bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cleansing efficacy of an auto-cleaning toothbrushing device with nylon bristles: a randomized-controlled pilot study
Authors: Keller Mathias , Keller Gregor , Eller Thomas , Sigwart Lukas , Wiesmüller Vera , Steiner René , Offermanns Vincent , Kapferer-Seebacher Ines 
Published: October 2022

Abstract
Objectives
To compare the cleansing efficacy of an auto-cleaning device with nylon bristles (Y-brush®) to that of manual toothbrushing.

Materials and methods
Twenty probands refrained from oral hygiene for 3 days. Rustogi Modified Navy Plaque Index was assessed before and after (randomized) toothbrushing either with the auto-cleaning device for 5 s per jaw or with a manual toothbrush for a freely chosen time up to 4 min. The clinical investigation was repeated in a cross-over design. In a third trial period, the brushing time for auto-cleaning was increased to 15 s per jaw. The study was supplemented by plaster cast analyses.

Results
Full-mouth plaque reduction was higher with manual toothbrushing than with auto-cleaning for 5 s per jaw (p < 0.001). There was no statistically significant difference on smooth tooth surfaces but on marginal and interdental sites. Increasing the brushing time of auto-cleaning to 15 s per jaw resulted in a comparable full-mouth plaque reduction as with manual toothbrushing (p = 0.177). In 95% of individuals, the device was too short not completely covering second molars. In 30.67% of teeth, the gingival margin was not covered by bristles.

Conclusions
Auto-cleaning devices with nylon bristles have a future potential to reach plaque reduction levels comparable to manual toothbrushing, although manufacturers must focus on improving an accurate fit.

Clinical relevance
Under the premise of an ameliorated fit, the auto-cleaning device might be recommendable for people with low brushing efficacy. Interdental sites remain a failure point if adjunct interdental cleaning is not viable.
Gel Biter: food texture discriminator based on physical reservoir computing with multiple soft materials
Authors: Hirose Kosuke , Sudo Ikuma , Ogawa Jun , Watanabe Yosuke , Shiblee M. D. Nahin Islam , Khosla Ajit , Kawakami Masaru , Furukawa Hidemitsu 
Published: October 2022

AbstractThe human oral structure contains organs with distinctly different physical properties, such as teeth, gums, and tongues. When food enters the oral cavity, we can recognize the tactile sensation and shape of the object from multiple perspectives through the texture of the teeth and tongue. Therefore, it is possible to regard oral structures as a group of tactile sensors based on these functions. In this study, we developed a soft-matter artificial mouth that can accurately detect subtle differences in texture by creating and combining oral structural organs using polymer materials with different physical properties and mounting them as end-effectors for a robot arm. The same piezoelectric film sensor was embedded inside each organ, making it possible to acquire tactile sensations from the same object as completely different signal waveforms. We tested whether the sensor data obtained from each soft-matter material could be used for excellent object recognition by applying various machine learning methods. In an actual experiment, we learned the waveform data obtained from chewing sweets and snacks, such as rice crackers, and applied machine learning to classify the data, which led to an accuracy rate of over 90%.
The steady state and response to a periodic stimulation of the firing rate for a theta neuron with correlated noise
Authors: Franzen Jannik , Ramlow Lukas , Lindner Benjamin 
Published: October 2022

AbstractThe stochastic activity of neurons is caused by various sources of correlated fluctuations and can be described in terms of simplified, yet biophysically grounded, integrate-and-fire models. One paradigmatic model is the quadratic integrate-and-fire model and its equivalent phase description by the theta neuron. Here we study the theta neuron model driven by a correlated Ornstein-Uhlenbeck noise and by periodic stimuli. We apply the matrix-continued-fraction method to the associated Fokker-Planck equation to develop an efficient numerical scheme to determine the stationary firing rate as well as the stimulus-induced modulation of the instantaneous firing rate. For the stationary case, we identify the conditions under which the firing rate decreases or increases by the effect of the colored noise and compare our results to existing analytical approximations for limit cases. For an additional periodic signal we demonstrate how the linear and nonlinear response terms can be computed and report resonant behavior for some of them. We extend the method to the case of two periodic signals, generally with incommensurable frequencies, and present a particular case for which a strong mixed response to both signals is observed, i.e. where the response to the sum of signals differs significantly from the sum of responses to the single signals. We provide Python code for our computational method: https://github.com/jannikfranzen/theta_neuron.
Photocatalytic activation of Ag-doped SrSnO3 nanorods under visible light for reduction of p-nitrophenol and methylene blue mineralization
Authors: Ghubish Z. , Kamal R. , Mahmoud Hala R. , Saif M. , Hafez H. , El-Kemary M. 
Published: October 2022

AbstractThe utilization of solar energy for the treatment of wastewater pollutants by photocatalysts has been considered a promising solution to address environmental problems. Herein, we have synthesized silver nanoparticle-doped strontium stannate (Ag-doped SrSnO3) nanorods by hydrothermal method followed by ultrasonic treatment. The developed nanocomposites were applied for photocatalytic reduction of p-nitrophenol (4-NP) and methylene blue (MB) mineralization under visible light illumination. The effect of hydrothermal duration time (16–25) h, Cetyltrimethylammonium bromide (CTAB) and silver nanoparticles (Ag NPs) concentration (0.5–2.5) wt% on the crystal, surface, optical, photoluminescence as well as photocatalytic activity were studied. A well-defined crystalline cubic phase of SrSnO3 was obtained. CTAB inhibits the crystal growth of SrSnO3. Reduction of 4-NP and MB mineralization were used as two-model reactions for testing the effect of Ag doping concentration on the photocatalytic activities of Ag/SrSnO3 under visible light illumination. The obtained results show that 2.0 wt% of Ag-doped SrSnO3 exhibits efficient photocatalytic reduction of 4-NP with 98.2% conversion within 5 min of reaction time. Also, 87% of the MB sample was mineralized after 1 h of visible illumination using 2.0% Ag/SrSnO3 in the presence of H2O2. Besides, we have discussed the possible photocatalytic mechanism for reduction of 4-NP and mineralization of MB using 2.0 wt% of Ag doped SrSnO3 under visible light illumination.
Preparation, investigation, and temperature sensing application of rGO/SnO2/Co3O4 composite
Authors: Morsy Mohamed , Darwish A. G. , Mokhtar M. M. , Elbashar Yahia , Elzwawy Amir 
Published: October 2022

AbstractThe uprising era of technological applications seeks solutions that facilitate daily life activities. Sensors with their different types provide fast and reliable information. The employment of graphene oxide in these sensors complies with the general requirement for sensor's functionalization and easily achieves the purpose for which the sensor was prepared. In this report, we have synthesized rGO/SnO2/Co3O4 composite with a star-like structure through a facile chemical route. The mentioned structure was employed as a temperature sensor within a temperature range of 25–125 °C and a wide span of relative humidity values. In order to assess the quality of preparation and the sensing ability, the composite was inspected by the following techniques: XRD, FTIR, SEM, and thermal analysis in addition to the sensing measurements. The XRD results affirmed the successful incorporation of the SnO2/Co3O4 onto the rGO with 18 nm average crystallite size. The SEM results revealed the characteristic star-like structure with a mean length of 100 nm. The main functional groups are reflected in the FTIR results. The outcomes elucidated a linear response between the resistance and temperature, where the temperature coefficient of resistance is estimated to be 0.006/°C. These results confirm the validity of this structure for temperature sensing applications.
Stepwise Excited-state Double Proton Transfer and Fluorescence Decay Analysis
Authors: Wróblewski Tomasz , Ushakou Dzmitryi 
Published: October 2022

AbstractThis work considers excited state intramolecular proton transfers (ESIPT) occurred in multiple hydroxyl-containing compounds with one proton transfer site in the normal form. If several hydroxyl groups are located close to each other in a molecule, then the ESIPT process can lead to the next one. A proton donor site in the first ESIPT will be a proton acceptor during the second reaction. Therefore, a number of consecutive excited state proton transfers can occur. This work deals with the case of two successive proton transfers occurred in the molecular system. Such process is called as a stepwise excited state intramolecular double proton transfer (stepwise ESIDPT). It leads to the formation of two molecular tautomers. Therefore, fluorescence of such compounds can contain different emission bands correspond to emission of normal form and two tautomers. In this work, a rigorous analysis of fluorescence decay kinetics has been made using the model with three species, including a normal molecular form and two tautomers. The work presents theoretical framework of fluorescence decay analysis of ESIDPT process taking into account three species emission. Theoretically, the stepwise proton transfers can be consisted of more than two ESIPT reactions. It depends on molecular structure and number of involved hydroxyl groups. Here, a formal analysis of fluorescence decay kinetics has been made in the case of a stepwise process consisting of two proton transfers. Moreover, the quantum-chemical calculations have been performed in the case of scutellarein. It is a multiple hydroxyl-containing flavone and, therefore, it can be applied as a model molecule to study stepwise intramolecular proton transfers. The hypothetical scheme of ESIDPT has been proposed for this compound.
Graphical abstract
A flexible scope theory of intensionality
Authors: Elliott Patrick D. 
Published: October 2022

AbstractExtant attempts to incorporate intensionality into the grammar either systematically over-generate, or systematically under-generate. In this paper, building on Keshet (Linguist and Philos 33(4):251–283, 2011), we aim to reconcile a scopal account of de re with the possibility of de re readings out of scope islands. By adapting compositional techniques for dealing with exceptionally scoping indefinites (Charlow, in On the semantics of exceptional scope, PhD thesis, Rutgers University, 2014; The scope of alternatives: indefiniteness and islands. Linguist and Philos 43(4):427–472, 2020), we develop an intensional grammar in which exceptional de re is achieved via cyclic scope. World-sensitive expressions are converted into scope-takers via a constrained inventory of type-flexible operators. Type flexibility explains the possibility of apparently island-violating de re by predicting the possibility of cyclic scope-taking. We argue that the resulting theory—which we dub the flexible scope theory—is sufficiently expressive to address the under-generation issues of current accounts, while still capturing constraints on de re in an explanatory fashion.
Investigations on speaker adaptation using a continuous vocoder within recurrent neural network based text-to-speech synthesis
Authors: Mandeel Ali Raheem , Al-Radhi Mohammed Salah , Csapó Tamás Gábor 
Published: October 2022

AbstractThis paper presents an investigation of speaker adaptation using a continuous vocoder for parametric text-to-speech (TTS) synthesis. In purposes that demand low computational complexity, conventional vocoder-based statistical parametric speech synthesis can be preferable. While capable of remarkable naturalness, recent neural vocoders nonetheless fall short of the criteria for real-time synthesis. We investigate our former continuous vocoder, in which the excitation is characterized employing two one-dimensional parameters: Maximum Voiced Frequency and continuous fundamental frequency (F0). We show that an average voice can be trained for deep neural network-based TTS utilizing data from nine English speakers. We did speaker adaptation experiments for each target speaker with 400 utterances (approximately 14 minutes). We showed an apparent enhancement in the quality and naturalness of synthesized speech compared to our previous work by utilizing the recurrent neural network topologies. According to the objective studies (Mel-Cepstral Distortion and F0 correlation), the quality of speaker adaptation using Continuous Vocoder-based DNN-TTS is slightly better than the WORLD Vocoder-based baseline. The subjective MUSHRA-like test results also showed that our speaker adaptation technique is almost as natural as the WORLD vocoder using Gated Recurrent Unit and Long Short Term Memory networks. The proposed vocoder, being capable of real-time synthesis, can be used for applications which need fast synthesis speed.
Automatic facial emotion recognition at the COVID-19 pandemic time
Authors: Castellano Giovanna , De Carolis Berardina , Macchiarulo Nicola 
Published: October 2022

AbstractPeople use various nonverbal communicative channels to convey emotions, among which facial expressions are considered the most important ones. Thus, automatic Facial Expression Recognition (FER) is a fundamental task to increase the perceptive skills of computers, especially in human-computer interaction. Like humans, state-of-art FER systems are able to recognize emotions from the entire face of a person. However, the COVID-19 pandemic has imposed a massive use of face masks that help in preventing infection but may hamper social communication and make the recognition of facial expressions a very challenging task due to facial occlusion. In this paper we propose a FER system capable to recognize emotions from masked faces. The system checks for the presence of a mask on the face image and, in case of mask detection, it extracts the eyes region and recognizes the emotion only considering that portion of the face. The effectiveness of the developed FER system was tested in recognizing emotions and their valence only from the eyes region and comparing the results when considering the entire face. As it was expected, emotions that are related mainly to the mouth region (e.g., disgust) are barely recognized, while positive emotions are better identified by considering only the eyes region. Moreover, we compared the results of our FER system to the human annotation of emotions on masked faces. We found out that the FER system outperforms the human annotation, thus showing that the model is able to learn proper features for each emotion leveraging only the eyes region.
Experimental and numerical characterization of a D-shaped PCF refractive index sensor
Authors: Azab Mohammad Y. , Hameed Mohamed Farhat O. , Mahdiraji Ghafour Amouzad , Adikan Faisal Rafiq Mahamd , Obayya S. S. A. 
Published: October 2022

AbstractHighly sensitive D-shaped plasmonic photonic crystal fiber (PCF) sensor is proposed, analyzed and fabricated for refractive index (RI) sensing. The reported sensor relies on the coupling between the core guided mode and the surface plasmon mode at the metallic/dielectric interface. The resonance frequency is a function of the analyte RI within a range of 1.33–1.354. Therefore, the reported D-shaped PCF holds great potential as a highly sensitive RI sensor to detect an unknown analyte refractive index within the tested RI range. The geometrical parameters are studied to maximize the sensor sensitivity by using full vectorial finite element method. Then, the optimum design is fabricated by using stack and draw technique. The fabricated PCF sensor achieves high sensitivity of 294.11 nm/RIU with a resolution of $$3.4 \times 10^{ - 4} \;{\text{RIU}}$$

3.4
×

10

-
4

RIU

. The reported RI sensor can be used for glucose concentration detection where the analyte refractive index changes with the glucose concentration within the studied RI range. Hence, this design will play a significant role in the biomedical sensor industry.
The wellbeing of women and men with and without disabilities: evidence from cross-sectional national surveys in 27 low- and middle-income countries
Authors: Emerson Eric , Llewellyn Gwynnyth 
Published: October 2022

Abstract
Background
Little is known about disability-related inequities in personal wellbeing (PWB) in low- and middle-income countries (LMICs).

Method
Secondary analysis of data collected in Round 6 of UNICEF’s Multiple Indicator Cluster Surveys (MICS) undertaken in 27 LMICs (n = 296,693 women, 66,557 men). Data were aggregated across countries by mixed effects multi-level modelling and meta-analysis.

Results
Women and men with disabilities were less likely than their non-disabled peers to report being happy and to be satisfied with their life. These differences were evident in all countries for women and in 18 of 22 countries for men. Aggregated data indicated that: (1) women with disabilities were 14–15% less likely to be happy and 17% less likely to be satisfied with their lives; (2) men with disabilities were 15–17% less likely to be happy and 17–19% less likely to be satisfied with their lives; (3) disability-related inequalities in personal wellbeing were reduced by 22–26% for women and 11–22% for men by adjusting for differences in living conditions.

Conclusions
Future releases of MICS data could prove a valuable resource in monitoring country-level progress to realising Sustainable Development Goal 3 and the extent to which progress is equitable between women and men and between people with/without disabilities. Results also suggest that a significant proportion of the disability-related inequities in wellbeing may be accounted for by modifiable differences in their living conditions and life experiences.
A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks
Authors: Ma Xiaoyu , Sardy Sylvain , Hengartner Nick , Bobenko Nikolai , Lin Yen Ting 
Published: October 2022

AbstractTo fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack). More recently learners known as artificial neural networks (ANN) have shown great successes in many machine learning tasks, in particular fitting nonlinear associations. Small learning rate, stochastic gradient descent algorithm and large training set help to cope with the explosion in the number of parameters present in deep neural networks. Yet few ANN learners have been developed and studied to find needles in nonlinear haystacks. Driven by a single hyperparameter, our ANN learner, like for sparse linear associations, exhibits a phase transition in the probability of retrieving the needles, which we do not observe with other ANN learners. To select our penalty parameter, we generalize the universal threshold of Donoho and Johnstone (Biometrika 81(3):425–455, 1994) which is a better rule than the conservative (too many false detections) and expensive cross-validation. In the spirit of simulated annealing, we propose a warm-start sparsity inducing algorithm to solve the high-dimensional, non-convex and non-differentiable optimization problem. We perform simulated and real data Monte Carlo experiments to quantify the effectiveness of our approach.
The determinants of university strategic positioning and the obscuring of institutional diversity: an Australian case study
Authors: Zipparo Julian 
Published: October 2022

AbstractThe purpose of this paper is to contribute to the recent body of research exploring strategic positioning, and the processes and factors which influence the development and content of university strategies and plans, with lessons then applied to open questions of institutional diversity and its determinants. Following a sector level analysis of the contents of university positioning documents, an in-depth case study is developed of a large Australian university, where the interaction of intra-institutional ‘meso’ layers is explored to show a confluence of factors contributing to positioning. The case demonstrates that institutional positioning involves the selective crafting of narratives for multiple purposes, including the seeking and portrayal of internal cohesion, identity enhancement, and resource seeking. Importantly, while cross-institutional comparison of positioning narratives portrays an undifferentiated and somewhat homogenous sector, positioning is found within the case institution to obscure what is significant internal diversity and complexity. The implications of these findings for research exploring institutional diversity, and policies seeking to stimulate it, are discussed.
Maxillomandibular advancement for obstructive sleep apnea: a retrospective prognostic factor study for surgical response
Authors: Zhou Ning , Ho Jean-Pierre T. F. , Visscher Wouter P. , Su Naichuan , Lobbezoo Frank , de Lange Jan 
Published: October 2022

Abstract

Purpose
To identify potential predictors of surgical response to maxillomandibular advancement (MMA) in patients with obstructive sleep apnea (OSA) from the most common clinically available data (patient-related, polysomnographic, cephalometric, and surgical variables).

Methods
This was a retrospective study comprised of consecutive patients who underwent MMA for moderate to severe OSA. Relevant clinical, polysomnographic, cephalometric, and surgical variables were collected as independent variables (predictors). The association of the independent variables with a favorable surgical response to MMA was assessed in univariate and multivariate analyses.

Results
In 100 patients (82% male; mean age 50.5 years), the mean apnea hypopnea index [AHI] was 53.1 events/h. The rate of favorable surgical response was 67%. Based on multivariate analysis, patients with cardiovascular disease (CVD) had 0.140 times lower odds of a favorable response to MMA (OR: 0.140 [0.038, 0.513], P = 0.003). For each 1-unit increase in central apnea index (CAI) and superior posterior airway space (SPAS), there were 0.828 and 0.724 times lower odds to respond favorably to MMA (OR: 0.828 [0.687, 0.997], P = 0.047; and 0.724 [0.576, 0.910], P = 0.006), respectively.

Conclusion
The findings of this study suggest that the surgical outcome of MMA may be less favorable when patients with OSA have certain phenotypic characteristics: the presence of CVD, higher CAI and larger SPAS. If confirmed in future studies, these variables may guide patient selection for MMA.