High Precision Research Articles

The Role of Preoperative Abdominal Ultrasound in the Preparation of Patients Undergoing Primary Metabolic and Bariatric Surgery: A Machine Learning Algorithm on 4418 Patients' Records.

The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined. Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables. Four thousand four hundred eighteen patients' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976. Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost-benefit analysis, is necessary to fully evaluate routine preoperative ultrasound's overall utility and economic impact in this patient population.

Right anterior insula ASL hypoperfusion as a diagnostic biomarker of prodromal and mild dementia with Lewy bodies: preliminary evidence using a Bayesian approach.

Identifying and validating a biomarker with high specificity in early-stage dementia with Lewy bodies (DLB) using a feasible method is crucial to enhance the current suboptimal diagnostic procedure. Previous research revealed abnormalities, including hypoperfusion in the right anterior insular cortex at group level, in prodromal DLB. Exploring hypoperfusion of the right anterior insula, at an individual-level and assessing its relevance as a potential imaging biomarker in early DLB, has, to our knowledge, not been investigated. Our preliminary study aims to assess the feasibility of the technique and to provide a methodological framework for further investigation. We assessed the feasibility and accuracy of the hypoperfusion of the right anterior insula per arterial spin labelling magnetic resonance imaging (ASL-MRI) as a diagnostic biomarker in early DLB and provided rough estimates of its sensitivity and specificity. Defining the region of interest based on previous research, we established the biomarker as the hypoperfusion of the right anterior insula. Discriminative and analytical performances were assessed in comparison to a control group of treatment-resistant depression patients. Bayesian diagnostic reasoning was employed to assess the biomarker diagnostic usability in early DLB in two scenarios: healthy elderly controls and mild cognitive impairment. Additionally, we updated probabilities by integrating data from the Mayo-clinic cognitive fluctuations scale and real-time quaking-induced conversion (RT-QuIC) α-synuclein data. Lastly, a whole-brain perfusion analysis of DLB patients was conducted to identify further brain regions with discriminative abilities. We successfully replicated the right anterior insular hypoperfusion (RAI-Hypo) in all DLB patients at the individual level. The overall sensitivity of the biomarker was 96%, and the specificity was 92%. Bayesian testing revealed the biomarker's highest performance in early-stage DLB with cognitive fluctuations, showcasing a diagnostic potential associated with a high precision and moderate accuracy. In a cognitively non-impaired population, the RAI-Hypo showed a limited usability and lacked in selectivity to qualify as a screening tool. The exploratory whole-brain analysis revealed perfect discriminative capacities in the bilateral anterior insulae and the left inferior parietal lobule. Further studies are needed to confirm our preliminary results. If performance is maintained in subsequent studies and is compared to a more suitable control population, the proposed biomarker may be eventually sufficient to discriminate early-stage DLB from non-DLB.

Harmonic Oscillator Staging Coordinates for Efficient Path Integral Simulations of Quantum Oscillators and Crystals.

Imaginary-time path integral (PI) is a rigorous quantum mechanical tool to compute static properties at finite temperatures. However, the stiff nature of the internal PI modes poses a sampling challenge. This is commonly tackled using staging coordinates, in which the free particle (FP) contribution of the PI action is diagonalized. We introduce novel and simple staging coordinates that diagonalize the entire action of the harmonic oscillator (HO) model, rendering it efficiently applicable to (exclusively) systems with harmonic character, such as quantum oscillators and crystals. The method is not applicable to fluids or systems with imaginary modes. Unlike FP staging, the HO staging provides a unique treatment of the centroid mode. We provide implementation schemes for PIMC and PIMD simulations in NVT ensemble. Sampling efficiency is assessed in terms of the precision and accuracy of estimating the energy and heat capacity of a one-dimensional HO and an asymmetric anharmonic oscillator (AO). In PIMC, the HO coordinates propose collective moves that perfectly sample the HO contribution, then (for AO) the residual anharmonic term is sampled using standard Metropolis method. This results in a high acceptance rate and, hence, high precision, in comparison to the FP staging. In PIMD, the HO coordinates naturally prescribe definitions for the fictitious masses, yielding equal frequencies of all modes when applied to the HO model. This allows for a substantially larger time step sizes relative to standard staging, without affecting accuracy or integrator stability. For completeness, we also present results using normal mode (NM) coordinates, based on both HO and FP models. While staging and NM coordinates show similar performance (for FP or HO), staging is computationally preferable due to its cheaper scaling with the number of beads. The simplicity and the enhanced sampling gained by the HO coordinates open avenues for efficient estimation of nuclear quantum effects in more complex systems with harmonic character, such as real molecular bonds and quantum crystals.

Fast and accurate distal locking of interlocked intramedullary nails using computer-vision and a 3D printed device

IntroductionDistal locking is a challenging and time-consuming step in interlocked intramedullary nailing of long bone fractures. Current methods have limitations in terms of simplicity, universality, accuracy, speed, and safety. We propose a novel device and software for distal locking using computer vision.Methods and materialsThe device consists of an universal ancillary clamp, a telescopic arm, a viewfinder clamp, and a radio-opaque cross. The software uses a camera photo from the C-arm intensifier and adjusts for geometric projection deformities. The software employs edge detection, Hough transform, perspective interpolation, and vector calculation algorithms to locate the distal hole center. The device and software were designed, manufactured, and tested using 3D CAD, FEM, DRR, and performance testing on phantom bones.ResultsThe device and software showed high accuracy and precision of 98.7% and 99.2% respectively in locating the distal hole center and calculating the correctional vector. The device and software also showed high success ratio in drilling the hole and inserting the screw. The device and software reduced the radiation exposure for the surgeon and the patient. The success ratio of the device and software was validated by the physical testing, which simulated the real clinical scenario of distal locking. The radiation exposure was as low as 5 s with a radiation dose of 0.2mSv, drastically reducing radiation exposure during distal locking.DiscussionOur device and software have several advantages over other distal locking methods, such as simplicity, universality, accuracy, speed, and safety. Our device and software also have some disadvantages, such as reliability and legislation. Our device and software can be compared with other distal locking methods based on these criteria. Our device and software have some limitations and challenges that need to be addressed in the future, such as clinical validation, and regulatory approval.ConclusionThe device showed promising results in terms of low-cost, reusability, low radiation exposure, high accuracy, fast distal locking, high stiffness, and adaptability. The device has several advantages over other distal locking techniques, such as free-hand technique, mechanical aiming devices, electromagnetic navigation systems, and computer-assisted systems. We believe that our device and software have the potential to revolutionize the distal locking technique and to improve the outcomes and quality of life of the patients with long bone fractures.

Study on ultra-precision diamond cutting of polymers: Factors affecting dimensional accuracy and material removal mechanism

Polymers with surface microstructure have promising prospects for applications in the domains of aerospace, integrated circuits, and optical engineering. Ultra-precision cutting has unique advantages in the preparation of microstructure with high precision and complex shape. However, the inherent characteristics of polymers such as high elasticity, strong toughness, and poor thermal conductivity bring ultra-precision cutting a great challenge. In this study, the rectangular groove microstructures on polymers were fabricated by ultra-precision diamond cutting, and the influence of matrix material, feedrate and cutting depth on cutting performance and dimensional accuracy was quantitatively evaluated. The results indicate that the polyimide (PI) exhibits a good machinability compared with polyetheretherketone (PEEK) and polytetrafluoroethylene (PTFE). In addition, the feedrate have a negligible influence on the morphologies and dimensional accuracy of groove structure, while the groove width decreases and the ridge width increases as the cutting depth increases from 10 μm to 100 μm. The groove structure has the best dimensional accuracy when the cutting depth is 10 μm. Furthermore, the material removal mechanism of PI was discussed detailedly based on the results of numerical simulation and experiment.

DNA-binding factor footprints and enhancer RNAs identify functional non-coding genetic variants

BackgroundGenome-wide association studies (GWAS) have revealed a multitude of candidate genetic variants affecting the risk of developing complex traits and diseases. However, the highlighted regions are typically in the non-coding genome, and uncovering the functional causative single nucleotide variants (SNVs) is challenging. Prioritization of variants is commonly based on genomic annotation with markers of active regulatory elements, but current approaches still poorly predict functional variants. To address this, we systematically analyze six markers of active regulatory elements for their ability to identify functional variants.ResultsWe benchmark against molecular quantitative trait loci (molQTL) from assays of regulatory element activity that identify allelic effects on DNA-binding factor occupancy, reporter assay expression, and chromatin accessibility. We identify the combination of DNase footprints and divergent enhancer RNA (eRNA) as markers for functional variants. This signature provides high precision, but with a trade-off of low recall, thus substantially reducing candidate variant sets to prioritize variants for functional validation. We present this as a framework called FINDER—Functional SNV IdeNtification using DNase footprints and eRNA.ConclusionsWe demonstrate the utility to prioritize variants using leukocyte count trait and analyze variants in linkage disequilibrium with a lead variant to predict a functional variant in asthma. Our findings have implications for prioritizing variants from GWAS, in development of predictive scoring algorithms, and for functionally informed fine mapping approaches.

The completeness of accreting neutron star binary candidates from Chinese Space Station Telescope

Abstract Neutron star (NS) has many extreme physical conditions, and one may obtain some important informations about NS via accreting neutron star binary (ANSB) systems. The upcoming Chinese Space Station Telescope (CSST) provides an opportunity to search for a large sample of ANSB candidates. Our goal is to check the completeness of the potential ANSB samples from CSST data. In this paper, we generate some ANSBs and normal binaries under CSST photometric system by binary evolution and binary population synthesis method and use a machine learning method to train a classification model. Although the Precision (94.56 %) of our machine learning model is as high as before study, the Recall is only about 63.29 %. The Precision/Recall is mainly determined by the mass transfer rate between the NSs and their companions. In addition, we also find that the completeness of ANSB samples from CSST photometric data by the machine learning method also depends on the companion mass and the age of the system. ANSB candidates with low initial mass companion star (0.1 M⊙ to 1 M⊙) have a relatively high Precision (94.94 %) and high Recall (86.32 %), whereas ANSB candidates with higher initial mass companion star (1.1 M⊙ to 3 M⊙) have similar Precision (93.88 %) and quite low Recall (42.67 %). Our results indicate that although the machine learning method may obtain a relative pure sample of ANSBs, a completeness correction is necessary for one to obtain a complete sample.

Automatic Identification and Classification of Surface Defects in Small-Sized Optics

Abstract Precision optics are widely used in lighting systems, imaging systems and high precision inspection equipment. The presence of surface defects in optical components can seriously affect the design performance of the equipment, so the optical components must be rigorously inspected to eliminate defective optical components. Currently, engineering products are moving toward smaller sizes, resulting in smaller optical elements. However, realizing small-sized optical elements is a great challenge because it requires micrometer-scale high-resolution image acquisition and automatic detection of defects on their surfaces. A machine learning-based surface defect detection method is proposed for a wide variety of surface defects and small sizes. A dark-field micro-scattering imaging system is used to acquire dark-field images. Then image segmentation and feature analysis are performed on each image to extract the original feature data and compressed with relifF algorithm. Based on the compressed feature data, a classification model is built using a support vector mechine(SVM). The detection method can classify three kinds of defects, namely, dig, scratch, and scuff mark, with an accuracy of up to 98%. The experimental results of this study show that the method can effectively and accurately detect several microdefects occurring in small-size optical components, thus providing valuable insights for the optimization of mass production parameters of optical components.

FC-YOLO: An aircraft skin defect detection algorithm based on multi-scale collaborative feature fusion

Abstract Aircraft skin defects pose a threat to the safety and airworthiness of the aircraft. The front line of engineering has requirements of high precision and stable defect detection, which cannot be met by existing deep learning methods, due to conflicting information between multi-scale features. Herein, a Fine-Coordinated YOLO (FC-YOLO) algorithm is proposed to detect aircraft skin defects. Firstly, the ELAN-C module with Coordinate Channel Attention mechanism is applied to the backbone network to enhance multi-scale detection precision. Secondly, the Adaptive-Path Aggregation Network structure is proposed to make features containing more information by adding a shortcut weighted by the Adaptively Spatial Feature Fusion (ASFF) module. The ASFF adaptively allocates the weights of features with different sizes to reduce the inconsistency of features between different levels during feature fusion to improve detection precision. Finally, the SCYLLA-IoU loss function is introduced to calculate the directional loss between the bounding box and the ground truth box to elevate the stability of the training. Experiments are executed with a self-constructed ASD-DET dataset and the public NEU-DET dataset. Results show that the mAP of FC-YOLO is improved by 3.1% and 2.7% compared to that of the original YOLOv7 on the ASD-DET dataset and the NEU-DET dataset. In addition, on the ASD-DET dataset and NEU-DET dataset, the mAP of FC-YOLO was higher than that of YOLOv8, RT-DETR by 1.4%, 1.6% and 2.2%, 3.8%, respectively. By which, it is shown that the proposed FC-YOLO algorithm is promising for the future automatic visual inspection of aircraft skin.

Development of Wafer Bonding System for High Precision Bonding Alignment

Development of Wafer Bonding System for High Precision Bonding Alignment

From haystack to high precision: advanced sequencing methods to unraveling circulating tumor DNA mutations

Identifying mutations in cancer-associated genes to guide patient treatments is essential for precision medicine. Circulating tumor DNA (ctDNA) offers valuable insights for early cancer detection, treatment assessment, and surveillance. However, a key issue in ctDNA analysis from the bloodstream is the choice of a technique with adequate sensitivity to identify low frequent molecular changes. Next-generation sequencing (NGS) technology, evolving from parallel to long-read capabilities, enhances ctDNA mutation analysis. In the present review, we describe different NGS approaches for identifying ctDNA mutation, discussing challenges to standardized methodologies, cost, specificity, clinical context, and bioinformatics expertise for optimal NGS application.

Femtosecond Laser‐Induced Regulation of Photo‐ and Persistent Luminescence of Perovskite Crystals

AbstractManipulation of photoluminescence (PL) and persistent luminescence (PersL) provides a powerful tool for anti‐counterfeiting applications. Here, Sb3+‐doped CsCdCl3 perovskite single crystals (SCs) can be selectively irradiated via utilizing ultra‐fast femtosecond (fs) laser, creating tunable PL colors and PersL duration with high precision. The PL color of the synthesized SCs changes from cyan to orange along with the wavelength of the fs laser, for the successful regulation of the optical procedure from a single‐photon to a two‐photon absorption process. Moreover, an orange PersL of CsCdCl3:Sb3+ SC is observed after being charged with a fs laser, and the corresponding duration time can be feasibly controlled with the pump wavelength. In particular, CsCdCl3:Sb3+ is capable of ultrafast carrier capture (1 s) under fs laser compared to ultraviolet lamp pre‐irradiation enabling a high‐resolution micro‐PersL in photon trapping/de‐trapping modes. These findings not only give a new solution for the fabrication high‐resolution micro‐PL and trajectory‐writing micro‐PersL patterns, but also provide a deep insight to understand the photon–matter interactions.

Investigation of process parameters of electrohydrodynamic jetting for 3D printed PCL fibrous scaffolds with complex geometries

Tissue engineering is a promising technology in the field of regenerative medicine with its potential to create tissues de novo. Though there has been a good progress in this field so far, there still exists the challenge of providing a 3D micro-architecture to the artificial tissue construct, to mimic the native cell or tissue environment. Both 3D printing and 3D bioprinting are looked upon as an excellent solution due to their capabilities of mimicking the native tissue architecture layer-by-layer with high precision and appreciable resolution. Electrohydrodynamic jetting (E-jetting) is one type of 3D printing, in which, a high electric voltage is applied between the extruding nozzle and the substrate in order to print highly controlled fibres. In this study, an E-jetting system was developed in-house for the purpose of 3D printing of fibrous scaffolds. The effect of various E-jetting parameters, namely the supply voltage, solution concentration, nozzle-to-substrate distance, stage (printing) speed and solution dispensing feed rate on the diameter of printed fibres were studied at the first stage. Optimized parameters were then used to print Polycaprolactone (PCL) scaffolds of highly complex geometries, i.e., semi-lunar and spiral geometries, with the aim of demonstrating the flexibility and capability of the system to fabricate complex geometry scaffolds and biomimic the complex 3D micro-architecture of native tissue environment. The spiral geometry is expected to result in better cell migration during cell culture and tissue maturation.

Determination of ivermectin in plasma and whole blood using LC-MS/MS

Background Ivermectin is a widely used drug for the treatment of helminthiasis and filariasis worldwide, and it has also shown promise for malaria elimination through its potent mosquito-lethal activity. The objective of this study was to develop and validate a high-throughput and sensitive method to quantify ivermectin in plasma and whole blood samples, using automated sample extraction followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Methods Phospholipids were removed in patient whole blood (100 µl) and plasma (100 µl) samples using a 96-well plate Hybrid-solid phase extraction technique. Ivermectin and its isotope-labelled internal standard (ivermectin-D2) were separated on an Agilent Poroshell 120 EC-C18 50mm × 3.0mm I.D. 2.7µm, using a mobile phase of acetonitrile: ammonium formate 2 mM containing 0.5% formic acid (90: 10, v/v). Detection was performed using a triple quadrupole mass spectrometer in the positive ionization mode. Results The method was validated in the concentration range 0.970 - 384 ng/ml in both plasma and whole blood matrices. Intra- and inter-batch precisions during the validation were below 15%. There was no carryover or matrix effects detected. Ivermectin is a stable compound and results showed no degradation in the different stability tests. Conclusions The validated method proved to have high sensitivity and precision, good selectivity and to be suitable for clinical application or laboratory quantification of ivermectin in plasma or whole blood samples.

Can isometric testing substitute for the one repetition maximum squat test?

When measuring maximum strength, a high accuracy and precision is required to monitor the training adaptations. Based on available reliability parameters, the literature suggests the replacement of the one repetition maximum (1RM) by isometric testing to save testing time. However, from a statistical point of view, correlation coefficients do not provide the required information when aiming to replace one test by another. Therefore, the literature suggests the inclusion of the mean absolute error (MAE), the mean absolute percentage error (MAPE) for agreement analysis. Consequently, to check the replaceability of 1RM testing methods, the current study examined the agreement of isometric and dynamic testing methods in the squat and the isometric mid-thigh pull. While in accordance with the literature, correlations were classified high r = 0.638-0.828 and ICC = 0.630-0.828, the agreement analysis provided MAEs of 175.75-444.17 N and MAPEs of 16.16-57.71% indicating an intolerable high measurement error between isometric and dynamic testing conditions in the squat and isometric mid-thigh pull. In contrast to previous studies, using MAE, MAPE supplemented by CCC and BA analysis highlights the poor agreement between the included strength tests. The recommendation to replace 1RM testing with isometric testing routines in the squat does not provide suitable concordance and is not recommended.

Geometry accuracy control in abrasive water jet taper hole machining of ultra‐thick carbon fiber‐reinforced polymer (CFRP) laminates

AbstractThe primary factors affecting the geometric accuracy of abrasive water jet (AWJ) machining of ultra‐thick carbon fiber‐reinforced polymer (CFRP) laminates are the cutting front drag and kerf width deviation caused by energy dissipation. Firstly, this study comprehensively analyzes the influence of the coupling relationship between cutting front drag and kerf width deviation on the geometric accuracy of hole machining. Secondly, a gradient distribution theory for jet traverse speed with cutting depth is proposed for taper hole machining characteristics. Finally, a general geometric error model applicable to both straight and taper hole machining of ultra‐thick CFRP laminates using AWJ is established, along with a geometric error compensation method. A series of experiments validate the accuracy of the proposed geometric error model and compensation method. The novelty of this research lies in unifying the geometric error models for straight and taper hole machining of ultra‐thick CFRP laminates by considering the gradient distribution of jet traverse speed. The proposed error compensation method reduces the high degree of freedom required for machine tools. This study provides a general geometric error model and compensation strategy for AWJ hole machining of ultra‐thick CFRP laminates, which has significant engineering value for achieving 3D controllable AWJ machining of complex ultra‐thick CFRP components.Highlights The high geometric precision taper holes machining technique is a necessary prerequisite for achieving precise machining of complex trajectories in ultra‐thick CFRP with abrasive water jet. The influence of the coupling relationship between cutting front drag and kerf taper on the geometric accuracy of hole processing is comprehensively analyzed. A model considering the gradient distribution of traverse speed during taper holes machining was established, and a geometric error model considering this gradient distribution of traverse speed was developed. A taper holes machining geometric error compensation method with high engineering applicability was proposed. Geometric error prediction experiments and error compensation experiments were conducted, and the results proved the accuracy of the geometric error model and error compensation method.

Lead-free ferroelectrics with giant unipolar strain for high-precision actuators

The trade-off between electrostrain and strain hysteresis for piezo/ferroelectric materials largely restrains the development of high precision actuators and remains unresolved over the past few decades. Here, a simple composition of (Bi0.5Na0.5)1-x/100Srx/100TiO3 in the ergodic relaxor state is collaboratively designed through the segregated domain structure with the ferroelectric core, local polarization heterogeneity, and defect engineering. The ferroelectric core can act as a seed to facilitate the field-induced nonpolar-to-polar transition. Together with the internal bias field caused by defect dipoles and adjusted through electric field cycling and heat treatment technology, a giant unipolar strain of 1.03% is achieved in the x = 30 ceramic with a low hysteresis of 27%, while the electric-field-independent large-signal piezoelectric strain coefficient of ~1000 pm/V and ultralow hysteresis of <10% can be obtained in the x = 35 ceramic. Intriguingly, the low-hysteresis high strain also exhibits near-zero remnant strain, excellent temperature and cycling stability.

A comprehensive review on fructosyl peptide oxidase as an important enzyme for present hemoglobin A1c assays.

Glycated proteins are generated by binding of glucose to the proteins in blood stream through a nonenzymatic reaction. Hemoglobin A1c (HbA1c) is a glycated protein with glucose at the N-terminal of β-chain. HbA1c is extensively used as an indicator for assessing the blood glucose concentration in diabetes patients. There are different conventional clinical methods for the detection of HbA1c. However, enzymatic detection method has newly obtained great attention for its high precision and cost-effectiveness. Today, fructosyl peptide oxidase (FPOX) plays a key role in the enzymatic measurement of HbA1c, and different companies have marketed HbA1c assay systems based on FPOX. Recent investigations show that FPOX could be used in assaying HbA1 without requiring HbA1c primary digestion. It could also be applied as a biosensor for HbA1c detection. In this review, we have discussed the recent improvements of FPOX properties, different methods of FPOX purification, solubility, and immobilization, and also the use of FPOX in HbA1c biosensors.

Universal Quantum Fisher Information and Simultaneous Occurrence of Landau‐Class and Topological‐Class Transitions in Non‐Hermitian Jaynes‐Cummings Models

AbstractLight‐matter interactions provide an ideal testground for interplay of critical phenomena, topological transitions, quantum metrology, and non‐Hermitian physics with high controllability and tunability. The present work considers two fundamental non‐Hermitian Jaynes‐Cummings models in light‐matter interactions that possess real energy spectra in parity‐time (PT) symmetry and anti‐PT symmetry. The quantum Fisher information is shown to be critical around the transitions at the exceptional points and exhibit a super universality, with respect to different parameters, all energy levels, both models, symmetric phases, and symmetry‐broken phases, which guarantees a universally high measurement precision in quantum metrology. In particular, the transitions are found to be both symmetry‐breaking Landau‐class transitions (LCTs) and symmetry‐protected topological‐class transitions (TCTs), thus realizing a simultaneous occurrence of critical LCTs and TCTs that are conventionally incompatible due to contrary symmetry requirements. Besides establishing a paradigmatic case to break the incompatibility of the LCTs and the TCTs in non‐Hermitian systems, the both availabilities of the sensitive critical feature and the robust topological feature can also provide more potential for designing quantum devices or sensors.

Mechanical Characterization of Sisal Fiber Reinforced PP Composite Panels

ABSTRACT This study investigates the mechanical properties of single and double-layer woven sisal mat-reinforced PP composite panels. Sisal fibers were extracted using the manual decortication method, resulting in fibers with a density of 1.43 g/cm3 and a diameter ranging from 0.4 mm to 0.6 mm. To improve the bonding between the sisal fibers and the matrix, the fibers were hand-spun into yarn and woven into mats. The study focuses on the unique material combination and the use of sisal as a natural fiber reinforcement. The 18 mm thick panels were tested for water absorption following ASTM D570, compression strength, and tensile strength following ASTM D3039 using the UTES-100 High Precision universal strength tester machine. Composite panels with single layers of 10% and 15% woven fabric mat, loaded with 8 kg and 10 kg, exhibited compressive strengths of 11.6KN and 12.5KN, respectively. Panels reinforced with two layers of 20% and 30% sisal woven fabric mat, loaded with 8 kg and 10 kg, had compression strengths of 12.2KN and 12.5KN, respectively. Moreover, composite samples with 15% single layer and 30% double-layer sisal woven fabric mat demonstrated a equal compression strength of 12.5KN, falling within the range recommended by ISO13006:2012. The tensile strength of 16.99MPa, although slightly below the recommended ISO13006 value of 20MPa for commercial-grade panels, indicates promising results. The study’s findings suggest that higher fiber content and additional reinforcement layers lead to increased compression and tensile strength. Furthermore, the moisture absorption rate of the developed composite panels was significantly lower than the 0.5% water absorption rate authorized by the American National Standard Institute.