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As the world confronts simultaneous climate and health emergencies, the spread of emerging infectious diseases, particularly arboviruses, underscores the intersection of planetary health, global mobility, and disease risk. Viral pathogens like Oropouche, dengue, and chikungunya are extending their reach, with expanding vector habitats (ticks, mosquitoes, and others) driven by global warming and changing ambient humidity. Arboviral risks due to these unfavorable vector dynamics are exacerbated by voluntary and involuntary migration of people, urbanization with attendant crowding, and suboptimal water, sanitation, and garbage disposal capacities. The poor surveillance and infectious disease control capacities in low-income settings are now exacerbated by public health infrastructure retrenchments in high income nations like the United States. We emphasize the need for urgent, transdisciplinary integration of climate science, epidemiology, human and animal research, and global health security, suggesting bold strategies to prepare for a new era of cross-border microbial threats.

Over the past few years, chaotic image encryption has gained extensive attention. Nevertheless, the current studies on chaotic image encryption still possess certain constraints. To break these constraints, we initially created a two-dimensional enhanced logistic modular map (2D-ELMM) and subsequently devised a chaotic image encryption scheme based on vector-level operations and 2D-ELMM (CIES-DVEM). In contrast to some recent schemes, CIES-DVEM features remarkable advantages in several aspects. Firstly, 2D-ELMM is not only simpler in structure, but its chaotic performance is also significantly better than that of some newly reported chaotic maps. Secondly, the key stream generation process of CIES-DVEM is more practical, and there is no need to replace the secret key or recreate the chaotic sequence when handling different images. Thirdly, the encryption process of CIES-DVEM is dynamic and closely related to plaintext images, enabling it to withstand various attacks more effectively. Finally, CIES-DVEM incorporates lots of vector-level operations, resulting in a highly efficient encryption process. Numerous experiments and analyses indicate that CIES-DVEM not only boasts highly significant advantages in terms of encryption efficiency, but it also surpasses many recent encryption schemes in practicality and security.

Background Accurate vector species identification is essential to distinguish the co-existence of primary and secondary vectors of malaria sustaining transmission in different settings. This evaluation reviews the identity, bionomics, and behaviour of malaria vectors where composition shifted in the forest ecological zone in Mkpat-Enin Local Government Area of Akwa Ibom State, Nigeria. Methods Anopheline mosquito samples were collected from pyrethrum spray catch collections and CDC light traps from 2016 through 2022. Samples were morphologically identified and subjected to polymerase chain reaction assays and sequencing analysis to confirm the identity of unamplified and/or misidentified samples. Mosquito bionomics such as abundance, indoor and outdoor human biting rates (HHR), indoor resting density (IRD), biting time, Plasmodium falciparum infection and blood meal sources of the mosquito samples were determined from the 2021 and 2022 samples. Data analysis was performed using one-way ANOVA (analysis of variance) tests and chi-square tests in GraphPad Prism version 9.0. Results A total of eight Anopheles species were identified: Anopheles coustani , Anopheles funestus group, Anopheles gambiae sensu lato ( s.l .) , Anopheles maculipalpis , Anopheles marshallii group, Anopheles moucheti , Anopheles nili, and Anopheles obscurus . The outcome of the analysed data confirmed a shift in the composition from An. gambiae s.l. to the An. marshallii group. The IRD, indoor and outdoor HBR of the An. marshallii group were not significantly different from that of An. gambiae s.l. in 2021 (p > 0.05) but significantly higher in 2022 (p < 0.05). The peak indoor and outdoor HBR of the An. marshallii group were observed to be higher than those of An. gambiae s.l. during the dry season. In both years, the An. gambiae s.l. and the An. marshallii group mosquitoes showed comparable preference for bovine blood meal. The preference for human blood meal was not significantly different (p = 0.21) between both species. The An. marshallii group was found to have been infected with Plasmodium falciparum sporozoites (n = 2) alongside An. gambiae sensu stricto ( s.s .) (n = 1) and Anopheles coluzzii (n = 2). Conclusion The An. marshallii group was confirmed as an abundant malaria vector species in. Mkpat-Enin Local Government Area of Akwa Ibom State. While similar indoor vector control interventions are recommended for both species; other interventions may be needed to address the early evening outdoor biting observed in the An. marshallii group.

Background Understanding the behaviour of local malaria vectors is essential as effectiveness of the commonly used vector-targeted malaria control tools heavily relies on behaviour of the major malaria vectors. This study was conducted to determine species composition, biting behaviour, host preference and infectivity of anopheline mosquitoes, and assess utilization of insecticide-treated nets (ITNs) in a low transmission setting in Southwest Ethiopia. Methods Adult anopheline mosquitoes were collected using human landing catches (HLCs), Centers for Disease Control and Prevention (CDC) light traps (LTs) and Pyrethrum Spray Catches (PSCs) from June 2016 to May 2018 in Kishe, Jimma Zone, Southwest Ethiopia. The anopheline mosquitoes were morphologically identified. Moreover, sub-sample of An. gambiae s.l. was identified to species using polymerase chain reaction (PCR). Circum-sporozoite proteins (CSPs) and blood meal sources of the anopheline mosquitoes were tested using enzyme-linked immunosorbent assay (ELISA). In addition, a cross-sectional survey was conducted to assess ITN utilization by the inhabitants. Results A total of 3659 anopheline mosquitoes comprising An. coustani complex (84.4%), An. gambiae s.l. (11.3%), and An. pharoensis and An. squamosus comprising less than 5% were collected. The anopheline mosquitoes showed marked outdoor (67%) and early evening (63%) biting behaviour. An. coustani complex and An. gambiae s.l. were predominantly zoophilic and anthropophilic, respectively. None of the sampled anopheline were CSP-positive. Most of the households (97.8%) owned at least one ITN, with modest usage by the inhabitants (73.4%). ITN usage was significantly higher among under-five children (AOR = 7.9, 95% CI: 4.41–14.03), household heads and spouses (AOR = 4.8, 95% CI: 3.0–7.59), those with sufficient access to ITNs (AOR = 1.8, 95% CI: 1.39–2.35), and who were not utilizing alternative mosquito repellents (AOR = 2.2, 95% CI: 1.58–2.99). Conclusion The anopheline mosquito species exhibited predominantly outdoor and early evening biting activity. Household ITN coverage was high with slight gap in usage. Vector control interventions should target outdoor and early biting vectors to further suppress the local mosquito population. Moreover, sensitization of the community on consistent use of ITNs is required.

Seal lice ( Echinophthirius horridus ) are bloodsucking ectoparasites of phocid seals and vectors of pathogens like the heartworm, Acanthocheilonema spirocauda . Grey and harbour seal populations are recovering in German waters and wildlife health surveillance is crucial for wildlife conservation. A new, high effort sampling protocol for seal lice was applied for grey and harbour seals along the German North- and Baltic Sea coast. Freshly dead seals were systematically sampled within a health monitoring of stranded seals over 12 months. Prevalence, intensity and distribution patterns of seal lice were analysed. 58% of harbour seals ( n  = 71) and 70% of grey seals ( n  = 10) were infected with seal lice. A majority of harbour seals displayed mild levels of infection, while three were moderately and two were severely infected. The head was the preferred predilection site, indicating that E. horridus prefers body areas with frequent access to atmospheric oxygen. Nits and different developmental stages were recorded in all age classes in grey and harbour seals in all seasons. For the first time, copulating specimens of E. horridus were recorded on a dead harbour seal, highlighting that E. horridus reproduces throughout the year on seals of all age classes in German waters.

The rapid advancement of 5G communication underscores the need for heightened efficiency within wireless sensor networks (WSNs), where challenges such as data loss, inefficiency, and jitter are exacerbated by complex operations. This paper presents the optimal pheromone-based route discovery stage (OpRDS) algorithm, inspired by the natural foraging behaviors of ants, as a novel solution designed to optimize routing processes in the dynamic and demanding 5G environments. The study conducts a comparative analysis of OpRDS against traditional routing protocols, including the ad hoc on-demand distance vector (AODV), destination-sequenced distance-vector (DSDV), dynamic source routing (DSR), and zone routing protocol (ZRP), focusing on key performance metrics such as packet delivery ratio (PDR), latency, throughput, routing overhead (RO), energy consumption (EC), network lifespan, route discovery speed, and scalability. Our results reveal that OpRDS significantly outperforms the conventional protocols, evidencing a 2% increase in PDR, a 5.5% decrease in latency, a 6.7% rise in throughput, an 8.3% reduction in RO, an 11.1% decrease in EC (resulting in an 11% extension of network lifespan), a 10% improvement in route discovery speed, and a 6.7% enhancement in scalability. These findings highlight the algorithm's superior efficiency and adaptability in addressing the robust demands of 5G networks.

Kalman filter (KF) is often based on two models, which are phase angle vector (PAV) model and orthogonal vector (OV) model, in the application of distorted grid AC signal detection. However, these two models lack rigorous and detailed derivation from the principle of dynamic modeling. This paper presents a phase angle vector dynamic (PAVD) model and an orthogonal vector dynamic (OVD) model, which are combined with Kalman filter for detecting distorted grid AC signal. They reveal that the state noise covariance of the dynamic model−based KF is related to the sampling cycle, and overcome the defect of more detecting error for conventional model−based KF. Experiment and evaluation results show that the proposed KF algorithms are reasonable and effective. Therefore, this paper contributes a guiding significance for the application of KF algorithm in harmonic detection.

Robot cloud service platform is a combination of cloud computing and robotics, providing intelligent cloud services for many robots. However, to select a cloud service that satisfys the robot’s requirements from the massive services with different QoS indicator in the cloud platform is an NP hard problem. In this paper, based on the cost model between the cloud platform, cloud services and cloud service robotics, we propose a two-stage service selection strategy, namely, candidate services selection stage according to the specific QoS requirements of service robots and final cost optimization stage. Additionally, with respect to optimizing the final cost for the model, we propose a Dynamic Vector Hybrid Genetic Algorithm (DVHGA) that is integrated with local and global search process as well as a three-phase parameter updating policy. Specifically, inspired by momentum optimization in deep learning, dynamic vector is integrated with DVHGA to modify the weights of QoS and ensure the reasonable allocation of resources. Moreover, we suggest a linear evaluation method for the service robots and the cloud platform concerning time and final cost at the same time, which could be expected to be used in the real application environment. Finally, the empirical results demonstrate that the proposed DVHGA outperforms other benchmark algorithms, i.e., DABC, ESWOA, GA, PGA and GA-PSO, in convergence rate, total final cost and evaluation score.

Background Malaria is still a heavy public health concern in Madagascar. Few studies combining parasitology and entomology have been conducted despite the need for accurate information to design effective vector control measures. In a Malagasy region of moderate to intense transmission of both Plasmodium falciparum and P. vivax , parasitology and entomology have been combined to survey malaria transmission in two nearby villages. Methods Community-based surveys were conducted in the villages of Ambohitromby and Miarinarivo at three time points (T1, T2 and T3) during a single malaria transmission season. Human malaria prevalence was determined by rapid diagnostic tests (RDTs), microscopy and real-time PCR. Mosquitoes were collected by human landing catches and pyrethrum spray catches and the presence of Plasmodium sporozoites was assessed by TaqMan assay. Results Malaria prevalence was not significantly different between villages, with an average of 8.0% by RDT, 4.8% by microscopy and 11.9% by PCR. This was mainly due to P. falciparum and to a lesser extent to P. vivax . However, there was a significantly higher prevalence rate as determined by PCR at T2 ( χ 2 2 = 7.46, P = 0.025). Likewise, mosquitoes were significantly more abundant at T2 ( χ 2 2 = 64.8, P < 0.001), especially in Ambohitromby. At T1 and T3 mosquito abundance was higher in Miarinarivo than in Ambohitromby ( χ 2 2 = 14.92, P < 0.001). Of 1550 Anopheles mosquitoes tested, 28 (1.8%) were found carrying Plasmodium sporozoites. The entomological inoculation rate revealed that Anopheles coustani played a major contribution in malaria transmission in Miarinarivo, being responsible of 61.2 infective bites per human (ib/h) during the whole six months of the survey, whereas, it was An. arabiensis , with 36 ib/h, that played that role in Ambohitromby. Conclusions Despite a similar malaria prevalence in two nearby villages, the entomological survey showed a different contribution of An. coustani and An. arabiensis to malaria transmission in each village. Importantly, the suspected secondary malaria vector An. coustani , was found playing the major role in malaria transmission in one village. This highlights the importance of combining parasitology and entomology surveys for better targeting local malaria vectors. Such study should contribute to the malaria pre-elimination goal established under the 2018–2022 National Malaria Strategic Plan.

Epidemiology is the science of how disease develops in populations, with applications in human, animal and plant diseases. For plant diseases, epidemiology has developed as a quantitative science with the aims of describing, understanding and predicting epidemics, and intervening to mitigate their consequences in plant populations. Although the central focus of epidemiology is at the population level, it is often necessary to recognise the system hierarchies present by scaling down to the individual plant/cellular level and scaling up to the community/landscape level. This is particularly important for diseases caused by plant viruses, which in most cases are transmitted by arthropod vectors. This leads to range of virus-plant, virus-vector and vector-plant interactions giving a distinctive character to plant virus epidemiology (whilst recognising that some fungal, oomycete and bacterial pathogens are also vector-borne). These interactions have epidemiological, ecological and evolutionary consequences with implications for agronomic practices, pest and disease management, host resistance deployment, and the health of wild plant communities. Over the last two decades, there have been attempts to bring together these differing standpoints into a new synthesis, although this is more apparent for evolutionary and ecological approaches, perhaps reflecting the greater emphasis on shorter often annual time scales in epidemiological studies. It is argued here that incorporating an epidemiological perspective, specifically quantitative, into this developing synthesis will lead to new directions in plant virus research and disease management. This synthesis can serve to further consolidate and transform epidemiology as a key element in plant virus research.