Individual Peaks Research Articles

The effects of face mask on speech production and its implication for forensic speaker identification-A cross-linguistic study.

This study aims to understand the effects of face mask on speech production between Mandarin Chinese and English, and on the automatic classification of mask/no mask speech and individual speakers. A cross-linguistic study on mask speech between Mandarin Chinese and English was then conducted. Continuous speech of the phonetically balanced texts in both Chinese and English versions were recorded from thirty native speakers of Mandarin Chinese (i.e., 15 males and 15 females) with and without wearing a surgical mask. The results of acoustic analyses showed that mask speech exhibited higher F0, intensity, HNR, and lower jitter and shimmer than no mask speech for Mandarin Chinese, whereas higher HNR and lower jitter and shimmer were observed for English mask speech. The results of classification analyses showed that, based on the four supervised learning algorithms (i.e., Linear Discriminant Analysis, Naïve Bayes Classifier, Random Forest, and Support Vector Machine), undesirable performances (i.e., lower than 50%) in classifying the speech with and without a face mask, and highly-variable accuracies (i.e., ranging from 40% to 89.2%) in identifying individual speakers were achieved. These findings imply that the speakers tend to conduct acoustic adjustments to improve their speech intelligibility when wearing surgical mask. However, a cross-linguistic difference in speech strategies to compensate for intelligibility was observed that Mandarin speech was produced with higher F0, intensity, and HNR, while English was produced with higher HNR. Besides, the highly-variable accuracies of speaker identification might suggest that surgical mask would impact the general performance of the accuracy of automatic speaker recognition. In general, therefore, it seems wearing a surgical mask would impact both acoustic-phonetic and automatic speaker recognition approaches to some extent, thus suggesting particular cautions in the real-case practice of forensic speaker identification.

EXPERIMENTAL STUDY OF THE INFLUENCE OF REGISTER FORMALITY ON THE PREFERRED REALIZATION OF THE COMPLEMENT CLAUSE IN RUSSIAN

In Russian, sentential complements (that-clauses) are optionally preceded by the demonstrative to ‘that’ (sometimes called ‘correlative’), with the required case marking or preposition selected by the verb. Several factors have been suggested in the literature as influencing the choice of the construction with to, including the matrix predicate as well as information structure. Th is work investigates the influence of register formality on the preferred realization of the complement. It is hypothesized that the construction with to, being the more explicit variant, is associated with more formal registers. Th is hypothesis has been previously tested on the basis of corpus data and received limited support. Here it is tested in a (two-alternative) forced-choice experiment where the register (news vs. spoken) is manipulated within items and subjects. 18 alternating predicates were tested, with two matched pairs of sentences with the contrasted registers constructed for each predicate. In addition, the experiment tested the influence of lexical biases, as measured by the ‘collostructional analysis’ or by relative frequency of the alternating constructions in the corpus. Th e results showed a reliable effect of lexical biases, as well as a much weaker but significant effect of formality suggesting that in the news register the construction with to is preferred more oft en compared to the spoken register, in line with the experimental hypothesis, whereas register did not interact with the lexical bias. Interestingly, a substantial amount of variation in the results was due to lexical biases as well as individual speaker preferences for one or the other construction.

Physical preparation of the Australian national male field hockey team exceeded the movement demands of the Tokyo 2020 Olympic Games tournament

ABSTRACT This investigation explored differences in the pre-tournament preparation period relative to the movement demands of the Tokyo 2020 Olympic Games for the Australian male field-hockey team. Movement data was collected over 7 months prior to and during the 13-day Olympic tournament. Duration, distance (total; >80% individual peak velocity; >5 m.s−1), high-speed decelerations (>3.5 m.s−2), and total accelerations and decelerations (>2.5 m.s−2) were measured during each running-based session. A 13-day moving sum was calculated for each variable and compared to a player-specific “worst-case scenario” (WCS) for intra-tournament total movement demands. Summed 13-day movement demands exceeded the WCS for 6–58% of the preparation period across variables, for the entire squad. During the tournament, midfielders covered significantly greater sprint distance than Defenders (+84%,p = 0.020), with no other positional differences found. Greater variation in tournament movement demands was observed between players for accelerations, decelerations, and high-speed distance (CV = 19–46%) compared to duration and distance (CV = 4–9%). In conclusion, physical preparation exposed athletes to movement demands which surpassed WCS. Additionally, gross measures of training volume (duration and distance) are more generalisable to a squad; however, additional metrics such as sprint distance and high-speed decelerations are needed to better define positional and individual movement demands, and therefore, should be monitored by practitioners.

Test-retest reliability of resting-state EEG in young and older adults.

The quantification of resting-state electroencephalography (EEG) is associated with a variety of measures. These include power estimates at different frequencies, microstate analysis, and frequency-resolved source power and connectivity analyses. Resting-state EEG metrics have been widely used to delineate the manifestation of cognition and to identify psychophysiological indicators of age-related cognitive decline. The reliability of the utilized metrics is a prerequisite for establishing robust brain-behavior relationships and clinically relevant indicators of cognitive decline. To date, however, test-retest reliability examination of measures derived from resting human EEG, comparing different resting-state measures between young and older participants, within the same adequately powered dataset, is lacking. The present registered report examined test-retest reliability in a sample of 95 young (age range: 20-35 years) and 93 older (age range: 60-80 years) participants. A good-to-excellent test-retest reliability was confirmed in both age groups for power estimates on both scalp and source levels as well as for the individual alpha peak power and frequency. Partial confirmation was observed for hypotheses stating good-to-excellent reliability of microstates measures and connectivity. Equal levels of reliability between the age groups were confirmed for scalp-level power estimates and partially so for source-level power and connectivity. In total, five out of the nine postulated hypotheses were empirically supported and confirmed good-to-excellent reliability of the most commonly reported resting-state EEG metrics.

Near-isotropic enhancement of the 20 K critical current of REBa2Cu3O7 coated conductors from columnar defects

Normal-incidence irradiation by 100 MeV Ag ions is used to improve flux pinning in previously optimised commercial REBCO tapes from the American Superconductor Corporation. We observe distinct critical-current anisotropy enhancements below and above 40 K. Above 40 K a strong c-axis peak appears in the angular dependence of the critical current, as is usually expected upon the introduction of columnar defects. The critical current is enhanced significantly but only for a limited range of field angles. Close to the parallel-field direction there is no enhancement or even a reduction in critical current. Below 40 K, on the other hand, the enhancement is much broader with respect to field angle, creating an almost isotropic response at 20 K, 3 T. The absence of a prominent c-axis peak does not indicate a lack of pinning, since the absolute value of the critical current still increases by a factor of 2.8 compared to an unirradiated sample. Instead, we postulate that pre-existing point-like pinning centres act to mediate an interaction between the existing planar and newly-introduced columnar pins, broadening both contributions. The point-like pins become less effective with increasing temperature as the coherence length increases, leading to a reduction in this interaction and a separation of the individual peaks relating to planar and columnar pins. At 20 K, we achieve an enhancement in the angular-minimum critical current by a factor of 2.7, in a material that had already been process-optimised for low-temperature pinning.

Effects of nanosecond impulse and step excitation in pulsed electro acoustic measurements on signals for space charge determination in high-voltage electrical insulation

The presence of space charges in high-voltage insulation can influence the operational stresses of the dielectric materials; the topic is present in various, even distant domains such as power grids or transportation segments that are represented by electromobility, rail, more-electric aircraft, and space systems. In this article, the effects of nanosecond impulse and step excitation in the pulsed electro-acoustic measurements (PEA) of space charges in high-voltage electrical insulation have been investigated. Various parameters of a pulser (such as impulse width, rise time, and sensor thickness) have been investigated by using a designed programable pulser. The investigations have been performed on a polyethylene sample in one- or double-layer configurations. In the latter, an interlayer sprinkled charge was analyzed. The experimental results have shown the main PEA effect during the transition phase of the applied voltage. It was observed that the pulse transition has a critical importance for stimulating space-charge vibrations and generating elastic waves. Hence, the slope’s rise and fall times are crucial in pulser design. The pulser width also has an impact on a signal’s magnitude as well as on its dispersion and attenuation. The correspondence between a pulse and step excitation was presented. Some advantages are attributed to the step-based excitation in terms of fewer wave reflections and interferences as well as the avoidance of the wavelet cancelation effect for a very narrow pulse width. Hence, step excitation can result in the easier postprocessing and interpretation of individual peaks in the acquired PEA signal. Another advantage may be recognizing the space-charge polarity instead of the net result. Important recommendations refer to the tuning of pulser timing settings with respect to signal attenuation (especially in thicker specimens) and the adequate adjustment of the sensor’s thickness. The presented analysis and experimental results extend the insight into PEA measurement – especially with a focus on diagnostic applications.

A non-isothermal thermokinetic degradation study of the mesoporous Ni–Co layered double hydroxide using isoconversional approaches

The present study describes the phenomenological thermokinetic behavior of the mesoporous Ni–Co layered double hydroxide (LDH) and determines three basic parameters called ‘kinetic triplets’. The non-isothermal kinetic heating program was carried out at four different heating rates, viz. 5,10,15, and 20oC.min−1, respectively, in the temperature range of 50−800oC. Various isoconversional or model-free kinetics involving integral and differentials like Kissinger–Akahira–Sunose, Flynn-Wall-Ozawa, Friedman, and non-linear Vyazovkin methods were utilized. Due to the presence of physisorbed gas or moisture phases, the temperature integral from 50−198oC was excluded from the present study. The experimental and simulation results described the consistency in depicting the effective activation energies by either Friedman or non-linear Vyazovkin isoconversional methods. Also, it was observed that the variation in activation energies was found to differ by 9–10%, which confirms the Ni–Co LDH degradation undergoes a kinetically complex process. The evaluation of the preexponential factor and master plot determination of reaction models f(α) showed that the mesoporous Ni–Co LDH degradation pathway strongly depends on kinetic compensation effect and undergoes a reaction process governed by nucleation models. Furthermore, the kinetics of pseudo-components of Ni–Co LDH (mathematical deconvolution analysis) showed that the second (three subtransitions) and third stage (two subtransitions) degradation process are controlled by a number of individual peak components in the thermodynamic temperature range 536–727 K (second) and 727–803 K (third).

Comparing the effect of electron beam, beta and ultraviolet C exposure on the luminescence emission of commercial dosimeters

This paper reports on the luminescence characterization of TLD-100 (LiF: Ti, Mg), TLD-200 (CaF2: Dy), TLD-400 (CaF2: Mn) and GR-200 (LiF: Mg, Cu, P) dosimeters exposed to electro beam, beta and ultraviolet C radiation -UVC-. All of them show high sensitivity to radiation regardless of whether it is ionizing or partially ionizing radiation based on their luminescence properties (cathodoluminescence -CL- or thermoluminescence -TL-). CL emission differs significantly among them in shape and intensity due to their chemical compositions. LiF samples display three maxima at: (i) 300–450 nm linked to intrinsic and structural defects, (ii) a green waveband probably due to F3+ centres or the presence of hydroxyl groups and (iii) the red-infrared emission band associated with F2 centres. However, CL spectra from the CaF2 dosimeters display meaningful differences due to the dopant. TLD-200 is characterized by an emission with four sharp individual peaks in the green-IR spectral region (due to the Dy3+), whilst TLD-400 exhibits a broad maximum peaked at ̴500 nm (linked to the Mn2+). On the other hand, the variation in the TL glow curves allows to discriminate the TLDs exposed to beta and UVC radiation since they give rise to different chemical-physical processes and that have been studied from the estimation of the kinetic parameters by means of the Computerised Glow Curve Deconvolution (CGCD) method.

Different lexicons make different rivals

Analogy-based theories assume that in situations of affix competition, language users create novel word forms on the basis of similar existing forms in their Mental Lexicons ( Baayen et al. 2011 ; Daelemans & van den Bosch 2005; Skousen 1989 ). Interestingly, however, simulation studies employing computational implementations of analogical theories have almost invariably adopted a rather abstractionist view of the Mental Lexicon, representing the word stock of the language, and abstracting away from differences between individual speakers (see, e.g., Arndt-Lappe 2014 ; Chapman & Skousen 2005 ; Eddington 2006 ; Nieder et al. 2021 ). This is a problem because it precludes the possibility of testing a central prediction of analogical theories: if affixes are assigned on the fly on the basis of similar words in the lexicon, then speakers with different lexicons should make different choices. The present paper provides a proof-of-concept study addressing this issue for the form-based rivalry between the two English adjectival suffixes - ic and - ical. Analogical Modeling of Language (AML; Skousen et al. 2013 ) is used as a computational model. On the basis of a survey of the distribution of derivatives in different registers in the British National Corpus, predictions of the analogical model are compared for a simulated speaker with a large vocabulary (including academic words) and a simulated speaker with a small vocabulary that is based mainly on words from spoken language. The statistical analysis of the simulations reveals that, while sharing some basic properties, the two models make very clear – and testable – predictions about speaker differences.

Numerical simulations for characterization of missing articulatory information in ultrasound imaging of speech

The air–tissue interface at the tongue surface allows submental (below the chin) B-mode ultrasound images to depict the shape of the tongue in real time, useful for measuring and understanding typical and disordered tongue articulation during speech production. However, parts of the tongue are obscured; depending on an individual speaker's anatomy and tongue movement patterns, the anterior tongue tip may be shadowed by the mandible bone and the sublingual airspace. To characterize this missing information about the tongue tip in ultrasound images, midsagittal ultrasound images were numericallysimulated. Three-dimensional anatomic models were constructed using magnetic resonance imaging (MRI) data to map tongue tissue, surrounding air, and an estimated position of the mandible. Pulse-echo ultrasound images were then numerically simulated using the open-source k-Wave toolbox. Acoustic properties of the medium and an imaging array model are identified that allow simulations to replicate features in ultrasound images recorded from the same speakers as the MRI data, while maintaining computational efficiency. The potential to recover missing information on the tongue tip position from reverberation artifacts is assessed.

End-to-end child-adult speech diarization in naturalistic conditions of preschool classrooms

Speech and language development are early indicators of overall analytical and learning ability in pre-school children. Early childhood researchers are interested in analyzing naturalistic versus controlled lab recordings to assess both quality and quantity of such communication interactions between children and adults/teachers. Unfortunately, present-day speech technologies are not capable of addressing the wide dynamic scenario of early childhood classroom settings. Due to diversity of acoustic events/conditionsin daylong audio streams, automated speaker diarization technology is limited and must be advanced to address this challenging domain for audio segmentation and meta-data information extraction. We investigate a Deep Learning-based diarization solution for segmenting classroom interactions of 3–5 year-old children engaging with teachers. Here, the focus is on speaker-label diarization which classifies speech segments as belonging to either Adults or Children, partitioned across multiple classrooms. Our proposed ECAPA-TDNN model achieves a best F1-score of 65.5% on data from two classrooms, based on open dev and test sets for each classroom. Also, F1-scores for individual speaker labels provide a breakdown of performance across naturalistic child classroom engagement. The study demonstrates the prospects of addressing educational assessment needs through communication audio stream analysis, while maintaining both security and privacy of all children and adults.

Abstract P207: Heterogeneity in Obesity in Relation to Related to Hypertension: Investigating the Role of Metabolic Pathways

Background: While obesity is associated with hypertension, there is heterogeneity in risk by weight status and we know little about whether and which metabolic pathways play a role in exacerbating differential risk across weight status categories. Methods: Fasting blood was collected at the Yr. 20 follow-up exam in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. We conducted Ultra-High-Performance Liquid Chromatography high resolution mass spectrometry untargeted metabolomics in 1,769 individuals (ages 37-54, 58% female, 66% Black) classified as normotensive (no hypertension diagnosis or medication and SBP/DBP ≤ 130/80). We identified 7,522 metabolomic peaks and 8 principal components, which we included in a multivariable-adjusted proportional hazards model with an interaction term to assess whether the association between these metabolite measures and incident hypertension (HTN) varied by BMI. We then employed multivariate analysis using Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) models using 70% of the sample within each obesity category to predict incident HTN at ten years in normal weight, overweight and obese groups based on the high dimensional metabolomics data. The remaining 30% of individuals in each obesity category were then used to evaluate the predictive value of the OPLS-DA models. Finally, we used mummichog software and Fisher’s exact tests, to conduct pathway enrichment analysis using data from both the individual peak and the OPLS-DA models. Results: We identified 723 metabolites where the association with long term risk of HTN differed by BMI, although none were statistically significant after adjustment for multiple comparisons. However, we found strong evidence of effect modification for metabolites via principal components and OPLS-DA. For the 3 rd principal component, which explained 5% of the variation across all peaks, we found a significant interaction with BMI (p-value = 0.0043). In external test data sets, OPLS-DA models predicted incident HTN relatively well in normal weight individuals (AUC of 77%) but not well in overweight and obese individuals (AUC of 49% and 56% respectively). We identified several pathways with a differential HTN risk by BMI shown in the OPLS-DA and proportional hazards models. In the phenylamine pathway there was substantial differentiation between those with and without incident HTN risk for normal weight only and across the lysine degradation pathway only for individuals who were obese. Conclusions: Our findings identify variation in hypertension risk by BMI, with suggestive evidence for a role of metabolomic pathways and combinations of metabolites. Overall, metabolites predicted 10-year incident hypertension very well in individuals of normal weight (but not obese status), indicating heterogeneity in hypertension risk by weight status.

The Curious Case of Impersonators and Singers: Telling Voices Apart and Telling Voices Together under Naturally Challenging Listening Conditions.

Vocal identity processing depends on the ability to tell apart two instances of different speakers whilst also being able to tell together two instances of the same speaker. Whilst previous research has examined these voice processing capabilities under relatively common listening conditions, it has not yet tested the limits of these capabilities. Here, two studies are presented that employ challenging listening tasks to determine just how good we are at these voice processing tasks. In Experiment 1, 54 university students were asked to distinguish between very similar sounding, yet different speakers (celebrity targets and their impersonators). Participants completed a 'Same/Different' task and a 'Which is the Celebrity?' task to pairs of speakers, and a 'Real or Not?' task to individual speakers. In Experiment 2, a separate group of 40 university students was asked to pair very different sounding instances of the same speakers (speaking and singing). Participants were presented with an array of voice clips and completed a 'Pairs Task' as a variant of the more traditional voice sorting task. The results of Experiment 1 suggested that significantly more mistakes were made when distinguishing celebrity targets from their impersonators than when distinguishing the same targets from control voices. Nevertheless, listeners were significantly better than chance in all three tasks despite the challenge. Similarly, the results of Experiment 2 suggested that it was significantly more difficult to pair singing and speaking clips than to pair two speaking clips, particularly when the speakers were unfamiliar. Again, however, the performance was significantly above zero, and was again better than chance in a cautious comparison. Taken together, the results suggest that vocal identity processing is a highly adaptable task, assisted by familiarity with the speaker. However, the fact that performance remained above chance in all tasks suggests that we had not reached the limit of our listeners' capability, despite the considerable listening challenges introduced. We conclude that voice processing is far better than previous research might have presumed.

On How “Individual Speech Systemˮ and “the Language Systemˮ Relate in Lev Shcherba’s Conception

The article discusses the relationship between the concepts of individual speech systems and language system in the linguistic conception of Lev Shcherba. As shown by Shcherba, the most important resource that ensures human speech activity is not an abstract knowledge of the language system, but the language material, which is the totality of everything spoken and understood in a certain specific situation in one or another era of life of a given social group. To the extent that language material is reflected in the memory of each individual speaker, it forms individual speech systems that provide each person with the ability to receive and produce speech. Considered in its entirety, the linguistic material creates the basis for describing language systems, i.e., for compiling dictionaries and grammars of a given language. Individual speech systems are a psychological phenomenon; therefore, the content of these systems units includes, on the one hand, sets of sensory images aroused in the minds of individual native speakers by these units, and on the other hand, the knowledge of these speakers about the designated objects. As for language systems, then, according to Shcherba, these are verbal descriptions of language, and therefore the description of content of elements of language systems should be predominantly verbal. The article shows that any attempts to describe the language system on the basis of all existing language material are unattainable in practice. Usually dictionaries and grammars are compiled on the basis of limited number of uses of language units that reflects the individual speech systems of a certain number of native speakers. When compiling explanatory dictionaries, this circumstance causes the appearance of not quite correct interpretations of words, due to the insufficient amount of language material used or errors made in its generalization.

Development of Supervised Speaker Diarization System Based on the PyAnnote Audio Processing Library.

Diarization is an important task when work with audiodata is executed, as it provides a solution to the problem related to the need of dividing one analyzed call recording into several speech recordings, each of which belongs to one speaker. Diarization systems segment audio recordings by defining the time boundaries of utterances, and typically use unsupervised methods to group utterances belonging to individual speakers, but do not answer the question "who is speaking?" On the other hand, there are biometric systems that identify individuals on the basis of their voices, but such systems are designed with the prerequisite that only one speaker is present in the analyzed audio recording. However, some applications involve the need to identify multiple speakers that interact freely in an audio recording. This paper proposes two architectures of speaker identification systems based on a combination of diarization and identification methods, which operate on the basis of segment-level or group-level classification. The open-source PyAnnote framework was used to develop the system. The performance of the speaker identification system was verified through the application of the AMI Corpus open-source audio database, which contains 100 h of annotated and transcribed audio and video data. The research method consisted of four experiments to select the best-performing supervised diarization algorithms on the basis of PyAnnote. The first experiment was designed to investigate how the selection of the distance function between vector embedding affects the reliability of identification of a speaker's utterance in a segment-level classification architecture. The second experiment examines the architecture of cluster-centroid (group-level) classification, i.e., the selection of the best clustering and classification methods. The third experiment investigates the impact of different segmentation algorithms on the accuracy of identifying speaker utterances, and the fourth examines embedding window sizes. Experimental results demonstrated that the group-level approach offered better identification results were compared to the segment-level approach, and the latter had the advantage of real-time processing.

DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra.

The quantitative deconvolution of 1D-NMR spectra into individual resonances or peaks is a key step in many modern NMR workflows as it critically affects downstream analysis and interpretation. Depending on the complexity of the NMR spectrum, spectral deconvolution can be a notable challenge. Based on the recent deep neural network DEEP Picker and Voigt Fitter for 2DNMR spectral deconvolution, we present here an accurate, fully automated solution for 1D-NMR spectral analysis, including peak picking, fitting, and reconstruction. The method is demonstrated for complex 1Dsolution NMR spectra showing excellent performance also for spectral regions with multiple strong overlaps and a large dynamic range whose analysis is challenging for current computational methods. The new tool will help streamline 1D-NMR spectral analysis for a wide range of applications and expand their reach toward ever more complex molecular systems and their mixtures.

Personality trait estimation in group discussions using multimodal analysis and speaker embedding

The automatic estimation of personality traits is essential for many human–computer interface (HCI) applications. This paper focused on improving Big Five personality trait estimation in group discussions via multimodal analysis and transfer learning with the state-of-the-art speaker individuality feature, namely, the identity vector (i-vector) speaker embedding. The experiments were carried out by investigating the effective and robust multimodal features for estimation with two group discussion datasets, i.e., the Multimodal Task-Oriented Group Discussion (MATRICS) (in Japanese) and Emergent Leadership (ELEA) (in European languages) corpora. Subsequently, the evaluation was conducted by using leave-one-person-out cross-validation (LOPCV) and ablation tests to compare the effectiveness of each modality. The overall results showed that the speaker-dependent features, e.g., the i-vector, effectively improved the prediction accuracy of Big Five personality trait estimation. In addition, the experimental results showed that audio-related features were the most prominent features in both corpora.

Effects of accumulated versus continuous individualized exercise on postprandial glycemia in young adults with obesity

ABSTRACT Background: Elevated postprandial glucose (PPG) is an independent risk factor for cardiovascular disease. Post-meal exercise effectively reduces PPG concentrations. However, the effect of accumulated versus continuous post-meal exercise on PPG control remains unclear. This study aimed to investigate the effects of individualized accumulated or continuous exercise on PPG in young adults with obesity. Twenty young adults with obesity (11 males) completed three 4-h randomized crossover trials with 6–14-day washout periods: (1) sitting (SIT), (2) one 30-min walking bout (CONT), and (3) three 10-min walking bouts separated by 20-min resting (ACCU). Walking was initiated 20 min before individual PPG peak after breakfast, which was predetermined by continuous glucose monitoring. Blood samples were collected at 15–30 min intervals, and the 24-h glucose was monitored via continuous glucose monitoring. Results: The 4-h PPG incremental area under the curve (iAUC) was 12.1%±30.9% and 21.5%±21.5% smaller after CONT (P = 0.022) and ACCU (P < 0.001), respectively, than after SIT. PPG concentrations were lower during CONT at 30–60 min and during ACCU at 30–105 min after breakfast than during SIT (all P < 0.05). The 4-h plasma insulin and C-peptide iAUC, and mean amplitude of glycemic excursions were lower after CONT and ACCU than after SIT (all P < 0.05). Conclusions: Both continuous and accumulated exercises reduced PPG, insulin, and C-peptide concentrations and improved glucose fluctuations. Accumulated exercise maintained lower PPG concentrations for a longer time than continuous exercise in young adults with obesity. Clinical Trial Information: Clinical trial registration No. ChiCTR 2000035064, URL: http://www.chictr.org.cn/showproj.aspx?proj=56584; (registered July 29, 2020).

Novel Multidimensional Liquid Chromatography Workflow with In-Loop Enzymatic Digests of Multiple Heart-Cuts for Fast and Flexible Characterization of Biotherapeutic Protein Variants

Multidimensional liquid chromatography (mD-LC) is becoming a powerful tool for complete characterization of individual peaks and protein variants through separation methods such as nondenaturing ion exchange (IEC) or size-exclusion chromatography coupled to reversed-phase (RP) chromatography. The flexibility of commercially available and customized mD-LC systems is still limited in terms of enzymatic peak processing between chromatographic dimensions. In this regard, only a few column-immobilized proteases are available for detailed peak characterization by mD-LC coupled to mass spectrometry (mD-LC-MS). Here, we present a purpose-built and automated multiple heart-cutting mD-LC design with a novel analytical workflow involving in-loop enzymatic heart-cut digestion between the first-dimensional column and transfer to the second dimension before MS or MS/MS analyses. The setup facilitates the spike-in of any enzyme to multiple heart-cuts for multilevel analysis, for example, for peptide mapping, fragment generation, or deglycosylation, to reduce heterogeneity and provide maximum flexibility in terms of incubation time for optimal peak characterization. We demonstrate the application of IEC coupled to RP-LC-MS and automated in-loop deglycosylation and on-column reduction of an IgG antibody combined with upper hinge region cleavage for Fab generation. We further employ mD-LC-MS and mD-LC-MS/MS to assess post-translational modifications of a bispecific antibody and to support molecule selection by evaluating the best downstream purification strategy. The novel design and automated workflow of the mD-LC system described here offers enhanced flexibility for in-solution processing and real-time monitoring of multiple heart-cuts enabling streamlined characterization of unknown biotherapeutic charge and size variants.

Effect of interface quality on photoluminescence of encapsulated MoSe&lt;sub&gt;2&lt;/sub&gt; monolayers

Photoluminescence spectra of excitons and trions in MoSe2 monolayers encapsulated with hexagonal boron nitride under nonresonant laser excitation were studied. When the size of the laser excitation spot decreases from 8 to 3 nm, individual peaks with a line width of ~2 meV emerge in the photoluminescence spectra, which were unresolved with a larger spot. Studies of the sample surface using a scanning electron microscope revealed the existence of a large number of features at the interfaces of structures with characteristic sizes ranging from submicron to micron and more. It was expected that the lines appearing in the spectrum at small excitation spot sizes were associated with similar submicron inhomogeneities. A study of a specially made heterostructure covered by a metal mask with holes of 1.6 microns in diameter confirmed this assumption.