailed simulation models and experimental validation, using data collected from controlled lab environments to evaluate the effectiveness of various tuning methods. These methods include adjusting the proportional, integral, and derivative gains to optimize motor responsiveness and system stability. The results indicate that with appropriate tuning, PID controllers can significantly enhance DC motor performance, leading to reduced overshoot, faster response times, and greater overall system reliability. The research concludes that adaptive PID control strategies, which dynamically adjust parameters in response to changing operating conditions, provide a robust solution for improving DC motor control in complex, dynamic, and nonlinear environments. This study lays the groundwork for future innovations in automation and precision-driven industries, offering insights that could be applied across a wide range of applications.

First Report of Powdery Mildew Caused by Golovinomyces ambrosiae on Symphyotrichum subulatum in China.

Symphyotrichum subulatum (Michx.) G. L. Nesom (syn. Aster subulatus), an annual herb in the Asteraceae family, is native to North America. Nowadays, it has become an invasive weed in several provinces of China, including Jiangsu, Zhejiang, and Sichuan (Li and Xie, 2002). Despite being invasive, this species holds significance in Chinese medicine, where it is used for the external treatment of eczema and swollen sore poison (Hu, 2020). In June 2023, symptoms of powdery mildew were observed in S. subulatum populations in Deyang and Nanchong, Sichuan Province, China. About 32.73% among 55 surveyed S. subulatum plants showed signs of infection. Symptoms initially appeared as small, scattered white powdery patches on the leaves, which enlarged and coalesced over time. Subsequently, hyphal growth forming extensive conidia covered up to 90% of the leaf area on both surfaces (Fig. S1A, B), and the infected leaves withered and fell off (Fig. S1A). A specimen was archived at China West Normal University (SsPM-ZL). Conidiophores were cylindrical and erect, 66.4 to 183.2 µm (avg. 108.2±40.8 μm) in length (n=30) (Fig. S1C). Conidia, produced singly, were ellipsoid-ovoid to nearly cylindrical, measuring 29.5 to 36.7 μm in length (avg. 32.9±2.6 μm) and 16.0 to 19.9 μm in width (avg. 17.4±1.3 μm), lacking distinct fibrosin bodies (n=30) (Fig. S1D). Under a scanning electron microscope, turgid conidia displayed reticulate wrinkles on the surface, with gentle contractions or bulges at both poles (Fig. S1E, F). Based on these characteristics, the powdery mildew fungus was consistent with the genus Golovinomyces (Bradshaw et al. 2022a). To confirm the identity of the causal fungus of specimen (SsPM-ZL), the calmodulin (CAM), RNA polymerase II subunit (RPB2), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glutamine synthetase (GS), and the internal transcribed spacer (ITS) were amplified using PMCAMF/R, PMRPB2F/R, PMGAPDH1/3R, PMGSF/R, and PM5/ITS4 primers (Bradshaw et al. 2022b), and deposited in GenBank (CAM: OR761878; RPB2: OR761881; GAPDH: OR761879; GS: OR761880; ITS: OR758452). BLAST analysis showed 99 to 100% identity with the sequences of Golovinomyces ambrosiae (FH00941234) for CAM (ON101658, 99.65%), RPB2 (ON119165, 100%), GS (ON075690, 99.78%), and ITS (ON073876, 99.47%). Phylogenetic analysis was performed in MEGAX with maximum likelihood method (Kumar et al. 2016) and clustered SsPM-ZL into the G. ambrosiae clade with a 100% bootstrap support value based on the concatenated sequences of CAM, RPB2, GAPDH, GS and ITS (Fig. S2). Combining morphological and phylogenetic analyses, SsPM-ZL was identified as Golovinomyces ambrosiae. To evaluate pathogenicity, leaves of 3 healthy potted S. subulatum plants (3 leaves per plant) were inoculated by gently pressing them with diseased leaves, while 3 non-contact plants were used as control. Plants in two groups were incubated in separate greenhouses maintained at 27±1°C, with a photoperiod of 14 hours and a relative humidity of 80%. After 7 days, the inoculated plants exhibited symptoms of powdery mildew (Fig. S1H, J), while the control plants remained asymptomatic (Fig. S1G, I). Morphological characteristics of the artificially induced powdery mildew were consistent with those on naturally infected plants. Powdery mildew caused by G. ambrosiae has been reported affecting Helianthus tuberosus (Huang et al. 2017) and Bidens pilosa (Mukhtar et al. 2022) in China. To our knowledge, this is the first report of powdery mildew caused by G. ambrosiae on S. subulatum in China. Our finding will provide the fundamental knowledge for future powdery mildew diagnosis and the development of potential control strategies.

Efficacy of L-arabinose in managing cucumber Fusarium wilt and the underlying mechanism of action.

Cucumber Fusarium wilt (CFW), triggered by Fusarium oxysporum f. sp. cucumerinum, leads to substantial yield reductions in global cucumber (Cucumis sativus L.) production. Common management strategies for CFW include soil fumigation, grafting, and crop rotation. However, these methods have limitations regarding safety and efficacy stability, necessitating the development of new, cost-effective, and eco-friendly control strategies. Our prior research demonstrated that L-arabinose, an inexpensive and safe sugar commonly used in food and beverages, effectively suppressed bacterial wilt in tomatoes. This study explores the potential of L-arabinose in managing CFW and investigates its mechanism of action. Soil applications of L-arabinose, ranging from 0.00001 to 0.01%, effectively suppressed CFW. The most significant suppressive effect was observed at 0.01%, reducing the disease severity index by 67.5% compared to the control treatment. Microscopic examination of transverse root sections showed that pathogen hyphae colonized the epidermis but seldom penetrated the cortical layer of roots in L-arabinose-treated seedlings. In contrast, the entire root tissue of control seedlings was colonized by the pathogen. Quantitative real-time PCR revealed a significant increase in the expression of defense-related genes dependent on salicylic acid, jasmonic acid, and ethylene in L-arabinose-treated plants compared to control plants, 6 and 10 days post pathogen inoculation. This study demonstrated that soil application of L-arabinose can effectively suppress CFW by priming root tissues for multiple defense signaling pathways. Therefore, L-arabinose holds potential as a new fungicide for managing CFW. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Superior target genes and pathways for RNAi-mediated pest control revealed by genome-wide analysis in the beetle Tribolium castaneum.

An increasing human population, the emergence of resistances against pesticides and their potential impact on the environment call for the development of new eco-friendly pest control strategies. RNA interference (RNAi)-based pesticides have emerged as a new option with the first products entering the market. Essentially, double-stranded RNAs targeting essential genes of pests are either expressed in the plants or sprayed on their surface. Upon feeding, pests mount an RNAi response and die. However, it has remained unclear whether RNAi-based insecticides should target the same pathways as classic pesticides or whether the different mode-of-action would favor other processes. Moreover, there is no consensus on the best genes to be targeted. We performed a genome-wide screen in the red flour beetle to identify 905 RNAi target genes. Based on a validation screen and clustering, we identified the 192 most effective target genes in that species. The transfer to oral application in other beetle pests revealed a list of 34 superior target genes, which are an excellent starting point for application in other pests. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses of our genome-wide dataset revealed that genes with high efficacy belonged mainly to basic cellular processes such as gene expression and protein homeostasis - processes not targeted by classic insecticides. Our work revealed the best target genes and target processes for RNAi-based pest control and we propose a procedure to transfer our short list of superior target genes to other pests. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Immune Suppression and Rapid Invasion of Nile Tilapia Gills Following an Acute Challenge by Flavobacterium davisii

Flavobacterium davisii is one of the causative agents of columnaris disease, significantly impacting Nile tilapia aquaculture. This study examines the invasion and immune evasion mechanisms of a highly virulent F. davisii strain through transcriptomic profiling of tilapia gills following acute immersion. We identified 8192 differentially expressed genes (DEGs) at 2 h, 6 h, and 12 h post-infection. They are enriched in pathways related to oxidative stress, immune suppression, tissue necrosis, and bacterial infection. Notably, early overexpression of rhamnose-binding lectin and mucin genes facilitated bacterial adhesion. Key immune genes, including those encoding major histocompatibility complex (MHC), immunoglobulins (Ig), Toll-like receptors (TLRs), and chemokines, were downregulated, indicating immune suppression. Conversely, immune evasion genes such as Fc receptor-like (FcRL) and programmed death-ligand 1 (PDL1) were upregulated, along with genes associated with reactive oxygen species (ROS) production, leading to increased tissue damage. Additionally, the upregulation of fibroblast growth factor and collagen genes suggested active tissue repair. In conclusion, F. davisii rapidly invades its host by enhancing adhesion to gill tissues, suppressing immune function, and inducing tissue damage. These findings enhance our understanding of F. davisii infection mechanisms and support the future breeding of disease-resistant tilapia and the development of sustainable control strategies.

Molecular characterization of rabies virus from wild and domestic animals in the Sultanate of Oman.

Rabies virus (RV) is endemic in some Arabian countries. However, it is difficult to control RV without understanding the epidemiological evolution of endemic RV isolates. The current study aimed to characterize RV from domestic and wild animal clinical cases in Oman. Twelve brain samples from domestic (Five camels, three goats and one cattle) and wild animals (Two foxes and one honey badger) were investigated from different locations in Oman between 2017 and 2020. All samples were confirmed by RV nucleoprotein (N) gene-specific primers. Seven out of the 12 amplified samples were successfully sequenced and subjected to sequence and phylogenetic analysis. The detected RVs shared an in-between 96.8%-98.7% and 96.9%-99% nucleotide and amino acid identities, respectively. However, the wild animal RVs shared only 92.6%-93.9% and 95.9% nucleotide and amino acid identities with the domestic animal RVs, respectively. Negri bodies were detected histologically in six brain samples from camels (n = 3), goats (n = 1) and foxes (n = 2). The RVs from domestic animals shared 97%-98.7% and 98%-100% nucleotide and amino acid identities with the previously published fox RVs from Oman and Gulf countries. Phylogenetic analysis suggested that all RV sequences belong to a distinct clade confined to the previously reported clade V within the Middle Eastern Cluster. As indicated by the analysis of RVs from different locations between 2017 and 2020, a genetic variant isolated to the Gulf region may exist within the Middle East clade. Moreover, it appears that new RV lineages are emerging rapidly within this region. Therefore, a comprehensive genomic and phylogenetic analysis of the circulating RV is important for the development of future prevention and control strategies.

Time-dependent corrosion behavior of EH36 steel caused by Pseudomonas aeruginosa based on big data monitoring technology

Marine microbial corrosion poses a significant threat to the safe service of marine engineering equipment. Previous studies have often failed to thoroughly analyze the continuous and prolonged microbial corrosion process, resulting in an incomplete understanding of microbial corrosion mechanisms involved at various stages and the development of ineffective control strategies. This study employed a corrosion big data online real-time monitoring technique to investigate the time-dependent corrosion behavior of EH36 steel caused by Pseudomonas aeruginosa in aerobic environments over a 30-d incubation period. It was found that P. aeruginosa accelerated the corrosion of EH36 steel in the early stages by enhancing the cathodic oxygen reduction process. As oxygen levels declined, P. aeruginosa transitioned from aerobic to anaerobic respiration, promoting corrosion through biocatalytic nitrate reduction. In the later stages, the reduction in sessile cell counts, extreme low oxygen concentration, and dense surface film increased the charge transfer and film resistances, ultimately leading to corrosion inhibition. The weight loss and electrochemical data confirmed the effectiveness of the big data monitoring technique in investigating microbial corrosion, which provides new approaches for diagnosing and preventing microbial corrosion.

Light-duty gasoline vehicle emission deterioration insights from large-scale inspection/maintenance data: The synergistic impact of usage characteristics

Accurately estimating vehicle emissions is crucial for effective air quality management. As key data for emission inventory construction, emission factors (EFs) are influenced by vehicle usage characteristics and experience deterioration. Current deterioration models often employ single-factor approaches based on vehicle age or accumulated mileage, which fail to capture the effects of varying usage intensities within the same mileage or age intervals. This study addressed this limitation by developing a novel emission deterioration model that incorporates multi-dimensional usage characteristics and that utilizes a large-scale inspection and maintenance (I/M) dataset for light-duty gasoline vehicles (LDGVs). The modeling results reveal distinct deterioration patterns for different pollutants and highlight the synergistic effects of the usage duration and intensity: natural aging significantly impacts HC and NOx emissions, while CO emissions are more strongly affected by intensive use. Specifically, China V LDGVs that were driven 4 × 104 km/yr exhibited HC, CO, and NOx deterioration rates per mile that were approximately 4.1 % lower, 10.3 % higher, and 1.1 % higher, respectively, than those of vehicles driven 2 × 104 km/yr as the mileage increased from 5 × 104 km to 10 × 104 km. By leveraging timely emission data and explicitly accounting for usage intensity, this study corrected biases in local emission estimates by 5–85 % with respect to estimates from commonly used models. This framework enables the development of more effective control strategies and refinements to policy evaluations in megacities with I/M programs.

Evolutionary dynamic of the coupled awareness-epidemic networks with higher-order structure

Mitigating epidemic spreading and outbreaks is crucial to reducing their significant impacts on people’s lives. Although research has begun to consider the impact of information networks on disease transmission in recent years, most studies have not fully considered the high-order characteristics in network structures. To better capture the dynamics of epidemic spreading and comprehensively understand and predict epidemic transmission patterns, a model of epidemic spreading in a coupled awareness-epidemic model, considering higher-order structures, is proposed. Extensive simulations on real and synthetic structured networks show that information networks influence the spread on physical contact networks by altering individual behaviors, leading to a transition from bistability to a single stable state induced by higher-order structures. Through theoretical analysis, it is proved that the corresponding conclusion is that as the information influence value (an indicator that measures the impact of information networks on physical contact networks) decreases, the impact of higher-order structures on the system’s dynamic behavior gradually weakens. This leads to the disappearance of the bistable phenomenon originally caused by the presence of higher-order structures, and the system transitions from a bistable state to a single stable state. This transition is accompanied by an increase in the threshold for epidemic outbreaks and a decrease in the stable infection density. This work contributes to a deeper understanding of the influence of information on epidemic dynamics, providing important theoretical guidance for the future development of more effective prevention and control strategies.

Insights into genomic sequence diversity of the SAG surface antigen superfamily in geographically diverse Eimeria tenella isolates

Eimeria tenella is among the protozoan parasites that cause the infectious disease coccidiosis in chickens, incurring huge economic losses to the global poultry industry. Surface antigens (EtSAGs) involved in host-parasite interaction are potential targets for control strategies. However, the occurrence of genetic diversity for EtSAGs in field populations is unknown, as is the risk of such diversity to the efficacy of EtSAG-based control approaches. Here, the extent of EtSAG genetic diversity and its implications on protein structure and function is assessed. Eighty-seven full-length EtSAG genomic sequences were identified from E. tenella genome assemblies of isolates sampled from continents including North America (United States), Europe (United Kingdom), Asia (Malaysia and Japan) and Africa (Nigeria). Limited diversity was observed in the EtSAG sequences. However, distinctive patterns of polymorphism were identified between EtSAG subfamilies, suggesting functional differences among these antigen families. Polymorphisms were sparsely distributed across isolates, with a small number of variants exclusive to specific geographical regions. These findings enhance our understanding of EtSAGs, particularly in elucidating functional differences among the antigens that could inform the development of more effective and long-lasting anticoccidial control strategies.

Rhythms in insect olfactory systems: underlying mechanisms and outstanding questions.

Olfaction is a critical sensory modality for invertebrates, and it mediates a wide range of behaviors and physiological processes. Like most living organisms, insects live in rhythmic environments: the succession of nights and days is accompanied by cyclic variations in light intensity and temperature, as well as in the availability of resources and the activity of predators. Responding to olfactory cues in the proper temporal context is thus highly adaptive and allows for the efficient allocation of energy resources. Given the agricultural or epidemiological importance of some insect species, understanding olfactory rhythms is critical for the development of effective control strategies. Although the vinegar fly Drosophila melanogaster has been a classical model for the study of olfaction and circadian rhythms, recent studies focusing on non-model species have expanded our understanding of insect olfactory rhythms. Additionally, recent evidence revealing receptor co-expression by sensory neurons has brought about an ongoing paradigm shift in our understanding of insect olfaction, making it timely to review the state of our knowledge on olfactory rhythms and identify critical future directions for the field. In this Review, we discuss the multiple biological scales at which insect olfactory rhythms are being analyzed, and identify outstanding questions.

Fixed-time adaptive sliding mode-based trajectory tracking control for Wheeled Mobile Robot: Theoretical development and real-time implementation

Wheeled mobile robots (WMR) are common autonomous systems requiring efficient control methods. This work investigates fixed-time adaptive sliding mode control (FxT-ASMC) for the trajectory tracking task of a WMR subject to disturbances/uncertainties. The developed control strategy seeks to avoid the chattering problem, cope with disturbances when the upper limit is undefined, and enhance the convergence of the system states. Indeed, a new adaptive technique has been developed to effectively handle disturbances, even in the absence of prior knowledge regarding their upper bound. This technique consists in estimating the switching gain for each channel separately. On the other hand, an appropriate design of the reaching law ensures the fixed-time convergence of the sliding variables to zero. Additionally, sliding variables are designed in a way that guarantees the tracking errors will stabilize within a set amount of time. This kind of convergence was demonstrated using Lypunov stability theory. In order to realize the trajectory tracking control structure, the FxT-ASMC system is incorporated with a classical kinematic controller. The efficiency of the suggested control methodology is proven via simulations and practical implementation.

PREVALENCE OF SNAIL VECTORS OF SCHISTOSOMIASIS ALONG ANTAU RIVER, KEFFI, NASARAWA STATE

Schistosomiasis, or bilharzia, is a parasitic disease that affects over 230 million people worldwide, with 700 million at risk, primarily in tropical and subtropical regions, including Nigeria. The disease is transmitted through freshwater snails that host Schistosoma parasites. This study aims to understand the prevalence of snail vectors responsible for transmitting schistosomiasis along Antau River, Keffi, Nasarawas State. A snail sampling survey conducted at three locations - Saura Bridge, Antau Bridge, and Mannu Bridge - along Antau River yielded a total of 216 snails. The distribution showed Saura Bridge with the highest population (96 snails, 44.4%), followed by Antau Bridge (81 snails, 37.5%) and Mannu Bridge (39 snails, 18.1%). Five snail species were identified, with Melanoides spp dominating (173 snails, 80.1%), followed by Anisus spp (28 snails, 13.0%), Planorbarius spp (11 snails, 5.1%), Biomphalaria spp (3 snails, 1.4%), and Physa spp (1 snail, 0.5%). Biomphalaria spp, a known schistosomiasis vector, had a high cercarial shedding rate (66.7%) near Antau Bridge, signaling a potential risk for disease transmission. Physico-chemical analysis revealed favorable snail habitat conditions, with a mean water temperature of 28.0°C, pH of 7.0, and dissolved oxygen ranging from 6.58 mg/L to 6.75 mg/L. The study concludes that while the overall risk of schistosomiasis transmission may be low due to the small population of Biomphalaria spp, targeted vector control measures are necessary, particularly around Antau Bridge, to prevent further transmission of schistosomiasis. Key recommendations include regular monitoring of snail populations, public health education, and targeted mollusciciding to control the Biomphalaria spp population. The findings provide data for the development of control strategies aimed at reducing the burden of schistosomiasis in the region.

Molecular insights into Solanum sisymbriifolium’s resistance against Globodera pallida via RNA-seq

BackgroundThe presence of potato cyst nematodes (PCN) causes a significant risk to potato crops globally, leading to reduced yields and economic losses. While the plant Solanum sisymbriifolium is known for its resistance to PCN and can be used as a trap crop, the molecular mechanisms behind this resistance remain poorly understood. In this study, genes differentially expressed were identified in control and infected plants during the early stages of the S. sisymbriifolium - G. pallida interaction.ResultsGene expression profiles were characterized for two S. sisymbriifolium cultivars, Melody and Sis6001, uninfected and infected by G. pallida. The comparative transcriptome analysis revealed a total of 4,087 and 2,043 differentially expressed genes (DEGs) in response to nematode infection in the cultivars Melody and Sis6001, respectively. Gene ontology (GO) enrichment analysis provided insights into the response of the plant to nematode infection, indicating an activation of the plant metabolism, oxidative stress leading to defence mechanism activation, and modification of the plant cell wall. Genes associated with the jasmonic and salicylic acid pathways were also found to be differentially expressed, suggesting their involvement in the plant’s defence response. In addition, the analysis of NBS-LRR domain-containing transcripts that play an important role in hypersensitive response and programmed cell death led to the identification of ten transcripts that had no annotations from the databases, with emphasis on TRINITY_DN52667_C1_G1, found to be upregulated in both cultivars.ConclusionsThese findings represent an important step towards understanding the molecular basis underlying plant resistance to nematodes and facilitating the development of more effective control strategies against PCN.

First Description of Loreto Virus in Three Culicidae Species from the Atlantic Forest, Bahia, Brazil

Loreto virus (LORV) is an insect-specific virus classified into the proposed taxon Negevirus. It was originally described in Iquitos, Peru, in 1977. Here, we describe three novel LORV genomes obtained from the isolates of three pooled samples of Trichoprosopon digitatum, Aedes (Ochlerotatus) fulvus, and Limatus durhamii collected in Ilhéus—Bahia, 2014. Samples were submitted to RNA sequencing on the Illumina platform to recover the LORV genome. The genomes presented, on average, 81.5% nucleotide identity and 92.6% global amino acid identity with the LORV reference genome (NC_034158). Subsequently, phylogenetic analysis was performed based on a multiple sequence alignment of the concatenated amino acid sequences predicted for the three ORFs of the Negevirus genomes, and the target sequences were clustered within the LORV clade. The taxon Negevirus is in constant expansion of its species content and host range. New data about insect specific negeviruses are important for virus evolution studies, along with those approaching interactions with the hosts and their influence in the transmission of arboviruses. Also, the assessment of these data may allow the development of biologic control strategies for arboviral vectors. This is the original report of the identification of LORV in Brazil, infecting three Culicidae species hosts native to the Atlantic Forest biome.

MaxEnt modeling of Klebsiella pneumoniae: predicting future distribution and evaluating the risk for public health

Klebsiella pneumoniae is a Gram-negative bacterium known for causing infections such as pneumonia, urinary tract infections, and bloodstream infections in humans. Its increasing drug resistance poses a significant threat. Understanding the effects of climate change on this bacterium is crucial to managing its impacts effectively. In this study, we employed MaxEnt modeling to explore the current and future distribution of K. pneumoniae under different climate change scenarios for 2050 and 2070. Our models utilized 280 valid occurrence points and 19 bioclimatic variables, with Mean Annual Temperature and Mean Annual Precipitation being the most influential variables. The models demonstrated high accuracy, with an AUC of 0.889. Our findings revealed that K. pneumoniae has a cosmopolitan distribution, with the highest suitability observed in Southeastern Asia, Central Africa, and Southern Europe. Future predictions indicated an apparent expansion of its range across almost all continents, particularly in the RCP 8.5 2070 scenario. Results have crucial implications for epidemiology, as they enable the identification of current and potential future disease hotspots and geographical patterns. This knowledge can inform the development of effective infection control strategies. Furthermore, it provides valuable insights for decision-makers and policymakers in allocating resources efficiently for medical control and prevention strategies.

Chaos and feasibility analysis of a healthy lifestyle’s sustainability using fractional-order polycystic ovarian syndrome’s effect on infertility

In this study, we developed a fractional-order model for polycystic ovarian syndrome issue transmission in women through four compartments with the Mittag-Leffler kernel. For biological feasibility, we discussed the positivity and boundedness of solutions with fixed point mappings in Banach spaces. Sensitivity analysis is performed using different variables as response functions each time, employing Latin Hyper-cube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) with 200 iterations. Further, the reproductive number is determined for the model’s biological feasibility with an analysis of parameter impact through Matlab software. The solutions are examined for global stability using the Lyapunov function with a first derivative. Chaos Control will use the regulate for linear responses approach to bring the system to stabilize according to its points of equilibrium. Numerical solutions are derived by using a Newton polynomial in the generalized form of the Mittag-Leffler kernel, which illustrates the effect of the fractional operator and parameters involved in the system. Results are also analyzed with different assumptions of parameter values and initial conditions to observe the different impacts of treatment to overcome the risk of infertility in women. Such type of investigation will be useful to investigate the spread of disease as well as helpful in developing control strategies to overcome the risk of problems and best management care pre-detection of the issue and for treatment.