Reliable Method Research Articles

Stress exposure, perceived stress severity, and their effects on health

While stress is one of the central concepts in many contemporary theories of health, there is no universal definition of stress or stressors. Stress is usually understood as a subjective experience of tension, pressure, distress, fear or negative emotions that occurs as a result of a perceived threat to one’s mental or physical well-being and is accompanied by an evolved biological response that facilitates adaptive reaction. While stress is conceptualized as a taxing condition, it is not understood as uniformly harmful per se. In fact, stress response is often cited as an adaptive reaction. Moreover, not every incident of stress exposure results in a disease or has an undermining effect on health. Mere exposure to stress does not warrant the healthy organism’s falling ill. Yet stress has been shown to affect health both directly and indirectly, having impact on multiple chronic conditions. Stressors vary in their severity and their ability to leave their mark on health, and it is therefore important to develop reliable methods of measuring stress to better understand how stress affects health and instigates pathology. One of the difficulties of measuring the effects of stress is connected to the distinction between external stressors and their internal appraisal. More recently, stress researchers began to make a distinction between stress exposure (i.e., facing an objectively measurable stressor) and perceived stress severity (i.e., a subjective experience of stress resulting from individual’s facing a stressor). The latter has been shown to have a superior predictive ability in terms of negative health outcomes (both breadth and depth of observed effects) compared to the former. Measurement-wise, subjective stress also tends to yield more precise results, which makes it preferable as a stress-assessment tool. The present article is a literature review study that delves into this distinction and attempts to shed light onto its implications for measuring stress and its effects on health.

A liquid-phase loop-mode argon purification system

Noble gas and liquid detectors rely on high chemical purity for successful operation. While gaseous purification has emerged as a reliable method of producing high-purity noble fluids, the requirement for large mass flows drives the development of liquid-phase purification. We constructed a medium-scale liquid argon (LAr) purification system based on a copper catalyst and 4 Å molecular sieve capable of purifying 1 t of commercial LAr 5.0 to a long effective triplet lifetime of τ3 ∼ 1.3 μs. We further demonstrate that a quenched effective triplet lifetime of τ3 ∼ 1 μs, due to contamination by air, can be recovered in loop-mode purification to τ3 ∼ 1.3 μs after > 20 volume exchanges.

Time-dependent fatigue reliability analysis of heavy-haul railway steel bridges

Fatigue of heavy-haul railway bridges has been an ongoing concern due to the excessive stresses and frequent cyclic effects of freight trains. Current fracture-based fatigue research, which promotes fatigue reliability analysis caused by crack propagation, is challenged by the dilemma between the detailed modeling of cyclic stress and the reflection of temporal characteristics of loading conditions. In addition, due to the strong non-Gaussian nature of the fatigue limit state function and the computational inefficiency of integrating finite element analysis, current time-dependent reliability methods need to be further developed. To evaluate the fatigue reliability of heavy-haul railway steel bridges considering the temporal dependence of cyclic train loading, a time-dependent fatigue reliability methodology is developed in this study with two innovations. Firstly, a cyclic stress range model is proposed based on the load analysis at the bridge level, which can capture the time-dependent characteristics of the incurred stress range throughout service life. Then, an improved outcrossing rate method for strong non-Gaussian fatigue limit state functions is developed to reduce the computational costs associated with reliability analysis integrated with the finite element model. The developed time-dependent fatigue reliability methodology is then applied to a heavy-haul railway steel truss bridge located in Shandong, China, which proves its efficiency and accuracy in evaluating the time-dependent fatigue reliability of heavy-haul railway steel bridges. Furthermore, the developed methodology is able to provide insight into the balance between bridge fatigue damage and freight volume, and it is found that the combination of small train axle weight and high operation frequency is the optimal solution to achieve the fatigue reliability of the steel bridge while fulfilling the freight demand.

Rapid Determination of Diverse Ganoderic Acids in Ganoderma Using UPLC–MS/MS

Background:: Ganoderma is known for its pharmaceutical, nutritional, and functional benefits. Its primary bioactive components are ganoderic acids. However, previous quantification methods only analyzed an individual or limited number of ganoderic acids. This study aims to develop a reliable method for simultaneously quantifying the major ganoderic acids to enhance Ganoderma quality control and study its active ingredients. Methods:: We developed a rapid quality assessment method to simultaneously determine the eleven ganoderic acids in Ganoderma using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The sample extraction method, along with mass spectrometric detection and chromatographic separation conditions was optimized. The separation was carried out using the ACQUITY UPLC BEH C18 column with a gradient elution of 0.1% (v/v) formic acid in water and acetonitrile. The mass spectrometry utilized negative mode electrospray ionization (ESI), with quantitative analysis being carried out in the MRM mode. Results:: The calibration curves showed good correlation coefficients (r2 > 0.998). The recovery range was 89.1–114.0%. The intra-day and inter-day relative standard deviation (RSD) were below 6.8% (n = 6) and 8.1% (n = 6), respectively. Furthermore, the detection and quantification limits were 0.66–6.55 μg/kg and 2.20–21.84 μg/kg, respectively. All 11 ganoderic acids in the sample solution remained stable at room temperature for 72 hours. A total of 11 ganoderic acids were quantified in the 13 Ganoderma samples. The levels of ganoderic acids were higher in Ganoderma lucidum than in Ganoderma sinense. Conclusion:: The method developed in this study can quantify ganoderic acids in Ganoderma lucidum, thus establishing a technical foundation for evaluating the Ganoderma quality.

Avaliação visual do índice de área foliar em campos de café (Coffea arabica L.)

ABSTRACT The application of leaf area index (LAI) in coffee crop management depends on the availability of methodologies for proper estimation. The objective of this study was to develop a methodology for the visual assessment of LAI in coffee fields and to establish a protocol for training, evaluation, and feedback for evaluators. Four rounds of LAI measurements were conducted using visual estimates, two instruments (LAI 2200-C and AccuPAR LP-80), and defoliation of coffee hedgerows in Poás, Costa Rica. In each round, five workers visually estimated the LAI values on two occasions separated by 15 days, and feedback reinforcement was provided to each worker at the end of each round. Visual assessments showed high repeatability and reproducibility and the estimates were adjusted to the linear regression model in most cases. Evaluators improved their capacity to visually assess the LAI throughout the rounds, as the value of R2increased consistently for most workers, with values as high as 0.87. Instrumentation evaluation of LAI produced R2values of 0.5-0.6, with significant underestimation bias. The performance of the different methods is discussed in the context of widely spaced hedgerows. The proposed visual methodology constitutes a statistically sound, rapid, simple, and reliable method for determining the LAI of coffee fields to aid in decision-making for crop management.

A materials informatics framework based on reduced‐order models for extracting structure–property linkages of additively manufactured continuous fiber‐reinforced polymer composites

AbstractThe innovative combination of additive manufacturing (AM) and continuous fiber‐reinforced polymer composites (CFRPCs) confers products with the dual advantages of integrated manufacturing and designability of properties, but lack an efficient and reliable method for property prediction. This study presents a materials informatics framework using reduced‐order models and machine learning (ML) to extract the structure–property (SP) linkages between microstructures and macroscopic elastic properties of AM‐CFRPCs. The initial step involves generating microstructural 2D cross‐sections and representative volume elements (RVEs) with random fiber and pore distributions based on the minimum potential method. Then, finite element (FE) calculations are performed on RVEs to obtain nine macroscopic elastic properties. Following that, the quantification and dimensionality reduction of the 2D cross‐sectional dataset are conducted separately using two‐point spatial correlations and principal component analysis (PCA). Finally, a Bayesian optimized composite kernel support vector regression (CK‐SVR) algorithm is used to effectively establish complex mapping relationships between the reduced‐order representations of the microstructures and the mechanical properties. Despite the reduced‐order dataset containing only 3–6 variables, the framework generates an interpretable model exhibiting excellent accuracy with all predicted R2 values surpassing 0.91. Therefore, this framework presents a prospective solution for expediting the design and optimization of AM‐CFRPCs.Highlights A materials informatics scheme is proposed to predict the 9 elastic properties of AM‐CFRPCs. Microstructures are quantified and dimensionally reduced by two‐point statistics and PCA. SP linkages are established between 2D cross‐sections and 3D macromechanical properties. Modified CK‐SVR exhibits higher prediction accuracy compared to conventional models.

High-Precision Localization of Passive Intermodulation Source in Radio Frequency Transmission Lines Based on Dual-Frequency Signals

With the development of communication technology, the interference from passive intermodulation to the communication system has become increasingly severe. Locating the source of passive intermodulation and then repairing or replacing the device experiencing passive intermodulation is a reliable method. Therefore, this paper proposes a dual-frequency signal localization method based on the principle of phase ranging to accurately locate the passive intermodulation sources in RF cables. This method switches the test signal frequency to obtain the phase of passive intermodulation signals at different frequencies to localize the passive intermodulation source. This paper analyzes the principle of the passive intermodulation localization method based on dual-frequency signals, establishes a localization system for experiments, and finally, analyzes the experimental error to propose an optimization strategy. Through experimental verification, this method can stabilize the positioning error of a passive intermodulation source in a transmission line less than 0.06 m. Meanwhile, this method has high positioning accuracy and the advantages of slight computational complexity, fast positioning speed, and only a small number of requirements on hardware resources. It can work in communication scenarios like satellite and base stations, providing a new technical solution for localizing passive intermodulation interference sources in 5G and 6G communication systems.

Stability Evaluation of the Goaf Based on Combination Weighting and Cloud Model

Goaf has become one of the most significant sources of hazard affecting the safety of metal and nonmetal mines. Evaluation of goaf stability is of paramount importance for mine safety production. First, 13 indices such as rock mass structure, geological structure, and goaf volume are selected based on engineering experience and literature review to assess the stability of goaf. These indices are classified according to the characteristics of each factor, and a stability evaluation system for underground mine goaf is constructed. Second, the analytic hierarchy process method based on group decision theory is utilized to calculate the subjective weight of each index. Additionally, the CRITIC method is used to calculate the objective weight of each index. Finally, game theory is used to combine the subjective and objective weights, thereby improving the accuracy of the index weight. The stability grade of the goaf is calculated using the normal cloud model. The FLAC3D numerical simulation is used to analyze the stability of the goaf and verify the accuracy of the model. The abovementioned model is utilized for assessing the stability of the goaf in the Duimenshan mine section. The results indicate that 90% of the goaf area is in a stable or relatively stable condition, while the remaining 10% is unstable. The evaluation outcomes were compared with FLAC3D numerical simulations, highlighting a scientific and reliable method with an accuracy rate of 90%.

Gaidai Multivariate Reliability Method for Energy Harvester Operational Safety, Given Manufacturing Imperfections

Gaidai Multivariate Reliability Method for Energy Harvester Operational Safety, Given Manufacturing Imperfections

The immediate effect of cervical rotation-traction manipulation on cervical paravertebral soft tissue: a study using soft tissue tension cloud chart technology

BackgroundTo evaluate the reliability of the Soft Tissue Tension Cloud Chart (STTCC) technology, an original method combining multi-point Cervical Paravertebral Soft Tissue Test (CPSTT) with MATLAB software, we conducted a preliminary analysis on the immediate effects of Orthopaedic Manual Therapy (OMT) on cervical paravertebral soft tissue.Methods30 patients with Cervical Spondylotic Radiculopathy (CSR) were included in this study. We analyzed the differences in CPSTT before and after treatment with Cervical Rotation-Traction Manipulation (CRTM), a representative OMT technique in Traditional Chinese Medicine, using the STTCC technology.ResultsThe STTCC results demonstrated that post-treatment CPSTT levels in CSR patients were significantly lower than pre-treatment levels after application of CRTM, with a statistically significant difference (P < 0.001). Additionally, pre-treatment CPSTT levels on the symptomatic side (with radicular pain or numbness) were higher across the C5 to C7 vertebrae compared to the asymptomatic side (without symptoms) (P < 0.001). However, this difference disappeared after CRTM treatment (P = 0.231).ConclusionsThe STTCC technology represents a reliable method for analyzing the immediate effects of OMT. CSR patients display uneven distribution of CPSTT characterized by higher tension on the symptomatic side. CRTM not only reduces overall cervical soft tissue tension in CSR patients, but can also balance the asymmetrical tension between the symptomatic and asymptomatic sides.Trial registrationThis study was approved by the Chinese Clinical Trials Registry (Website: .https://www.chictr.org.cn.) on 20/04/2021 and the Registration Number is ChiCTR2100045648.

Development of a simple UPLC-MS/MS method coupled with a modified QuEChERS for analyzing multiple antibiotics in vegetables and applied to pollution assessment

Antibiotics used in livestock husbandry can contaminate the environment through animal excretions and aquaculture wastewater. Absorption of these antibiotics by vegetables may pose health risks to humans through the food chain. However, research on detecting multi-antibiotics in vegetables remains limited. This study aims to develop a reliable and sensitive method to quantify 72 antibiotics from six classes in vegetable samples using modified QuEChERS and UPLC-MS/MS methods. The QuEChERS method was optimized by investigating extraction solvents, salting-out agents, and adsorbents. The percentage recovery of the 72 analyte antibiotics from spiked vegetable samples ranged between 61.5% and 117.8%. Intra-day and inter-day precision were below 12.1% and 15.4%, respectively. The limits of detection and quantification were 0.010–0.232 µg.kg−1 and 0.032–0.772 µg.kg−1, respectively. The method demonstrated a weak matrix effect for 61.1% of the tested compounds. Applying the developed method to analyze 248 vegetable samples, 15 antibiotics were detected, ranging from 0.010 µg.kg−1 to 561.0 µg.kg−1 fresh weight. Notably, bean sprouts showed the presence of multiple antibiotics, suggesting the possible misuse of antibiotics in their production.

From Clicks to Security: Investigating Continuous Authentication via Mouse Dynamics

In the realm of computer security, the importance of efficient and reliable user authentication methods has become increasingly critical. This paper examines the potential of mouse movement dynamics as a consistent metric for continuous authentication. By analysing user mouse movement patterns in two contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond conventional methodologies by employing a range of machine learning models. These models are carefully selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as reflected in their mouse movements. This multifaceted approach allows for a more nuanced and comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine learning models employed in this study demonstrate competent performance in user verification, marking an improvement over previous methods used in this field. This research contributes to the ongoing efforts to enhance computer security and highlights the potential of leveraging user behavior, specifically mouse dynamics, in developing robust authentication systems.

SegEIR-Net: A Robust Histopathology Image Analysis Framework for Accurate Breast Cancer Classification.

Breast Cancer (BC) is a significant threat affecting women globally. An accurate and reliable disease classification method is required to get an early diagnosis. However, existing approaches lack accurate and robust classification. This study aims to design a model to classify BC Histopathology images accurately by leveraging segmentation techniques. This work proposes a combined segmentation and classification approach for classifying BC using histopathology images to address these issues. Chan-Vese algorithm is used for segmentation to accurately delineate regions of interest within the histopathology images, followed by the proposed SegEIR-Net (Segmentation using EfficientNet, InceptionNet, and ResNet) for classification. Bilateral Filtering is also employed for noise reduction. The proposed model uses three significant networks, ResNet, InceptionNet, and EfficientNet, concatenates the outputs from each block followed by Dense and Dropout layers. The model is trained on the breakHis dataset for four different magnifications and tested on BACH (BreAst Cancer Histology) and UCSB (University of California, Santa Barbara) datasets. SegEIR-Net performs better than the existing State-of-the-Art (SOTA) methods in terms of accuracy on all three datasets, proving the robustness of the proposed model. The accuracy achieved on breakHis dataset are 98.66%, 98.39%, 97.52%, 95.22% on different magnifications, and 93.33% and 96.55% on BACH and UCSB datasets. These performance results indicate the robustness of the proposed SegEIR-Net framework in accurately classifying BC from histopathology images.

Assessment of focused ultrasound stimulation to induce peripheral nerve activity and potential damage in vivo.

Peripheral neuroprostheses are aimed to restore loss of sensory and motor functions by interfacing axons in the peripheral nerves. Most common interfaces in neuroprostheses are electrodes that establish electrical connection with peripheral axons. However, some challenges arise related to long-term functionality, durability, and body response. Recently, focused ultrasound stimulation (FUS) has emerged as a non-invasive approach to modulate the nervous system. However, it is controversial whether FUS can induce axon depolarization. We have assessed FUS applied in vivo to the rat peripheral nerve, with two objectives: first, to test whether FUS activates peripheral nerves under different stimulation conditions, and second, to evaluate if FUS inflicts damage to the nerve. FUS was delivered with three ultrasound transducers (Sonic Concept H115, H107, and H102) covering the largest set of parameters examined for FUS of peripheral nerves so far. We did not obtain reliable evoked action potentials in either nerves or muscles, under any FUS condition applied, neither over the skin nor directly to the nerve exposed. Additional experiments ex vivo and in vivo on mice, confirmed this conclusion. When FUS stimulation was applied directly to the exposed sciatic nerve, neuromuscular function decreased significantly, and recovered one week later, except for FUS at 0.25 MHz. Histologically, degenerating nerve fibers were observed, with a tendency to be higher with the lower FUS frequency. Past reports on the ability of ultrasound to stimulate the peripheral nerve are controversial. After testing a wide range of FUS conditions, we conclude that it is not a reliable and safe method for stimulating the peripheral nerve. Special consideration should be taken, especially when low-frequency FUS is applied, as it may lead to nerve damage.

An Innovative Clinical Evaluation Protocol after Total Ankle Arthroplasty: A Pilot Study Using Inertial Sensors and Baropodometric Platforms

Background: Total ankle arthroplasty (TAA) has grown in popularity and indications, with encouraging results over time. Today, preoperative and postoperative evaluations are mainly performed using clinical test and diagnostic imaging, but there is a deficiency in objectively evaluating the biomechanics of the foot and ankle, which serve as the functional markers for monitoring the effectiveness and outcomes of surgery. Inertial measurement units associated with plantar pressure measurements may provide an accurate and reliable method of evaluating function through the analysis of gait and ankle joint mobility. The aim of this study was to introduce an innovative technology, to assess its accuracy and feasibility compared to standard clinical assessment methods and to objectify kinematic outcomes in patients with end-stage ankle OA before and after TAA surgery. Methods: A consecutive series of eight patients with symptomatic end-stage osteoarthritis and treated with TAA was prospectively evaluated using clinical scores (AOFAS, MOxFQ, VAS, SF-36, 17-IFFI), physical tests (FPI, ALT), plantar pressure measurements with FLEX EPS/R2 Letsense® baropodometric platform, gait analysis and wearable sensors-based ankle motion and kinematic outcomes using Wiva Science inertial sensors by Letsense®. Data were collected preoperatively and 4 months after surgery. Results: All PROMs exhibited statistical significance in improvement from pre- to postoperative periods, except for one. Physical examinations showed no significant changes of the foot shape and alignment. Plantar pressure analyses revealed no significant changes in static and dynamic evaluations, but a more uniform distribution of plantar pressure was observed between the two periods. Inertial sensor parameters demonstrated no significant differences, except for a significant reduction in stride length and step length for the operated foot after surgery. Conclusions: Gait analysis using inertial sensors and plantar pressure measurements offer ease of handling, cost effectiveness, portability and swift data reading, making them highly appealing for widespread clinical use. Integrating these tools into the routine assessments of patients with TAA holds promise for advancing precision of treating this condition and our depth of its understanding, contributing to more comprehensive and insightful patient care.

Research on correlation between dynamic resilient modulus and CBR of coarse-grained chlorine saline soil

A large area of coarse-grained saline soil is distributed in saline soil areas, and chlorine saline soil with a high salt content is a typical representative. The dynamic resilient modulus was accurately predicted using the California-bearing ratio (CBR) value to determine the relationship between the dynamic resilient modulus of coarse-grained chloride saline soil and its CBR value. Indoor dynamic triaxial tests and CBR tests were conducted to investigate the evolution of the dynamic resilient modulus (MR) and CBR of coarse-grained chlorine saline soil under the influence of the stress level, water content, and salt content. The test results showed that the dynamic resilient modulus increased with an increase in the confining pressure and bulk stress and decreased as the deviator stress increased; however, the CBR increased with an increase in the corresponding unit pressure. The higher the salt and water contents, the more obvious the influence of stress on the dynamic resilient modulus and CBR value. Under the same stress level, the decrease in the dynamic resilient modulus and CBR gradually increased with increasing salt and moisture content, and the effect of salt tended to be more significant than that of water. Based on the correlation between the dynamic resilient modulus and CBR revealed by the experiment, a more widely applicable model was selected from the existing theoretical models related to CBR for the regression analysis of the test data, and a prediction model of the dynamic resilient modulus based on the CBR value was proposed (MR = 21.06CBR0.52). This prediction model had a high correlation coefficient (R2 = 0.893) and could effectively predict the dynamic resilient modulus of coarse-grained chlorine saline soil using CBR values. The results provide a simple and reliable method for determining the design parameters of a coarse-grained saline soil subgrade.

Cyberbullying Detection: A Comparative Study of Classification Algorithms

In the realm of social media, cyberbullying's pervasive impact raises urgent concerns about its emotional and psychological toll on victims. This study addresses the imperative of effectively detecting cyberbullying. By leveraging ML and DL techniques, we aim to develop reliable methods that accurately identify instances of cyberbullying in social media data, enhancing detection efficiency and accuracy. This facilitates timely intervention and support for affected individuals. In this comprehensive analysis of existing systems, various ML and DL models are extensively texted for cyberbullying detection. The evaluated models include Random Forest, XgBoost, Naive Bayes, SVM, CNN, RNN, and BERT. Pre-processed datasets are utilized to train and evaluate the models. To evaluate the ability of each model to reliably identify cyberbullying in social media data, performance metrics such as F1 score, recall, precision, and accuracy are used. The findings of this study demonstrate the efficacy of different ML and DL models in monitoring cyberbullying in social media data. Among the models evaluated, the BERT model exhibits exceptional performance, achieving the highest accuracy rates of 88.8% for binary classification and 86.6% for multiclass classification.

Solvent-Free Fabrication of Anisotropic Microparticles with Precise 3D Shape Control Using Dipping-Based Micromolding.

We present an innovative solvent-free micromolding technique for rapidly fabricating complex polymer microparticles with three-dimensional (3D) shapes utilizing a surface tension-induced dipping process. Our fabrication process involves loading a photocurable solution into micromolds through mold dipping. The loaded solution, induced by surface tension, undergoes spatial deformation upon mold removal caused by surface forces, ultimately acquiring an anisotropic shape before photopolymerization. Results show that the amount of photocurable solution loaded depends on the degree of capillary penetration, which can be adjusted by varying the dipping time and mold height. It enables the production of polymer particles with precisely controlled 3D shapes without diluting them with volatile organic solvents. Sequential micromolding enables the spatial stacking of the polymer domain through a bottom-up approach, facilitating the creation of complex multicompartmental microparticles with independently controlled compartments. Finally, we demonstrated the successful simultaneous conjugation of multiple model-fluorescent proteins through the biofunctionalization of microparticles, indicating functional stability and effective conjugation of hydrophilic molecules such as proteins. We also extend our capacity to create bicompartmental microparticles with distinct functionalities in each compartment, revealing spatially controlled functional structures. In summary, these findings demonstrate a straightforward, rapid, and reliable method for producing highly uniform complex particles with precise control over the 3D shape and compartmentalization, all accomplished without the use of organic solvents.

Outcomes of Head and Neck Free Tissue Transfer Requiring Vein Grafting: Systematic Review and Meta-analysis.

To systematically review the literature to determine the prevalence of free flap failure in head and neck free flaps requiring vein grafting. Search strategies created in collaboration with a medical librarian were implemented using PubMed, Cochrane, Scopus, Web of Science, and Google Scholar from inception to August 2022. The population of interest included adult and pediatric patients undergoing reconstruction of oncologic or traumatic head and neck defects with a free flap requiring a vein graft that presents the success/failure rate. The primary outcome was the flap failure rate, and the secondary outcome was the flap compromise/revision rate. Inclusion and exclusion criteria were designed to capture all study designs. Initially, 2778 articles were identified by the search strategy. Two reviewers independently performed the review, data extraction for analysis, and a quality assessment. Primary Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed. Meta-analysis was performed using a random effects model. Eleven studies of 789 flaps were included for data extraction. Random effects meta-analysis resulted in an estimated prevalence of free flap failure of 12.30% (95% confidence interval: 6.39%-19.49%, I2 = 77.4%). Taking into account that head and neck free tissue transfers that require a vein graft are typically associated with more challenging reconstructions and the lack of a suitable alternative, vein grafts appear to be a reliable method for bridging the gap between the flap and recipient vessels in head and neck free tissue transfer when indicated.

The role of stimulus combinations in the repeated assessment of resurgence

The current study examined the role of stimulus combinations on the repeated assessment of resurgence. Using a within-session resurgence procedure, rats were exposed to different conditions, each with distinct stimulus combinations (AAA, ABA, ABB, ABC and AAB). Two arrangements of stimulus changes were compared: Experiment 1 involved changes in stimulus combinations every five sessions, while Experiment 2 implemented changes every session. Resurgence was observed in both experiments; however, Experiment 2 demonstrated more consistent and repeated resurgence when stimulus combinations changed every session. Notably, the ABA, ABB and ABC conditions showed the highest percentage of sessions in which resurgence was observed. Lastly, the current study extends the application of the within-session resurgence procedure to rats and auditory stimuli, providing a reliable method for assessing resurgence in single subjects under different variable conditions.