Minimum Size Research Articles

Facile Synthesis and Characterization of Fluorescent Polystyrene Nanospheres for Homogeneous Light-Initiated Chemiluminescence Immunoassay.

Homogeneous light-initiated chemiluminescence technology (LICA) is widely used in clinical diagnostics due to the advantages of high sensitivity, minimal reagent usage, and no need for washing. Luminescent microspheres receive singlet oxygen emitted by photosensitive microspheres to generate optical signals. Therefore,1O2-initiated luminescent nanospheres are crucial, but there are few reports on the preparation of 1O2-initiated luminescent nanospheres. Herein, monodisperse luminescent Eu/C-28@PS (Eps) nanospheres were prepared and optimized using chelate Eu (TTA)3phen and 4-(2-phenyl-5,6-dihydro1,4-oxathiin-3-yl)-N, N-ditetradecylbenzenamine (C-28) as probe dye via THF/water swelling-shrinking procedure. Various swelling parameters were studied to obtain the swelling conditions that produce the minimum particle size and narrow size distribution, which shows good results in uniform particle size distribution (~ 250nm, a PDI of 0.03), surface carboxylate content (1.18mmol/g), and BSA loading capability (129.8mg/g) in the case of 20mg total probe dosage and 2h of incubation at 40°C using 14% THF/water mixture as a co-solvent system. The composition of the entrapped probe has a gain effect on the 1O2-initiated fluorescent signal and the optimal ratio of Eu (TTA)3phen: C-28 (1:1) was obtained on a commercial analyzer using IgG and anti-human IgG as models in PBS buffer. These results indicate that monodisperse luminescent Eps nanospheres are suitable as light-initiated chemiluminescence sensors and have great application potential in early detection, screening tests, and prognostic evaluation of patients.

Coexistence through sustainable conservation strategies for sitatunga Tragelaphus spekii in African ecosystems

Sitatunga Tragelaphus spekii is an antelope species adapted to the dense swamps and marshes of Sub‐Saharan Africa, where traditional population survey techniques have been ineffective and encountered difficulties in making estimations. The species formerly occurred alongside waterways throughout the lowland forest zone of West and central Africa, extending into swamp systems in the savanna zones of central, East, and southern Africa. In most parts of Africa, the sitatunga population is declining, and attracting the attention of conservationists. Furthermore, its geographical range has been recorded to have shrunk. The present study reviewed major threats to sitatunga, assessed previous and current management approaches, and proposed new approaches to effectively manage its declining populations in Africa. To achieve the study objectives, published literature, reports, online information, expert knowledge, and personal experience were reviewed to acquire relevant information. Results indicated that sitatunga are threatened due to increased habitat loss, population isolation, political instability, water level changes, habitat fragmentation, illegal hunting, and diseases. Current wildlife management approaches raise many doubts as to their effectiveness. National‐level management may unsustainably segment management actions while the protected area approach manages only part of the range of wildlife. The current tenure system in most parts of Africa discourages human–wildlife co‐existence, whereas human–wildlife conflict management approaches only treat the symptoms and not the root cause of the problems. If wildlife, including sitatunga, are to persist in Africa, management approaches should be changed and include re‐focusing of the management context at the ecosystems and landscape level; assessing the genetic diversity of sitatunga; promoting better wetland management, including the aspect of human dimension in management; using non‐invasive techniques to genetically estimate the minimum population size; assessing inbreeding; and enhancing the implementation strategy of wildlife policy in African countries. Changing the attitude of the local community may take time, but it is a pivotal point if humans and wildlife are to coexist.

Super‐Resolved Protein Imaging Using Bifunctional Light‐Up Aptamers

AbstractEfficient labeling methods for protein visualization with minimal tag size and appropriate photophysical properties are required for single‐molecule localization microscopy (SMLM), providing insights into the organization and interactions of biomolecules in cells at the molecular level. Among the fluorescent light‐up aptamers (FLAPs) originally developed for RNA imaging, RhoBAST stands out due to its remarkable brightness, photostability, fluorogenicity, and rapid exchange kinetics, enabling super‐resolved imaging with high localization precision. Here, we expand the applicability of RhoBAST to protein imaging by fusing it to protein‐binding aptamers. The versatility of such bifunctional aptamers is demonstrated by employing a variety of protein‐binding aptamers and different FLAPs. Moreover, fusing RhoBAST with the GFP‐binding aptamer AP3 facilitates high‐ and super‐resolution imaging of GFP‐tagged proteins, which is particularly valuable in view of the widespread availability of plasmids and stable cell lines expressing proteins fused to GFP. The bifunctional aptamers compare favorably with standard antibody‐based immunofluorescence protocols, as they are 7‐fold smaller than antibody conjugates and exhibit higher bleaching‐resistance. We demonstrate the effectiveness of our approach in super‐resolution microscopy in secondary mammalian cell lines and primary neurons by RhoBAST‐PAINT, an SMLM protein imaging technique that leverages the transient binding of the fluorogenic rhodamine dye SpyRho to RhoBAST.

Steiner 3-Wiener Index of Zigzag Polyhex Nanotubes.

Let G be a connected graph and S be a k element subset of the vertex set V(G) of G. Steiner distance is a natural generalization of the usual graph distance. The Steiner-k distance dG(S) between the vertices of S is the minimum size among all connected subgraphs whose vertex set contains S. The generalized indices based on Steiner distances have several applications in the real world. It is a well-known fact that "Steiner Problem" is NP-complete and hence any parameter based on Steiner distance is also an NP problem. The objective of this work is to determine the Steiner 3-Wiener index for an important chemical structure called the zigzag polyhex nanotube. In this paper, we present an algorithm for computing the Steiner 3-Wiener index (SW3) for zigzag polyhex nanotubes. The developed algorithm addresses the complexities associated with exponential increments in the number of vertices as the nanotube's circumference or length expands. The obtained SW3 values for zigzag polyhex nanotubes can be used for Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) analyses. We have presented an algorithm and listed the numerical values of SW3 for various parameters of circumference and length of a zigzag polyhex nanotube to facilitate their utilization in QSAR/ QSPR analyses. We have obtained the time complexity for the algorithm, which shows that the SW3 values are computationally intensive. To explain this complex nature, we have used multiple linear regression to fit log SW3 values corresponding to log p and log q, the radius and length of a nanotube. The algorithm addresses the complexities associated with the exponential increase in vertices as the nanotube's circumference or length expands. Furthermore, we provide SW3 values for various parameter combinations up to circumference or length 17, and a general relation to determine the value of SW3, facilitating its utilization in real-world applications. These values serve as crucial descriptors for understanding the structural nuances of zigzag polyhex nanotubes, that find applications in material science, drug design, drug discovery, etc.

INFLUENCE OF ONLINE REVIEWS ON CONSUMERS' HOTEL BOOKING INTENTIONS IN THAILAND: TRUST AND VALUE AS MEDIATING FACTOR

Purpose: The objective of this study is to explore the influence of online reviews on hotel booking intentions among consumers in Thailand, considering the mediating effects of trust and perceived value. Theoretical Framework: The Online Reviews (OR) construct, adapted from Wen et al. (2021), and the Trust (TRT) construct, assessed with measures from Ladhari and Michaud (2015). The Trust scale included four slightly modified items aligned with study objectives. The Value (VAL) construct was evaluated using measures from S. Y. Kim et al. (2017). Lastly, Booking Intention (BI) was assessed using four aspects adopted from Chakraborty and Biswal (2019). Design/methodology/approach: This study investigates the impact of online reviews on hotel booking intentions, employing trust and value as mediating factors. Utilizing a quantitative design through a survey conducted in Thailand, purposive sampling was employed to ensure diversity, with a minimum sample size of 379 determined to achieve a 0.05% sampling error at 95% confidence. Statistical methods, including a 5-point Likert scale, were utilized for data analysis, measure validation, and model reliability assessment, employing SEM analysis with ADENCO software. Descriptive statistics offered insights, contributing to a comprehensive understanding of the factors influencing individuals in Thailand when initiating and managing social entrepreneurial ventures. The study's methodology ensures robustness, reliability, and addresses potential biases through thorough sampling, statistical techniques, and validation procedures. Findings: The results emphasize the substantial influence of online reviews on trust, value perception, and hotel booking intentions. Demographic insights reveal sample characteristics and response variations. These findings deepen our understanding of factors influencing consumers' decisions in hotel booking. Research, Practical & Social implications: The demographic analysis conducted in this study reveals a gender distribution of 27.5% male and 72.5% female participants, primarily aged over 55 (49.1%), with 67.5% holding bachelor's degrees and earning between 30,001-50,000 baht (35.4%). Notably, civil servants and state enterprise employees dominate the occupational landscape (44%). Employing structural equation modeling (SEM), the study confirms that trust and value perception mediate the relationship. It elucidates significant connections between online reviews and trust, online reviews and value perception, and trust and booking intentions. The model remarkably clarifies a substantial portion of the variance in the dependent variables, ranging from 53.5% to 65.7%, highlighting the influential role of online reviews in shaping trust, value perception, and booking intentions. This study delves into the impact of online reviews on hotel booking intentions, with a specific focus on trust and value perception as mediators. Key findings encompass: 1) Online reviews significantly influence consumers' hotel booking intentions, playing a pivotal role in decision-making. 2) Trust and value perception mediate the relationship between online reviews and booking intentions, underscoring their profound impact on consumer behavior. 3) Employing a quantitative research design and survey data collection, the study provides systematic insights from a diverse participant sample. 4) The research not only supports existing literature on online reviews, trust, value perception, and hotel booking intentions but also contributes novel insights to these domains. Originality/Value: This study uncovers essential roles of online reviews, trust, and value perception in hotel booking, enlightening practitioners and researchers on digital-era consumer behavior.

SMALL OBJECT DETECTION APPROACH BASED ON ENHANCED SINGLE-SHOT DETECTOR FOR DETECTION AND RECOGNITION OF INDONESIAN TRAFFIC SIGNS

The detection and recognition of traffic signs are crucial components of advanced driving assistance systems (ADAS) that enhance road safety. Current traffic sign detection and recognition model technology is proficient in identifying and interpreting traffic signs. However, for accurate detection and recognition, the traffic sign in the image must be of a certain minimum pixel size or distance from the driver's sight line for proper detection. The ADAS system should be capable of detecting and recognizing road traffic signs from a considerable distance as they come into the driver's line of vision. The higher the vehicle speed, the greater the distance required for the sign to be detected and recognized, allowing the driver sufficient time to react according to the sign's meaning. Addressing these challenges, this research proposes an enhanced version of the single shot detector (SSD) algorithm, commonly used in object detection, to improve the algorithm's ability to detect small objects. The proposed method involves adding an auxiliary layer module to the original SSD architecture to increase the feature map resolution and expand the conventional layer's receptive space. With the Enhanced SSD algorithm, the detection capability of the SSD can be significantly enhanced in terms of accuracy. The limitations of this study are related to the influence of occlusion and clutter, which might affect the performance of object detection, especially for small objects, which are more susceptible to being influenced by various factors. The research results demonstrate that Enhanced SSD improves object detection accuracy compared to the original SSD, with a mean average precision (mAP) of 97.87 compared to 95.35 for detecting 21 traffic signs in Indonesia.

Distinguish microphase-separated structures of diblock copolymers using local order parameters

The microphase-separated structures of block copolymers are inherently highly ordered local structures, commonly characterized by differences in domain width and curvature. By focusing on diblock copolymers, we propose local order parameters (LOPs) that accurately distinguish between adjacent microphase-separated structures on the phase diagram. We used the Molecular Assembly structure Learning package for Identifying Order parameters (MALIO) to evaluate the structure classification performance of 186 candidate LOPs. MALIO calculates the numerical values of all candidate LOPs for the input microphase-separated structures to create a dataset, and then performs supervised machine learning to select the best LOPs quickly and systematically. We evaluated the robustness of the selected LOPs in terms of classification accuracy against variations in miscibility and fraction of block. The minimum local area size required for LOPs to achieve their classification performances is closely related to the characteristic sizes of the microphase-separated structures. The proposed LOPs are potentially applicable over a large area on the phase diagram.

RNA Polymerase II is a Polar Roadblock to a Progressing DNA Fork.

DNA replication and transcription occur simultaneously on the same DNA template, leading to inevitable conflicts between the replisome and RNA polymerase. These conflicts can stall the replication fork and threaten genome stability. Although numerous studies show that head-on conflicts are more detrimental and more prone to promoting R-loop formation than co-directional conflicts, the fundamental cause for the RNA polymerase roadblock polarity remains unclear, and the structure of these R-loops is speculative. In this work, we use a simple model system to address this complex question by examining the Pol II roadblock to a DNA fork advanced via mechanical unzipping to mimic the replisome progression. We found that the Pol II binds more stably to resist removal in the head-on configuration, even with minimal transcript size, demonstrating that the Pol II roadblock has an inherent polarity. However, an elongating Pol II with a long RNA transcript becomes an even more potent and persistent roadblock while retaining the polarity, and the formation of an RNA-DNA hybrid mediates this enhancement. Surprisingly, we discovered that when a Pol II collides with the DNA fork head-on and becomes backtracked, an RNA-DNA hybrid can form on the lagging strand in front of Pol II, creating a topological lock that traps Pol II at the fork. TFIIS facilitates RNA-DNA hybrid removal by severing the connection of Pol II with the hybrid. We further demonstrate that this RNA-DNA hybrid can prime lagging strand replication by T7 DNA polymerase while Pol II is still bound to DNA. Our findings capture basal properties of the interactions of Pol II with a DNA fork, revealing significant implications for transcription-replication conflicts.

OptiRet-Net: An Optimized Low-Light Image Enhancement Technique for CV-based Applications in Resource-Constrained Environments

The illumination of images can significantly impact computer-vision applications such as image classification, multiple object detection, and tracking, leading to a significant decline in detection and tracking accuracy. Recent advancements in deep learning techniques have been applied to low-light image enhancement (LLIE) to combat this issue. Retinex theory-based methods following a decomposition-adjustment pipeline for LLIE have performed well in various aspects. Despite their success, current research on Retinex-based deep learning still needs to improve in terms of optimization techniques and complicated convolution connections, which can be computationally intensive for end-device deployment. We propose an Optimized Retinex-based CNN (OptiRet-Net) deep-learning framework to address these challenges for the low-light image enhancement problem. Our results demonstrate that the proposed method outperforms existing state-of-the-art models in terms of full reference metrics with a PSNR of 21.87, SSIM of 0.80, LPIPS of 0.16, and zero reference metrics with a NIQE of 3.4 and PIQE of 56.6. Additionally, we validate our approach using a comprehensive evaluation comprising five datasets and nine prior methods. Furthermore, we assess the efficacy of our proposed model combining low-light multiple object tracking applications using YOLOX and ByteTrack in versatile video coding (VVC/H.266) across various quantization parameters. Our findings reveal that LLIE-enhanced frames surpass their tracking results with a MOTA of 80.6% and a remarkable precision rate of 96%. Our model also achieves minimal file sizes by effectively compressing the enhanced low-light images while maintaining their quality, making it suitable for resource-constrained environments where storage or bandwidth limitations are a concern.

Feasibility of biogas upgrading at a WWTP after pre-treatment application: Techno-economic assessment validation with pilot test data

Improving the efficiency of anaerobic digestion (AD) of sewage sludge (SS) is a critical step toward the achievement of energy neutrality in wastewater treatment plants (WWTPs), as required by the European Green Deal. This study used a comparative techno-economic assessment (TEA) to evaluate the feasibility of producing biomethane, at a WWTP, through upgrading biogas with a double-stage permeation membrane plant. The biogas was originally generated from the AD of a mixture of primary sludge (PS) and either raw or pre-treated waste activated sludge (WAS), where biological or thermo-alkali pre-treatments were applied to increase the WAS intrinsic low degradability.The TEA was supported by the results of pilot-scale tests, carried out on WAS, which mimicked (i) a traditional mesophilic AD process; (ii) a two-stage AD process, where a temperature-phased anaerobic digestion (TPAD, 3 days, 55 °C + 20 days, 38 °C) was performed to biologically pre-treat WAS; (iii) a traditional mesophilic AD process preceded by a thermo-alkali (4 g NaOH/100 g TS, 90 °C, 90 min) pre-treatment.The TEA was carried out in two phases. In the first, the minimum size of the WWTP capable of making the costs necessary for the implementation of the biogas upgrading plant equal to the revenues coming from selling biomethane (at 62 €/MWh) in 10 years was calculated in the absence of pre-treatments. It resulted of 500,000 equivalent inhabitants (e.i.). In the second phase, for the WWTP size found previously, the effect of either biological or thermo-alkali pre-treatments on the economic balance was evaluated, that is the gain (or the loss) associated to the selling of biomethane, compared to the reference price of 62 €/MWh. It was found that the TPAD increased the biogas productivity by only 23.6%, too little to compensate the amount of heat necessary for the pre-treatment and the purchase cost of the additional reactor. Conversely, the thermo-alkali pre-treatment, which enhanced the WAS biogas productivity by 110%, increased the biomethane revenues by approx. 10 €/MWh, compared to the scenario without pre-treatments. This study offers useful data to WWTP managers who want to introduce WAS pre-treatments, combined with interventions for biogas upgrading, in a new or existing sludge line of a WWTP.

Influences of size effect and workpiece temperature during cryogenic micro milling of soft viscoelastic polymer: an experimental assessment

Application of tool-based micromachining in soft polymer has been limited due to high adhesion and low elastic modulus of this material at room temperature. This study aims to evaluate the machinability of a typical viscoelastic soft polymer and understand the effect of material and process parameters on machining performances. In this study, a micro-milling process using cryogenic-assisted cooling is proposed and the importance of temperature control toward glass transition zone was particularly addressed. To identify insight of machinability in micro domain, this article also determines minimum uncut chip thickness (MUCT) and size effects by considering the variations of cutting force and surface integrity with the ratio of h/re (uncut chip thickness (h) to cutting edge radius (re)). The experimental results reveal that consideration of size effect during micromilling of soft viscoelastic polymer helps in reduction of machined surface roughness (Sa) value. Based on the cutting force pattern, it is evaluated that higher machining stability can be achieved during cryogenic machining by reduction of specific cutting force value. Moreover, temperature range around glass transition zone yields more promising experimental outcomes, outperforming other cooling zones.

DETERMINING THE DOMINANT METRIC DIMENSION FOR VARIOUS GRAPHS

In this paper, we examine the dominating metric dimension of various graph types. A resolving set is a subset of vertices that uniquely identifies each vertex in the graph based on its distances to others, and the metric dimension is the minimum size of such a set. A dominating set ensures each vertex is adjacent to at least one vertex in the set. When a set is both resolving and dominating, it forms a dominating resolving set, and the smallest such set defines the dominating metric dimension, denoted as . We calculate the dominating metric dimension for the splitting graph of book graph, globe graph, tortoise graph, and graph.

Development of N-alkylated benzimidazole based cubosome hydrogel for topical treatment of burns.

The current study focuses on assessing the activity of the N-alkylated benzimidazole based cubosomal hydrogel (cubogel) for the topical treatment of burn wounds. The study involves the synthesis of six benzimidazole derivatives (1-6) and their characterization by FT-IR and 1H and 13C NMR spectroscopy. The further study involves the design and formation of nanoparticles known as cubosomes loaded with selected 1-benzyl-1-benzimidazole (API 6) and the development of a cubogel for the topical treatment of burn wounds. Cubosomes were prepared by the homogenization method, using glyceryl monooleate (GMO) as a lipid polymer and poloxamer 407 (P407) as a surfactant. Cubosomes undergo in vitro characterizations (measurement of particle size, zeta potential, polydispersity index (PDI), % entrapment efficiency, drug release in phosphate buffer saline of pH 6.8, and surface morphology by utilizing TEM (transmission electron microscopy). Formulation D3 (2.5% of GMO, 1% of P407, and 2.5% of PVA) emerged as the optimized formulation, displaying a minimum particle size (PS) of 129.9 ± 1 nm, entrapment efficiency (%EE) of 96.67 ± 0.89%, and a drug release of 86 ± 2.7% at 24 h. Carbopol 940 hydrogel was prepared and incorporated with the optimized formulation to prepare cubogel. This optimized cubogel provided 92.56 ± 0.014% in vitro drug release within 24 h. An in vivo histopathological study was conducted on an animal model (rabbit) to assess the efficacy of cubogel in wound healing and wound contraction. Then cubogel was compared with the commercially available creams Clotrimazole® and Polyfax®. The wound treated with newly developed cubogel has maximum wound contraction (96.70%) as compared to the standard creams. The findings revealed that the newly formulated cubogel was highly effective in treating burns, showing superior performance to commercial products without inducing side effects. Additionally, benzimidazole derivative loaded cubogel caused a sustained release for treating burn wounds without any bacterial infections. The current results further suggested phase 0 clinical trials.

On the uniqueness and computation of commuting extensions

A tuple (Z1,…,Zp) of matrices of size r×r is said to be a commuting extension of a tuple (A1,…,Ap) of matrices of size n×n if the Zi pairwise commute and each Ai sits in the upper left corner of a block decomposition of Zi (here, r and n are two arbitrary integers with n<r). This notion was discovered and rediscovered in several contexts including algebraic complexity theory (in Strassen's work on tensor rank), in numerical analysis for the construction of cubature formulas and in quantum mechanics for the study of computational methods and the study of the so-called “quantum Zeno dynamics.” Commuting extensions have also attracted the attention of the linear algebra community. In this paper we present 3 types of results:(i)Theorems on the uniqueness of commuting extensions for three matrices or more.(ii)Algorithms for the computation of commuting extensions of minimal size. These algorithms work under the same assumptions as our uniqueness theorems. They are applicable up to r=4n/3, and are apparently the first provably efficient algorithms for this problem applicable beyond r=n+1.(iii)A genericity theorem showing that our algorithms and uniqueness theorems can be applied to a wide range of input matrices.

Nanochannels in Fused Silica through NaOH Etching Assisted by Femtosecond Laser Irradiation

Sodium hydroxide (NaOH) is increasingly drawing attention as a highly selective etchant for femtosecond laser-modified fused silica. Unprecedented etching contrasts between the irradiated and pristine areas have enabled the fabrication of hollow, high-aspect-ratio structures in the bulk of the material, overcoming the micrometer threshold as the minimum feature size. In this work, we systematically study the effect of NaOH solutions under different etching conditions (etchant concentration, temperature, and etching time) on the tracks created by tightly focused femtosecond laser pulses to assess the best practices for the fabrication of hollow nanostructures in bulk fused silica.

RF NEMS switches based on graphene for low pull-in voltage and excellent RF performance

This study introduces a novel graphene RF NEMS capacitive switch and conducts an extensive analysis of its RF performance using CST and COMSOL Multiphysics software. The switch’s characteristic impedance matching is accomplished through a coplanar waveguide (CPW) structure, incorporating a dielectric layer topped with conductive graphene beam electrodes. Simulation results reveal that the monolayer graphene RF NEMS switch maintains an insertion loss of 0.003 ~ 0.015 dB and an isolation greater than 40 dB across an ultra-wideband (UWB) frequency range of DC ~ 140 GHz. Moreover, the switch demonstrates a switching time of 4.03 ps at a pull-in voltage of 1 V. The performance of multilayer graphene RF NEMS switches was also evaluated. The study further investigates the operational mechanism of the graphene RF NEMS switch and performs finite element analysis on the proposed design. The graphene RF NEMS switch discussed herein offers significant advantages, including minimal size, lightweight, cost-effectiveness, low pull-in voltage, rapid response time, excellent RF performance, and reduced space consumption in circuitry. Its potential applications span a range from L to F bands, encompassing data storage, communication systems, sensors, remote sensing and military uses.

Novel carboxylic-MWCNTs photoresist for fabricating sub-diffraction polymer nanowires via STED lithography

A novel composite photoresist, derived from acrylates and carboxylic-functionalized multi-walled carbon nanotubes (MWNTs-COOH), has been developed for the fabrication of sub-diffraction-sized polymer nanowires using STED-inspired lithography. The MWNTs-COOH dispersed in highly cross-linking acrylate monomers benefits to a reduced inhibition laser power for improving lithography. With the MWNTs-COOH, the inhibition laser power is decreased from 5 mW to 3 mW, while the achievable minimum feature size is increased from 121 nm to 48 nm. This innovative approach holds significant promise for the development of sub-diffraction MWCNTs/polymer composite-based devices in the fields of Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS).

Per-recruit analysis and proposed sustainable harvest strategy for rednose labeo Labeo rosae and Mosambique tilapia Oreochromis mossambicus in Flag Boshielo Dam, Olifants River, South Africa

Inland fisheries development in South Africa has been proposed to improve rural livelihoods and food security. However, inland fisheries are susceptible to collapse through overfishing. Therefore, establishing biological reference points for these fisheries is essential for long-term sustainability. Here, spawner-biomass-per-recruit (SBR) analysis was used to set biological reference points for a gillnet fishery targeting the rednose labeo Labeo rosae and Mozambique tilapia Oreochromis mossambicus at Flag Boshielo Dam on the Oliphants River in Limpopo Province, South Africa. Both species are currently exploited at the impoundment by subsistence fishers that keep their entire catch. The current yields are estimated at 59 and 172 g yr−1 for L. rosae and O. mossambicus, respectively. The per-recruit analysis showed that age-at-first-capture for both species should be 4 years, at minimum lengths of 280 mm TL and 250 mm TL for L. rosae and O. mossambicus, respectively, with fishers using a minimum mesh size of 100 mm to reduce the risk of stock collapse. To maintain a SBR value greater than 25% of a pristine population, the L. rosae yield could be increased to 98 g yr−1, while the O. mossambicus yield could be increased to 176 g yr−1, following implementation of the recommended mesh size and size limits. A per-recruit analysis for O. mossambicus that includes recruitment variability and error to accurately calculate the biological reference points is recommended.

Sample size for assessing a diagnostic accuracy of AI-based software in radiology

Introduction. Determining the minimum sample size for solving various tasks is an extremely important and at the same time unexplored problem. There are many methods, but most of them are not applicable for AI-based software validation.Aim: To consider a methodology for determining a balance of classes “norm”/ “abnormality” and propose a statistical approach to determine the data amount necessary for testing AI-based software (validation).Material and Methods. The results of AI-based software were analyzed using dataset of mammograms. Mammograms were classified by the presence of breast cancer (“abnormality”) and the absence of breast cancer (“norm”). The general set contains 123,301 unique studies. The original balance of classes in the study was “norm” 89.3%/“abnormality” 10.7%. As the results of AI-based software (ML-algorithm), a probability of the presence of pathology in the entire study was taken. The following values were used as empirical data (GT): 0 – in case of Bi-RADS classes 1 or 2 diagnosed by a doctor, and 1 – in case of Bi-RADS classes 3, 4, 5. Each data sample is transferred to AI-based software for processing. Quality metrics are calculated based on its results: AUC ROC. All the described actions were repeated 10,000 times for all the studied balances of “norm”/”abnormality”. Based on the results of AUC ROC calculations, mean values were calculated for different random data series with the same balances. Mean AUC ROC values were subjected to analysis.Results. A maximum value of the coefficient of variation of AUC ROC values for 10% “abnormality” share is achieved at the number of studies equal to 190; for the 20% share, it is 80 studies; for the 30% share – 120 studies, for the 40% share – 110 studies, and for the 50% share – 70 studies.Conclusion. Summarizing the conducted study results, it can be concluded that when testing AI-based software, it is necessary to consider that the number of studies reflecting the greatest heterogeneity of AUC ROC values (the largest deviation from the mean value) is different for various class balances. If the purpose of validation is to establish the worst-case behavior of AUC ROC values, then for the studied AI-based software, the “abnormality” share should be 10%, and the number of studies 190. If the validation is carried out under conditions of a limited amount of data, then the “abnormality” share should be 50% and the number of studies equal to 70.

Multi-mode high resolution TFM imaging of microdefects based on laser ultrasonic full matrix capture

The identification and visualization of submillimeter microdefects have long been a critical focus within the realm of ultrasonic testing. The utilization of high-frequency signals is imperative due to the small acoustic interaction structure. An additional benefit of using lasers is their non-contact nature and ability to utilize multiple imaging modes, effectively reducing false or missed detections and enhancing credibility. This study proposes an advanced optimization algorithm for imaging and quantitative evaluation of submillimeter microdefects using laser ultrasonic full matrix capture (FMC) and total focusing method (TFM). The analysis of acoustic directionality under laser excitation and detection provides a foundation for mode selection. In preprocessing, the multi-scale principal component analysis (MSPCA) method is introduced to suppress coherent noise and blind spots. Moreover, phase coherence methods are implemented to further reduce mode artifacts, background noise, and residual surface acoustic wave (SAW). Additionally, multi-mode imaging and mode fusion are achieved using reflected longitudinal waves, reflected shear waves, converted longitudinal waves, and converted shear waves. Experiments were carried out on two different types of microdefects, namely side drilled holes (SDHs) and blind holes (BHs), resulting in high resolution TFM imaging with a minimum BH size of 0.3 mm. The outcomes demonstrate the efficacy of MSPCA in suppressing coherent noise, with further enhancement in imaging quality after phase coherence weighting. In addition, the −6 dB threshold of multi-mode images also provided the size information. This research is poised to contribute to the resolution of quality assessment challenges in powder metallurgy, welding, and additive manufacturing processes.