Variable Positions Research Articles

A new blood parasite of the accentor birds: description, molecular characterization, phylogenetic relationships and distribution.

Haemoproteus bobricklefsi sp. nov. (Haemosporida, Haemoproteidae) was found in the dunnock Prunella modularis and represents the first blood parasite described in accentor birds of the Prunellidae. The description is based on the morphology of blood stages and includes information about a barcoding segment of the mitochondrial cytochrome b gene (lineage hDUNNO01) and the full mitochondrial genome, which can be used for identification and diagnosis of this infection. The new parasite can be readily distinguished from described species of haemoproteids parasitizing passeriform birds due to markedly variable position of nuclei in advanced and fully grown macrogametocytes. Illustrations of blood stages of the new species are given, and phylogenetic analyses based on partial mitochondrial cytochrome b gene sequences and the full mitochondrial genome identified the closely related lineages. DNA haplotype networks showed that transmission occurs in Europe and North America. This parasite was found in the dunnock in Europe and several species of the Passerellidae in North America. It is probably of Holarctic distribution, with the highest reported prevalence in the UK. The parasite distribution seems to be geographically patchy, with preference for areas of relatively cool climates. Phylogenetic analysis suggests that H. bobricklefsi sp. nov. belongs to the Parahaemoproteus subgenus and is probably transmitted by biting midges belonging to Culicoides (Ceratopogonidae). The available data on molecular occurrence indicate that this pathogen is prone to abortive development, so worth attention in regard of consequences for bird health.

Resource Allocation in UAV-D2D Networks: A Scalable Heterogeneous Multi-Agent Deep Reinforcement Learning Approach

In unmanned aerial vehicle (UAV)-assisted device-to-device (D2D) caching networks, the uncertainty from unpredictable content demands and variable user positions poses a significant challenge for traditional optimization methods, often making them impractical. Multi-agent deep reinforcement learning (MADRL) offers significant advantages in optimizing multi-agent system decisions and serves as an effective and practical alternative. However, its application in large-scale dynamic environments is severely limited by the curse of dimensionality and communication overhead. To resolve this problem, we develop a scalable heterogeneous multi-agent mean-field actor-critic (SH-MAMFAC) framework. The framework treats ground users (GUs) and UAVs as distinct agents and designs cooperative rewards to convert the resource allocation problem into a fully cooperative game, enhancing global network performance. We also implement a mixed-action mapping strategy to handle discrete and continuous action spaces. A mean-field MADRL framework is introduced to minimize individual agent training loads while enhancing total cache hit probability (CHP). The simulation results show that our algorithm improves CHP and reduces transmission delay. A comparative analysis with existing mainstream deep reinforcement learning (DRL) algorithms shows that SH-MAMFAC significantly reduces training time and maintains high CHP as GU count grows. Additionally, by comparing with SH-MAMFAC variants that do not include trajectory optimization or power control, the proposed joint design scheme significantly reduces transmission delay.

Inundation and evacuation of shoreline populations during landslide-triggered tsunamis: an integrated numerical and statistical hazard assessment

Abstract. The volcanic island of Stromboli (southern Tyrrhenian Sea, Italy) is renowned for its persistent, periodic, low-intensity explosive activity, whose spectacular manifestations attract tens of thousands of tourists every year. However, sporadic more intense major explosive and effusive eruptions and paroxysms pose serious threats to the island. In addition to direct hazards, granular slides of volcanic debris and pyroclastic avalanches, which can rapidly reach the sea and potentially generate tsunamis, are often associated with such unpredictable eruptive activity. Due to the very fast propagation of the tsunami around the island and the consequent short tsunami warning time (ranging from less than a minute to only a few minutes), mitigation efforts and evacuation from the Strombolian coast must be carefully planned. In this paper, we describe a new GIS-assisted procedure that allows us to combine the outputs of an ensemble of 156 pre-computed landslide-generated tsunami hazard scenarios (with variable landslide volume, position, and density), statistical exposure data (i.e. the number of inhabitants and tourists), and digital geographic information to obtain a quantitative (scenario-based) risk analysis. By means of the analysis of the road network and coastal morphology, we develop a model with routes and times to reach a safe area from every pixel in the inundated area and an appraisal of the time needed to escape versus the wave arrival time. This allows us to evaluate and quantify the effectiveness of potential risk mitigation by means of evacuation. The creation of an impact score linking the predicted inundation extent and the tsunami warning signals is intended, in the long term, to be used to predict the intensity of future tsunamis and to adapt evacuation plans accordingly. The model, here applied to Stromboli, is general and can be applied to other volcanic islands. Evacuating an island hosting several thousand tourists every summer with very little warning time underlines the absolute necessity for such mitigation efforts, aimed at informing hazard planners and managers and all other stakeholders.

Synthesis of a Truncated Microcystin Tetrapeptide Molecule from a Partial Mcy Gene Cluster in Microcystis Cultures and Blooms.

Microcystis spp. threaten freshwater ecosystems through the proliferation of cyanobacterial harmful algal blooms (cyanoHABs) and production of the hepatotoxin, microcystin. While microcystin and its biosynthesis pathway, encoded by the mcy genes, have been well studied for over 50 years, a recent study found that Microcystis populations in western Lake Erie contain a transcriptionally active partial mcy operon, in which the A2 domain of mcyA and mcyB-C are present but the mcyD-J genes are absent. Here, we investigate the potential biosynthetic products and the evolutionary history of this partial operon. Our results reveal two candidate tetrapeptide constructs, with an X variable position, to be produced by strains with the partial operon. The partial operon appears necessary and sufficient for tetrapeptide biosynthesis and likely evolved from a single ancestor hundreds to tens of thousands of years ago. Bioactivity screens using Hep3B cells indicate a mild elevation of some markers of hepatotoxicity and inflammation, suggesting the need to further assess the effects of these novel secondary metabolites on freshwater ecosystems and public health. The need to assess these effects is even more pressing given the detection of tetrapeptides in both culture and western Lake Erie, which is a vital source of fresh water. Results from this study emphasize previous findings in which novel bacterial secondary metabolites may be derived from the molecular evolution of existing biosynthetic machinery under different environmental forcings.

Exploration on flutter mechanism of a damaged transonic rotor blade using high-fidelity fluid–solid coupling method

Structural damage in turbomachinery is a primary origin of aeronautic accidents, which is receiving increased attention. This study is thus focused on the aeroelastic analysis of damaged blades, including the onset of flutter and underlying mechanisms. First, a high-fidelity fluid–solid coupling system is established with computational fluid dynamics (CFD) and computational structural dynamics (CSD) technologies, via which the dynamic aeroelastic analysis is conducted based on static aeroelastic deformation. Second, a damaged rotor blade is parametrically modelled with variable damage levels, extents, and positions. Finally, the modal identification method of spectral proper orthogonal decomposition (SPOD) is applied to observe flow details and provide physical insight into the flutter mechanism for damaged blades. Numerical analysis finds that there is a critical damage level below which the aeroelastic stability is positively improved with increasing damage level; otherwise, a significant loss of stability is induced. The damage location and extent further affect this critical damage level and the change rate crossing the threshold. The simulation with CFD/CSD finds that the high pressure near the trailing edge induced from boundary layer separation suppresses vibrations in stable conditions, but motivates vibrations during flutter, which is because of the high-pressure spread to nearing blades. SPOD modes reveal that high-frequency disturbances with large scale are primary factors inducing flutter, which is further stimulated by the high-order disturbances with small scale. This study provides a crucial foundation for the fatigue prediction for rotor blades in service and the optimisation design for high-performance turbomachinery in the near future.

An Attempt for Numerical Optimisation of a Micro-Groove Geometry at The Rake Face When Turning Ti6Al4V Alloy with Indexable Inserts

Machining of Ti6Al4V is considered difficult because the material removal rates are relatively small if the tool wear shall be low. In recent years the reduction of process forces as well as tool wear have been investigated by introducing textures (pockets) into the tool surface. To advance the understanding how those textured tools function and to reduce the experimental effort, a smoothed particle hydrodynamics (SPH) model of the orthogonal cutting process with a parametrised tool containing a single pocket on the rake face with variable position and depth is presented. This simulation model is used to enhance the understanding of rake face textures in order to design optimum cutting tools for given process parameters. Using an optimisation algorithm, an optimum texture geometry is determined numerically and is then experimentally validated, followed by a discussion, why process force reductions are lower than predicted.

Adaptive positioning of large-scale aircraft components using a simplified image-based visual servoing via online measurement of ball-head center

In digital alignment systems, ensuring fast and accurate alignment between the ball head on large aircraft components and the ball socket of the positioner is the key to aircraft assembly efficiency and quality. Image-based visual servoing is one of the most advanced techniques with high efficiency and positioning accuracy, but it does not account for measuring the ball-head position. Moreover, variable target positions, similar feature interference, and poor lighting conditions pose great challenges to the fast and robust visual measurement of ball-head position. Hence, an online visual measurement method is introduced to measure the absolute position of the ball head in real time. An adaptive region of interest extraction algorithm and an improved edge following method are introduced to extract the elliptical contour from the ball-head image, and ellipse detection is achieved through a simple triplet selection algorithm. A geometric model based on the perspective projection of the sphere is established for estimating the ball-head center. Then, the simplified image-based visual servoing method is developed by constantizing the image Jacobian matrix. Next, an adaptive positioning method of large-scale aircraft components with multiple ball heads is proposed from a holistic perspective. Finally, experiments show that the final positioning accuracy of each ball head in the X/Y plane is less than ± 0.05 mm, with an efficiency almost ten times that of the conventional method. After adaptive adjustment, the position and angle errors of the simulated component are reduced within 0.6 mm and 0.3°, respectively.

Safety Analysis of Metallic Tokamak-I Against Electromagnetic and Structural Loads

During tokamak operation, the structural integrity of the vacuum vessel (VV) of Metallic Tokamak-I (MT-I), a small spherical tokamak, was evaluated. This evaluation involved simulating real experimental data of electromagnetic (EM) and structural loads using the ANSYS platform. Internal heat generation, induced currents, and inertial and pressure loads in the VV were analyzed to determine their effects on the VV. This analysis was conducted on a 180-deg sector model over a 10-ms-event period. To create multiple checkpoint events, the plasma current was assumed to be formed at variable positions of the VV, hence inducing variable current for each event. The events are divided into four cases based on the radial and vertical displacements of plasma. The response of the VV structure was calculated using coupling of EM and structural modules of ANSYS. It is observed from the numerical results that the maximum stress on the VV is in a safe range and that the temperature rise on the vessel can be reduced by natural convection only if the event is ended in 10 ms. A prolonged event can result in permanent deformation in the VV structure. A disruption event on the limiter region is also studied.

Three-Dimensional Evaluation of Impacted Mandibular Third Molar Angulation and its Impact on Lingual Cortical Bone Thickness: A Retrospective Cone-Beam Computed Tomography Study

Background: The removal of impacted lower third molars surgically can cause complications, and the lingual cortical bone thickness in this region becomes a determining factor in the risk of perforation and injury to the lingual nerve (LN). This study was conducted to assess the relationship between different angulations of impacted lower third molars based on Winter’s classification and the thickness of the lingual cortical bone. Variations in lingual cortical bone thickness among the genders were evaluated as well. Methods: Cone-beam computed tomography (CBCT) scans of 50 impacted lower third molar teeth of 50 patients (26 men and 24 women) were evaluated in this study. The lingual bone thickness surrounding impacted lower mandibular teeth was measured at three key points, namely, the cemento-enamel junction of the second mandibular molar, the mid-root of the impacted third molar, and the root apex of the impacted third molar. Mesiodistal angulation and buccolingual angulations of the impacted mandibular third molars underwent investigation. Statistical analysis was conducted using SPSS 23. Data were analyzed using the independent sample t test, one-way ANOVA, multiple linear regression analysis, and Fisher’s exact test. Results: There was a statistically significant relationship between the means of lingual cortical bone thickness surrounding the third molars based on Winter’s classification of third molars impacted at mesiodistal angulation (P=0.00). Regarding gender, buccolingual angulation demonstrated a statistically significant relationship among the means of lingual bone thickness around the third molars (P=0.022). Conclusion: In our study, the thickness of the lingual cortical bone was notably affected in the middle and apical areas of the impacted third molar region. The variable position of the LN near the mandible third molar region was significant in dental procedures due to its proximity. Three-dimensional (3D) imaging CBCT provides preoperative risk assessment that reduces preventable complications that cannot be answered by 2D imaging.

Histomorphometric and developmental analysis of human fetal caecum and appendix with its embryological significance

PurposeThe variable positions of the appendix can mislead surgeons and physicians to a wrong diagnosis. When appendicitis happens in subhepatic caecum, it can be misdiagnosed and can lead to severe complications during surgical procedures. Therefore, this study aimed to understand the histomorphometric development of the appendix and caecum and to identify when lymphoid follicles appear in the appendix during fetal life.MethodsThe study was conducted on a total of 50 fetuses. The caecum and appendix were carefully dissected. Their position and various measurements were observed. Afterwards, the appendix was taken out for histological processing. All three layers, mucosa, submucosa, and muscularis externa were measured using Image Analyzer Software Image Pro Premiere 9.1, and the appearance of lymphoid follicles was also examined. Results were analyzed using SPSS statistical software.ResultsDuring the 1st, 2nd, and 3rd trimesters the most common caecum type was type 1: as a lengthy tube, type 3: The lateral wall expanded more, thus it has an asymmetric saccule, and type 4: adult-like caecum. The caecum was mostly situated in the right lumbar region in the 2nd and 3rd trimesters. In the 1st trimester, it was subhepatic in position. The most common position of the appendix was 11 o’clock in 1st and 3rd trimesters. 2nd trimester’s most common position of the appendix was 12 o’clock. The thickness of the mucosa, submucosa, and the muscularis externa increases as the trimester increases. The lymphoid follicles have appeared during the 2nd trimester.ConclusionThe knowledge from this study will be useful in the diagnosis and treatment of malformations, pathology, and anomalies of the caecum and appendix due to congenital causes.

An air‐cooled cylindrical Li‐ion 5 × 5 battery module with a novel flow‐diverting arrangement and variable vent positions for electric vehicles: A numerical thermal analysis

AbstractThermal management of lithium‐ion batteries has received a lot of interest in the automobile sector. In commercial electric motor vehicles, an efficient battery cooling arrangement, particularly active cooling approaches, has been chosen as an ideal option. When building battery cooling systems, the physical structure and arrangement of the battery pack (BP) are vital. The current study presents a revolutionary design of a BP that incorporates cylindrical cells in a square duct and an air‐cooling (AC) medium circulated in its surroundings with the help of variable vents for inlet and outlet. A forced‐AC system is used to test lithium‐ion battery cells grouped in a 5 × 5 configured battery module. To investigate the impact of heat generation on battery thermal performance, a complete thermal analysis was performed at different discharge rates of 0.5, 1, 2, 3, and 4 C. As compared with both inlet vents at an equidistance configuration with an inlet velocity of 12 m/s and a flow rate of 1.210(−2) kg/s, the results show that the proposed design minimizes heat accumulation by enhancing the heat transfer. As a result, the peak temperature and temperature disparity decreased by 6.76% and 85.32%, respectively. A flow‐dispersing disc of 30 mm in size enhances temperature uniformity in comparison to the other intake vent design, hence improving battery safety and longevity.

Prediction of coal and gas outburst hazard using kernel principal component analysis and an enhanced extreme learning machine approach

In order to enhance the accuracy and efficiency of coal and gas outburst disaster risk prediction, a novel approach combining kernel principal component analysis (KPCA) with an improved whale optimization algorithm (IWOA) optimized extreme learning machine (ELM) is proposed for precise forecasting of coal and gas outburst disasters in mines. Firstly, based on the influencing factors of coal and gas outburst disasters, nine coupling indexes are selected, including gas pressure, geological structure, initial velocity of gas emission, and coal structure type. The correlation between each index was analyzed using the Pearson correlation coefficient matrix in SPSS 27 software, followed by extraction of the principal components of the original data through kernel principal component analysis (KPCA). The whale optimization algorithm (WOA) was enhanced by incorporating adaptive weight, variable helix position update, and optimal neighborhood disturbance to augment its performance. The improved Whale Optimization Algorithm (IWOA) is subsequently employed to optimize the weight ф of the Extreme Learning Machine (ELM) input layer and the threshold g of the hidden layer, thereby enhancing its predictive accuracy and mitigating to some extent the issue of "over-fitting" associated with ELM. The principal components extracted by KPCA were utilized as input, while the outburst risk grade served as output. Subsequently, a comparative analysis was conducted between these results and those obtained from WOA-SVC, PSO-BPNN, and SSA-RF models. The IWOA-ELM model accurately predicts the risk grade of coal and gas outburst disasters, with results consistent with actual situations. Compared to other models tested, the model's performance showed an increase in Ac by 0.2, 0.3, and 0.2 respectively; P increased by 0.15, 0.2167, and 0.1333 respectively; R increased by 0.25, 0.3, and 0.2333 respectively; F1-Score increased by 0.2031, 0.2607, and 0.1864 respectively; Kappa coefficient k increased by 0.3226, 0.4762 and 0.3175, respectively. The practicality and stability of the IWOA-ELM model were verified through its application in a Shanxi Province coal mine where predicted values matched actual values exactly. This indicates that this model is more suitable for predicting coal and gas outburst disaster risks.

FOX Optimization Algorithm Based on Adaptive Spiral Flight and Multi-Strategy Fusion.

Adaptive spiral flight and multi-strategy fusion are the foundations of a new FOX optimization algorithm that aims to address the drawbacks of the original method, including weak starting individual ergodicity, low diversity, and an easy way to slip into local optimum. In order to enhance the population, inertial weight is added along with Levy flight and variable spiral strategy once the population is initialized using a tent chaotic map. To begin the process of implementing the method, the fox population position is initialized using the created Tent chaotic map in order to provide more ergodic and varied individual beginning locations. To improve the quality of the solution, the inertial weight is added in the second place. The fox random walk mode is then updated using a variable spiral position updating approach. Subsequently, the algorithm's global and local searches are balanced, and the Levy flying method and greedy approach are incorporated to update the fox location. The enhanced FOX optimization technique is then thoroughly contrasted with various swarm intelligence algorithms using engineering application optimization issues and the CEC2017 benchmark test functions. According to the simulation findings, there have been notable advancements in the convergence speed, accuracy, and stability, as well as the jumping out of the local optimum, of the upgraded FOX optimization algorithm.

Seismocardiography and echocardiography: the correlation in the systolic complex

Aim. This study aimed to investigate the correlation between seismocardiographic and echocardiographic systolic variables and whether a decrease in preload could be detected by the seismocardiography (SCG). Methods. This study included a total of 34 subjects. SCG and electrocardiography were recorded simultaneously followed by echocardiography (echo) in both supine and 30◦ head-up tilted position. The SCG signals was segmented into individual heartbeats and systolic fiducial points were defined using a detection algorithm. Statistical analysis included correlation coefficient calculations and paired sample tests. Results. SCG was able to measure a decrease in preload by almost all of the examined systolic SCG variables. It was possible to correlate certain echo variables to SCG time intervals, amplitudes, and peak to peak intervals. Also, changes between supineand tilted position of some SCG variables were possible to correlate to changes in echo variables. LVET, IVCT, S’, strain, SR, SV, and LVEF were significantly correlated to relevant SCG variables. Conclusion. This study showed a moderate correlation, between systolic echo and systolic SCG variables. Additionally, systolic SCG variables were able to detect a decrease in preload.

Multitarget adaptive virtual fixture based on task learning for hydraulic manipulator

AbstractHeavy‐duty construction tasks implemented by hydraulic manipulators are highly challenging due to unstructured hazardous environments. Considering many tasks have quasirepetitive features (such as cyclic material handling or excavation), a multitarget adaptive virtual fixture (MAVF) method by teleoperation‐based learning from demonstration is proposed to improve task efficiency and safety, by generating an online variable assistance force on the master. First, the demonstration trajectory of picking scattered materials is learned to extract its distribution and the nominal trajectory is generated. Then, the MAVF is established and adjusted online by a defined nonlinear variable stiffness and position deviation from the nominal trajectory. An energy tank is introduced to regulate the stiffness so that passivity and stability can be ensured. Taking the operation mode without virtual fixture (VF) assistance and with traditional weighted adaptation VF as comparisons, two groups of tests with and without time delay were carried out to validate the proposed method.

Morphological variations in the African palm weevil, Rhynchophorus phoenicis (F) (Coleoptera: Curculionidae), in Kenya and Uganda

We investigated morphological differences in the African palm weevil (Rhynchophorus phoenicis) from Kenya (Busia and Kwale) and Uganda using a LEICA EZ4HD stereo microscope and an absolute digimatic caliper. Ten pronotal colour patterns were recorded, of which two (brown with two black spots and black with/without very faint brown bands of variable lengths and positions) are reported for the first time. Pronota of most R. phoenicis from Busia and Uganda were black with/without very faint brown bands of variable lengths and positions. Samples of R. phoenicis from Kwale were dominated by four reddish brown and three black bands, which either ran through the pronotal length or the reddish-brown bands coalesced anteriorly. The following pronotal colour patterns were male-specific: (i) two reddish brown bands, approximately ¾ the pronotal length and coalescing anteriorly, (ii) two reddish brown bands running through the pronotal length but discontinuous towards the posterior end and (iii) a brown pronotum with two black spots. Only the females had (i) two faint reddish brown bands running through the pronotal length, fading posteriorly and (ii) four reddish brown and three black bands, two of the former on either halves coalescing posteriorly. Females had longer snouts and mesocoxal distance, and wider elytra than males. Males possessed a longer profemur than females. Morphometric polymorphism was not linked to the site of sample collection. These findings provide additional diagnostic features and improve sexing of P. phoenicis and open opportunities for further research on the mechanisms for polymorphism in the species.

Influence of variable hinge positioning on coronal and sagittal alignment in uniplanar medial open-wedge high tibial osteotomy.

There is a high risk of increasing the posterior tibial slope (PTS) during medially opening-wedge high tibial osteotomy (mowHTO). Most recently, the idea of intentional simultaneous coronal and sagittal correction, using uniplanar cutting techniques has emerged. This study aims to examine the influences of variable hinge positioning and osteotomy gap height on the sagittal and coronal plane. Twenty uniplanar mowHTOs were performed in standardised (left) solid-foam proximal tibia models. In the different models, hinge position was rotated stepwise by 10°, between 90° (cutting straight medial to lateral) and 0° (cutting straight anterior to posterior) (n = 10). Additionally, gap heights of 5 and 10 mm were produced and analysed. Logistic regression analysis was performed to calculate a predictive regression formula for the relation between gap height, hinge rotation and the changes of medial proximal tibia angle (MPTA), medial and lateral PTS. Between cutting angles of 90 and 20°, the MPTA was mainly influenced by the gap height (0.95° MPTA per 1 mm gap height), but not by the cutting angle. Between 20 and 0°, the MPTA was decreased by 3.6° per 10° of rotation, but not by the gap height. Between cutting angles of 90 and 10°, the PTS was increased linearly by 0.97° per 10° of rotation and by 0.61° per 1 mm gap height. In mowHTO with lateral hinge positions, the MPTA is mainly influenced by gap height. Changes of PTS can be avoided by a straight lateral hinge position. In posterior hinge locations (0-20°), changes of MPTA are mainly caused by hinge rotation, but not by gap height. Level III, Case-control study.

Sequencing and characterization of human bocavirus genomes from patients diagnosed in Southern France between 2017 and 2022.

The diversity and evolution of the genomes of human bocavirus (HBoV), which causes respiratory diseases, have been scarcely studied. Here, we aimed to obtain and characterize HBoV genomes from patients's nasopharyngeal samples collected between 2017 and 2022 period (5 years and 7 months). Next-generation sequencing (NGS) used Illumina technology after having implemented using GEMI an in-house multiplex PCR amplification strategy. Genomes were assembled and analyzed with CLC Genomics, Mafft, BioEdit, MeV, Nextclade, MEGA, and iTol. A total of 213 genomes were obtained. Phylogeny classified them all as of Bocavirus 1 (HBoV1) species. Five HBoV1 genotypic clusters determined by hierarchical clustering analysis of 27 variable genome positions were scattered over the study period although with differences in yearly prevalence. A total of 167 amino acid substitutions were detected. Besides, coinfection was observed for 52% of the samples, rhinoviruses then adenoviruses (HAdVs) being the most common viruses. Principal component analysis showed that HBoV1 genotypic cluster α tended to be correlated with HAdV co-infection. Subsequent HAdV typing for HBoV1-positive samples and negative controls demonstrated that HAdVC species predominated but HAdVB was that significantly HBoV1-associated. Overall, we described here the first HBoV1 genomes sequenced for France. HBoV1 and HAdVB association deserves further investigation.

Overturning resistant capacities of rocking frames with supplemental vibration control devices under pulse-type excitations

Rocking structures are vulnerable to overturn under earthquake shaking. It is necessary to reduce the overturning probability of rocking structures. Recently, inerters were proposed to control the vibrations of rocking columns, and it was found that the structure equipped with inerter has reduced probability of overturning. However, inerter does not have capacity to dissipate energy, its control performance is believed able to be enhanced once being used in conjunction with dampers. Therefore, this paper approaches rocking structural vibration control from two directions: by applying supplemental inertia and applying supplemental damping to the structure. To this end, inerter, clutched-inerter and viscous damper are selected as control devices, and two combined scenarios are also considered, with configuration Ⅰ consisting of an inerter and a viscous damper in parallel and configuration Ⅱ consisting of a clutched-inerter and a viscous damper in parallel. The analytical models of a rocking frame with supplemental control devices in variable positions are presented and the equations of motion for each model are derived. In addition, the maximum coefficient of restitution of the rocking frame with supplemental control device is derived based on the angular momentum-impulse theorem. The effects and applicable conditions of the considered devices are evaluated by means of assessing the overturning resistances, maximum responses and fragility curves of rocking frames under different conditions. The results show that, with appropriate damping coefficient and apparent mass of the inerter, the combined configurations Ⅰ and Ⅱ provide better control effectiveness than the cases with inerter, clutched-inerter or viscous damper applied individually.

Haplotype determination of the Bombyx mori nucleopolyhedrovirus by Nanopore sequencing and linkage of single nucleotide variants.

Naturally occurring isolates of baculoviruses, such as the Bombyx mori nucleopolyhedrovirus (BmNPV), usually consist of numerous genetically different haplotypes. Deciphering the different haplotypes of such isolates is hampered by the large size of the dsDNA genome, as well as the short read length of next generation sequencing (NGS) techniques that are widely applied for baculovirus isolate characterization. In this study, we addressed this challenge by combining the accuracy of NGS to determine single nucleotide variants (SNVs) as genetic markers with the long read length of Nanopore sequencing technique. This hybrid approach allowed the comprehensive analysis of genetically homogeneous and heterogeneous isolates of BmNPV. Specifically, this allowed the identification of two putative major haplotypes in the heterogeneous isolate BmNPV-Ja by SNV position linkage. SNV positions, which were determined based on NGS data, were linked by the long Nanopore reads in a Position Weight Matrix. Using a modified Expectation-Maximization algorithm, the Nanopore reads were assigned according to the occurrence of variable SNV positions by machine learning. The cohorts of reads were de novo assembled, which led to the identification of BmNPV haplotypes. The method demonstrated the strength of the combined approach of short- and long-read sequencing techniques to decipher the genetic diversity of baculovirus isolates.