Individual Peaks Research Articles

Overload and variable amplitude load effects on the fatigue strength of welded joints

Different load spectra and individual load peaks might substantially relax high residual stresses as well as induce compressive residual stresses in welded components and, consequently, affect the fatigue performance of these joints. Consideration of peak loads and resulting relaxation of residual stresses in fatigue analyses can substantially enhance the accuracy of life prediction. The aim of the current study is to experimentally investigate the fatigue strength of welded joints subjected to different levels of overloads and variable amplitude (VA) loads and to develop local fatigue assessment method to account for the relaxation of residual stresses via a mean stress correction using the 4R method. The 4R method applies a local stress ratio for the mean stress correction considering material strength, residual stresses, applied stress ratio of external loading and local weld geometry in elastic–plastic material behaviour. Fatigue tests were carried out on fillet-welded longitudinal gusset joints made of S700 high-strength steels under applied stress ratio R = 0–0.1. A mild strength steel (S355) and ultra-high-strength steel (S1100) were selected as reference steel grades for the fatigue testing to study the material strength effects. Numerical analyses were conducted to evaluate the fatigue notch factors using the effective notch stress concept with the reference radius of rref = 1.0 mm and theory of critical distance (TCD) using the point method. The experimental results indicated that a substantial improvement in the fatigue strength capacity can be claimed in the joints subjected to tensile overloads, particularly in the studied S700 and S1100 steels. The higher-level overload (0.8fy), corresponding to the nominal cross-sectional area, improved the mean fatigue strength of the welded joints manufactured of high-strength S700 steel by approximately 60%, while the lower overload (0.6fy) improved the mean fatigue strength by 20%. In addition, a use of equivalent nominal stresses for the joints subjected to VA loads resulted in conservative assessments when employing S–N curves obtained for the CA loading. The 4R method, via the local mean stress correction for individual cycles, provided higher accuracy for the fatigue assessments.

5,8-Quinolinedione Attached to Quinone Derivatives: XRD Diffraction, Fourier Transform Infrared Spectra and Computational Analysis

Quinoline and isoquinoline moieties occur in many natural and synthetic compounds exhibiting high biological activity. The purpose of this study was to analyze the chemical structures of 5,8-quinolinedione and 5,8-isoquinoline derivatives using FT-IR spectroscopy supplemented with theoretical DFT calculations. Spectroscopic measurements were conducted using the attenuated total reflection (ATR) mode in the frequency range of 4000–400 cm−1. An analysis of FT-IR spectra was carried out, assigning the characteristic vibration frequencies of various functional groups to individual peaks. It was found that the experimental and calculated FT-IR spectra showed a good correlation for all the compounds under study. The most significant difference in the spectra occurred in the region of carbonyl bands. For compounds with the 5,8-quinolinedione moiety, two separated C=O vibration peaks were observed, while for compounds with the 5,8-isoquinolinedione moiety, the carbonyl vibrations created only one peak. This difference makes it possible to distinguish between the 5,8-quinolinedione and 5,8-isoquinolinedione derivatives.

Speaker diarization with variants of self-attention and joint speaker embedding extractor

The speaker diarization task pertains to the automated differentiation of speakers within an audio recording, while lacking any prior information regarding the speakers. The introduction of the self-attention mechanism in End-to-End Neural Speaker Diarization (EEND) has elegantly resolved the issue of overlapping speakers. The Transformer model equipped with self-attention mechanism has shown great potential in collecting global information, yielding remarkable outcomes in various tasks. However, the individual speaker characteristics are predominantly reflected in the contextual information, which conventional self-attention would not adequately address. In this study, we propose a hierarchical encoders model to augment the encoders’ acquisition of speaker information in two distinct ways: (1) Constraining the perceptual field of the self-attentive mechanism with left-right windows or Gaussian weights to highlight contextual information; (2) Utilizing a pre-trained time-delay neural network based speaker embedding extractor to alleviate the shortcomings of speaker feature extraction ability. We evaluate the proposed methods on a simulated dataset of two speakers and a real conversation dataset. The model with the most favorable outcomes among the proposed enhancements achieves a diarization error rate of 7.74% on the simulated dataset and 21.92% on MagicData-RAMC after adaptation. These results compellingly demonstrate the efficacy of the proposed methods.

In search of gravity mode signatures in main sequence solar-type stars observed by Kepler

Gravity modes (g modes), mixed gravito-acoustic modes (mixed modes), and gravito-inertial modes (gi modes) possess unmatched properties as probes for stars with radiative interiors. The structural and dynamical constraints that they are able to provide cannot be accessed by other means. While they provide precious insights into the internal dynamics of evolved stars as well as massive and intermediate-mass stars, their non-detection in main sequence (MS) solar-type stars make them a crucial missing piece in our understanding of angular momentum transport in radiative zones and stellar rotational evolution. In this work, we aim to apply certain analysis tools originally developed for helioseismology in order to look for g-mode signatures in MS solar-type stars. We select a sample of the 34 most promising MS solar-type stars with Kepler four-year long photometric time series. All these stars are well-characterised late F-type stars with thin convective envelopes, fast convective flows, and stochastically excited acoustic modes (p modes). For each star, we compute the background noise level of the Fourier power spectrum to identify significant peaks at low frequency. After successfully detecting individual peaks in 12 targets, we further analyse four of them and observe distinct patterns of surrounding peaks with a low probability of being noise artifacts. Comparisons with the predictions from reference models suggest that these patterns are compatible with the presence of non-asymptotic low-order pure g modes, pure p modes, and mixed modes. Given their sensitivity to both the convective core interface stratification and the coupling between p- and g-mode resonant cavities, such modes are able to provide strong constraints on the structure and evolutionary states of the related targets. Considering the granulation and activity background of the stars in our sample, we subsequently compute the corresponding mode velocity necessary to trigger a detectable luminosity fluctuation. We use it to estimate the surface velocity, ⟨vr⟩, of the candidate modes we have detected. In this case, we find ⟨vr⟩∼10 cm s−1. These results could be extremely useful for characterising the deep interior of MS solar-type stars, as the upcoming PLATO mission will considerably expand the size of the available working sample.

‘It’ Is Not for Everyone: Variation in Speakers’ Evaluation of Sociopragmatic Pronouns in Limburgian

This paper explores the different ways in which speakers of Limburgian think and feel about sociopragmatic pronouns in their dialect, in which women can traditionally be referred to with both ziej ‘she’ and het ‘she’ (lit. ‘it’). Previous research revealed variation between speakers regarding the use of het, which appears to be associated with differences in interpretation and evaluation. This study investigates this further by analyzing how individual speakers evaluate non-feminine pronouns for women. Our data show that many speakers have a relatively high level of awareness, discussing four key themes: (i) how female reference in Limburgian differs from that of Dutch; (ii) the appropriateness of using the pronouns for certain referents and/or in certain social situations; (iii) the various connotations the pronouns may have; and (iv) how they navigate between-speaker differences regarding pronoun evaluation in daily life. Importantly, this high level of awareness is not present in all speakers. These results indicate that the use or non-use of the pronoun het for female referents may be conditioned by cognitive automaticity for some speakers, and by a conscious, emotionally charged consideration about its desirability for others. Our findings, therefore, suggest the importance of integrating cognition and sociality in linguistic theorizing.

Modeling the effects of transcranial magnetic stimulation on spatial attention

Objectives. Transcranial magnetic stimulation (TMS) has been widely used to modulate brain activity in healthy and diseased brains, but the underlying mechanisms are not fully understood. Previous research leveraged biophysical modeling of the induced electric field (E-field) to map causal structure–function relationships in the primary motor cortex. This study aims at transferring this localization approach to spatial attention, which helps to understand the TMS effects on cognitive functions, and may ultimately optimize stimulation schemes. Approach. Thirty right-handed healthy participants underwent a functional magnetic imaging (fMRI) experiment, and seventeen of them participated in a TMS experiment. The individual fMRI activation peak within the right inferior parietal lobule (rIPL) during a Posner-like attention task defined the center target for TMS. Thereafter, participants underwent 500 Posner task trials. During each trial, a 5-pulse burst of 10 Hz repetitive TMS (rTMS) was given over the rIPL to modulate attentional processing. The TMS-induced E-fields for every cortical target were correlated with the behavioral modulation to identify relevant cortical regions for attentional orientation and reorientation. Main results. We did not observe a robust correlation between E-field strength and behavioral outcomes, highlighting the challenges of transferring the localization method to cognitive functions with high neural response variability and complex network interactions. Nevertheless, TMS selectively inhibited attentional reorienting in five out of seventeen subjects, resulting in task-specific behavioral impairments. The BOLD-measured neuronal activity and TMS-evoked neuronal effects showed different patterns, which emphasizes the principal distinction between the neural activity being correlated with (or maybe even caused by) particular paradigms, and the activity of neural populations exerting a causal influence on the behavioral outcome. Significance. This study is the first to explore the mechanisms of TMS-induced attentional modulation through electrical field modeling. Our findings highlight the complexity of cognitive functions and provide a basis for optimizing attentional stimulation protocols.

Data Augmentation based Cross-Lingual Multi-Speaker TTS using DL with Sentiment Analysis

Text to S peech (TTS) algorithms have made tremendous strides in recent years in terms of their ability to generate speech in a single language that sounds as natural as possible. However, because to a lack of available training data, the synthesis of speech from the same person in various languages continues to be difficult. It might be challenging to locate people who are proficient in numerous languages at a level equivalent to native speakers. Voice conversion is one method that may be used to create a polyglot corpus, which can then be used to solve this problem. This entails making use of a voice representation model that has been trained on 53 different languages through the application of hybrid deep learning in order to capture speaker-invariant qualities. In this study, we present a novel approach for the conversion of voices across different languages by employing Generated Adversarial Networks (GANs) to train a multilingual TTS system. The concept of individual likeness loss in order to address the special difficulty of maintaining one's individual speaking identity during the training process can be offered. This work is focused to provide the impression that voice data coming from a variety of languages and speakers was produced by the same individual, and one way to do so is by using this word. In order to determine the extent to which our model is useful, two experiments that compared it against benchmarks that made use of varying degrees of parameter sharing between languages are carried out. The purpose of these experiments was to evaluate the accuracy of pronunciation as well as the caliber of the synthetic voice during transitions between different languages.

Grid tariff designs to address electrification and their allocative impacts

This paper investigates volumetric grid tariff designs considering different pricing mechanisms and resulting in cost-allocative impacts across socio-techno-economic consumer categories. In a case study of 1.56 million Danish households divided into 90 socio-techno-economic categories, we compare three alternative grid tariffs and investigate their impact on annual electricity bills. The results of our design, consisting of a time-dependent threshold penalizing individual peak consumption and a system peak tariff, show (a) a range of different allocations that distribute the burden of additional grid costs across both technologies and (b) strong positive outcomes, including reduced expenses for lower-income groups and smaller households.

Stereochemistry of aminoacylated cardiolipins and phosphatidylglycerols from bacteria.

Hydrophilic interaction liquid chromatography (HILIC) connected with electrospray high-resolution tandem mass spectrometry (MS) was used for the analysis of unusual amino acid (AA) substituted phosphatidylglycerols (PG) and cardiolipins (CL) in mesophilic and thermophilic bacteria. Individual peaks from the lipid class separation by HILIC were isolated and hydrolyzed to determine the absolute configuration of the aminoacyl side chain. The configuration of the aminoacyl side chain was assigned by indirect liquid chromatography (LC) enantiomer separation after the hydrolysis of the aminoacylated (aminoacyl) lipids using N-(4-nitrophenoxycarbonyl)-l-phenylalanine 2-methoxyethyl ester as chiral derivatizing agent and reversed phase LC-MS for analysis. When two chromatographic methods were combined, less common AAs, such as d-allo-Ile and d-allo-Thr, were identified. The taxonomic classification of bacteria showed that bacteria of the family Bacillaceae (Bacillus and Geobacillus) produce branched-chain AAs, that is, d-allo-Ile, d-Ile, and d-Leu. These AAs were present only in the genera Bacillus and Geobacillus and not in Alicyclobacillus acidoterrestris (family Alicyclobacillaceae). On the contrary, hydroxy AAs, that is, l- and d-Thr, and l- and d-allo-Thr, were identified as aminoacyl-PG and aminoacyl-CL in A. acidoterrestris and were not present in the genera Bacillus and Geobacillus. Therefore, the complete analysis made it possible to identify the stereochemistry of AAs in aminoacyl PGs and CLs and use this fact for chemotaxonomy.

An Automatic Speaker Clustering Pipeline for the Air Traffic Communication Domain

In air traffic management (ATM), voice communications are critical for ensuring the safe and efficient operation of aircraft. The pertinent voice communications—air traffic controller (ATCo) and pilot—are usually transmitted in a single channel, which poses a challenge when developing automatic systems for air traffic management. Speaker clustering is one of the challenges when applying speech processing algorithms to identify and group the same speaker among different speakers. We propose a pipeline that deploys (i) speech activity detection (SAD) to identify speech segments, (ii) an automatic speech recognition system to generate the text for audio segments, (iii) text-based speaker role classification to detect the role of the speaker—ATCo or pilot in our case—and (iv) unsupervised speaker clustering to create a cluster of each individual pilot speaker from the obtained speech utterances. The speech segments obtained by SAD are input into an automatic speech recognition (ASR) engine to generate the automatic English transcripts. The speaker role classification system takes the transcript as input and uses it to determine whether the speech was from the ATCo or the pilot. As the main goal of this project is to group the speakers in pilot communication, only pilot data acquired from the classification system is employed. We present a method for separating the speech parts of pilots into different clusters based on the speaker’s voice using agglomerative hierarchical clustering (AHC). The performance of the speaker role classification and speaker clustering is evaluated on two publicly available datasets: the ATCO2 corpus and the Linguistic Data Consortium Air Traffic Control Corpus (LDC-ATCC). Since the pilots’ real identities are unknown, the ground truth is generated based on logical hypotheses regarding the creation of each dataset, timing information, and the information extracted from associated callsigns. In the case of speaker clustering, the proposed algorithm achieves an accuracy of 70% on the LDC-ATCC dataset and 50% on the more noisy ATCO2 dataset.

Senior official speeches and severe price discontinuities in the foreign exchange market

Purpose This study aims to better understand the effects of speeches as a valuable communication tool for central banks. It extends the analysis of the effects of public speeches on jumps to determine whether individual speakers matter partly because of their name, position or institution. Design/methodology/approach This study detects intraday jumps using a robust-to-jump volatility estimator that accounts for deterministic seasonality. As a result, this study removes spurious jumps that occur when volatility is high and consider the relatively small jumps that occur when volatility is low. After identifying jumps, this study examines their reactions to senior official speeches and macroeconomic news surrounding the US and European Union (EU) financial crises. Findings Despite having the most influential individual speakers, this study finds that the impact of the Federal Reserve (Fed) and European Central Bank (ECB) is mitigated because the two institutions have a relatively small impact on currency jumps. This finding shows that the speaker’s name is more important than his or her institution affiliation. While the Federal Reserve Bank President and Chief Executive, as well as ECB board members, significantly reduce jump sizes, particularly during the EU crisis period, both the Fed Chairman and the ECB President increase the magnitude of the jump in both the US crisis and noncrisis periods, contributing to market instability. Practical implications The implications of the results include international portfolio management, currency derivatives pricing and hedging, risk management and market efficiency. Originality/value The findings contribute to a better understanding of the effects of senior official speech attributes on currency jumps in various economic states. The results raise questions about the speaker’s name, institution and position’s effectiveness in calming markets and reducing uncertainty.

On the small flat vowel systems of Australian languages

The vowel systems of Australian languages could best be characterized as “small and flat.” Small, because about 50% of Australian languages have a three-vowel system with another 20% or so distinguishing four or five vowel qualities. Flat, because, while there is the usual degree of separation between front and back vowels along the horizontal (F2) axis of the vowel space (700–2400 Hz), variation along the vertical (F1) axis is typically restricted to a range of 350-900 Hz, leaving the ‘close’ vowel area noticeably under-exploited. Thus, rather than the [i, a, u] values as traditionally transcribed, 3-vowel languages have the phonetic (Cardinal Vowel) qualities of [e, ɐ, o] and 5-vowel languages have [e, ɛ, ɐ, ɔ, o]. I suggest that, as with the atypical consonant inventories, the lack of close vowels in these languages may be explained in terms of the historical influence of the hearing status of their speakers. Reduction in vowel space in individual speakers is one consequence of hearing impairment caused by otitis media, which can reduce hearing levels under 500 Hz by up to 40 dB. The Australian Aboriginal population has the highest prevalence of otitis media in the world by far (50 to 90%).

Deconvolution of DSC peaks of high-temperature phases in an illite/smectite–CaCO3 mixture

Heat flow curves measured in differential scanning calorimetry (DSC) may contain overlapping peaks corresponding to multiple-step processes. To analyze the individual steps in such a process, a deconvolution of the overlapping peaks into the individual peaks is necessary. Using the Frazer-Suzuki function to describe asymmetric peaks, we apply a nonlinear least squares analysis to perform the decomposition of heat flow curves measured for a mixture of an illite/smectite clay with 19.6 wt.% of CaCO3. The curves contain two overlapping peaks associated with the crystallizations of gehlenite and anorthite in the temperature interval from 900 °C to 1050 °C. Several versions of the decomposition analysis may be used, depending on the number of optimized parameters. These may range from four to all eight parameters (four for either peak). We applied the versions with seven and eight fitting parameters, yielding results that are in very good agreement with the experimental data.

Thermoluminescence properties of nano-alumina with two different particle sizes

This research aims to examine the thermoluminescence (TL) properties of nano-sized alumina, including the relationship between TL intensity and absorbed dose, the identification of individual luminescence peaks, and determining trap parameters for use as a possible dosimeter. The samples were exposed to 530 to 2646 Gy doses from 60Co irradiation. The results show that micro-sized α-Al2O3 had a main dosimetry peak at Tm = 435 K, while nano-α-Al2O3 samples with particle sizes of 40 and 50 nm displayed a TL luminescence glow curve, with the primary dosimetry peak located in the low-temperature range and a complex structure at higher temperatures (above 500 K). The primary dosimetry peak was influenced by nanoparticle size, with a maximum of 460 K for the 40 nm sample and 467 K for the 50 nm sample. The main dosimetry peak was described by the superposition of two peaks

Photoluminescence and thermoluminescence properties of pure and rare-earth-doped ZrO2 prepared by Pechini-type sol-gel.

In this article, photoluminescence (PL) and thermoluminescence (TL) properties of ZrO2 , ZrO2 :Dy3+ , ZrO2 :Dy3+ -Gd3+ , ZrO2 :Dy3+ -Yb3+ , ZrO2 :Dy3+ -Er3+ , and ZrO2 :Dy3+ -Sm3+ phosphors synthesized by the Pechini method were investigated. The crystal structure, thermal properties, morphology, PL and TL properties were investigated using X-ray powder diffraction (XRD), differential thermal analysis/thermogravimetric analysis (DTA/TGA), scanning electron microscopy (SEM), PL and TL, respectively. The room temperature emission bands corresponding to 4 F9/2 →6 HJ (J= 9/2, 11/2, 13/2 and 15/2) transitions of Dy3+ ions were measured. The phosphors were analysed using Tm -TSTOP , variable dose, and computerized glow curve fitting methods. Reusability, dose-response, and fading characteristics were investigated. The phosphors have a natural TL emission that vanished by heating treatment. Moreover, new peaks with similar properties to the natural emissions were observed after high-dose irradiation and long-term fading experiments. The glow curves of the phosphors have 13 individual peaks and many low- and high-temperature satellite peaks. The origin of the peaks is ZrO2 host material and doping with rare-earth ions (Gd3+ , Dy3+ , Yb3+ , Er3+ and Sm3+ ) does not lead to a new glow peak. The dopants cause drastic changes in individual peak intensities of ZrO2 .The initial fading rates of all the phosphors are relatively fast, but they slow down as time goes on.

Linguistic and relational strategies for advice giving in an online commercial context

Abstract Studies on online advice-giving have focused on non-profit public platforms but rarely examined it in commercial contexts, where the advisor has the motive of seeking economic interests. This study investigates advice-giving in the first five-minute part of paid live talks, which is free but designed to entice the audience to pay for the remaining part. Transcripts of 123 five-minute recordings are collected. This study analyzes individual speakers’ use of discursive moves and the corresponding relational strategies, as well as their effectiveness in boosting online sales. The results indicate that four discursive moves, i.e., metacomment, general information, advice, and assessment, are the most frequently used, with a large majority of advice phrased in declaratives. Statistical analysis showed that inexperienced, non-expert, and low-community-status speakers tend to use more bonding, and expert, experienced, high-community-status, and male speakers prefer to use more hedging. In addition, the effects of bonding, empathizing, and hedging on sales are consistently positive, while those of criticizing are negative; the above effects are moderated by the speaker’s social status. This study adds to the understudied issue of advisors’ relational negotiations and their resultant outcome in public commercial contexts.

Differences in Strength and Fatigue Resistance of Scapular Protractors and Retractors Between Symptomatic and Asymptomatic Dyskinesis.

Scapular dyskinesis is a shoulder dysfunction that can be asymptomatic or associated with pain or weakness. Reduced strength and fatigue resistance of the scapular protractor and retractor muscles that stabilize the scapula might contribute to dyskinesis. To determine the strength and fatigue resistance profiles of participants with symptomatic or asymptomatic scapular dyskinesis and compare them with healthy control (HC) individuals using isokinetic assessment. Cross-sectional study. University hospital. Twenty HC individuals and 21 overhead athletes with symptomatic (n = 10) or asymptomatic (n = 11) scapular dyskinesis. Strength (peak torque, maximum work), fatigue resistance (total work), and protraction:retraction ratios measured during a closed chain isokinetic protocol (40 repetitions in concentric mode at 24.4 cm/s). The scapular protractors' strength and fatigue resistance were higher (P < .01) in HC individuals (peak torque = 5.0 ± 0.9 N/kg, maximum work = 2.4 ± 0.5 J/kg, total work = 72.4 ± 0.6 J/kg) than in asymptomatic (peak torque = 3.4 ± 0.7 N/kg, maximum work = 1.7 ± 0.4 J/kg, total work = 50.0 ± 13.7 J/kg) or symptomatic (peak torque = 3.8 ± 0.6 N/kg, maximum work = 1.8 ± 0.3 J/kg, total work = 58.1 ± 12.9 J/kg) dyskinetic participants. The symptomatic dyskinetic group presented the highest retractor strength and fatigue resistance (P < .01) values (peak torque = 5.2 ± 0.6 N/kg, maximum work = 2.9 ± 0.8 J/kg, total work = 87.7 ± 22.7 J/kg), followed by the HC individuals (peak torque = 4.7 ± 1.0 N/kg, maximum work = 2.1 ± 0.5 J/kg, total work = 65.3 ± 17.9 J/kg) and the asymptomatic dyskinetic participants (peak torque = 3.9 ± 1.0 N/kg, maximum work = 1.9 ± 0.6 J/kg, total work = 58.6 ± 18.5 J/kg). The protraction:retraction ratios showed a gradual decrease (P < .001) from the HC individuals (1.1) to the asymptomatic (0.9) and symptomatic (0.7) dyskinetic participants. Scapular dyskinesis is characterized by weaker scapular protractors and reduced agonist:antagonist ratios, especially when patients are symptomatic. Targeting the scapular protractors to achieve a better balance of scapular musculature in rehabilitation and strengthening programs may improve shoulder symptoms and function, but more interventional studies are required.

The synergistic impacts of hybrid nanofillers of graphene nanoplatelets/carbon nanotubes on curing behavior of an epoxy‐vinyl ester interpenetrating polymer network nanocomposite coating

AbstractThis study investigated the synergistic effects of hybrid graphene nanoplatelet (GnP)/multi walled carbon nanotube (MWCNT) nanofillers at various loadings on the kinetics of curing of the epoxy (EP)/vinyl ester (VE) interpenetrating polymer network (IPN) system, with a mass ratio of 1:1. Fourier transform infrared spectroscopy (FTIR), dynamic mechanical thermal analyzer (DMTA) and differential scanning calorimetry (DSC) were used to monitor the interpenetration process of EP and VE and likely interactions between the components of the different resin systems in IPN. The curing behavior of all prepared samples under non‐isothermal conditions was studied using DSC at four heating rates. Two different isoconversional approaches were applied to evaluate the reaction kinetics, that is, the Friedman and the advanced Vyazovkin methods. The obtained activation energy curves for all samples revealed a complex curing behavior involving three stages; early IPN stage, IPN growth stage, and late IPN stage. Then, the activation energy values for each reaction step were determined based on the Friedman method. The presence of GnP/MWCNT nanoparticles showed no catalytic effect on the reaction of VE with methyl ethyl ketone peroxide (MEKP). In contrast, incorporating GnP/MWCNT nanoparticles significantly decreases the activation energy values of the reaction of ring opening of epoxides with methyl tetrahydrophthalic anhydride (MTHPA) 1‐methyl imidazole (‐Mi) and the reaction of esterification of the hydroxyl groups of VE with MTHPA.Highlights Model‐free methods used to curing study of epoxy‐vinyl ester IPN nanocomposites FTIR, DSC and DMTA used for evaluation IPN formation of EP/VE It showed that the improvement of dispersion and compatibility by using of GnP/MWCNT hybrid Frideman and Vyazovkin methods used to calculate Ea of nanocomposites DSC thermograms were deconvoluted into three individual peaks.

Dawn of the Transformer Era in Speech Emotion Recognition: Closing the Valence Gap.

Recent advances in transformer-based architectures have shown promise in several machine learning tasks. In the audio domain, such architectures have been successfully utilised in the field of speech emotion recognition (SER). However, existing works have not evaluated the influence of model size and pre-training data on downstream performance, and have shown limited attention to generalisation, robustness, fairness, and efficiency. The present contribution conducts a thorough analysis of these aspects on several pre-trained variants of wav2vec2.0 and HuBERT that we fine-tuned on the dimensions arousal, dominance, and valence of MSP-Podcast, while additionally using IEMOCAP and MOSI to test cross-corpus generalisation. To the best of our knowledge, we obtain the top performance for valence prediction without use of explicit linguistic information, with a concordance correlation coefficient (CCC) of. 638 on MSP-Podcast. Our investigations reveal that transformer-based architectures are more robust compared to a CNN-based baseline and fair with respect to gender groups, but not towards individual speakers. Finally, we show that their success on valence is based on implicit linguistic information, which explains why they perform on-par with recent multimodal approaches that explicitly utilise textual information. To make our findings reproducible, we release the best performing model to the community.

Systemic Ropivacaine Concentrations Following Local Infiltration Analgesia and Femoral Nerve Block in Older Patients Undergoing Total Knee Arthroplasty.

The study examined the pharmacokinetic profile of fixed formulation mixtures comprising 225 mg of ropivacaine for local infiltration analgesia with or without epinephrine, and femoral nerve block in older patients presenting for orthopedic surgery and explored potential influences of block type, age, and body weight on this profile. Twenty four patients scheduled for total knee arthroplasty were randomly assigned to three groups: femoral nerve block, local infiltration analgesia with epinephrine and local infiltration analgesia without epinephrine. Blood samples were collected at 10, 30, 60, and 120 min following the block and total plasma concentrations of ropivacaine were quantified by high performance liquid chromatography. The mean individual peak total plasma concentrations of ropivacaine in local infiltration analgesia with and without epinephrine, and femoral nerve block group were 0.334, 0.490 and 0.545 μg mL-1 (p = 0.16). Local infiltration with epinephrine group had significantly lower plasma ropivacaine concentrations at 30, 60 and 120 minutes. The plasma ropivacaine concentrations exceeded 2.2 μg mL-1 in one patient. Age, but not body weight, had a moderate correlation with peak plasma ropivacaine concentration (r = 0.37, p = 0.08). Administration of a fixed 225 mg dose of ropivacaine for local infiltration analgesia with epinephrine and femoral nerve block results in plasma ropivacaine concentrations below the toxicity threshold, indicating their safety. The use of local infiltration analgesia with epinephrine provides a greater safety margin, as local infiltration analgesia without epinephrine may lead to ropivacaine concentrations associated with symptoms of local anesthetic toxicity.