Similar Shape Research Articles

FSN-YOLO: Nearshore Vessel Detection via Fusing Receptive-Field Attention and Lightweight Network

Vessel detection is critical for ensuring maritime transportation and navigational safety, creating a pressing need for detection methodologies that are more efficient, precise, and intelligent in the maritime domain. Nonetheless, accurately detecting vessels across multiple scales remains challenging due to the diversity in vessel types and locations, similarities in ship hull shapes, and disturbances from complex environmental conditions. To address these issues, we introduce an innovative FSN-YOLO framework that utilizes enhanced YOLOv8 with multi-layer attention feature fusion. Specifically, FSN-YOLO employs the backbone structure of FasterNet, enriching feature representations through super-resolution processing with a lightweight Convolutional Neural Network (CNN), thereby achieving a balance between processing speed and model size without compromising accuracy. Furthermore, FSN-YOLO uses the Receptive-Field Attention (RFA) mechanism to adaptively fine-tune the feature responses between channels, significantly boosting the network’s capacity to capture critical information and, in turn, improve the model’s overall performance and enrich the discriminative feature representation of ships. Experimental validation on the Seaship7000 dataset showed that, compared to the baseline YOLOv8l approach, FSN-YOLO considerably increased accuracy, recall rates, and mAP@0.5:0.95 by absolute margins of 0.82%, 1.54%, and 1.56%, respectively, positioning it at the forefront of current state-of-the-art models.

Enhanced heavy metal adsorption capacity of surface-functionalized Philippine natural zeolite in simulated wastewater

The adsorption efficiency of surface-functionalized Philippine natural zeolite (PNZ) for heavy metal uptake from single and mixed metal ion-simulated wastewater solution is reported in this work. Atomic adsorption spectroscopy (AAS) findings revealed that NaCl-modified PNZ (MPNZ) exhibited the highest zinc ion adsorption of 99.96 % while PNZ yielded an adsorption of 95.61 %. The adsorption isotherms of raw PNZ and MPNZ both show similar shapes that reflect Type IV adsorption-desorption isotherms with Type H2 hysteresis loop which can be observed for micro-mesoporous materials (pore containing 2–50 nm). An increase in PNZ pore size from 10.11 nm to 13.36 nm for NaCl-PNZ and 15.59 for NaOH-PNZ is observed after alkaline treatment. EDS confirmed the decrease in Si/Al ratio from 4.02 to 3.76, indicative of possible higher negative charge in the PNZ framework which is favorable for an enhanced Coulombic or electrostatic interaction with the cationic heavy metals being detected in this study. MPNZ demonstrated an adsorption capacity of 99.96 % for copper in mixed-ion solution while 88.49 % and 86.67 % were obtained for zinc and nickel, respectively. These values are higher compared to PNZ having only 32.21 % uptake for zinc and 38.00 % for nickel. A hierarchy of the average metal adsorption capacity showed the order: copper > nickel > zinc. Rapid adsorption at the first hour of the adsorption reaction was attained in all solutions while samples with pH 9 exhibited the highest Ni2+ and Zn2+ percent removal. Moreover, the increase in initial solution concentration led to lower adsorption efficiency and the maximum uptake was attained at 100 ppm. The equilibrium data of adsorption and mechanism were suitably described by Langmuir isotherm model. With these, surface functionalization of PNZ has further enhanced its cationic adsorption capacity on heavy metals in both single and mixed-ion solution having promising potential for wastewater remediation.

Time division multiplexing based multi-spectral semantic camera for LiDAR applications

The recent progress in the development of measurement systems for autonomous recognition had a substantial impact on emerging technology in numerous fields, especially robotics and automotive applications. In particular, time-of-flight (TOF) based light detection and ranging (LiDAR) systems enable to map the surrounding environmental information over long distances and with high accuracy. The combination of advanced LiDAR with an artificial intelligence platform allows enhanced object recognition and classification, which however still suffers from limitations of inaccuracy and misidentification. Recently, multi-spectral LiDAR systems have been employed to increase the object recognition performance by additionally providing material information in the short-wave infrared (SWIR) range where the reflection spectrum characteristics are typically very sensitive to material properties. However, previous multi-spectral LiDAR systems utilized band-pass filters or complex dispersive optical systems and even required multiple photodetectors, adding complexity and cost. In this work, we propose a time-division-multiplexing (TDM) based multi-spectral LiDAR system for semantic object inference by the simultaneous acquisition of spatial and spectral information. By utilizing the TDM method, we enable the simultaneous acquisition of spatial and spectral information as well as a TOF based distance map with minimized optical loss using only a single photodetector. Our LiDAR system utilizes nanosecond pulses of five different wavelengths in the SWIR range to acquire sufficient material information in addition to 3D spatial information. To demonstrate the recognition performance, we map the multi-spectral image from a human hand, a mannequin hand, a fabric gloved hand, a nitrile gloved hand, and a printed human hand onto an RGB-color encoded image, which clearly visualizes spectral differences as RGB color depending on the material while having a similar shape. Additionally, the classification performance of the multi-spectral image is demonstrated with a convolution neural network (CNN) model using the full multi-spectral data set. Our work presents a compact novel spectroscopic LiDAR system, which provides increased recognition performance and thus a great potential to improve safety and reliability in autonomous driving.

Exploration and Maintenance of Homeomorphic Orbit Revs in the Elliptic Restricted Three-Body Problem

A novel station-keeping strategy leveraging periodic revolutions of homeomorphic orbits in the Elliptic Restricted Three-Body Problem within the pulsating frame is presented. A systemic approach founded on arc-length continuation is presented for the discovery, computation, and classification of periodic revolutions that morph from their traditional circular restricted three-body counterparts to build an a priori dataset. The dataset is comprehensive in covering all possible geometric architectures of the restricted problem. Shape similarity is quantified using Hausdorff distance and works as a filter for the station-keeping algorithm in relation to appropriate target conditions. Finally, an efficient scheme to quantify impulsive orbit maintenance maneuvers that minimize the total fuel cost is presented. The proposed approach is salient in its generic applicability across any elliptic three-body system and any periodic orbit family. Finally, average annual station-keeping costs using the described methodology are quantified for selected “orbits of interest” in the cis-lunar and the Sun–Earth systems. The robustness and efficacy of the approach instill confidence in its applicability for realistic mission design scenarios.

Diabatic heating structures varying with convective and rainfall intensities in different areas of the pan-South China Sea region

This study investigates and compares diabatic heating structures related to vertical velocity, cloud types, and rainfall intensities in the northeast rainy sea subregion named Dongsha, the west rainless sea subregion named Xisha, and the north rainy land subregion named Coastland in the pan-SCS region. The diabatic heating rate of >2 K hr−1 over Dongsha and Coastland has a higher frequency and a deeper distribution than over Xisha where it requires stronger upward motion to achieve the same heating rate, indicating more frequent and deeper convection over the north coastal sea and land areas than the west sea area of the pan-SCS region. The deep convective Q1 profiles show a stronger peak at ∼500 hPa and a weaker peak at ∼700 hPa over two sea subregions while a single peak at ∼500 hPa over Coastland. The nimbostratus Q1 profile has a weakened heating peak at 350–550 hPa over Dongsha, 500–600 hPa over Xisha, and 425–575 hPa over Coastland. The shallow cumulus Q1 profile of Dongsha shows weak heating in the mid-to-lower troposphere while that of Xisha and Coastland has hardly heating. Latent heating and vertical turbulence significantly affect the diabatic heating structure related to deep convective clouds and nimbostratus but hardly affect that related to shallow cumulus. Despite cloud types, Dongsha has the strongest diabatic heating among the three subregions due to its geographical advantages. The no-rainfall Q1 profiles over three subregions have a similar shape with a weak cooling peak at ∼700 hPa due to boundary-layer evaporation and eddies. But the small-rainfall Q1 profiles present upper heating and lower cooling over sea subregions whereas the opposite over Coastland possibly due to stronger surface sensible heating on the land. From moderate to heavy rainfall, the Q1 profiles over three subregions are similar with a heating maximum at ∼500 hPa associated with deep convection, except for heating intensity which is much stronger over Xisha than the other two subregions. This suggests that Xisha presents stronger convection to achieve the same rainfall intensity as Dongsha and Coastland, which is closely due to a positive effect of coastal terrain blocking and uplifting on precipitation for Dongsha and Coastland whereas a negative effect of the Annam Mountains for Xisha.

Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm

Caladium is a popular ornamental plant and has business potential. However, difficulties in recognizing the type of Caladium often occur because of the similarities in shape, pattern, and color of the leaves between the different kinds of Caladium. To overcome this problem, research will use machine learning with the Convolutional Neural Network (CNN) algorithm to build a mobile application that can accurately classify four types of Caladiums. The data set used is 1200 data with four classes; each class has 300 data. The best model is found with the parameter epoch 100, learning rate 0.001, and batch size 64. The model is then implemented in a mobile application with two menus, "Take a photo" and "Choose an image," which will display the classification output and confidence values of the four types of Caladiums. Testing with 30 test data per class achieves 0.975 accuracy on both menus. On the “Take a photo” menu, precision is 0.974, recall is 0.9725, and f1-score is 0.965. Meanwhile, on the “Choose an image” menu a precision and recall value is 0.975, and f1-score value of 0.97.

Shape Evolution in Two Acts: Morphological Diversity of Larval and Adult Neoaustraranan Frogs.

Phenotypic traits can evolve independently at different stages of ontogeny, optimizing adaptation to distinct ecological contexts and increasing morphological diversity in species with complex life cycles. Given the relative independence resulting from the profound changes induced by metamorphosis, niche occupation and resource utilization in tadpoles may prompt evolutionary responses that do not necessarily affect the adults. Consequently, diversity patterns observed in the larval shape may not necessarily correspond to those found in the adult shape for the same species, a premise that can be tested through the Adaptive Decoupling Hypothesis (ADH). Herein, we investigate the ADH for larval and adult shape differentiation in Neoaustrarana frogs. Neoaustrarana frogs, particularly within the Cycloramphidae family, exhibit remarkable diversity in tadpole morphology, making them an ideal model for studying adaptive decoupling. By analyzing 83 representative species across four families (Alsodidae, Batrachylidae, Cycloramphidae, and Hylodidae), we generate a morphological dataset for both larval and adult forms. We found a low correlation between larval and adult shapes, species with a highly distinct larval shape having relatively similar shape when adults. Larval morphological disparity is not a good predictor for adult morphological disparity within the group, with distinct patterns observed among families. Differences between families are notable in other aspects as well, such as the role of allometric components influencing shape and morphospace occupancy. The larval shape has higher phylogenetic structure than the adult. Evolutionary convergence emerges as a mechanism of diversification for both larval and adult shapes in the early evolution of neoaustraranans, with shape disparity of tadpoles reaching stable levels since the Oligocene. The widest occupation in morphospace involves families associated with dynamically changing environments over geological time. Our findings support the ADH driving phenotypic diversity in Neoaustrarana, underscoring the importance of considering ontogenetic stages in evolutionary studies.

Allotendoplasty in Treatment of Habitual Patella Dislocation in Adults

Background. Habitual dislocation of patella is a congenital disease that manifests in early childhood or adolescent age and requires surgical treatment. In case this condition has not been rectified timely, the congenial patellar luxation develops the properties of a habitual dislocation accompanied by pain syndrome and osteoarthrosis development in the patellofemoral and knee joints. In most cases reconstructive surgery is used for this disease treatment; it is aimed at the strengthening of the knee joint interval compartment, with the formation of a fibrous graſt or a vertical strip of it, which are moved to the knee joint outside compartment and fixed to adjacent tissues with sutures. However, such surgery is possible only in case of preserved anatomic structures of the knee medial compartment. In adult patients, aſter multiple patellar dislocations, the interval joint capsule and medial aponeurosis lose their normal structure, become weakened, strained, and loose. That is why the patient’s own tissues from that area cannot be used for reconstructive surgery.The purpose of the study is to develop the new low-traumatic method of treatment for habitual dislocation of kneecap in adult patients to ensure its reliable stabilization as related to the joint surface on distal femoral epimetaphys, and to prevent patella dislocation relapse.Material and methods. Surgery technique consists of the lateral release of knee joint, mobilization of patellar ligament and its excision together with the fragment of tibial tuberosity osseous. On 1.5–2.0 cm medially from the area of own patellar ligament harvesting in tibia epimetaphys, the new bed with the similar form and shape is formed, and the excised tibial tuberosity fragment with patellar ligament is introduced there and fixed with a Cancellous screw.The area of own patellar ligament harvestingis filled up with autogenous osseous tissue taken from the medial part of tibia epimetaphys when forming the new bed for the excised tibial tuberosity fragment. Transversal tunnelis formedin the quadriceps tendon above the patella; allotendonis pulledvia this tunnel. The allotendon ends are sutured together, thus forming the duplication, analogous to the ligament, and fixit, stretched to “pes anserinus” of the shin onits anterior-interior surface.Conclusion. The new technology of allotendoplasty for the treatment of habitual kneecap dislocation in adult patients facilitates the surgical technique, additionally strengthens medial compartment tissues of the knee, reliably stabilizes the patella as related to its joint surface on distal femoral epimetaphys, eliminates patella dislocation relapse, normalizes the knee and patellofemoral joints functioning by preventing osteoarthrosis progression in them.

Rotated Lorenz Curves of Biological Size Distributions Follow Two Performance Equations

The Lorenz curve is used to describe the relationship between the cumulative proportion of household income and the number of households of an economy. The extent to which the Lorenz curve deviates from the line of equality (i.e., y = x) is quantified by the Gini coefficient. Prior models are based on the simulated and empirical data of income distributions. In biology, the Lorenz curves of cell or organ size distributions tend to have similar shapes. When the Lorenz curve is rotated by 135 degrees counterclockwise and shifted to the right by a distance of 2, a three-parameter performance equation (PE), and its generalized version with five parameters (GPE), accurately describe this rotated and right-shifted curve. However, in prior studies, PE and GPE were not compared with the other Lorenz equations, and little is known about whether the skewness of the distribution could influence the validity of these equations. To address these two issues, simulation data from the beta distributions with different skewness values and six empirical datasets of plant (organ) size distributions were used to compare PE and GPE with three other Lorenz equations in describing the rotated and right-shifted plant (organ) size distributions. The root-mean-square error and Akaike information criterion were used to assess the validity of the two performance equations and the three other Lorenz equations. PE and GPE were both validated in describing the rotated and right-shifted simulation and empirical data of plant (organ) distributions. Nevertheless, GPE worked better than PE and the three other Lorenz equations from the perspectives of the goodness of fit, and the trade-off between the goodness of fit and the model structural complexity. Analyses indicate that GPE provides a powerful tool for quantifying size distributions across a broad spectrum of organic entities and can be used in a variety of ecological and evolutionary applications. Even for the simulation data from hypothetical extreme skewed distribution curves, GPE still worked well.

Photoluminescence study of anatase TiO2 photocatalysts at the pico- and nanosecond timescales.

We studied the photoluminescence decay kinetics of three nanosized anatase TiO2 photocatalysts (particle diameter: 7, 25, or 200nm) at the pico- and nanosecond timescales for elucidating the origin of the luminescence. Luminescence spectra from these photocatalysts obtained under steady-state excitation conditions comprised green luminescence that decayed on the picosecond timescale and red luminescence that persisted at the nanosecond timescale. Among the photocatalysts with different sizes, there were marked differences in the rate of luminescence decay at the picosecond timescale (<600ps), although the spectral shapes were comparable. The similarity in the spectral shape indicated that self-trapped excitons (STEs) directly populated in the bulk of the particle by light excitation emit the luminescence in a picosecond timescale, and the difference in the rate of luminescence decay originated from the quenching at the particle surface. Furthermore, we theoretically considered excitation light intensity dependence on the quantum yield of the luminescence and found that the quenching reaction was not limited by the diffusion of the STEs but by the reaction at the particle surface. Both the spectral shape and time-evolution of the red luminescence from the deep trapped excitons in the nanosecond timescale varied among the photocatalysts, suggesting that the trap sites in different photocatalysts have different characteristics with respect to luminescence. Therefore, the relation between trap states and photocatalytic activity will be elucidated from the red luminescence study.

Automated segmentation and recognition of C. elegans whole-body cells.

Accurate segmentation and recognition of C.elegans cells are critical for various biological studies, including gene expression, cell lineages, and cell fates analysis at single-cell level. However, the highly dense distribution, similar shapes, and inhomogeneous intensity profiles of whole-body cells in 3D fluorescence microscopy images make automatic cell segmentation and recognition a challenging task. Existing methods either rely on additional fiducial markers or only handle a subset of cells. Given the difficulty or expense associated with generating fiducial features in many experimental settings, a marker-free approach capable of reliably segmenting and recognizing C.elegans whole-body cells is highly desirable. We report a new pipeline, called automated segmentation and recognition (ASR) of cells, and applied it to 3D fluorescent microscopy images of L1-stage C.elegans with 558 whole-body cells. A novel displacement vector field based deep learning model is proposed to address the problem of reliable segmentation of highly crowded cells with blurred boundary. We then realize the cell recognition by encoding and exploiting statistical priors on cell positions and structural similarities of neighboring cells. To the best of our knowledge, this is the first method successfully applied to the segmentation and recognition of C.elegans whole-body cells. The ASR-segmentation module achieves an F1-score of 0.8956 on a dataset of 116 C.elegans image stacks with 64 728 cells (accuracy 0.9880, AJI 0.7813). Based on the segmentation results, the ASR recognition module achieved an average accuracy of 0.8879. We also show ASR's applicability to other cell types, e.g. platynereis and rat kidney cells. The code is available at https://github.com/reaneyli/ASR.

A design approach to obtaining highly polar liquid crystal dimers

ABSTRACT The synthesis and characterisation of 10 members of the [4[(E)-[4-[4-[ω-(4-cyanophenyl)phenoxy]alkyloxy]-3-nitrophenyl]methylideneamino]phenyl] 2,4-dimethoxybenzoates is reported in which the number of methylene units in the flexible spacer is increased from three to twelve. The mesogenic units are based on cyanobiphenyl and 3-nitrobenzylideneaniline benzoate and linked by the spacer such that their dipoles are parallel giving rise to a large longitudinal dipole moment. All 10 members of the series show a nematic phase, and the nematic-isotropic transition temperatures, TNI, and associated entropy changes show a strong dependence on the length and parity of the spacer. This behaviour is attributed to the average shapes of the molecules and their flexibility. The heptyl member was further characterised using dielectric spectroscopy revealing a high value of dielectric permittivity reflecting the large dipole moment of the molecules and possibly indicating local short-range ferroelectric order. The synthesis and characterisation of two members of the [4[(E)-[4-[4-[3-(ω-cyanophenyl)phenoxy]alkyloxy]-4-nitrophenyl]methylideneamino]phenyl] 2,4-dimethoxybenzoates are also described for which the difference in shape between odd and even members is reduced. Both dimers are exclusively nematogenic and the difference between TNI for the odd and even member is smaller reflecting the more similar molecular shapes. The potential for developing dimers that exhibit the ferroelectric nematic phase is discussed.

Parametrization of biological assumptions to simulate growth of tree branching architectures.

Modeling and simulating the growth of the branching of tree species remains a challenge. With existing approaches, we can reconstruct or rebuild the branching architectures of real tree species, but the simulation of the growth process remains unresolved. First, we present a tree growth model to generate branching architectures that resemble real tree species. Secondly, we use a quantitative morphometric approach to infer the shape similarity of the generated simulations and real tree species. Within a functional-structural plant model, we implement a set of biological parameters that affect the branching architecture of trees. By modifying the parameter values, we aim to generate basic shapes of spruce, pine, oak and poplar. Tree shapes are compared using geometric morphometrics of landmarks that capture crown and stem outline shapes. Five biological parameters, namely xylem flow, shedding rate, proprioception, gravitysense and lightsense, most influenced the generated tree branching patterns. Adjusting these five parameters resulted in the different tree shapes of spruce, pine, oak, and poplar. The largest effect was attributed to gravity, as phenotypic responses to this effect resulted in different growth directions of gymnosperm and angiosperm branching architectures. Since we were able to obtain branching architectures that resemble real tree species by adjusting only a few biological parameters, our model is extendable to other tree species. Furthermore, the model will also allow the simulation of structural tree-environment interactions. Our simplifying approach to shape comparison between tree species, landmark geometric morphometrics, showed that even the crown-trunk outlines capture species differences based on their contrasting branching architectures.

Impact Disruption of Bjurböle Porous Chondritic Projectile

The ∼200 m s−1 impact of a single 400 kg Bjurböle L/LL ordinary chondrite meteorite onto sea ice resulted in the catastrophic disruption of the projectile. This resulted in a significant fraction of decimeter-sized fragments that exhibit power-law cumulative size and mass distributions. This size range is underrepresented in impact experiments and asteroid boulder studies. The Bjurböle projectile fragments share similarities in shape (sphericity and roughness at small and large scales) with asteroid boulders. However, the mean aspect ratio (3D measurement) and apparent aspect ratio (2D measurement) of the Bjurböle fragments is 0.83 and 0.77, respectively, indicating that Bjurböle fragments are more equidimensional compared to both fragments produced in smaller-scale impact experiments and asteroid boulders. These differences may be attributed either to the fragment source (projectile versus target), to the high porosity and low strength of Bjurböle, to the lower impact velocity compared with typical asteroid collision velocities, or potentially to fragment erosion during sea sediment penetration or cleaning.

Misclassification of Opisthorchis viverrini and Minute Intestinal Fluke Eggs by Routine Laboratory Staff Using Images from the Kato-Katz Method.

The Kato-Katz method is a commonly used diagnostic tool for helminth infections, particularly in field studies. This method can yield inaccurate results when samples contain eggs that are similar in appearance, such as Minute Intestinal Fluke (MIF) and Opisthorchis viverrini (OV) eggs. The close resemblance of eggs can be problematic and raises the possibility of false diagnoses. The objectives were to compare the diagnostic performance of the Kato-Katz method for accurately identifying MIF and OV and to provide evidence of possible misclassification. Methods: Based on questionnaire responses from 15 (young parasitologists and public health staff), the test comprised 50 MIF egg images and 50 OV egg images, for a total of 100 Google Form questionnaires. The morphology of MIF and OV eggs found size and shape similarity and found that the shoulder rims were small, while the OV egg found the knobs had disappeared. The opercular conjunction was apparent, the shoulder rims and miricidium were prominent. The average percentage of correctly classified infections was 61.6 ± 12.1%. The accuracy percentages for both public health staff and young parasitologists in identifying were found to be 59.0 ± 14.8 and 66.8 ± 2.8, respectively. There was no significant difference observed in both groups. These findings highlight the need for improving the accuracy of parasite identification. Preserving stool samples before the Kato-Katz method can help mitigate the potential degradation or distortion of parasite eggs. The incorrect classification of both eggs had an impact on treatment plans and the policy of parasite control programs.

A Close Look at Lyα Emitters with JWST/NIRCam at z ≈ 3.1

We study 10 spectroscopically confirmed Lyα emitters (LAEs) at z ≈ 3.1 in the Ultra Deep Survey field, covered by the James Webb Space Telescope/NIRCam in the Public Release Imaging for Extragalactic Research program. All LAEs are detected in all NIRCam bands from F090W to F444W, corresponding to rest frame wavelengths of 2200 Å to 1.2 μm. Based on morphological analysis of the F200W images, three out of the 10 targets are resolved into pair-like systems with separations of <0.″9, and another three show asymmetric structures. We then construct the spectral energy distributions (SEDs) of these LAEs, which show little to no extinction. All sources, including the pairs, show similar SED shapes, with a prominent flux excess in the F200W band, corresponding to extremely strong [O iii]+Hβ emission lines (EWrest = 740–6500 Å). The median effective radii, stellar mass, and UV slope of our sample are 0.36 kpc, 3.8 × 107 M ⊙, and −2.48, respectively. The average burst age, estimated by stellar mass over star formation rate, is <40 Myr. These measurements reveal an intriguing starbursting dwarf galaxy population lying off the extrapolations of the z ∼ 3 scaling relations to the low-mass end: ∼0.7 dex above the star-forming main sequence, ∼0.35 dex below the mass–size relation, and bluer in the UV slope than typical high-z galaxies at similar UV luminosities. We speculate that these numbers may require a larger main-sequence scatter or tail in the dwarf galaxy regime toward the starburst outliers.

Optical spectra in pure-silica-core single mode optical fibers after high-fluence reactor irradiation

The paper describes the study of radiation-induced attenuation (RIA) spectra in reactor-irradiated single mode at λ=1.55 μm optical fibers (OFs) with differente high-temperature coatings (polyimyde, aluminum and copper). The OFs were previously irradiated up to fast neutron fluence 1.8·1020 n/cm2 and gamma dose 2.32 GGy. After three years of storage at room temperature (RT), the RIA spectra were examined in the range of 650–1700 nm. All RIA mechanisms acting in this spectral range were identified: a tail of non-bridging oxygen hole center, a long-wavelength RIA (LWRIA) band with a maximum at λ > 1600 nm, unstructured “grey” loss due to coating microbendings or damage, and an absorption band peaking at 930 nm (E=1.33 eV). It was found out that the LWRIA can be significantly annealed at RT in polyimide-coated OFs. Grey loss were found to be more stable than those causing LWRIA.The LWRIA arising in reactor- and gamma-irradiated OFs have close thermal stability at RT and exhibit a similar shapes, which close to the absorption band of self-trapped holes (STH). This suggests a STH-like nature of the LWRIA.

Molecular Identification and Phylogenetic Analysis of Cymbidium Species (Orchidaceae) Based on the Potential DNA Barcodes matK, rbcL, psbA-trnH, and Internal Transcribed Spacer

Numerous Cymbidium species have significant commercial value globally due to their exotic ornamental flowers. Identifying Cymbidium species is challenging due to their similar shapes, which hinders their rational use and the conservation of germplasm resources. In the present study, firstly, four plastid loci (matK, rbcL, psbA-trnH, and atpF-atpH) and a nuclear locus (internal transcribed spacer, ITS) were initially examined to identify Cymbidium species. Secondly, we inferred the interspecific phylogeny of Cymbidium species using ITS sequences. All of these DNA regions, with the exception of atpF-atpH, could be readily amplified from Cymbidium, and the corresponding DNA sequences can be successfully obtained by sequencing. Our research demonstrated that ITS exhibited the highest intra- and interspecific divergences, the greatest barcoding gap, and the highest proportion of species identification. The phylogenetic analysis of Cymbidium species based on the ITS regions primarily corroborated the results obtained using traditional morphological methods. A comparative analysis of candidate DNA barcodes has shown that the ITS can be used not only for barcoding Cymbidium species but also for the phylogenetic analysis of Cymbidium.

Artificial neural network for preliminary design and optimisation of civil aero-engine nacelles

Abstract Within the context of preliminary aerodynamic design with low order models, the methods have to meet requirements for rapid evaluations, accuracy and sometimes large design space bounds. This can be further compounded by the need to use geometric and aerodynamic degrees of freedom to build generalised models with enough flexibility across the design space. For transonic applications, this can be challenging due to the non-linearity of these flow regimes. This paper presents a nacelle design method with an artificial neural network (ANN) for preliminary aerodynamic design. The ANN uses six intuitive nacelle geometric design variables and the two key aerodynamic properties of Mach number and massflow capture ratio. The method was initially validated with an independent dataset in which the prediction error for the nacelle drag was 2.9% across the bounds of the metamodel. The ANN was also used for multi-point, multi-objective optimisation studies. Relative to computationally expensive CFD-based optimisations, it is demonstrated that the surrogate-based approach with ANN identifies similar nacelle shapes and drag changes across a design space that covers conventional and future civil aero-engine nacelles. The proposed method is an enabling and fast approach for preliminary nacelle design studies.

Italian neonatal birthweight charts derived from INeS not separated by birth order

BackgroundIdentifying high-risk neonates with abnormal fetal growth is crucial for health risk prediction and early intervention. Small for gestational age (SGA) and large for gestational age (LGA) classifications highlight neonates having a higher risk for postnatal diseases. Accurate diagnosis depends on precise anthropometric measurements and appropriate reference data. In 2010, specific neonatal charts for Italian singletons (INeS charts) were published, tracing separately for first- and later-born neonates due to a 3% birth weight difference. We present INeS charts for birth weight non-separated by first- and later-born babies useful when information on parity is unavailable or unreliable, or for better comparisons with other neonatal charts that are not separated by birth-order.MethodsINeS charts were traced using a parametric function. Starting with the parameters estimates published in a different paper, INeS charts not separated by birth order were traced for the gestational age range of 23 to 42 weeks. In a second step the charts were parametrized as Cole and Green Lambda Mu and Sigma (LMS) model, allowing computation of standard deviation scores.ResultsThe centiles of non-separated INeS charts follow between first- and later-born charts. Distances varied due to changing first-born proportions with gestational age, Max differences of about 100g with later born and 70g with first-born were observed at term. S and L functions have a similar shape for boys and girls. S function shows a pick at about 29 weeks, L function has positive values in all the range of gestational age with a pick at 39 weeks.ConclusionsThe study presents non-separated Birth Weight INeS charts, bridging the gap when parity information is unavailable. Differences with separated charts were generally small, making them reliable for neonatal health assessment. Insights from L and S parameters contribute to standardized birth weight and adjust it by sex and Gestational Age, useful for defining SGA or LGA neonates. The paper enhances neonatal care tools, showcasing INeS chart flexibility in different clinical scenarios and supporting neonatology research.