Length Matching Research Articles

An analytical approach for designing sCO2 centrifugal compressors using the loss-integrated throughflow method

Several studies have focused on the analytical modeling of centrifugal compressors. These models are commonly used in design, optimization and evaluation of rotor geometry. Existing models, which rely on either the meanline method (1D model) or the streamline curvature-based throughflow method (2D model) combined with semi-empirical pressure loss relations, are closed-loop models that do not account for pressure loss distribution along the blade channel. Additionally, these models simplify the rotor’s three-dimensional geometry, focusing primarily on the β angle and meanline length. To address these limitations, we introduce an open-loop analytical approach called the ’loss-integrated throughflow method’ (LITM). This method computes pressure losses step-by-step along the blade’s channel geometry using the three-dimensional cross-section of the rotor as input data. The motivation behind this new approach is to develop an alternative tool for the preliminary design of supercritical CO2 (sCO2) compressors, providing insight into the relation between losses and rotor geometry beyond just the β angle and meanline length. In the present work we compare simulation results with a one-dimensional (1D) mathematical model that has been validated against experimental data for sCO2. We compare three sets of rotors, where each set shares identical β angles and meanline lengths. When compared against the 1D model, our model yields deviations ranging from 2.8% to 21.9% for rotors with matching meanline lengths and β angles. This suggests that factors other than the variables previously considered influence pressure losses. As a result of this study, we conclude that the proposed analytical model offers potential to refine the preliminary design for sCO2 rotors.

Effects of anther-stigma position on cross-pollination efficiency in a hermaphroditic plant.

Evolution of cross-pollination efficiency depends on the genetic variation of flower traits, the pollen vector, and flower trait matching between pollen donors and recipients. Trait matching has been almost unexplored among nonheterostylous species, and we examined whether the match of anther length in pollen donors and stigma length in pollen recipients influences the efficiency of cross-pollination. To explore potential constraints for evolutionary response, we also quantified genetic variation and covariation among sepal length, petal length and width, stamen length, style length, and herkogamy. We created 58 experimental arrays of Turnera velutina that varied in the extent of mismatch in the position of anthers and stigmas between single-flowered plants. Genetic variation and correlations among flower traits were estimated under greenhouse conditions. Style length, but not herkogamy, influenced the efficiency of cross-pollination. Plants with stamen length that matched the style length of other plants were more efficient pollen donors, whereas those with the style protruding above the stamens of other plants were more efficient pollen recipients. Significant broad-sense heritability (0.22 > hB 2 < 0.42) and moderate genetic correlations (0.33 > r < 0.85) among floral traits were detected. Our results demonstrated that anther-stigma mismatch between flowers contributed to variation in the efficiency of cross-pollination. The genetic correlations between stamen length and other floral traits suggests that any change in cross-pollination efficiency would be driven by changes in style rather than in stamen length.

Unravelling the Photoelectrochemical Water Splitting of Nanometer-Thick Carbon Nitride Layer.

Matching the thickness of the graphitic carbon nitride (CN) nanolayer with the charge diffusion length is expected to compensate for the poor intrinsic conductivity and charge recombination in CN for photoelectrochemical cells (PEC). Herein, the compact CN nanolayer with tunable thickness is in situ coated on carbon fibers. The compact packing along with good contact with the substrate improves the electron transport and alleviates the charge recombination. The PEC investigation shows CN nanolayer of 93nm-thick yields an optimum photocurrent of 116µAcm-2 at 1.23V versus RHE, comparable to most micrometer-thick CN layers, with a low onset potential of 0.2V in 1m KOH under 1 sun illumination. This optimum performance suggests the electron diffusion length matches with the thickness of the CN nanolayer. Further deposition of NiFe-layered double hydroxide enhanced the surface water oxidation kinetics, delivering an improved photocurrent of 210µAcm-2 with IPCE of 12.8% at 400nm. The CN nanolayer also shows extended potential in PEC organic synthesis. This work experimentally reveals the PEC behavior of the nanometer-thick CN layer, providing new insights into CN in the application of energy and environment-related fields.

Centrifuger: lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification

Centrifuger is an efficient taxonomic classification method that compares sequencing reads against a microbial genome database. In Centrifuger, the Burrows-Wheeler transformed genome sequences are losslessly compressed using a novel scheme called run-block compression. Run-block compression achieves sublinear space complexity and is effective at compressing diverse microbial databases like RefSeq while supporting fast rank queries. Combining this compression method with other strategies for compacting the Ferragina-Manzini (FM) index, Centrifuger reduces the memory footprint by half compared to other FM-index-based approaches. Furthermore, the lossless compression and the unconstrained match length help Centrifuger achieve greater accuracy than competing methods at lower taxonomic levels.

Hierarchical Cross Traffic Scheduling Based on Time-Aware Shapers for Mobile Time-Sensitive Fronthaul Network

To solve the problem of jitter and low network throughput caused by the impact of background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for background flows, named hierarchical crossover traffic scheduling mechanism based on time-aware shaper (HC-TAS) by improving the traditional counterpart. Then, in this new model, we designed an inbound scheduling algorithm based on frame length matching and an outbound scheduling algorithm based on queue status, making sure that smaller data frames will not be blocked by large data frames. This greatly improves the utilization of timeslots in the scheduling process and reduces the jitter impact of background flows. To verify its performance, we conducted experiments in a simulated fronthaul network conforming to IEEE 802.1CM. The experimental results show that, under the condition that the jitter is guaranteed to be zero, compared with two mainstream scheduling schemes, Comb-FITting and TAS + Preemption, our proposed scheme can achieve lower maximum end-to-end delay and higher link utilization. The proposed HC-TAS meets the requirements of low jitter and high bandwidth utilization in 5G fronthaul network, and the research results provide a technical basis for the application and development of general time-sensitive networks as well.

Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications

The engineering sector is undergoing digital transformation (DT) alongside shifts in labor patterns. This study concentrates on piping design within plant engineering, aiming to develop a system for optimal piping route design using artificial intelligence (AI) technology. The objective is to overcome limitations related to time and costs in traditional manual piping design processes. The ultimate aim is to contribute to the digitalization of engineering processes and improve project performance. Initially, digital image processing was utilized to digitize piping and instrument diagram (P&amp;ID) data and establish a line topology set (LTS). Subsequently, three-dimensional (3D) modeling digital tools were employed to create a user-friendly system environment that visually represents piping information. Dijkstra’s algorithm was implemented to determine the optimal piping route, considering various priorities during the design process. Finally, an interference avoidance algorithm was used to prevent clashes among piping, equipment, and structures. Hence, an auto-routing system (ARS), equipped with a logical algorithm and 3D environment for optimal piping design, was developed. To evaluate the effectiveness of the proposed model, a comparison was made between the bill of materials (BoM) from Company D’s chemical plant project and the BoM extracted from the ARS. The performance evaluation revealed that the accuracy in matching pipe weight and length was 105.7% and 84.9%, respectively. Additionally, the accuracy in matching the weight and quantity of fittings was found to be 99.7% and 83.9%, respectively. These findings indicate that current digitalized design technology does not ensure 100% accurate designs. Nevertheless, the results can still serve as a valuable reference for attaining optimal piping design. This study’s outcomes are anticipated to enhance work efficiency through DT in the engineering piping design sector and contribute to the sustainable growth of companies.

Clustering and optimization of nodes, beams and panels for cost-effective fabrication of free-form surfaces

Free-form surfaces are increasingly used in contemporary architectural designs for their unique and elegant shapes. However, fabricating these doubly curved surfaces using panel and frame systems presents challenges due to the shape variability of nodes, beams and panels. In this study, we propose a mesh-based computational design framework that clusters and optimizes these components together, reducing the shape variety of elements for free-form surfaces. Our method employs a vertex-based similarity metric to partition panels into user-defined groups and clusters beams based on edge lengths. A box-constrained optimization is introduced to achieve congruent faces and matching beam lengths while considering various functional constraints. Additionally, connection holes on node surfaces are clustered and optimized to allow their use at multiple locations. The practicality of our approach is demonstrated through the design and construction of a full-scale pavilion, resulting in a significant reduction in the shape variety of building elements.

The hidden fitness of the male zebra finch courtship song.

Vocal learning in songbirds is thought to have evolved through sexual selection, with female preference driving males to develop large and varied song repertoires1-3. However, many songbird species learn only a single song in their lifetime4. How sexual selection drives the evolution of single-song repertoires is not known. Here, by applying dimensionality-reduction techniques to the singing behaviour of zebra finches (Taeniopygia guttata), we show that syllable spread in low-dimensional feature space explains how single songs function as honest indicators of fitness. We find that this Gestalt measure of behaviour captures the spectrotemporal distinctiveness of song syllables in zebra finches; that females strongly prefer songs that occupy more latent space; and that matching path lengths in low-dimensional space is difficult for young males. Our findings clarify how simple vocal repertoires may have evolved in songbirds and indicate divergent strategies for how sexual selection can shape vocal learning.

Optimizing the measurement of sample entropy in resting-state fMRI data.

The complexity of brain signals may hold clues to understand brain-based disorders. Sample entropy, an index that captures the predictability of a signal, is a promising tool to measure signal complexity. However, measurement of sample entropy from fMRI signals has its challenges, and numerous questions regarding preprocessing and parameter selection require research to advance the potential impact of this method. For one example, entropy may be highly sensitive to the effects of motion, yet standard approaches to addressing motion (e.g., scrubbing) may be unsuitable for entropy measurement. For another, the parameters used to calculate entropy need to be defined by the properties of data being analyzed, an issue that has frequently been ignored in fMRI research. The current work sought to rigorously address these issues and to create methods that could be used to advance this field. We developed and tested a novel windowing approach to select and concatenate (ignoring connecting volumes) low-motion windows in fMRI data to reduce the impact of motion on sample entropy estimates. We created utilities (implementing autoregressive models and a grid search function) to facilitate selection of the matching length m parameter and the error tolerance r parameter. We developed an approach to apply these methods at every grayordinate of the brain, creating a whole-brain dense entropy map. These methods and tools have been integrated into a publicly available R package ("powseR"). We demonstrate these methods using data from the ABCD study. After applying the windowing procedure to allow sample entropy calculation on the lowest-motion windows from runs 1 and 2 (combined) and those from runs 3 and 4 (combined), we identified the optimal m and r parameters for these data. To confirm the impact of the windowing procedure, we compared entropy values and their relationship with motion when entropy was calculated using the full set of data vs. those calculated using the windowing procedure. We then assessed reproducibility of sample entropy calculations using the windowed procedure by calculating the intraclass correlation between the earlier and later entropy measurements at every grayordinate. When applying these optimized methods to the ABCD data (from the subset of individuals who had enough windows of continuous "usable" volumes), we found that the novel windowing procedure successfully mitigated the large inverse correlation between entropy values and head motion seen when using a standard approach. Furthermore, using the windowed approach, entropy values calculated early in the scan (runs 1 and 2) are largely reproducible when measured later in the scan (runs 3 and 4), although there is some regional variability in reproducibility. We developed an optimized approach to measuring sample entropy that addresses concerns about motion and that can be applied across datasets through user-identified adaptations that allow the method to be tailored to the dataset at hand. We offer preliminary results regarding reproducibility. We also include recommendations for fMRI data acquisition to optimize sample entropy measurement and considerations for the field.

A transmission electron microscopy study of the crystallographic characteristics of magnetite needles in plagioclase

The correct and precise crystal forms and the crystallographic orientation relationships (CORs) of ten main magnetite needle groups in the plagioclase host were unequivocally determined by transmission electron microscopy from &gt;100 selected magnetite needles with well defined shape orientations in petrographic thin sections of a gabbro core sample drilled from the Mid-Atlantic Ridge. The as-observed CORs of magnetite in plagioclase are in accordance with the optimal matching in the oxygen sublattices of the two structures via the close alignment between two sets of close-packed (c.p.) oxygen arrays parallel to {111}m in magnetite (m) and two sets of quasi-c.p. oxygen arrays parallel to (150)p, (150)p, (112)p, (312)p, (021)p or (121)p in plagioclase (p), as demonstrated for the first time in the accumulated oxygen number versus normal distance [from the (hkl) plane] plots. Such a simple oxygen sublattice matching principle does not rely on the length matching for the specific pair of lattice directions or on the d-spacing matching for the specific pair of lattice planes of the two structures, and therefore must be generally applicable for any mineral/oxide inclusions with a c.p. or quasi-c.p. oxygen sublattice formed via precipitation in open or closed systems. The topotaxial nuclei then undergo extended growth along the kinetically fast growth direction of the two structures with the most similar oxygen distribution patterns, i.e. along the normal direction of the aligned pair of oxygen arrays, thereby yielding the pronounced shape orientations such as magnetite needles in plagioclase.

Person group detection with global trajectory extraction in a disjoint camera network

Person group detection refers to the grouping of people with similar spatio-temporal trajectories. In this work, we address the problem of automatically detecting groups of people from disjoint camera views, which has an essential application in public safety but has not been seriously studied. The main challenge of this task is that the sparse distribution of cameras in a large surveillance area makes it difficult to infer and match people’s trajectories across cameras. To address this challenge, we propose a CCRF (Cyclic Conditional Random Fields) based model for cross-camera trajectory extraction, which takes both visual appearance and heterogeneous spatio-temporal information (including camera locations, video capture times, and the map of the surveillance area) as input and infers multiple candidate cross-camera trajectories for each person. Then, for each pair of people, we propose to use a dynamic trajectory warping (DTW) method to measure the similarity of their trajectories. DTW uses visual features to optimize the selection of trajectories and addresses the problem of trajectory length matching. Since there is no existing dataset that can directly support our research, we enrich our previously built Person Trajectory Dataset by adding the person group annotation and then verify the effectiveness of the proposed method on this dataset. The dataset and code are released at https://github.com/zhangxin1995/PTD_GROUP.

Low-loss and broadband wafer-scale optical interposers for large-scale heterogeneous integration.

We design, fabricate, and demonstrate a low-loss and broadband optical interposer with high misalignment tolerance for large-scale integration of many chips using thermal compression flip-chip bonding. The optical interposer achieves flip-chip integration with photonic integrated circuit die containing evanescent couplers with inter-chip coupling loss of 0.54dB and ±3.53μm 3-dB misalignment tolerance. The loss measurement spectrum indicated wavelength-insensitive loss across O-band and C-band with negligible spectral dependence. Further, we demonstrate 1 to 100 wafer-scale equal power splitting using equal power splitters (EPS) and a path length matching design fabricated using a wafer-scale fabrication technique.

Comparison of quartz and sapphire optical chambers for infrared laser sealing of vascular tissues using a reciprocating, side-firing optical fiber: Simulations and experiments.

Infrared (IR) lasers are being tested as an alternative to radiofrequency (RF) and ultrasonic (US) surgical devices for hemostatic sealing of vascular tissues. In previous studies, a side-firing optical fiber with elliptical IR beam output was reciprocated, producing a linear IR laser beam pattern for uniform sealing of blood vessels. Technical challenges include limited field-of-view of vessel position within the metallic device jaws, and matching fiber scan length to variable vessel sizes. A transparent jaw may improve visibility and enable custom treatment. Quartz and sapphire square optical chambers (2.7 × 2.7 × 25 [mm3 ] outer dimensions) were tested, capable of fitting into a 5-mm-OD laparoscopic device. A 1470 nm laser was used for optical transmission studies. Razor blade scans and an IR beam profiler acquired fiber (550-µm-core/0.22NA) output beam profiles. Thermocouples recorded peak temperatures and cooling times on internal and external chamber surfaces. Optical fibers with angle polished distal tips delivered 94% of light at a 90° angle. Porcine renal arteries with diameters of 3.4 ± 0.7 mm (n = 13) for quartz and 3.2 ± 0.7 mm (n = 14) for sapphire chambers (p > 0.05), were sealed using 30 W for 5 s. Reflection losses at material/air interfaces were 3.3% and 7.4% for quartz and sapphire. Peak temperatures on the external chamber surface averaged 74 ± 8°C and 73 ± 10°C (p > 0.05). Times to cool down to 37°C measured 13 ± 4 s and 27 ± 7 s (p < 0.05). Vessel burst pressures (BP) averaged 883 ± 393 mmHg and 412 ± 330 mmHg (p < 0.05). For quartz, 13/13 (100%) vessels were sealed (BP > 360 mmHg), versus 9/14 (64%) for sapphire. Computer simulations for the quartz chamber yielded peak temperatures (78°C) and cooling times (16 s) similar to experiments. Quartz is an inexpensive material for use in a laparoscopic device jaw, providing more consistent vessel seals and faster cooling times than sapphire and current RF and US devices.

Is team-level injury analysis giving us the full story? Exploring a player-specific approach to analysing injuries

ABSTRACT An examination of team-level and player-specific injury incidence in Rugby Union, using different match exposure calculations, Match time-loss injuries and match exposure using Global Positioning Systems (GPS) was collected across three seasons (2016/17–2018/19). Team-level and player-specific injury incidence were calculated using standard match length and GPS exposure. The probability of one or two or more injuries was calculated using the Poisson probability. A total of 487 injuries were sustained by 111 players. Team-level injury incidence across three seasons using standard match length was lower than the injury incidence using GPS (59.5 vs 95.7 injuries/1000 match hours, respectively). More than 84% of players fell outside the 95% confidence intervals for the team-level injury incidence each season. When exposed to a lower number of match hours, at the same incidence the probability of only one injury was higher. When exposed to a higher number of match hours, at the same incidence the probability of sustaining two or more injuries was higher. The standard match length underestimates the team-level injury incidence if the entire player cohort has not provided consent. In addition, team-level injury incidence is a poor representation of the underlying injury incidence of players.

Monolithic InAs/InP Quantum Dash Mode-Locked Lasers for Millimeter-Wave-Over-Fiber Mobile Fronthaul Systems

Semiconductor monolithic mode-locked lasers (MLLs) are potential solutions for generating high-speed optical pulses in future mobile fronthaul networks in the millimeter-wave (mmW) bands. Our previous studies have investigated using buried heterostructure (BH) quantum dash (QDash) multi-wavelength lasers for photonic mmW applications. Here we present results from monolithic chip-scale ridge waveguide QDash MLLs for generating and transmitting mmW signals. Through optimizing epitaxy growth, waveguide design, and fabrication process, the five-layer ridge waveguide QDash MLL exhibits superior performance with regard to the coherent comb bandwidths, lasing threshold current, output power, and internal quantum efficiency. The generated mmW frequency at 28.36 GHz exhibits excellent frequency stability, with a drift of less than ± 50 kHz. For the first time, we have utilized the free-running five-layer ridge waveguide QDash MLL to implement single- and dual-optical carrier modulation schemes in the millimeter-wave-over-fiber (mmWoF) systems. Both modulation schemes have achieved satisfactory performance achieving error vector magnitude (EVM) performance much lower than the 3GPP requirements (<12.5%) for future networks. In particular, the single-carrier modulation scheme achieves higher conversion efficiency and improved EVM performance. In contrast, the dual-carrier modulation scheme alleviates the path length matching challenges, offering a low-cost and easy-to-implement solution in different usage scenarios.

The evolution of flower-pollinator trait matching, and why do some alpine gingers appear to be mismatched?

Morphological matching between flower and pollinator traits has been documented in diverse plant lineages. Indeed, the matching of corolla tube length and pollinator tongue length has been cited repeatedly as a classic case of coevolution. However, there are many possible evolutionary routes to trait matching. Our aim here is both to review the evolutionary mechanisms of plant-pollinator trait matching and to investigate a specific case of trait matching/mismatching in a genus of alpine gingers. Roscoea gingers with long corolla tubes in the western Himalayas have pollinators with correspondingly long tongues, but the match between corolla tube and pollinator tongue lengths is not seen in the eastern Himalayas. Six floral traits were measured, including corolla tube depth, an internal trait controlling pollinator access to nectar. We calculated coefficients of variation and phylogenetically controlled correlation patterns of these traits in six Roscoea species in order to gain possible insights into stabilizing selection and modularization of these traits. The distal (nectar-containing) portion of the corolla tube exhibited lower coefficients of variations than did the basal portion. This is consistent with the hypothesis that pollinators mediate stabilizing selection on the distal, but not basal, portion of the corolla tube. This result, combined with phylogenetic data, suggests that the elevated liquid level of nectar in the distal tube evolved subsequent to dispersal into the eastern Himalayan region and loss of long-tongue pollinators. After accounting for phylogeny, corolla tube length, anther length, style length and labellum width were all intercorrelated. Corolla-tube depth was not part of this covariational module, however, suggesting separate adaptation to short-tongued pollinators. The reduction in functional corolla tube depth in the Roscoea appears to be related to the loss of long-tongued pollinators associated with dispersal to the eastern Himalayas and pollination by short-tongued pollinators. The apparent mismatch between floral tubes and pollinator tongues is a case of cryptic trait matching between flowers and pollinators, underscoring the importance of combining floral anatomy with pollination ecology in assessing plant-pollinator trait matching.

Tera-sample-per-second arbitrary waveform generation in a synthetic dimension

Synthetic dimension opens new horizons in quantum physics and topological photonics by enabling new dimensions for field and particle manipulations. The most appealing property of the photonic synthetic dimension is its ability to emulate high-dimensional optical behavior in a unitary physical system. Here we show that the photonic synthetic dimension can transform technical problems in photonic systems between dimensionalities, providing unexpected solutions to technical problems that are otherwise challenging. Specifically, we propose and experimentally demonstrate a fully reconfigurable photonic Galton board (PGB) in the temporal synthetic dimension, in which the temporal high-speed challenge is translated into a spatial fiber-optic length matching problem, leading to the generation of tera-sample-per-second arbitrary waveforms with ultimate flexibility. In the experiments, an arbitrary waveform with a widely tunable sampling rate, ranging from 10.42 GSa/s to a record high of 1.64 TSa/s, is demonstrated. The concept of dimension conversion offers possible solutions to various physical dimension-related problems, such as super-resolution imaging, high-resolution spectroscopy, and high-precision time measurement.

PBP and PSP promote β' form crystallization of palm oil, palm stearin, and a cocoa butter replacer

AbstractTo precisely regulate the crystallization of lipids, an in‐depth understanding of the correlation between the structures of the crystallization promoters and their functionalities is crucial. The effects of the crystallization promoters 1,3‐dipalmitoyl‐2‐behenoyl‐glycerol (PBP) and 1,3‐dipalmitoyl‐2‐stearoyl‐glycerol (PSP) on the crystallization behavior of palm oil, palm stearin, and a cocoa butter replacer were investigated by differential scanning calorimetry, polarized light microscopy, and X‐ray diffraction. The chain‐length difference between PSP and PBP resulted in different thermally stable polymorphs. PBP was stabilized in the β‐3L form, but PSP was stabilized in the β′‐2L form. The addition of PBP and PSP significantly promoted nucleation and led to an earlier onset of crystallization during cooling. After isothermal and nonisothermal crystallization, the PSP and PBP increased the melting temperatures of the palm oil and the cocoa butter replacer but decreased the melting temperature of the palm stearin, since PBP and PSP effectively promoted β′ formation but retarded the β' to β transformation. Due to the differences in chain length and subcell matching, palm stearin crystallizes on PSP and PBP via different modes.Practical Applications: PBP and PSP have potential as β'‐form crystallization promoters for plastic fats. This research indicated the possibility of regulating the nanostructures of fats by structural design of the crystallization promoters.

Wellness Responses During Different Length Match Microcycles in Collegiate Women’s Lacrosse

Wellness Responses During Different Length Match Microcycles in Collegiate Women’s Lacrosse

Mentor and mentee matching

Pedagogic systems are gaining traction in the provision of training, learning, and continuing professional development (often required to maintain professional qualifications). An essential element in pedagogic systems is the matching of teachers (mentors) and students (mentees). In this paper we present an intelligent context-aware learning system based on profile criteria developed using big data analytic solutions. The proposed system is designed to provide systematic support for mentors based on student profiles. The goal of the proposed system is to match the mentor profiles with the type of pedagogic system, the student profile, the student requirements, and the student’s goals and expectations. The proposed system is predicated on the use of fuzzy logic definitions with a maximal length matching algorithm using expert knowledge. The proposed system implements a mentor (teacher) and mentee (student) matching algorithm based on their profile criteria. The proposed system has been successfully tested by matching mentor and mentee profiles and preferences. Experimental results show that the proposed system can access multi-factorial mentor and mentee profiles, effectively match suitable mentors (teachers) with appropriate mentees (students), and meet the mentee expectations.